The 100 most-cited articles in PLoS ONE, 2023

Graphics are widely used to provide summarization of complex data in scientific publications. Although there are many tools available for drawing graphics, their use is limited by programming skills, costs, and platform specificities. Here, we presented a freely accessible easy-to-use web server named SRplot that integrated more than a hundred of commonly used data visualization and graphing functions together. It can be run easily using all Web browsers and there are no strong requirements on the computing power of users' machines. With a user-friendly graphical interface, users can simply paste the contents of the input file into the text box according to the defined file format. Modification operations can be easily performed, and graphs can be generated in real-time. The resulting graphs can be easily downloaded in bitmap (PNG or TIFF) or vector (PDF or SVG) format in publication quality. The website is updated promptly and continuously. Functions in SRplot have been improved, optimized and updated depend on feedback and suggestions from users. The graphs prepared with SRplot…

With the proliferation of online data collection in human-subjects research, concerns have been raised over the presence of inattentive survey participants and non-human respondents (bots). We compared the quality of the data collected through five commonly used platforms. Data quality was indicated by the percentage of participants who meaningfully respond to the researcher's question (high quality) versus those who only contribute noise (low quality). We found that compared to MTurk, Qualtrics, or an undergraduate student sample (i.e., SONA), participants on Prolific and CloudResearch were more likely to pass various attention checks, provide meaningful answers, follow instructions, remember previously presented information, have a unique IP address and geolocation, and work slowly enough to be able to read all the items. We divided the samples into high- and low-quality respondents and computed the cost we paid per high-quality respondent. Prolific ($1.90) and CloudResearch ($2.00) were cheaper than MTurk ($4.36) and Qualtrics ($8.17). SONA cost $0.00, yet took the longest to…

As global awareness, science, and policy interventions for plastic escalate, institutions around the world are seeking preventative strategies. Central to this is the need for precise global time series of plastic pollution with which we can assess whether implemented policies are effective, but at present we lack these data. To address this need, we used previously published and new data on floating ocean plastics (n = 11,777 stations) to create a global time-series that estimates the average counts and mass of small plastics in the ocean surface layer from 1979 to 2019. Today's global abundance is estimated at approximately 82-358 trillion plastic particles weighing 1.1-4.9 million tonnes. We observed no clear detectable trend until 1990, a fluctuating but stagnant trend from then until 2005, and a rapid increase until the present. This observed acceleration of plastic densities in the world's oceans, also reported for beaches around the globe, demands urgent international policy interventions.

AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted the pLDDT and metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the same AlphaFold pLDDT metrics with the impact of a single mutation on structure using a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of…

OBJECTIVES: Hospital-acquired infections (HAIs) are significant problems as public health issues which need attention. Such infections are significant problems for society and healthcare organizations. This study aimed to carry out a systematic review and a meta-analysis to analyze the prevalence of HAIs globally. METHODS: We conducted a comprehensive search of electronic databases including EMBASE, Scopus, PubMed and Web of Science between 2000 and June 2021. We found 7031 articles. After removing the duplicates, 5430 studies were screened based on the titles/ abstracts. Then, we systematically evaluated the full texts of the 1909 remaining studies and selected 400 records with 29,159,630 participants for meta-analysis. Random-effects model was used for the analysis, and heterogeneity analysis and publication bias test were conducted. RESULTS: The rate of universal HAIs was 0.14 percent. The rate of HAIs is increasing by 0.06 percent annually. The highest rate of HAIs was in the AFR, while the lowest prevalence were in AMR and WPR. Besides, AFR prevalence in central Africa is…

INTRODUCTION: Antibiotic resistance (ABR) has substantial global public health concerns. This systematic review aimed to synthesise recent evidence estimating the economic burden of ABR, characterised by study perspectives, healthcare settings, study design, and income of the countries. METHODS: This systematic review included peer-reviewed articles from PubMed, Medline, and Scopus databases, and grey literature on the topic of the economic burden of ABR, published between January 2016 and December 2021. The study was reported in line with 'Preferred Reporting Items for Systematic Review and Meta-Analysis' (PRISMA). Two reviewers independently screened papers for inclusion first by title, then abstract, and then the full text. Study quality was assessed using appropriate quality assessment tools. Narrative synthesis and meta-analyses of the included studies were conducted. RESULTS: A total of 29 studies were included in this review. Out of these studies, 69% (20/29) were conducted in high-income economies and the remainder were conducted in upper-and-middle income economies. Most of…

OBJECTIVE: ChatGPT is the first large language model (LLM) to reach a large, mainstream audience. Its rapid adoption and exploration by the population at large has sparked a wide range of discussions regarding its acceptable and optimal integration in different areas. In a hybrid (virtual and in-person) panel discussion event, we examined various perspectives regarding the use of ChatGPT in education, research, and healthcare. MATERIALS AND METHODS: We surveyed in-person and online attendees using an audience interaction platform (Slido). We quantitatively analyzed received responses on questions about the use of ChatGPT in various contexts. We compared pairwise categorical groups with a Fisher's Exact. Furthermore, we used qualitative methods to analyze and code discussions. RESULTS: We received 420 responses from an estimated 844 participants (response rate 49.7%). Only 40% of the audience had tried ChatGPT. More trainees had tried ChatGPT compared with faculty. Those who had used ChatGPT were more interested in using it in a wider range of contexts going forwards. Of the three…

When evaluating the performance of quantitative models, dimensioned errors often are characterized by sums-of-squares measures such as the mean squared error (MSE) or its square root, the root mean squared error (RMSE). In terms of quantifying average error, however, absolute-value-based measures such as the mean absolute error (MAE) are more interpretable than MSE or RMSE. Part of that historical preference for sums-of-squares measures is that they are mathematically amenable to decomposition and one can then form ratios, such as those based on separating MSE into its systematic and unsystematic components. Here, we develop and illustrate a decomposition of MAE into three useful submeasures: (1) bias error, (2) proportionality error, and (3) unsystematic error. This three-part decomposition of MAE is preferable to comparable decompositions of MSE because it provides more straightforward information on the nature of the model-error distribution. We illustrate the properties of our new three-part decomposition using a long-term reconstruction of streamflow for the Upper Colorado…

Long-term adverse experiences following psychedelic use can persist for weeks, months, or even years, and are relatively unexplored in psychedelic research. Our convergent mixed-method study gained quantitative and qualitative data from 608 participants who reported extended difficulties following psychedelic experiences. Data was gathered on the context of use, the nature and duration of the challenges they experienced (including a written description of these), plus a range of possible risk factors and perceived causes. The most common forms of extended difficulty were feelings of anxiety and fear, existential struggle, social disconnection, depersonalization and derealization. For approximately one-third of the participants, problems persisted for over a year, and for a sixth, they endured for more than three years. It was found that a shorter duration of difficulties was predicted by knowledge of dose, drug type and lower levels of difficulty reported during the psychoactive experience, while a narrower range of difficulties was predicted by taking the drug in a guided setting.…

INTRODUCTION: Large language models, in particular ChatGPT, have showcased remarkable language processing capabilities. Given the substantial workload of university medical staff, this study aims to assess the quality of multiple-choice questions (MCQs) produced by ChatGPT for use in graduate medical examinations, compared to questions written by university professoriate staffs based on standard medical textbooks. METHODS: 50 MCQs were generated by ChatGPT with reference to two standard undergraduate medical textbooks (Harrison's, and Bailey & Love's). Another 50 MCQs were drafted by two university professoriate staff using the same medical textbooks. All 100 MCQ were individually numbered, randomized and sent to five independent international assessors for MCQ quality assessment using a standardized assessment score on five assessment domains, namely, appropriateness of the question, clarity and specificity, relevance, discriminative power of alternatives, and suitability for medical graduate examination. RESULTS: The total time required for ChatGPT to create the 50 questions was…

The accuracy of a classification is fundamental to its interpretation, use and ultimately decision making. Unfortunately, the apparent accuracy assessed can differ greatly from the true accuracy. Mis-estimation of classification accuracy metrics and associated mis-interpretations are often due to variations in prevalence and the use of an imperfect reference standard. The fundamental issues underlying the problems associated with variations in prevalence and reference standard quality are revisited here for binary classifications with particular attention focused on the use of the Matthews correlation coefficient (MCC). A key attribute claimed of the MCC is that a high value can only be attained when the classification performed well on both classes in a binary classification. However, it is shown here that the apparent magnitude of a set of popular accuracy metrics used in fields such as computer science medicine and environmental science (Recall, Precision, Specificity, Negative Predictive Value, J, F1, likelihood ratios and MCC) and one key attribute (prevalence) were all…

INTRODUCTION: Healthcare-associated infections (HAIs) have become a serious public health problem. Despite the fact that implementing evidence-based infection control strategies could prevent HAIs and save billions of dollars, Ethiopia lacks national surveillance studies on the rate, economic, and clinical burden of HAIs. OBJECTIVE: To assess the clinical and economic burden of HAIs in hospitalized patients at Ayder comprehensive specialized hospital. MATERIALS AND METHODS: A prospective cohort study design was conducted in patients with and without HAIs. A review of medical records, interviews, and patient bills was used to extract necessary information. The patients in the two arms were matched based on age, sex, Charlson comorbidity index, and ward type. Measurable factors were compared between infected and uninfected patients using the paired ttest or McNemar's test, as appropriate. Logistic regression was used to identify predictors of in-hospital mortality. Stata 14.1 was used to conduct all analyses. RESULTS: A total of 408 patients, 204 with HAIs and 204 without HAIs were…

Microplastics (MPs) are ubiquitous in the environment, in the human food chain, and have been recently detected in blood and lung tissues. To undertake a pilot analysis of MP contamination in human vein tissue samples with respect to their presence (if any), levels, and characteristics of any particles identified. This study analysed digested human saphenous vein tissue samples (n = 5) using μFTIR spectroscopy (size limitation of 5 μm) to detect and characterise any MPs present. In total, 20 MP particles consisting of five MP polymer types were identified within 4 of the 5 vein tissue samples with an unadjusted average of 29.28 ± 34.88 MP/g of tissue (expressed as 14.99 ± 17.18 MP/g after background subtraction adjustments). Of the MPs detected in vein samples, five polymer types were identified, of irregular shape (90%), with alkyd resin (45%), poly (vinyl propionate/acetate, PVAc (20%) and nylon-ethylene-vinyl acetate, nylon-EVA, tie layer (20%) the most abundant. While the MP levels within tissue samples were not significantly different than those identified within procedural…

Attention Deficit Hyperactivity Disorder (ADHD) is a developmental disorder, with an onset in childhood, that accompanies the person throughout their life, with prevalence between 3 and 5% in adults. Recent studies point towards a fourth core symptom of the disorder related to the emotional information processing that would explain the repercussions that ADHD has on the social, academic, and professional life of the people affected. This review aims to describe emotion dysregulation features as well as the brain activity associated in adults with ADHD. A search of the scientific literature was launched in specialized databases: PsycInfo, Medline, Eric, PsycArticle, Psicodoc and Scopus, following PRISMA guidelines. Twenty-two articles met the inclusion criteria: (a) an ADHD clinical diagnosis, (b) participants over 18 years old, (c) emotion regulation measurement, (d) empirical studies, and (c) in English. Due to the heterogeneity of the studies included, they were classified into three sections: measures and features of emotion regulation (ER) in people with ADHD, neurological and…

Recently, research has shown an increased spread of non-communicable diseases such as cancer. Lung cancer diagnosis and detection has become one of the biggest obstacles in recent years. Early lung cancer diagnosis and detection would reliably promote safety and the survival of many lives globally. The precise classification of lung cancer using medical images will help physicians select suitable therapy to reduce cancer mortality. Much work has been carried out in lung cancer detection using CNN. However, lung cancer prediction still becomes difficult due to the multifaceted designs in the CT scan. Moreover, CNN models have challenges that affect their performance, including choosing the optimal architecture, selecting suitable model parameters, and picking the best values for weights and biases. To address the problem of selecting optimal weight and bias combination required for classification of lung cancer in CT images, this study proposes a hybrid metaheuristic and CNN algorithm. We first designed a CNN architecture and then computed the solution vector of the model. The…

Machine learning (ML) models are used in clinical metabolomics studies most notably for biomarker discoveries, to identify metabolites that discriminate between a case and control group. To improve understanding of the underlying biomedical problem and to bolster confidence in these discoveries, model interpretability is germane. In metabolomics, partial least square discriminant analysis (PLS-DA) and its variants are widely used, partly due to the model's interpretability with the Variable Influence in Projection (VIP) scores, a global interpretable method. Herein, Tree-based Shapley Additive explanations (SHAP), an interpretable ML method grounded in game theory, was used to explain ML models with local explanation properties. In this study, ML experiments (binary classification) were conducted for three published metabolomics datasets using PLS-DA, random forests, gradient boosting, and extreme gradient boosting (XGBoost). Using one of the datasets, PLS-DA model was explained using VIP scores, while one of the best-performing models, a random forest model, was interpreted using…

In this study, we attempt to anticipate annual rice production in Bangladesh (1961-2020) using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme Gradient Boosting (XGBoost) methods and compare their respective performances. On the basis of the lowest Corrected Akaike Information Criteria (AICc) values, a significant ARIMA (0, 1, 1) model with drift was chosen based on the findings. The drift parameter value shows that the production of rice positively trends upward. Thus, the ARIMA (0, 1, 1) model with drift was found to be significant. On the other hand, the XGBoost model for time series data was developed by changing the tunning parameters frequently with the greatest result. The four prominent error measures, such as mean absolute error (MAE), mean percentage error (MPE), root mean square error (RMSE), and mean absolute percentage error (MAPE), were used to assess the predictive performance of each model. We found that the error measures of the XGBoost model in the test set were comparatively lower than those of the ARIMA model. Comparatively, the MAPE…

Technology for anticipating wind speed can improve the safety and stability of power networks with heavy wind penetration. Due to the unpredictability and instability of the wind, it is challenging to accurately forecast wind power and speed. Several approaches have been developed to improve this accuracy based on processing time series data. This work proposes a method for predicting wind speed with high accuracy based on a novel weighted ensemble model. The weight values in the proposed model are optimized using an adaptive dynamic grey wolf-dipper throated optimization (ADGWDTO) algorithm. The original GWO algorithm is redesigned to emulate the dynamic group-based cooperative to address the difficulty of establishing the balance between exploration and exploitation. Quick bowing movements and a white breast, which distinguish the dipper throated birds hunting method, are employed to improve the proposed algorithm exploration capability. The proposed ADGWDTO algorithm optimizes the hyperparameters of the multi-layer perceptron (MLP), K-nearest regressor (KNR), and Long Short-Term…

Import and export of fossil energy carriers are cornerstones of energy systems world-wide. If energy systems are to become climate neutral and sustainable, fossil carriers need to be substituted with carbon neutral alternatives or electrified if possible. We investigate synthetic chemical energy carriers, hydrogen, methane, methanol, ammonia and Fischer-Tropsch fuels, produced using electricity from Renewable Energy Source (RES) as fossil substitutes. RES potentials are obtained from GIS-analysis and hourly resolved time-series are derived using reanalysis weather data. We model the sourcing of feedstock chemicals, synthesis and transport along nine different Energy Supply Chains to Germany and compare import options for seven locations around the world against each other and with domestically sourced alternatives on the basis of their respective cost per unit of hydrogen and energy delivered. We find that for each type of chemical energy carrier, there is an import option with lower costs compared to domestic production in Germany. No single exporting country or energy carrier has…

INTRODUCTION: The prevalence of catheter-associated bloodstream infections (CLABSI) is high and is a severe health problem associated with an increase in mortality and elevated economic costs. There are discrepancies related to the risk factors of CLABSI since the results published are very heterogeneous and there is no synthesis in the description of all the predisposing factors. OBJECTIVE: We aimed to perform a systematic review and meta-analysis to synthesize and establish the risk factors predisposing to CLABSI reported in the literature. METHOD: This is a systematic review of observational studies following the PRISMA recommendations. MEDLINE and CINAHL databases were searched for primary studies from 2007 to 2021. The protocol was registered in PROSPERO CRD42018083564. RESULTS: A total of 654 studies were identified, 23 of which were included in this systematic review. The meta-analysis included 17 studies and 9 risk factors were analyzed (total parenteral nutrition (TPN), chemotherapy, monolumen and bilumen catheters, days of catheterization, immunosuppression, kidney disease…

The idea behind the spillover effect of FDI on economic growth is based on the idea that multinational companies can bring technological innovation and rich knowledge to host countries. Therefore, FDI plays a vital role in technological innovations. This study aims to investigate the impact of foreign direct investment (FDI) on the technological innovation of BRICS countries from 2000 to 2020. This study uses the latest econometric techniques, such as the cross-sectional dependence (CD) test, second-generation unit root tests, panel cointegration tests and the Dumitrescu-Hurlin causality test. For long-run run estimation, this study uses the augmented mean group (AMG) panel estimator and the common correlated effects mean group (CCEMG) estimator for empirical analysis. The findings of the study show that foreign direct investment (FDI), trade openness, economic growth, and research & development expenditure positively impact technological innovation in BRICS countries. Also, the model's long-term causality and lagged error correction term (ECT) are significantly negative. Suggested…

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that causes gradual memory loss. AD and its prodromal stage of mild cognitive impairment (MCI) are marked by significant gut microbiome perturbations, also known as gut dysbiosis. However, the direction and extent of gut dysbiosis have not been elucidated. Therefore, we performed a meta-analysis and systematic review of 16S gut microbiome studies to gain insights into gut dysbiosis in AD and MCI. METHODS: We searched MEDLINE, Scopus, EMBASE, EBSCO, and Cochrane for AD gut microbiome studies published between Jan 1, 2010 and Mar 31, 2022. This study has two outcomes: primary and secondary. The primary outcomes explored the changes in α-diversity and relative abundance of microbial taxa, which were analyzed using a variance-weighted random-effects model. The secondary outcomes focused on qualitatively summarized β-diversity ordination and linear discriminant analysis effect sizes. The risk of bias was assessed using a methodology appropriate for the included case-control studies. The geographic cohorts' heterogeneity…

Conspiracy beliefs have become a topic of increasing interest among behavioural researchers. While holding conspiracy beliefs has been associated with several detrimental social, personal, and health consequences, little research has been dedicated to systematically reviewing the methods that could reduce conspiracy beliefs. We conducted a systematic review to identify and assess interventions that have sought to counter conspiracy beliefs. Out of 25 studies (total N = 7179), we found that while the majority of interventions were ineffective in terms of changing conspiracy beliefs, several interventions were particularly effective. Interventions that fostered an analytical mindset or taught critical thinking skills were found to be the most effective in terms of changing conspiracy beliefs. Our findings are important as we develop future research to combat conspiracy beliefs.

BACKGROUND: According to the World Health Organization (WHO), dementia is the seventh leading reason of death among all illnesses and one of the leading causes of disability among the world's elderly people. Day by day the number of Alzheimer's patients is rising. Considering the increasing rate and the dangers, Alzheimer's disease should be diagnosed carefully. Machine learning is a potential technique for Alzheimer's diagnosis but general users do not trust machine learning models due to the black-box nature. Even, some of those models do not provide the best performance because of using only neuroimaging data. OBJECTIVE: To solve these issues, this paper proposes a novel explainable Alzheimer's disease prediction model using a multimodal dataset. This approach performs a data-level fusion using clinical data, MRI segmentation data, and psychological data. However, currently, there is very little understanding of multimodal five-class classification of Alzheimer's disease. METHOD: For predicting five class classifications, 9 most popular Machine Learning models are used. These…

The growth of the digital economy has created new forms of inequality of opportunity. This paper studies whether the development of the digital economy expands the income gap between urban and rural areas from theoretical and empirical. The research based on the panel data of 202 cities from 2011 to 2019 in China shows that: (1) Although the digital economy can promote the improvement of both urban and rural absolute income levels, it has a greater positive impact on urban residents' income levels than on rural residents', resulting in a widening of the urban-rural income gap. (2) The analysis of the action mechanism reveals that employment in the information service industry and the depth of digital finance use are two crucial mechanisms for the digital economy to widen the income gap between urban and rural areas. (3) The spatial Durbin model(SDM) and the spatial error model(SEM) based on three spatial weight matrices show that the impact of the digital economy on the urban-rural income gap is also characterized by spatial spillover, and the development of the digital economy will…

BACKGROUND: Although several epidemiological studies have linked social isolation to increased risk of mortality, the magnitude of any effect is unclear, in part because of the use of different measures of social isolation. OBJECTIVE: To examine the association between social isolation and all-cause mortality and investigate whether it differs in various subgroups or populations. DATA SOURCES: We searched for relevant studies in electronic databases: MEDLINE (1946 to December 31, 2021), EMBASE (1974 to December 31, 2021), and PsycINFO (1806 to December 31, 2021). SELECTION CRITERIA: We included both prospective and retrospective cohort studies that examined the association between social isolation and all-cause mortality among adults. DATA COLLECTION AND ANALYSIS: Two reviewers screened and extracted data independently. We contacted study authors to obtain missing information whenever possible. Data were pooled using a random effect model to calculate estimates of the effects of social isolation on all-cause mortality. RESULTS: Data from studies involving 1.30 million individuals…

Plant extract-based green synthesis of nanoparticles is an emerging class of nanotechnology that has revolutionized the entire field of biological sciences. Green synthesized nanoparticles are used as super-growth promoters and antifungal agents. In this study, selenium nanoparticles (SeNPs) were synthesized using Melia azedarach leaves extract as the main reducing and stabilizing agent and characterized by UV-visible spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray (EDX), and fourier transform infrared spectrometer (FTIR). The green synthesized SeNPs were exogenously applied on Mangifera indica infected with mango malformation disease. The SeNPs at a concentration of 30 μg/mL were found to be the best concentration which enhanced the physiological (chlorophyll and membrane stability index), and biochemical (proline and soluble sugar) parameters. The antioxidant defense system was also explored, and it was reported that green synthesized SeNPs significantly reduced the biotic stress by enhancing enzymatic and non-enzymatic…

BACKGROUND: Western literature has long explored help-seeking behaviours related to mental health issues. However, this has been relatively neglected in the Middle East despite an increase in mental health needs in the region. The purpose of this review was to conduct a systematic review and qualitative meta-synthesis exploring help-seeking behaviours related to mental health issues in the Middle East. METHODS: We conducted a systematic review and meta-synthesis to gain a comprehensive overview of what is known about mental health and help-seeking behaviours in the Middle East from published qualitative research in the Middle Eastern region. A search of electronic databases (MEDLINE, Embase, CINAHL, PsycINFO and QScience) was carried out from inception to July 2022. The quality of the included studies was assessed using the Critical Appraisal Skills Programme tool, and the review protocol was pre-registered with PROSPERO (Ref: CRD42022311494). RESULTS: We identified 16 qualitative studies exploring mental health-seeking behaviours in Middle East countries. Facilitators and barriers…

OBJECTIVES: Long-term health consequences of coronavirus disease (COVID-19), also known as "long COVID," has become a global health concern. In this systematic review, we aimed to synthesize the qualitative evidence on lived experiences of people living with long COVID that may inform health policymaking and practice. METHODS: We searched six major databases and additional sources and systematically retrieved relevant qualitative studies and conducted a meta-synthesis of key findings using the Joanna Briggs Institute (JBI) guidelines and reporting standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist. RESULTS: We found 15 articles representing 12 studies out of 619 citations from different sources. These studies provided 133 findings that were categorized into 55 categories. All categories were aggregated to the following synthesized findings: living with complex physical health problems, psychosocial crises of long COVID, slow recovery and rehabilitation, digital resources and information management, changes in social support, and…

The relationship between conscious experience and brain activity has intrigued scientists and philosophers for centuries. In the last decades, several theories have suggested different accounts for these relationships. These theories have developed in parallel, with little to no cross-talk among them. To advance research on consciousness, we established an adversarial collaboration between proponents of two of the major theories in the field, Global Neuronal Workspace and Integrated Information Theory. Together, we devised and preregistered two experiments that test contrasting predictions of these theories concerning the location and timing of correlates of visual consciousness, which have been endorsed by the theories' proponents. Predicted outcomes should either support, refute, or challenge these theories. Six theory-impartial laboratories will follow the study protocol specified here, using three complementary methods: Functional Magnetic Resonance Imaging (fMRI), Magneto-Electroencephalography (M-EEG), and intracranial electroencephalography (iEEG). The study protocol will…

PURPOSE: To evaluate the efficacy of a myopia control spectacle lens (DIMS) at slowing the progression of myopia in a population of European children in comparison with 0.01% atropine and combined DIMS and atropine. METHODS: The study was a non-randomised experimenter-masked prospective controlled observational study of individuals aged 6-18 years with progressing myopia but no ocular pathology. Participants were allocated, according to patient/parent choice, to receive 0.01% atropine eyedrops, DIMS (Hoya® MiyoSmart®) spectacles, combined atropine+DIMS or single vision spectacle lenses (control group). The key outcome variables, cycloplegic autorefraction spherical equivalent refraction (SER) and axial length (AL), were measured at baseline and after three, six, and 12 months. RESULTS: Of the 146 participants (mean age 10.3y ±3.2), 53 received atropine, 30 DIMS spectacles, 31 atropine+DIMS, and 32 single vision control spectacles. Generalized linear mixed model analysis revealed for SER, whilst controlling for age and SER at baseline, at each stage all treatment groups had…

Machine learning methods are widely used within the medical field. However, the reliability and efficacy of these models is difficult to assess, making it difficult for researchers to identify which machine-learning model to apply to their dataset. We assessed whether variance calculations of model metrics (e.g., AUROC, Sensitivity, Specificity) through bootstrap simulation and SHapely Additive exPlanations (SHAP) could increase model transparency and improve model selection. Data from the England National Health Services Heart Disease Prediction Cohort was used. After comparison of model metrics for XGBoost, Random Forest, Artificial Neural Network, and Adaptive Boosting, XGBoost was used as the machine-learning model of choice in this study. Boost-strap simulation (N = 10,000) was used to empirically derive the distribution of model metrics and covariate Gain statistics. SHapely Additive exPlanations (SHAP) to provide explanations to machine-learning output and simulation to evaluate the variance of model accuracy metrics. For the XGBoost modeling method, we observed (through…

Flux balance analysis (FBA) remains one of the most used methods for modeling the entirety of cellular metabolism, and a range of applications and extensions based on the FBA framework have been generated. Dynamic flux balance analysis (dFBA), the expansion of FBA into the time domain, still has issues regarding accessibility limiting its widespread adoption and application, such as a lack of a consistently rigid formalism and tools that can be applied without expert knowledge. Recent work has combined dFBA with enzyme-constrained flux balance analysis (decFBA), which has been shown to greatly improve accuracy in the comparison of computational simulations and experimental data, but such approaches generally do not take into account the fact that altering the enzyme composition of a cell is not an instantaneous process. Here, we have developed a decFBA method that explicitly takes enzyme change constraints (ecc) into account, decFBAecc. The resulting software is a simple yet flexible framework for using genome-scale metabolic modeling for simulations in the time domain that has full…

BACKGROUND: Breast cancer is known as one of the most common diseases among women, the psychological consequences of which are common in women and affect various aspects of their lives, so this study aims to investigate the prevalence of depression among women with breast cancer globally. METHOD: The present meta-analysis was performed by searching for keywords related to breast cancer and depression in 4 main databases: PubMed, Embase, Web of Sciences and Scopus in the period of January 2000 to November 2021 and the results of the study using R and CMA software were analyzed. RESULTS: A total of 71 studies were selected in English and the results of the analysis showed that the prevalence of depression in women with breast cancer is 30.2%, with Pakistan having the highest (83%) prevalence of depression and Taiwan having the lowest (8.3%). And in the WHO regions, EMRO region had the highest (49.7%) rate and SEARO region had the lowest (23%) prevalence of depression. Also, with increasing age, the prevalence of depression among women with breast cancer increases. CONCLUSION:…

One of the biggest challenges to be addressed in world agriculture is low nitrogen (N) use efficiency (<40%). To address this issue, researchers have repeatedly underlined the need for greater emphasis on the development and promotion of energy efficient, and environmentally sound novel fertilizers, in addition to improved agronomic management to augment nutrient use efficiency for restoring soil fertility and increasing farm profit. Hence, a fixed plot field experiment was conducted to assess the economic and environmental competency of conventional fertilizers with and without nano-urea (novel fertilizer) in two predominant cropping systems viz., maize-wheat and pearl millet-mustard under semi-arid regions of India. Result indicates that the supply of 75% recommended N with conventional fertilizer along with nano-urea spray (N75PK+nano-urea) reduced the energy requirement by ~8-11% and increased energy use efficiency by ~6-9% over 100% nitrogen through prilled urea fertilizer (business as usual). Furthermore, the application of N75PK+ nano-urea exhibited ~14% higher economic…

OBJECTIVES: The effectiveness of early childhood education and care (ECEC) programs for children's development in various domains is well documented. Adding to existing meta-analyses on associations between the quality of ECEC services and children's developmental outcomes, the present meta-analysis synthesizes the global literature on structural characteristics and indicators of process quality to test direct and moderated effects of ECEC quality on children's outcomes across a range of domains. DESIGN: A systematic review of the literature published over a 10-year period, between January 2010 and June 2020 was conducted, using the databases PsychInfo, Eric, EbscoHost, and Pubmed. In addition, a call for unpublished research or research published in the grey literature was sent out through the authors' professional network. The search yielded 8,932 articles. After removing duplicates, 4,880 unique articles were identified. To select articles for inclusion, it was determined whether studies met eligibility criteria: (1) study assessed indicators of quality in center-based ECEC…

INTRODUCTION: Artificial intelligence (AI) has the potential to transform clinical decision-making as we know it. Powered by sophisticated machine learning algorithms, clinical decision support systems (CDSS) can generate unprecedented amounts of predictive information about individuals' health. Yet, despite the potential of these systems to promote proactive decision-making and improve health outcomes, their utility and impact remain poorly understood due to their still rare application in clinical practice. Taking the example of AI-powered CDSS in stroke medicine as a case in point, this paper provides a nuanced account of stroke survivors', family members', and healthcare professionals' expectations and attitudes towards medical AI. METHODS: We followed a qualitative research design informed by the sociology of expectations, which recognizes the generative role of individuals' expectations in shaping scientific and technological change. Semi-structured interviews were conducted with stroke survivors, family members, and healthcare professionals specialized in stroke based in…

Recently, football has seen the creation of various novel, ubiquitous metrics used throughout clubs' analytics departments. These can influence many of their day-to-day operations ranging from financial decisions on player transfers, to evaluation of team performance. At the forefront of this scientific movement is the metric expected goals, a measure which allows analysts to quantify how likely a given shot is to result in a goal however, xG models have not until this point considered using important features, e.g., player/team ability and psychological effects, and is not widely trusted by everyone in the wider football community. This study aims to solve both these issues through the implementation of machine learning techniques by, modelling expected goals values using previously untested features and comparing the predictive ability of traditional statistics against this newly developed metric. Error values from the expected goals models built in this work were shown to be competitive with optimal values from other papers, and some of the features added in this study were…

INTRODUCTION: Surveys conducted internationally have found widespread interest in artificial intelligence (AI) amongst medical students. No similar surveys have been conducted in Western Australia (WA) and it is not known how medical students in WA feel about the use of AI in healthcare or their understanding of AI. We aim to assess WA medical students' attitudes towards AI in general, AI in healthcare, and the inclusion of AI education in the medical curriculum. METHODS: A digital survey instrument was developed based on a review of available literature and consultation with subject matter experts. The survey was piloted with a group of medical students and refined based on their feedback. We then sent this anonymous digital survey to all medical students in WA (approximately 1539 students). Responses were open from the 7th of September 2021 to the 7th of November 2021. Students' categorical responses were qualitatively analysed, and free text comments from the survey were qualitatively analysed using open coding techniques. RESULTS: Overall, 134 students answered one or more…

This study investigated the impact of the COVID-19 crisis on firm risk and performance in different country-level governance qualities in the MENA region. Analyzing a sample of 739 non-financial listed firms in 12 MENA countries for the period 2011-2020, we found that the COVID-19 crisis negatively impacted the performance of firms, especially low-performance firms, in most industries, and increased firm risk in general. Moreover, we found that national governance quality plays an important role in mitigating the negative impact of the COVID-19 crisis on firm operations. Specifically, national governance quality reduces the negative impact of the COVID-19 crisis on firm performance and the positive impact of the crisis on firm risk. The results are consistent with our contention that national governance quality contributes to creating a positive environment for businesses activities and reducing economic shocks.

Intimate Partner Violence (IPV) is a global public health issue, with notably high prevalence rates observed within Low-and Middle-Income Countries (LMICs). This systematic review aimed to examine the risk factors and consequences associated with IPV against women in LMICs. Following PRISMA guidelines, we conducted a systematic review using three databases: Web of Science, ProQuest Central, and Scopus, covering the period from January 2010 to January 2022. The study included only peer-reviewed journal articles in English that investigated IPV against women in LMICs. Out of 167 articles screened, 30 met the inclusion criteria, comprising both quantitative and mixed-method studies. Risk factors of IPV were categorised as: demographic risk factors (23 studies), family risk factors (9 studies), community-level factors (1 studies), and behavioural risk factors (14 studies), while consequences of IPV were categorised as mental health impacts (13 studies), physical impacts (5 studies), and societal impacts (4 studies). In this study, several risk factors were identified including lower…

An electrocardiograph (ECG) is widely used in diagnosis and prediction of cardiovascular diseases (CVDs). The traditional ECG classification methods have complex signal processing phases that leads to expensive designs. This paper provides a deep learning (DL) based system that employs the convolutional neural networks (CNNs) for classification of ECG signals present in PhysioNet MIT-BIH Arrhythmia database. The proposed system implements 1-D convolutional deep residual neural network (ResNet) model that performs feature extraction by directly using the input heartbeats. We have used synthetic minority oversampling technique (SMOTE) that process class-imbalance problem in the training dataset and effectively classifies the five heartbeat types in the test dataset. The classifier's performance is evaluated with ten-fold cross validation (CV) using accuracy, precision, sensitivity, F1-score, and kappa. We have obtained an average accuracy of 98.63%, precision of 92.86%, sensitivity of 92.41%, and specificity of 99.06%. The average F1-score and Kappa obtained were 92.63% and 95.5%…

Previous studies examining the impact of heritage tourism have focused on specific ecological, economic, political, or cultural impacts. Research focused on the extent to which heritage tourism fosters host communities' participation and enhances their capacity to flourish and support long-term health and wellbeing is lacking. This systematic review assessed the impact of heritage tourism on sustainable community development, as well as the health and wellbeing of local communities. Studies were included if they: (i) were conducted in English; (ii) were published between January 2000 and March 2021; (iii) used qualitative and/or quantitative methods; (iv) analysed the impact of heritage tourism on sustainable community development and/or the health and wellbeing of local host communities; and (v) had a full-text copy available. The search identified 5292 articles, of which 102 articles met the inclusion criteria. The included studies covering six WHO regions (Western Pacific, African, Americas, South-East Asia, European, Eastern Mediterranean, and multiple regions). These studies…

The topic of financial wellbeing is a current concern within the realm of personal and household finance. This study aims to examine the influence of cognitive factors, specifically financial literacy, mental budgeting, and self-control, on subjective financial wellbeing. While there exist multiple determinants of financial wellbeing, this research focuses on these particular cognitive factors. The present study aims to examine the mediating role of investment decision-making behavior in the association between cognitive factors and financial well-being. The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data collected from a sample of 449 Chinese university students, with the aim of assessing the empirical associations. The results indicate that financial literacy, mental budgeting, and self-control exert a favorable and noteworthy influence on an individual's financial well-being. The results indicate that individuals with a greater degree of financial literacy are more prone to achieving superior financial well-being. Moreover,…

Fifth-generation (5G)-enabled vehicular fog computing technologies have always been at the forefront of innovation because they support smart transport like the sharing of traffic data and cooperative processing in the urban fabric. Nevertheless, the most important factors limiting progress are concerns over message protection and safety. To cope with these challenges, several scholars have proposed certificateless authentication schemes with pseudonyms and traceability. These schemes avoid complicated management of certificate and escrow of key in the public key infrastructure-based approaches in the identity-based approaches, respectively. Nevertheless, problems such as high communication costs, security holes, and computational complexity still exist. Therefore, this paper proposes an efficient certificateless authentication called the ECA-VFog scheme for fog computing with 5G-assisted vehicular systems. The proposed ECA-VFog scheme applied efficient operations based on elliptic curve cryptography that is supported by a fog server through a 5G-base station. This work conducts a…

OBJECTIVES: To compare 2 frequently used area-level socioeconomic deprivation indices: the Area Deprivation Index (ADI) and the Social Vulnerability Index (SVI). METHODS: Index agreement was assessed via pairwise correlations, decile score distribution and mean comparisons, and mapping. The 2019 ADI and 2018 SVI indices at the U.S. census tract-level were analyzed. RESULTS: Index correlation was modest (R = 0.51). Less than half (44.4%) of all tracts had good index agreement (0-1 decile difference). Among the 6.3% of tracts with poor index agreement (≥6 decile difference), nearly 1 in 5 were classified by high SVI and low ADI scores. Index items driving poor agreement, such as high rents, mortgages, and home values in urban areas with characteristics indicative of socioeconomic deprivation, were also identified. CONCLUSIONS: Differences in index dimensions and agreement indicated that ADI and SVI are not interchangeable measures of socioeconomic deprivation at the tract level. Careful consideration is necessary when selecting an area-level socioeconomic deprivation measure that…

Speech deepfakes are artificial voices generated by machine learning models. Previous literature has highlighted deepfakes as one of the biggest security threats arising from progress in artificial intelligence due to their potential for misuse. However, studies investigating human detection capabilities are limited. We presented genuine and deepfake audio to n = 529 individuals and asked them to identify the deepfakes. We ran our experiments in English and Mandarin to understand if language affects detection performance and decision-making rationale. We found that detection capability is unreliable. Listeners only correctly spotted the deepfakes 73% of the time, and there was no difference in detectability between the two languages. Increasing listener awareness by providing examples of speech deepfakes only improves results slightly. As speech synthesis algorithms improve and become more realistic, we can expect the detection task to become harder. The difficulty of detecting speech deepfakes confirms their potential for misuse and signals that defenses against this threat are…

The sexual division of labor among human foraging populations has typically been recognized as involving males as hunters and females as gatherers. Recent archeological research has questioned this paradigm with evidence that females hunted (and went to war) throughout the Homo sapiens lineage, though many of these authors assert the pattern of women hunting may only have occurred in the past. The current project gleans data from across the ethnographic literature to investigate the prevalence of women hunting in foraging societies in more recent times. Evidence from the past one hundred years supports archaeological finds from the Holocene that women from a broad range of cultures intentionally hunt for subsistence. These results aim to shift the male-hunter female-gatherer paradigm to account for the significant role females have in hunting, thus dramatically shifting stereotypes of labor, as well as mobility.

BACKGROUND: The common cause of anemia in the general population is iron deficiency. Anemia is adversely affecting women of reproductive age and child health which in turn results in increased morbidity and maternal death, and also hamper social-economic growth. Reproductive women are more prone to anemia due to inadequate dietary intake and iron loss during menstruation and pregnancy. OBJECTIVES: This study examined the level and trend of anemia prevalence among the socially disadvantaged group (SC&ST, OBC) of women as compared to the other women (general) and identified the main responsible factors behind this. DATA AND METHODS: The data for this analysis has been taken from three rounds of National Family Health Survey (NFHS) conducted during 2005-2006 (NFHS 3), 2015-16 (NFHS 4) and 2019-21 (NFHS 5). Univariate and bivariate analyses were used to assess the level of anemia among reproductive age group women of different social groups. The regression model represents the relative risk of different confounding factors on the occurrence of anemia. GIS technique used for graphical…

Binaural beats are an auditory phenomenon that occurs when two tones of different frequencies, which are presented separately to each ear, elicit the sensation of a third tone oscillating at the difference frequency of the two tones. Binaural beats can be perceived in the frequency range of about 1-30 Hz, a range that coincides with the main human EEG frequency bands. The brainwave entrainment hypothesis, which assumes that external stimulation at a certain frequency leads to the brain's electrocortical activity oscillating at the same frequency, provides the basis for research on the effects of binaural beat stimulation on cognitive and affective states. Studies, particularly in more applied fields, usually refer to neuroscientific research demonstrating that binaural beats elicit systematic changes in EEG parameters. At first glance, however, the available literature on brainwave entrainment effects due to binaural beat stimulation appears to be inconclusive at best. The aim of the present systematic review is, thus, to synthesize existing empirical research. A sample of fourteen…

Masking entails hiding or concealing one's traits during social interactions. Research suggests that masking is particularly common for autistic people, though many non-autistic people also conceal aspects of their identity. Existing research has identified the key motivations and consequences of masking. No research to date, however, has considered how this might be affected by the social context in which masking is employed. This study compared the masking experiences of 285 autistic, 88 non-autistic neurodivergent and 99 neurotypical adults within a context in which masking is expected to be highly prevalent, namely the workplace. We used reflexive thematic analysis to explore the motivations, consequences, and contextual differences of workplace masking compared to other social contexts. Workplace masking was considered by participants in all three groups to be an adaptive response to a range of socially grounded workplace challenges and was usually employed as a strategy to safeguard against the threat of negative social and employment outcomes. Our non-autistic neurodivergent…

The resistance of plastic textiles to environmental degradation is of major concern as large portions of these materials reach the ocean. There, they persist for undefined amounts of time, possibly causing harm and toxicity to marine ecosystems. As a solution to this problem, many compostable and so-called biodegradable materials have been developed. However, to undergo rapid biodegradation, most compostable plastics require specific conditions that are achieved only in industrial settings. Thus, industrially compostable plastics might persist as pollutants under natural conditions. In this work, we tested the biodegradability in marine waters of textiles made of polylactic acid, a diffused industrially compostable plastic. The test was extended also to cellulose-based and conventional non-biodegradable oil-based plastic textiles. The analyses were complemented by bio-reactor tests for an innovative combined approach. Results show that polylactic acid, a so-called biodegradable plastic, does not degrade in the marine environment for over 428 days. This was also observed for the…

THP-1 monocyte, which can be differentiated into macrophages by PMA, is widely used in researches on pathogen infection and host innate immunity, but reports on the induction methods of PMA are different and lack a unified standard, and the transcriptome characteristics of macrophage compared with THP-1 cells remains unclear. In this research, we examined the differentiation effect of three factors including induction time, cell seeding density and PMA concentration by detecting the positive rate of CD14 expression. The concentration of 80ng/ml of PMA, the induction time of 24h, and the cell seeding density of 5×105 cells/ml, could respectively facilitates a relatively higher CD14 positive rate in THP-1 cells. Under this optimized conditions, the CD14 positive rate of THP-1 cells can reach 66.52%. Transcriptome sequencing showed that after the above induction, the mRNA expression of 3113 genes which were closely related to cell communication, signal transduction, cell response to stimulus, signaling receptor binding and cytokine activity were up-regulated, and the top 10 genes were…

To reduce adverse drug events (ADEs), hospitals need a system to support them in monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing (NLP), a computerized approach to analyze text data, has shown promising results for the purpose of ADE detection in the context of pharmacovigilance. However, a detailed qualitative assessment and critical appraisal of NLP methods for ADE detection in the context of ADE monitoring in hospitals is lacking. Therefore, we have conducted a scoping review to close this knowledge gap, and to provide directions for future research and practice. We included articles where NLP was applied to detect ADEs in clinical narratives within electronic health records of inpatients. Quantitative and qualitative data items relating to NLP methods were extracted and critically appraised. Out of 1,065 articles screened for eligibility, 29 articles met the inclusion criteria. Most frequent tasks included named entity recognition (n = 17; 58.6%) and relation extraction/classification (n = 15; 51.7%). Clinical involvement was reported in…

The nexus between green growth and ecological footprint is associated with crucial environmental implications. But this domain is not examined sufficiently and provides ambiguous findings. Furthermore, these studies have not addressed the role of natural resources, environmental innovation, and ICT in influencing ecological footprint. Our study analyzes the impact of green growth, ICT, environmental innovation, and natural resources on the ecological footprint ofemerging-7 and developed-7 economies. We employed CS-ARDL methodology to draw the long-run and short-run estimates of the said relationships. The obtained findings show that green growth, ICT, and environmental innovation reduce the ecological footprint in emerging economies in the long run. However, natural resources enhance the ecological footprint in emerging economies in the long run. Green growth, ICT, natural resources, and environmental innovation reduce the ecological footprint in the long run in developed economies. Based on these outcomes, the study recommends important policy suggestions.

Respondents select the type of psychological studies that they want to participate in consistence with their needs and individual characteristics, which creates an unintentional self-selection bias. The question remains whether participants attracted by psychological studies may have more psychological dysfunctions related to personality and affective disorders compared to the general population. We investigated (N = 947; 62% women) whether the type of the invitation (to talk about recent critical or regular life events) or the source of the data (either face-to-face or online) attracts people with different psychopathology. Most importantly, participants who alone applied to take part in paid psychological studies had more symptoms of personality disorders than those who had never before applied to take part in psychological studies. The current results strongly translate into a recommendation for either the modification of recruitment strategies or much greater caution when generalizing results for this methodological reason.

BACKGROUND: Surveys are an effective method for collecting a large quantity of data. However, incomplete responses to these surveys can affect the validity of the studies and introduce bias. Recent studies have suggested that monetary incentives may increase survey response rates. We intended to perform a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the effect of monetary incentives on survey participation. METHODS: A systematic search of electronic databases was conducted to collect studies assessing the impact of monetary incentives on survey participation. The primary outcome of interest was the response rates to incentives: money, lottery, and voucher. We used the Cochrane Collaboration tool to assess the risk of bias in randomized trials. We calculated the rate ratio (RR) with its 95% confidence interval (95% CI) using Review Manager Software (version 5.3). We used random-effects analysis and considered the data statistically significant with a P-value <0.05. RESULTS: Forty-six RCTs were included. A total of 109,648 participants from 14…

Advances in Artificial Intelligence (AI) are poised to transform society, national defense, and the economy by increasing efficiency, precision, and safety. Yet, widespread adoption within society depends on public trust and willingness to use AI-enabled technologies. In this study, we propose the possibility of an AI "trust paradox," in which individuals' willingness to use AI-enabled technologies exceeds their level of trust in these capabilities. We conduct a two-part study to explore the trust paradox. First, we conduct a conjoint analysis, varying different attributes of AI-enabled technologies in different domains-including armed drones, general surgery, police surveillance, self-driving cars, and social media content moderation-to evaluate whether and under what conditions a trust paradox may exist. Second, we use causal mediation analysis in the context of a second survey experiment to help explain why individuals use AI-enabled technologies that they do not trust. We find strong support for the trust paradox, particularly in the area of AI-enabled police surveillance, where…

Motivation as a catalyst for human conduct has been associated with lots of variables. However, self-efficacy and resilience as two important components of the individuals' psychological capital have not received enough scientific attention. This gets more significance considering the global COVID-19 pandemic with noticeable psychological consequences for the learners receiving online education. Hence, the current study proceeded to investigate the relationship between students' self-efficacy, resilience, and academic motivation in online education. To this aim, a convenience sample of 120 university students coming from two state universities in south of Iran participated in an online survey. The questionnaires used in the survey included the self-efficacy questionnaire, resilience questionnaire, and academic motivation questionnaire. Pearson correlation and multiple regression statistical methods were applied to analyze the obtained data. The results pointed to a positive relationship between self-efficacy and academic motivation. In addition, those with a higher degree of…

BACKGROUND: Carotid-femoral pulse wave velocity (cfPWV), the referent measure of aortic stiffness, is an established measure of vascular aging. In studies where cfPWV cannot be measured, alternative methods are needed to help promote research on vascular aging. This study examines the construct validity of a measure of PWV estimated from age and blood pressure (ePWV). The specific aims of the study are to: 1) explore the strength of association between ePWV, cfPWV, and other established measures of vascular aging; 2) examine the sensitivity and specificity of elevated ePWV (≥10m/s) in relation to elevated cfPWV (≥10m/s). METHODS: We measured cfPWV in two-hundred and fifty-two adults (mean age 57±12 years, 48% female) and calculated each participant's ePWV from their age and brachial blood pressure. Additional measures of vascular aging included: carotid intima-media thickness (cIMT); carotid stiffness measured as elastic modulus (cEp); and carotid augmentation index (cAIx). RESULTS: The correlations between cfPWV and measures of vascular aging were: cEp (r = 0.36), cIMT (r = 0.49),…

Deepfakes are a form of multi-modal media generated using deep-learning technology. Many academics have expressed fears that deepfakes present a severe threat to the veracity of news and political communication, and an epistemic crisis for video evidence. These commentaries have often been hypothetical, with few real-world cases of deepfake's political and epistemological harm. The Russo-Ukrainian war presents the first real-life example of deepfakes being used in warfare, with a number of incidents involving deepfakes of Russian and Ukrainian government officials being used for misinformation and entertainment. This study uses a thematic analysis on tweets relating to deepfakes and the Russo-Ukrainian war to explore how people react to deepfake content online, and to uncover evidence of previously theorised harms of deepfakes on trust. We extracted 4869 relevant tweets using the Twitter API over the first seven months of 2022. We found that much of the misinformation in our dataset came from labelling real media as deepfakes. Novel findings about deepfake scepticism emerged,…

With the threat of global warming, countries worldwide have enhanced their environmental campaigns on social media to increase users' willingness to take pro-environmental actions. In this study, we examined the direct and indirect effects of exposure to environmental information on Chinese young adults' (18-25 years old) intention to participate in environmental protection actions (e.g., recycling, using public transportation, involvement in an environmental group, and participation in eco-friendly events). Data were collected from a sample of 291 Chinese young adults using a web-based survey and a thoroughly designed questionnaire. The accumulated data were analyzed using SPSS version 20. Hierarchical regression and mediation analysis were performed for testing hypotheses. The results indicated that exposure to environmental information on Chinese social media platforms (WeChat and Xiaohongshu) positively affected individuals' intention to participate in pro-environmental behavior, perceived pro-environmental behavior control, pro-environmental attitude, and fear of victimization.…

This global umbrella review aimed to synthesise evidence of socioeconomic inequalities in the uptake of routine vaccinations and identify the mechanisms that may contribute to the association. To our knowledge, no attempt has been made to synthesise the global body of systematic reviews across a variety of vaccines, geographical locations, and measures of SES. The inclusion criteria were as follows: studies assessing vaccination uptake according to education, income, occupation/employment, and/or area-level deprivation; any country or universally recommended routine vaccination (according to the WHO); qualitative or quantitative reviews, published 2011-present. The searches were performed in eight databases. The screening process followed PRISMA-E guidelines, each stage was performed by one reviewer, and a 10% sample checked by a second for consistency. Included reviews underwent data extraction, quality appraisal (AMSTAR-2), and narrative synthesis according to country-context. After deduplication, 9,163 reports underwent title and abstract screening, leaving 119 full texts to be…

Respiratory macrophage subpopulations exhibit unique phenotypes depending on their location within the respiratory tract, posing a challenge to in vitro macrophage model systems. Soluble mediator secretion, surface marker expression, gene signatures, and phagocytosis are among the characteristics that are typically independently measured to phenotype these cells. Bioenergetics is emerging as a key central regulator of macrophage function and phenotype but is often not included in the characterization of human monocyte-derived macrophage (hMDM) models. The objective of this study was to expand the phenotype characterization of naïve hMDMs, and their M1 and M2 subsets by measuring cellular bioenergetic outcomes and including an expanded cytokine profile. Known markers of M0, M1 and M2 phenotypes were also measured and integrated into the phenotype characterization. Peripheral blood monocytes from healthy volunteers were differentiated into hMDM and polarized with either IFN-γ + LPS (M1) or IL-4 (M2). As expected, our M0, M1, and M2 hMDMs exhibited cell surface marker, phagocytosis,…

Inter-limb asymmetry refers to an imbalance in performance between the left and right limbs. Discrepancies throughout asymmetry research does not allow practitioners to confidently understand the effect of inter-limb asymmetries on athletic performance. Therefore, this review summarized the current literature using a meta-analytic approach, conforming to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines to identify the association between inter-limb asymmetry and athletic performance. A literature search using PubMed, Web of Science and SPORTDiscus databases yielded 11-studies assessing the effect of inter-limb asymmetries, measured via unilateral jump performance, on bilateral jump, change of direction (COD) and sprint performance in adult sports players. The quality of evidence was assessed via a modified Downs and Black checklist and in compliance with the Grading of Recommendations Assessment Development and Evaluation. Correlation coefficients were transformed via Fishers z (Zr), meta-analysed and then re-converted to correlation coefficients.…

BACKGROUND: Patients' expectations, as a central mechanism behind placebo and nocebo effects, are an important predictor of health outcomes. Yet, theoretically based generic assessment tools allowing for an integrated understanding of expectations across conditions and treatments are lacking. Based on the preliminary 35-item version, this study reports the development and validation of the Treatment Expectation Questionnaire (TEX-Q), a generic, multidimensional self-report scale measuring patients' expectations of medical and psychological treatments. METHODS: The TEX-Q was developed in a validation sample of n = 251 patients undergoing different treatments using exploratory factor analyses and item analyses, as well as analysis of convergent and divergent validity. Confirmatory factor analysis was conducted in an independent sample of n = 303 patients undergoing cancer treatment. Two-weeks test-retest reliability was assessed in n = 28 psychosomatic outpatients. RESULTS: Factor analyses revealed six theoretically founded stable subscales. The TEX-Q assesses expectations of…

Biodiversity loss is a major global challenge and minimizing extinction rates is the goal of several multilateral environmental agreements. Policy decisions require comprehensive, spatially explicit information on species' distributions and threats. We present an analysis of the conservation status of 14,669 European terrestrial, freshwater and marine species (ca. 10% of the continental fauna and flora), including all vertebrates and selected groups of invertebrates and plants. Our results reveal that 19% of European species are threatened with extinction, with higher extinction risks for plants (27%) and invertebrates (24%) compared to vertebrates (18%). These numbers exceed recent IPBES (Intergovernmental Platform on Biodiversity and Ecosystem Services) assumptions of extinction risk. Changes in agricultural practices and associated habitat loss, overharvesting, pollution and development are major threats to biodiversity. Maintaining and restoring sustainable land and water use practices is crucial to minimize future biodiversity declines.

BACKGROUND: Healthcare workers (HCWs) and healthcare students display high levels of vaccine hesitancy with impact on healthcare provision, patient safety, and health promotion. The factors related to vaccine hesitancy have been reported in several systematic reviews. However, this evidence needs to be synthesised, as interventions to reduce vaccination hesitancy in this population are needed. METHODS: This Umbrella Review aimed to explore the barriers and facilitators of vaccine hesitancy toward the COVID-19 vaccine for HCWs and healthcare students. The review was performed and reported in accordance with Joanna Briggs Institutes guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. A protocol was preregistered on PROSPERO (CRD42022327354). Eight databases were searched from November 2019 to 23rd May 2022 to identify any systematic reviews that explored factors associated with hesitancy towards the COVID-19 vaccine for HCWs or healthcare students. RESULTS: A total of 31 studies were included in the review. The majority of studies…

Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Currently, lung cancer diagnosis mainly relies on manual pathology section analysis, but the low efficiency and subjective nature of manual film reading can lead to certain misdiagnoses and omissions. With the continuous development of science and technology, artificial intelligence (AI) has been gradually applied to imaging diagnosis. Although there are reports on AI-assisted lung cancer diagnosis, there are still problems such as small sample size and untimely data updates. Therefore, in this study, a large amount of recent data was included, and meta-analysis was used to evaluate the value of AI for lung cancer diagnosis. With the help of STATA16.0, the value of AI-assisted lung cancer diagnosis was assessed by specificity, sensitivity, negative likelihood ratio, positive likelihood ratio, diagnostic ratio, and plotting the working characteristic curves of subjects. Meta-regression and subgroup analysis were used to investigate the value of AI-assisted lung cancer diagnosis. The results…

BACKGROUND: Artificial intelligence (AI) has gained momentum in behavioural health interventions in recent years. However, a limited number of studies use or apply such methodologies in the early detection of depression. A large population needing psychological-intervention is left unidentified due to barriers such as cost, location, stigma and a global shortage of health workers. Therefore, it is essential to develop a mass screening integrative approach that can identify people with depression at its early stage to avoid a potential crisis. OBJECTIVES: This study aims to understand the feasibility and efficacy of using AI-enabled chatbots in the early detection of depression. METHODS: We use Dialogflow as a conversation interface to build a Depression Analysisn (DEPRA) chatbot. A structured and authoritative early detection depression interview guide, which contains 27 questions combining the structured interview guide for the Hamilton Depression Scale (SIGH-D) and the inventory of depressive symptomatology (IDS-C), underpins the design of the conversation flow. To attain better…

Behavioral change has been increasingly recognized as a means for combating climate change. However, being concerned about climate problems and knowing the importance of individual actions in mitigating them is not enough for greater adherence to a more sustainable lifestyle. Psychological barriers such as (1) finding change unnecessary; (2) conflicting goals; (3) interpersonal relationships; (4) lack of knowledge; and (5) tokenism have been proposed as an explanation for the gap between environmental attitudes and actions. Yet, so far, this hypothesis has remained untested. This study aimed to assess if psychological barriers moderate the association between environmental attitudes and climate action. A sample of Portuguese individuals (N = 937) responded to a survey measuring climate change beliefs and environmental concerns as an index of environmental attitudes, a scale of self-reported frequency of environmental action, and finally, the dragons of inaction psychological barrier scale. Our participants revealed generally elevated positive environmental attitudes. These attitudes…

Cloud computing has now evolved as an unavoidable technology in the fields of finance, education, internet business, and nearly all organisations. The cloud resources are practically accessible to cloud users over the internet to accomplish the desired task of the cloud users. The effectiveness and efficacy of cloud computing services depend on the tasks that the cloud users submit and the time taken to complete the task as well. By optimising resource allocation and utilisation, task scheduling is crucial to enhancing the effectiveness and performance of a cloud system. In this context, cloud computing offers a wide range of advantages, such as cost savings, security, flexibility, mobility, quality control, disaster recovery, automatic software upgrades, and sustainability. According to a recent research survey, more and more tech-savvy companies and industry executives are recognize and utilize the advantages of the Cloud computing. Hence, as the number of users of the Cloud increases, so did the need to regulate the resource allocation as well. However, the scheduling of jobs in…

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process and helps to save the lives of a large number of people worldwide. Because they are non-invasive and spare patients from having an unpleasant biopsy, magnetic resonance imaging (MRI) scans are frequently employed to identify tumors. The manual identification of tumors is difficult and requires considerable time due to the large number of three-dimensional images that an MRI scan of one patient's brain produces from various angles. Moreover, the variations in location, size, and shape of the brain tumor also make it challenging to detect and classify different types of tumors. Thus, computer-aided diagnostics (CAD) systems have been proposed for the detection of brain tumors. In this paper, we proposed a novel unified end-to-end deep learning model named TumorDetNet for brain tumor detection and classification. Our TumorDetNet framework employs 48 convolution layers with leaky ReLU (LReLU) and ReLU activation functions to compute the most distinctive deep feature maps. Moreover,…

INTRODUCTION: Much of the data on BMI-mortality associations stem from 20th century U.S. cohorts. The purpose of this study was to determine the association between BMI and mortality in a contemporary, nationally representative, 21st century, U.S. adult population. METHODS: This was a retrospective cohort study of U.S. adults from the 1999-2018 National Health Interview Study (NHIS), linked to the National Death Index (NDI) through December 31st, 2019. BMI was calculated using self-reported height & weight and categorized into 9 groups. We estimated risk of all-cause mortality using multivariable Cox proportional hazards regression, adjusting for covariates, accounting for the survey design, and performing subgroup analyses to reduce analytic bias. RESULTS: The study sample included 554,332 adults (mean age 46 years [SD 15], 50% female, 69% non-Hispanic White). Over a median follow-up of 9 years (IQR 5-14) and maximum follow-up of 20 years, there were 75,807 deaths. The risk of all-cause mortality was similar across a wide range of BMI categories: compared to BMI of 22.5-24.9 kg/m2,…

Since the pandemic organizations have been required to build agility to manage risks, stakeholder engagement, improve capabilities and maturity levels to deliver on strategy. Not only is there a requirement to improve performance, a focus on employee engagement and increased use of technology have surfaced as important factors to remain competitive in the new world. Consideration of the strategic horizon, strategic foresight and support structures is required to manage critical factors for the formulation, execution and transformation of strategy. Strategic foresight and Artificial Intelligence modelling are ways to predict an organizations future agility and potential through modelling of attributes, characteristics, practices, support structures, maturity levels and other aspects of future change. The application of this can support the development of required new competencies, skills and capabilities, use of tools and develop a culture of adaptation to improve engagement and performance to successfully deliver on strategy. In this paper we apply an Artificial Intelligence model…

Purpureocillium lilacinum is a biocontrol Ascomycota fungus against various plant pathogens. In the present study, the efficacy of P. lilacinum was evaluated against a root-knot nematode, Meloidogyne incognita that infects eggplants. We performed an in vitro experiment in which the direct effects of P. lilacinum on the second-stage juvenile survival and egg hatching of M. incognita were tested at different exposure times. The results showed that P. lilacinum significantly reduced the rates of egg hatching and juvenile survival in a dose-dependent manner. Microscopic observation demonstrated that P. lilacinum directly penetrated the eggs and contacted the juveniles, indicating how P. lilacinum parasitizes M. incognita. We also performed a pot assay in which soil-grown eggplants were treated with P. lilacinum followed by inoculation with M. incognita. The results indicated that P. lilacinum effectively reduced the nematode population and the number of galls in plant roots. Interestingly, application of P. lilacinum resulted in significant enhancements in plant growth and biomass, even…

Communities of practice (CoPs) are defined as "groups of people who share a concern, a set of problems, or a passion about a topic, and who deepen their knowledge and expertise by interacting on an ongoing basis". They are an effective form of knowledge management that have been successfully used in the business sector and increasingly so in healthcare. In May 2023 the electronic databases MEDLINE and EMBASE were systematically searched for primary research studies on CoPs published between 1st January 1950 and 31st December 2022. PRISMA guidelines were followed. The following search terms were used: community/communities of practice AND (healthcare OR medicine OR patient/s). The database search picked up 2009 studies for screening. Of these, 50 papers met the inclusion criteria. The most common aim of CoPs was to directly improve a clinical outcome, with 19 studies aiming to achieve this. In terms of outcomes, qualitative outcomes were the most common measure used in 21 studies. Only 11 of the studies with a quantitative element had the appropriate statistical methodology to report…

BACKGROUND: eHealth has shown many benefits in health promotion and disease prevention. For engaging in and taking advantage of eHealth, eHealth literacy is essential. This systematic review aims to summarise and examine the existing evidence on determinants and outcomes of eHealth literacy in healthy adults. METHODS: We searched the relevant peer-reviewed articles published in English in six databases: MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and ProQuest. The inclusion criteria of the review were: 1) studies examining 'eHealth literacy', which refers to the ability to search, select, judge and apply online health information to address or solve health problems and to improve wellbeing; 2) the type of study included observational and experimental studies, mixed method studies or qualitative studies; 3) the participants were healthy adults; 4) the main outcomes were the determinants (i.e. influencing or associated factors) and outcomes (i.e. benefits and disadvantages) of eHealth literacy. Articles were assessed by two reviewers using the Joanna Briggs Institute critical…

BACKGROUND: Human Immunodeficiency Virus (HIV) significantly affects adolescents globally, with the sub-Saharan Africa (SSA) reporting a high burden of the disease. HIV testing, treatment, and retention to care are low among adolescents. We conducted a mixed-method systematic review to assess anti-retroviral therapy (ART) adherence; barriers and facilitators to ART adherence and ART outcomes among adolescents living with HIV and on ART in sub-Saharan Africa. METHODS: We conducted searches in four scientific databases for studies conducted between 2010 and March 2022 to identify relevant primary studies. Studies were screened against inclusion criteria and assessed for quality, and data was extracted. Meta-analysis of rates and odd ratios was used to plot the quantitative studies and meta-synthesis summarized the evidence from qualitative studies. RESULTS: A total of 10 431 studies were identified and screened against the inclusion/ exclusion criteria. Sixty-six studies met the inclusion criteria (41 quantitative, 16 qualitative, and 9 mixed-methods study designs). Fifty-three…

BACKGROUND: Community engagement (CE) is an essential component in a primary health care (PHC) and there have been growing calls for service providers to seek greater CE in the planning, design, delivery and evaluation of PHC services. This scoping review aimed to explore the underlying attributes, contexts and mechanisms in which community engagement initiatives contribute to improved PHC service delivery and the realisation of UHC. METHODS: PubMed, PsycINFO, CINAHL, Cochrane Library, EMBASE and Google Scholar were searched from the inception of each database until May 2022 for studies that described the structure, process, and outcomes of CE interventions implemented in PHC settings. We included qualitative and quantitative studies, process evaluations and systematic or scoping reviews. Data were extracted using a predefined extraction sheet, and the quality of reporting of included studies was assessed using the Mixed Methods Appraisal Tool. The Donabedian's model for quality of healthcare was used to categorise attributes of CE into "structure", "process" and "outcome". RESULTS:…

The land use and land cover (LULC) changes driven by the growing demands of mankind have a considerable effect on ecosystem services and functions. The study was carried out in the north-eastern highlands of Ethiopia to (1) analyze the effect of LULC changes between 1984 and 2021 and (2) assess the spatiotemporal variations in ecosystem service values (ESVs) and elasticity in response to LULC changes. Using Landsat imageries from 1984 to 2021, the spatiotemporal changes in LULC were evaluated with supervised image classification using maximum likelihood algorithm in ArcGIS software. Six LULC types were subsequently categorized, with overall accuracy and Kappa coefficients above 87% and 0.87, respectively. The ESVs were then estimated based on the Benefit Value Transfer (BVT) approach employing modified conservative value coefficients. The findings revealed a significant increase in cultivated land (9759.1ha) and built-up area (10174.41ha) during the stipulated periods and a drop in other land use types. The forest loss gradually decreased from 4.1% in the second period (1991-2001)…

BACKGROUND: The metabolic syndrome (MS) is a leading cause of death worldwide. Several studies have found MS to be prevalent in various African regions. However, no specific estimates of MS prevalence in African populations exist. The aim of this study was to estimate the overall prevalence of MS in the African populations. METHODS: A systematic review was conducted in PubMed, Web of Science, Africa Index Medicus, and African Journal Online Scopus to find studies published up to the 15th of August 2022. Pooled prevalence was calculated based on six diagnostic methods. The pooled prevalence of MS was estimated using a random-effects model. Our risk of bias analysis was based on the Hoy et al. tool. A Heterogeneity (I2) assessment was performed, as well as an Egger test for publication bias. PROSPERO number CRD42021275176 was assigned to this study. RESULTS: In total, 297 studies corresponding to 345 prevalence data from 29 African countries and involving 156 464 participants were included. The overall prevalence of MS in Africa was 32.4% (95% CI: 30.2-34.7) with significant…

Social networking is proliferating globally and in Vietnam, but this led to several negative aspects of adolescents' health, including physical activity, sleep quality, and depressive and anxiety symptoms. This study aimed to identify the relationship between social media usage and examine risk factors (Fear of Missing out and Risk of Neglect) on social media usage, and the overall quality of life and mental health among individuals actively using social media networks. An online cross-sectional study was conducted in three cities in Vietnam (Hanoi, Tuyen Quang, and Can Tho) from September through to October 2021. A structured questionnaire assessed for characteristics of social media use and other associated factors. 1891 participants were recruited, with 98.4% having access to social media. s. Factors like "PHQ-9 score", "Problematic Internet use", and "Time average used social media per day", were negatively associated with the EQ5D5L Index. By contrast, "Gender", and "Using smartphone" were positive factors of the EQ5D5L Index. "FOMO score" and "self-harm and suicide" were…

Artificial intelligence (AI) is widely used in the field of education at present, but people know little about its possible impacts, especially on the physical and mental development of the educated. It is important to explore the possible impacts of the application of artificial intelligence in education (AIEd) in order to avoid the possible adverse effects. Prior research has focused on theory to the exclusion of the psychological impact of AIEd, and the empirical research was relatively lacking. This study aimed to identify the influence of AIEd on adolescents' social adaptability via social support. A total of 1332 students were recruited using random sampling from 13 Artificial Intelligence Curriculum Reform Experimental Schools in Guangzhou, Southern China, completed the survey. There were 342 primary school students (Meanage = 10.6), 351 junior high school students (Meanage = 13.1), and 639 senior high school students (Meanage = 15.8). Results showed that AIEd has a negative impact on adolescents' social adaptability, and is significantly negatively correlated with social…

The construct of epistemic trust has received much consideration in recent psychological literature, even though mainly from a theoretical perspective. The overall aim of this study was to validate the first self-report measure of epistemic trust-the Epistemic Trust, Mistrust, and Credulity Questionnaire (ETMCQ)-in an Italian sample. Our primary goal was to test the factorial validity of the instrument, also exploring the influence of age, gender, and level of education on epistemic trust (Study 1, n = 843). Secondarily, we investigated the associations between epistemic trust, mistrust, credulity, and other aspects of psychological functioning, as well as with the presence of adverse childhood experiences in a smaller number of participants (Study 2, n = 445). Besides the ETMCQ, the survey included an ad hoc questionnaire investigating socio-demographic characteristics and self-report measures of reflective functioning, mentalized affectivity, traumatic experiences, attachment, and psychological symptoms. Statistical analysis showed a three-factor hierarchical structure similar to…

OBJECTIVES: This systematic review aimed to evaluate the association between smartphone addiction and sleep in medical students. The secondary outcomes included the prevalence of smartphone addiction, duration and purpose of its use, prevalence of poor sleep, duration and quality of sleep. METHODS: The authors searched PubMed, Cochrane Library, Embase, PsycINFO and CINAHL databases, from inception of each database to October 2022. Quantitative studies in the English language on smartphone addiction and sleep in students studying Western Medicine were included. The Rayyan application was used for title-abstract screening, and Joanna Briggs Institute (JBI) critical appraisal checklist to assess the risk of bias. Heterogeneity tests and meta-synthesis of data were performed using the meta-package in R software. Data on the activities used on the smartphone was synthesized qualitatively. RESULTS: A total of 298 abstracts were initially assessed for inclusion eligibility: 16 of them were eventually appraised, covering 9466 medical students comprising 3781 (39.9%) males and 5161 (54.5%)…

What is the reality of the misophonic experience in the general population? This is a study on misophonia in a large sample, representative of the UK general population. The study utilises a multidimensional psychometric tool, the S-Five, to study the intensity of the triggering misophonic sounds in everyday activities, the emotions/feelings related to them, and the norms of the key components of the misophonic experience: internalising and externalising appraisals, perceived threat and avoidance behaviours, outbursts, and the impact on functioning. Based on the S-Five scores and a semi-structured interview delivered by clinicians who specialise in misophonia, the estimated prevalence of people for whom symptoms of misophonia cause a significant burden in their life in the UK was estimated to be 18%. The psychometric properties of the S-Five in the UK general population were also evaluated and differences across gender and age were explored. Our results show that the five-factor structure is reproduced, and that the S-Five is a reliable and valid scale for the measurement of the…

Several studies applying Machine Learning to deception detection have been published in the last decade. A rich and complex set of settings, approaches, theories, and results is now available. Therefore, one may find it difficult to identify trends, successful paths, gaps, and opportunities for contribution. The present literature review aims to provide the state of research regarding deception detection with Machine Learning. We followed the PRISMA protocol and retrieved 648 articles from ACM Digital Library, IEEE Xplore, Scopus, and Web of Science. 540 of them were screened (108 were duplicates). A final corpus of 81 documents has been summarized as mind maps. Metadata was extracted and has been encoded as Python dictionaries to support a statistical analysis scripted in Python programming language, and available as a collection of Jupyter Lab Notebooks in a GitHub repository. All are available as Jupyter Lab Notebooks. Neural Networks, Support Vector Machines, Random Forest, Decision Tree and K-nearest Neighbor are the five most explored techniques. The studies report a detection…

Artificial Intelligence (AI) is increasingly influential across various sectors, including healthcare, with the potential to revolutionize clinical practice. However, risks associated with AI adoption in medicine have also been identified. Despite the general understanding that AI will impact healthcare, studies that assess the perceptions of medical doctors about AI use in medicine are still scarce. We set out to survey the medical doctors licensed to practice medicine in Portugal about the impact, advantages, and disadvantages of AI adoption in clinical practice. We designed an observational, descriptive, cross-sectional study with a quantitative approach and developed an online survey which addressed the following aspects: impact on healthcare quality of the extraction and processing of health data via AI; delegation of clinical procedures on AI tools; perception of the impact of AI in clinical practice; perceived advantages of using AI in clinical practice; perceived disadvantages of using AI in clinical practice and predisposition to adopt AI in professional activity. Our…

The goal of cancer screening is to detect disease at an early stage when treatment may be more effective. Cancer screening in dogs has relied upon annual physical examinations and routine laboratory tests, which are largely inadequate for detecting preclinical disease. With the introduction of non-invasive liquid biopsy cancer detection methods, the discussion is shifting from how to screen dogs for cancer to when to screen dogs for cancer. To address this question, we analyzed data from 3,452 cancer-diagnosed dogs to determine the age at which dogs of certain breeds and weights are typically diagnosed with cancer. In our study population, the median age at cancer diagnosis was 8.8 years, with males diagnosed at younger ages than females, and neutered dogs diagnosed at significantly later ages than intact dogs. Overall, weight was inversely correlated with age at cancer diagnosis, and purebred dogs were diagnosed at significantly younger ages than mixed-breed dogs. For breeds represented by ≥10 dogs, a breed-based median age at diagnosis was calculated. A weight-based linear…

Lactate, which is synthesized as an end product by lactate dehydrogenase A (LDHA) from pyruvate during anaerobic glycolysis, has attracted attention for its energy metabolism and oxidant effects. A novel histone modification-mediated gene regulation mechanism termed lactylation by lactate was recently discovered. The present study examined the involvement of histone lactylation in undifferentiated cells that underwent differentiation into osteoblasts. C2C12 cells cultured in medium with a high glucose content (4500 mg/L) showed increases in marker genes (Runx2, Sp7, Tnap) indicating BMP-2-induced osteoblast differentiation and ALP staining activity, as well as histone lactylation as compared to those cultured in medium with a low glucose content (900 mg/L). Furthermore, C2C12 cells stimulated with the LDH inhibitor oxamate had reduced levels of BMP-2-induced osteoblast differentiation and histone lactylation, while addition of lactate to C2C12 cells cultured in low glucose medium resulted in partial restoration of osteoblast differentiation and histone lactylation. These results…

Australia's headspace initiative is world-leading in nation-wide youth mental healthcare reform for young people aged 12 to 25 years, now with 16 years of implementation. This paper examines changes in the key outcomes of psychological distress, psychosocial functioning, and quality of life for young people accessing headspace centres across Australia for mental health problems. Routinely collected data from headspace clients commencing an episode of care within the data collection period, 1 April 2019 to 30 March 2020, and at 90-day follow-up were analysed. Participants came from the 108 fully-established headspace centres across Australia, and comprised 58,233 young people aged 12-25 years first accessing headspace centres for mental health problems during the data collection period. Main outcome measures were self-reported psychological distress and quality of life, and clinician-reported social and occupational functioning. Most headspace mental health clients presented with depression and anxiety issues (75.21%). There were 35.27% with a diagnosis: overall, 21.74% diagnosed…

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the…

We have recently been witnessing that our society is starting to heal from the impacts of COVID-19. The economic, social and cultural impacts of a pandemic cannot be ignored and we should be properly equipped to deal with similar situations in future. Recently, Monkeypox has been concerning the international health community with its lethal impacts for a probable pandemic. In such situations, having appropriate protocols and methodologies to deal with the outbreak efficiently is of paramount interest to the world. Early diagnosis and treatment stand as the only viable option to tackle such problems. To this end, in this paper, we propose an ensemble learning-based framework to detect the presence of the Monkeypox virus from skin lesion images. We first consider three pre-trained base learners, namely Inception V3, Xception and DenseNet169 to fine-tune on a target Monkeypox dataset. Further, we extract probabilities from these deep models to feed into the ensemble framework. To combine the outcomes, we propose a Beta function-based normalization scheme of probabilities to learn an…

OBJECTIVE: This study aims to meta-analyze the impact of high-intensity functional training on athletes' physical fitness and sport-specific performance. METHODS: A systematic search was conducted in five well-known academic databases (PubMed, Scopus, Web of Science, EBSCOhost, and the Cochrane Library) up to July 1, 2023. The literature screening criteria included: (1) studies involving healthy athletes, (2) a HIFT program, (3) an assessment of outcomes related to athletes' physical fitness or sport-specific performance, and (4) the inclusion of randomized controlled trials. The Physical Therapy Evidence Database (PEDro) scale was used to evaluate the quality of studies included in the meta-analysis. RESULTS: 13 medium- and high-quality studies met the inclusion criteria for the systematic review, involving 478 athletes aged between 10 and 24.5 years. The training showed a small to large effect size (ES = 0.414-3.351; all p < 0.05) in improving upper and lower body muscle strength, power, flexibility, and sport-specific performance. CONCLUSION: High-intensity functional training…

This study aimed to report trends in the global burden of osteoarthritis (OA) from 1990 to 2019 and predict the trends in the following years based on Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. The study included reporting on the prevalence and incidence rates, as well as disability-adjusted life years (DALYs). Additionally, the age-standardized incidence rate (ASR) and Estimated Annual Percent Change (EAPC) were analyzed along with related factors, finally, Bayesian age-period-cohort (BAPC) analysis were utilized to predict the trends in the upcoming years. In 2019, globally, there were about 414.7 million (95%UI: 368.8 to 464.4 million) OA incident cases, with an age-standardized incidence rate (ASR) about 492.21 (95% UI:438.66 to 551.5) per 100000. And there were about 527.8 million (95% UI: 478.7 to 584.8 million) OA prevalent cases in 2019. The DALYs for OA increased to about 189.49 million (95%UI: 95.71 to 376.60 million) from 1990 to 2019 (EAPC:0.14%; 95%CI: 0.12% to 0.16%). There was a positive association between ASR and Socio-demographic index…

BACKGROUND: Loneliness is a highly relevant public mental health issue. This work presents the validation of a single-item measure of loneliness and its subjective experience: "I am frequently alone/have few contacts". It can be used in large-scale population surveys where an economical assessment is of key importance. METHODS: Data was drawn from two representative German population surveys conducted in early and late 2020 (combined N = 4,984; 52.9% women; age: M = 48.39 years (SD = 17.88)). We determined the prevalence of loneliness in men and women across different age groups. In order to test concurrent validity, bivariate correlation analyses and Chi-square tests were performed. Convergent and discriminant validity were tested by investigating intercorrelations of the single-item measure of loneliness with another loneliness measure, other mental health outcomes, and associations with sociodemographic characteristics. RESULTS: Based on the single-item measure, 23.4% of participants reported some degree of loneliness, 3.4% among them severe loneliness. Comparisons with the LS-S…

Modern agricultural practices rely on synthetic fungicides to control plant disease, but the application of these fungicides has raised concerns regarding human and environmental health for many years. As a substitute, environmentally friendly fungicides have been increasingly introduced as alternatives to synthetic fungicides. However, the impact of these environmentally friendly fungicides on plant microbiomes has received limited attention. In this study, we used amplicon sequencing to compare the bacterial and fungal microbiomes in the leaves of powdery mildew-infected cucumber after the application of two environmentally friendly fungicides (neutralized phosphorous acid (NPA) and sulfur) and one synthetic fungicide (tebuconazole). The phyllosphere α-diversity of both the bacterial and fungal microbiomes showed no significant differences among the three fungicides. For phyllosphere β-diversity, the bacterial composition exhibited no significant differences among the three fungicides, but fungal composition was altered by the synthetic fungicide tebuconazole. While all three…

INTRODUCTION: In recent years, there has been increasing awareness of the lack of diversity among clinical trial participants. Equitable representation is key when testing novel therapeutic and non-therapeutic interventions to ensure safety and efficacy across populations. Unfortunately, in the United States (US), racial and ethnic minority populations continue to be underrepresented in clinical trials compared to their White counterparts. METHODS: Two webinars in a four-part series, titled "Health Equity through Diversity," were held to discuss solutions for advancing health equity through diversifying clinical trials and addressing medical mistrust in communities. Each webinar was 1.5 hours long, beginning with panelist discussions followed by breakout rooms where moderators led discussions related to health equity and scribes recorded each room's conversations. The diverse groups of panelists included community members, civic representatives, clinician-scientists, and biopharmaceutical representatives. Scribe notes from discussions were collected and thematically analyzed to…

The recurrence of mass coral bleaching and associated coral mortality in the past few decades have raised questions about the future of coral reef ecosystems. Although coral bleaching is well studied, our understanding of the spatial extent of bleaching events continues to be limited by geographical biases in data collection. To address this gap, we updated a previous observational database and spatially modelled the probability of past bleaching occurrence. First, an existing raw observational database was updated to cover the 1963-2017 period using searches of the academic and grey literature and outreach to coral reef monitoring organizations. Then, in order to provide spatially-explicit global coverage, we employed indicator kriging to spatially model the probability of bleaching occurrence each year from 1985 through 2017 at 0.05° x 0.05° lat-long resolution. The updated raw database has 37,774 observations, including 22,650 positive bleaching reports, three times that in the previous version. The spatial interpolation suggests that 71% of the world's coral reefs likely (>66%…