The 50 most-cited articles in F1000Research, 2022

Doublets are prevalent in single-cell sequencing data and can lead to artifactual findings. A number of strategies have therefore been proposed to detect them. Building on the strengths of existing approaches, we developed scDblFinder , a fast, flexible and accurate Bioconductor-based doublet detection method. Here we present the method, justify its design choices, demonstrate its performance on both single-cell RNA and accessibility (ATAC) sequencing data, and provide some observations on doublet formation, detection, and enrichment analysis. Even in complex datasets, scDblFinder can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives.

Background: The profession of pharmacy has evolved significantly in recent years in terms of professional service delivery. The aim of this study was to explore the current views of pharmacists in the United Arab Emirates (UAE) on pharmaceutical care services and the nature of barriers encountered in practice using qualitative and quantitative assessment methods. Methods: A cross-sectional study was conducted among hospital and community pharmacists (n = 305) between March and May 2021, using qualitative and quantitative assessment methods. In the qualitative phase, 15 interviews were conducted to explore five main criteria: patient information, inadequate patient counseling, prescribing errors prevention and identifying drug-related problems, lack of participation in health awareness programs, and barriers to pharmaceutical care implementation. In the quantitative phase, 305 consenting pharmacists completed a questionnaire on seven criteria: demographic profile, pharmacist-physician interaction, patient counseling assessment, patient reports of adverse drug events, pharmacist…

Background: The profession of pharmacy has evolved significantly in recent years in terms of professional service delivery. The aim of this study was to explore the current views of pharmacists in the United Arab Emirates (UAE) on pharmaceutical care services and the nature of barriers encountered in practice using qualitative and quantitative assessment methods. Methods: A cross-sectional study was conducted among hospital and community pharmacists (n = 305) between March and May 2021, using qualitative and quantitative assessment methods. In the qualitative phase, 15 interviews were conducted to explore five main criteria: patient information, inadequate patient counseling, prescribing errors prevention and identifying drug-related problems, lack of participation in health awareness programs, and barriers to pharmaceutical care implementation. In the quantitative phase, 305 consenting pharmacists completed a questionnaire on seven criteria: demographic profile, pharmacist-physician interaction, patient counseling assessment, patient reports of adverse drug events, pharmacist…

TBK1 is a serine-threonine protein kinase that has been linked to a number of diseases including amyotrophic lateral sclerosis and frontotemporal dementia. Reproducible research on TBK1 has been hampered by the lack of well characterized antibodies. In this study, we characterized 11 commercial antibodies for TBK1 for use in immunoblot, immunofluorescence and immunoprecipitation, using an isogeneic knock-out cell line as a control. We identify antibodies that appear specific for all three applications but invite the readers to interpret the present findings based on their own scientific expertise and use this report as a guide to select the most appropriate antibody for their specific needs.

Cow's milk is currently the most consumed product worldwide. However, due to various direct and indirect contamination sources, different chemical and microbiological contaminants have been found in cow's milk. This review details the main contaminants found in cow's milk, referring to the sources of contamination and their impact on human health. A comparative approach highlights the poor efficacy and effects of the pasteurization process with other methods used in the treatment of cow's milk. Despite pasteurization and related techniques being the most widely applied to date, they have not demonstrated efficacy in eliminating contaminants. New technologies have appeared as alternative treatments to pasteurization. However, in addition to causing physicochemical changes in the raw material, their efficacy is not total in eliminating chemical contaminants, suggesting the need for new research to find a solution that contributes to improving food safety.

Background : Work-related musculoskeletal disorders (MSD) are common in dentistry due to the prolonged static work involved during patient care, making dental health care personnel vulnerable to musculoskeletal complaints. We aimed to pool the prevalence estimates of MSD among various dental healthcare providers, including dentists, dental students, dental hygienists, and auxiliaries. Methods : A systematic search of five databases was performed (Scopus, Embase, CINAHL, Web of Science, Dentistry & Oral Sciences Source). The studies that reported the prevalence of MSD among dental healthcare workers and those written in English were selected. Screening and data extraction were performed by two review authors independently. Discrepencies were resolved by another review author. Risk of bias assessment was done using a nine-item questionnaire developed by Hoy et al . Pooled estimates were calculated using meta-analysis of proportions (random effects model). Results : Among the 3090 publications screened, 234 publications were included for full-text screening. Meta-analysis was performed…

Avian influenza (AI) is a zoonotic viral endemic disease that affects poultry, swine, and mammals, including humans. Highly pathogenic avian influenza (HPAI) is caused by influenza type A virus subtypes H5, and H7 which are naturally carried by a wild bird and often affect domestic poultry. Avian influenza (AI) is a major problem worldwide that causes significant economic losses in the poultry sector. Since 2003, the widespread H5N1 HPAI in poultry has led to high mortalities resulting in huge economic losses in the poultry sector in Indonesia. Domestic poultry is a key source of income that contributes to economic growth, both directly and indirectly, by reducing poverty among the people living in rural communities. Furthermore, in many developing countries, including Indonesia, rural people meet a portion of their food needs through backyard poultry. Nevertheless, this sector is strongly affected by biosecurity hazards, particularly in Indonesia by HPAI infections. Avian influenza (AI), subtype H5N1 has zoonotic significance, posing major risks to public health and poultry. Due to…

Background: This review aims to investigate the association of sex with the risk of multiple COVID-19 health outcomes, ranging from infection to death. Methods: Pubmed and Embase were searched through September 2020. We considered studies reporting sex and coronavirus disease 2019 (COVID-19) outcomes. Qualitative and quantitative data were extracted using standardised electronic data extraction forms with the assessment of Newcastle Ottawa Scale for risk of bias. Pooled trends in infection, hospitalization, severity, intensive care unit (ICU) admission and death rate were calculated separately for men and women and subsequently random-effects meta-analyses on relative risks (RR) for sex was performed. Results: Of 10,160 titles, 229 studies comprising 10,417,452 patients were included in the analyses. Methodological quality of the included studies was high (6.9 out of 9). Men had a higher risk for infection with COVID-19 than women (RR = 1.14, 95%CI: 1.07 to 1.21). When infected, they also had a higher risk for hospitalization (RR = 1.33, 95%CI: 1.27 to 1.41), higher risk for severe…

Abstract Background: India is taking steps to provide Universal Health Coverage (UHC). Out-of-pocket (OOP) health care payment is the most important mechanism for health care payment in India. This study aims to investigate the effect of OOP health care payments on catastrophic health expenditures (CHE). Methods: Data from the National Sample Survey Organization, Social Consumption in Health 2014 and 2018 are used to investigate the effect of OOP health expenditure on household welfare in India. Three aspects of catastrophic expenditure were analyzed in this paper: (i) incidence and intensity of ‘catastrophic’ health expenditure, (ii) socioeconomic inequality in catastrophic health expenditures, and (iii) factors affecting catastrophic health expenditures. Results: The odds of incidence and intensity of CHE were higher for the poorer households. Using the logistic regression model, it was observed that the odds of incidence of CHE was higher among the households with at least one child aged less than 5 years, one elderly person, one secondary educated female member, and if at least…

Background: People are more aware of halal products in commodity markets. Halal meat is an essential commodity for society in the Islamic commodity market in particular. The objective of this study was to analyze differences in research trends related to halal meat in published papers indexed by Scopus and Web of Science. The objective is to observe how was halal meat as commodity become the trend of research written by Indonesian authors, as well as what was the novelty of the research trend related to such tiopic. Methods: This study used purposive sampling with a bibliometric approach in collecting the samples. The samples were published papers from the Scopus and Web of Science (SCI) databases from 2006 to 25 th October 2021. The were 154 samples found from cSopus and 50 samples in Web of Science (SCI). Analysis was performed by VOSviewer and biblioshiny. Results: Overall, 154 papers from Scopus and 50 from SCI were analyzed. Scopus and SCI exhibited different research trends. Moreover, papers from Scopus were dominated by Indonesian authors; those from SCI were not. The source…

Background : While the PRISMA flow diagram is widely used for reporting standard systematic reviews (SRs), it was not designed for capturing the results of continual searches for studies in living systematic reviews (LSRs). The objectives of this study are (1) to assess how published LSRs report on the flow of studies through the different phases of the review for the different updates; (2) to propose an approach to reporting on that flow. Methods : For objective 1, we identified all LSRs published up to April 2021. We abstracted information regarding their general characteristics and how they reported on search results. For objective 2, we based our proposal for tailored PRISMA approaches on the findings from objective 1, as well as on our experience with conducting Cochrane LSRs. Results: We identified 279 living publications relating to 76 LSRs. Of the 279 publications, 11% were protocols, 23% were base versions (i.e., the first version), 50% were partial updates (i.e., does not include all typical sections of an SR), and 16% were full updates (i.e., includes all typical sections…

Background : It is well known that all medical professions are linked to work stress, including dentistry, which is seen as facing high risk due to the nature of the job, especially the working conditions. This study aimed to assess the impact of stress and its influencing factors among dentists during the coronavirus disease 2019 (COVID-19) pandemic in Bahrain. Methods : A cross-sectional survey was designed to assess the impact of stress and its influencing factors among Bahraini dentists. A total of 306 participants were randomly selected from 1489 registered professionals in the NHRA (National Health Regulatory Authority Bahrain). Results : Out of 306 participants invited in the survey, 253 responded. Overall, the participants reported moderate stress. All the variables of the study showed different effects, but the highest stressor with a strong correlation was “fear of social isolation” (FI) at the significance level of 0.01 (β= 0.393, t= 5.090, p < 0.05= (0.000) with f 2 = 0.201 above 0.15 and less than 0.35, which was considered as a moderate effect size of approximately…

The RAS family of proteins is among the most frequently mutated genes in human malignancies. In ovarian cancer (OC), the most lethal gynecological malignancy, RAS , especially KRAS mutational status at codons 12, 13, and 61, ranges from 6–65% spanning different histo-types. Normally RAS regulates several signaling pathways involved in a myriad of cellular signaling cascades mediating numerous cellular processes like cell proliferation, differentiation, invasion, and death. Aberrant activation of RAS leads to uncontrolled induction of several downstream signaling pathways such as RAF-1/MAPK (mitogen-activated protein kinase), PI3K phosphoinositide-3 kinase (PI3K)/AKT, RalGEFs, Rac/Rho, BRAF (v-Raf murine sarcoma viral oncogene homolog B), MEK1 (mitogen-activated protein kinase kinase 1), ERK (extracellular signal-regulated kinase), PKB (protein kinase B) and PKC (protein kinase C) involved in cell proliferation as well as maintenance pathways thereby driving tumorigenesis and cancer cell propagation. KRAS mutation is also known to be a biomarker for poor outcome and chemoresistance…

Sufficiency measures are potentially decisive for the decarbonisation of energy systems but rarely considered in energy policy and modelling. Just as efficiency and renewable energies, the diffusion of demand-side solutions to climate change also relies on policy-making. Our extensive literature review of European and national sufficiency policies fills a gap in existing databases. We present almost 300 policy instruments clustered into relevant categories and publish them as "Energy Sufficiency Policy Database". This paper provides a description of the data clustering, the set-up of the database and an analysis of the policy instruments. A key insight is that sufficiency policy includes much more than bans of products or information tools leaving the responsibility to individuals. It is a comprehensive instrument mix of all policy types, not only enabling sufficiency action, but also reducing currently existing barriers. A policy database can serve as a good starting point for policy recommendations and modelling, further research is needed on barriers and demand-reduction…

Background: Solid waste from coffee depulping process threatens the organism in environment as it produces organic pollutants. Evidence suggested that coffee by-product could valorize owing to its potential as antioxidant sources. The aim of this systematic review was to evaluate antioxidant activity of coffee by-products obtained from different coffee variants (arabica and robusta) and processing methods. Methods: The systematic review was conducted as of May 29, 2021 for records published within the last ten years (2011–2021) using seven databases: Embase, Medline, BMJ, Web of Science, Science Direct, Cochrane, and PubMed. Data on type of specimen, processing methods, and antioxidant activities were collected based on PRISMA guidelines. Results: Our data suggested that aqueous extract was found to be the most common processing method used to obtain the antioxidant from various coffee by-products, followed by methanol and ethanol extract. A variety of antioxidant properties ranging from strong to low activity was found depending on the variety, type of coffee by-products (cascara,…

Background : Maternal depression and anxiety are significant public health concerns that play an important role in the health and well-being of mothers and children. The COVID-19 pandemic, the consequential lockdowns and related safety restrictions worldwide negatively affected the mental health of pregnant and postpartum women. Methods: This regional study aimed to develop a machine learning (ML) model for the prediction of maternal depression and anxiety. The study used a dataset collected from five Arab countries during the COVID-19 pandemic between July to December 2020. The population sample included 3569 women (1939 pregnant and 1630 postpartum) from five countries (Jordan, Palestine, Lebanon, Saudi Arabia, and Bahrain). The performance of seven machine learning algorithms was assessed for the prediction of depression and anxiety symptoms. Results : The Gradient Boosting (GB) and Random Forest (RF) models outperformed other studied ML algorithms with accuracy values of 83.3% and 83.2% for depression, respectively, and values of 82.9% and 81.3% for anxiety, respectively. The…

Background: This systematic literature review (SLR) study is on Islamic financial technology (FinTech) business trends and challenges. It follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. This research identifies the gaps in Islamic FinTech, which require further studies. Moreover, it highlights the issues raised during the coronavirus disease 2019 (COVID-19) pandemic. Methods: This study is based on the FinTech business model (BM) classifications by Lee & Shin and Imerman & Fabozzi. Furthermore, the set of challenges used in this study are adopted from research by Lee & Shin and Li & Xu. The Scopus database was used to collect data using nine keywords. Articles and review papers published between 2016 and 2022 were included. Studies that were not published in English, and those with no ranking journals were excluded. The results were presented using bibliometric analysis. Results: The results showed 36 articles discussing Islamic FinTech business trends and challenges, and most of these studies are conducted on FinTech crowdfunding…

Background: The increasing penetration of smartphones and the Internet in developing countries caused the rise of e-retail. Conversational commerce is highly increasing via interaction through messengers. To extract the benefits of both trends, companies have adopted messenger chatbots. These chatbots use Artificial intelligence and natural language processing to give live responses to the customer and assist online shopping on the messenger interface. This research aims to discover the factors that affect the use of messenger chatbots and their influence on attitude and behavior intention. Methods: The research methodology includes the Technology Acceptance Model (TAM) with the variables of perceived usefulness, perceived ease of use, consumer trust, and anthropomorphism. The authors used an online survey for collecting the responses from 192 respondents and analyzed structural equation modelling. Results: Customer trust has shown the most decisive influence on customer attitude followed by Perceived Usefulness, Perceived Ease of Use. Also, the use of chatbots to make online…

Background: The availability of urban forest is under serious threat, especially in developing countries where urbanization is taking place rapidly. Meanwhile, there are many classifier algorithms available to monitor the extent of the urban forest. However, we need to assess the performance of each classifier to understand its complexity and accuracy. Methods: This study proposes a novel procedure using R language with RStudio software to assess four different classifiers based on different numbers of training datasets to classify the urban forest within the campus environment. The normalized difference vegetation indices (NDVI) were then employed to compare the accuracy of each classifier. Results: This study found that the Extreme Gradient Boosting (XGBoost) classifier outperformed the other three classifiers, with an RMSE value of 1.56. While the Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) were in second, third, and fourth place with RMSE values of 4.33, 6.81, and 7.45 respectively. Conclusions: The XGBoost algorithm is the most suitable…

Background: Rheumatoid arthritis (RA) is a highly prevalent, chronic inflammatory condition of the synovial joints that affects approximately 1% of the global population. The pathogenesis of RA is predominantly inflammatory in nature, thereby accelerating the co-occurrence of other immunoinflammatory conditions such as atherosclerosis. Apart from traditional cardiovascular risk factors, RA patients possess a multitude of other factors that predispose them to early atherosclerotic disease. The aim of this systematic review is to assess the prevalence of premature atherosclerosis in RA patients and elucidate the role that proinflammatory cytokines, neutrophil extracellular traps, RA-related autoantibodies, and endothelial dysfunction play in the pathophysiology of RA-mediated atherosclerosis. We also discussed novel biomarkers that can be used to predict early atherosclerosis in RA. Methods: This review followed the PRISMA guidelines to select and analyze relevant articles. A literature search for articles was performed on February 25, 2022, through three research databases including…

Abstract Self-amplifying RNA (saRNA) vaccines are able to induce a higher antigen-specific immune response with a more cost-effective and rapid production process compared to plasmid DNA vaccines. saRNAs are synthesized through in vitro transcription (IVT) however; this process has mainly been optimized for relatively short mRNAs. Here, we optimized the IVT process for long saRNAs, approximately 9.4 kb through a design of experiment (DoE) approach to produce a maximal RNA yield and validated the optimal IVT method on various sizes of RNA. We found that magnesium has the highest impact on RNA yield with acetate ions enabling a higher yield than chloride ions. In addition, the interaction between magnesium and nucleoside triphosphates (NTPs) is highly essential for IVT. Further addition of sodium acetate (NaOAc) during IVT provided no added benefit in RNA yield. Moreover, pyrophosphatase was not essential for productive IVT. The optimal IVT method can be used to synthesize different lengths of RNA. These findings emphasize the ability to synthesize high quality and quantity of saRNA…

Background : The unfurling COVID-19 pandemic has uncovered the defenselessness of the Lebanese food system leading to serious implication in maintaining a healthy sustainable lifestyle. Aim : The main purpose of this study is to examine the impact of the COVID-19 pandemic on food consumption patterns and dietary diversity of the Lebanese people. Methods: The online survey, completed between April and June 2020, consisted of a cross-sectional study on 2282 Lebanese participants (mean age: 29.36±12.221, 80.9% women) that was part of a survey across 38 different countries conducted by De Backer, C. et al . A food frequency questionnaire was used to investigate the consumption patterns along with the calculation of the Food Consumption Score (FCS), a proxy indicator of dietary diversity. Data collected on cooking attitudes, shopping, and food stock identify the community mitigation measures. Results : Home isolation due to COVID-19 induced an increase in the consumption of legumes and pulses (3.2%, p-value=0.001) and whole wheat groups (2.8%, p-value=0.03). In contrast, a decrease of…

In contrast to traditional methods like real-time polymerase chain reaction, next-generation sequencing (NGS), and especially small RNA-seq, enables the untargeted investigation of the whole small RNAome, including microRNAs (miRNAs) but also a multitude of other RNA species. With the promising application of small RNAs as biofluid-based biomarkers, small RNA-seq is the method of choice for an initial discovery study. However, the presentation of specific quality aspects of small RNA-seq data varies significantly between laboratories and is lacking a common (minimal) standard. The miRNA NGS Discovery pipeline (miND) aims to bridge the gap between wet lab scientist and bioinformatics with an easy to setup configuration sheet and an automatically generated comprehensive report that contains all essential qualitative and quantitative results that should be reported. Besides the standard steps like preprocessing, mapping, visualization, and quantification of reads, the pipeline also incorporates differential expression analysis when given the appropriate information regarding sample…

Background: Traditionally, research integrity studies have focused on research misbehaviors and their explanations. Over time, attention has shifted towards preventing questionable research practices and promoting responsible ones. However, data on the prevalence of responsible research practices, especially open methods, open codes and open data and their underlying associative factors, remains scarce. Methods: We conducted a web-based anonymized questionnaire, targeting all academic researchers working at or affiliated to a university or university medical center in The Netherlands, to investigate the prevalence and potential explanatory factors of 11 responsible research practices. Results: A total of 6,813 academics completed the survey, the results of which show that prevalence of responsible practices differs substantially across disciplines and ranks, with 99 percent avoiding plagiarism in their work but less than 50 percent pre-registering a research protocol. Arts and humanities scholars as well as PhD candidates and junior researchers engaged less often in responsible…

The banking and financial sectors have witnessed a significant development recently due to financial technology (FinTech), and it has become an essential part of the financial system. Many factors helped the development of this sector, including the pandemics such as Covid-19, the considerable increasing market value of the FinTech sector worldwide, and new technologies such as blockchain, artificial intelligence, big data, cloud computing and mobile technology. Moreover, changes in consumer's preferences, especially the Z-generation (digital generation). FinTech shifted the traditional business models to mobile platforms characterized by ease of access and swift transactions. Mobile technology became the main backbone for FinTech innovations and acts as a channel to deliver FinTech services that overcome all geographical and timing barriers, thus enhancing financial inclusion. Mobile perceived Trust (MPT), or the trust in using financial business models via mobile technology, is a crucial factor in the FinTech context that has mediation effects on the intention and adoption of…

Background: Some firms with good growth opportunities and additional funds could have difficulties accessing external finance. One possible way to enhance their financial inclusion could be an exciting approach to planning the money reserve collected on a firm’s account. Methods: This article aims to disclose the introduction of financial logistics as the new theoretical field of management science. The authors present, in this paper, the key findings on the development of logistical models of an optimum money reserve calculation taking into account digital transformation and industry 4.0 technologies and optimization methods. Results: The monetary reserve models are analogies of models of storekeeping in supply chains. The specific area of the theoretical research of logistics is shown in this paper, which could be disclosed as the subject of financial logistics as a science. The authors consider the term “Financial Logistics” based on logistics theory and money demand. Conclusions: Authors suggest the methodology of studying the nature of both financial and material flows of…

Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Geospatial techniques, especially WebGIS, have even been widely used to visualize the data on…

Background Broiler chickens have properties as meat-producing poultry and produce meat with soft fiber quality. Broiler’s embryo needs to be given attention, especially against disease. The purpose of the study was to observe the trend of the research topic and external factors which could affect the embryo’s growth of broiler. Method s This study used meta-data from Scopus. There were 162 samples started from 2006-to 2022. The data were analyzed using a bibliometric method with two software, Vosviewer, and Biblioshiy from R studio. Result s It was found that the study of broiler chicken embryos had developed well, especially those related to genetics, disease, and also the immunity system. But the result showed that topics about the disease, viruses, and bacteria were more popular than topics about the gene. The result also showed that based on the importance and development of topics, the words such as “chicken”, “genes”, “development”, “effect”, growth”, and “control” had importance for the study and developed well in research. It means that genes influenced the growth of the…

Inflammation plays a critical role in the development and progression of chronic diseases like type 2 diabetes mellitus, coronary artery disease, and chronic obstructive pulmonary disease. Inflammatory responses are indispensable for pathogen control and tissue repair, but they also cause collateral damage. A chronically activated immune system and the resultant immune dysregulation mediated inflammatory surge may cause multiple negative effects, requiring tight regulation and dampening of the immune response to minimize host injury. While chronic diseases are characterized by systemic inflammation, the mechanistic relationship of neutrophils and lymphocytes to inflammation and its correlation with the clinical outcomes is yet to be elucidated. The neutrophil to lymphocyte ratio (NLR) is an easy-to-measure laboratory marker used to assess systemic inflammation. Understanding the mechanisms of NLR perturbations in chronic diseases is crucial for risk stratification, early intervention, and finding novel therapeutic targets. We investigated the correlation between NLR and prevalent…

Background; Heart attack prediction is one of the serious causes of morbidity in the world’s population. The clinical data analysis includes a very crucial disease i.e., cardiovascular disease as one of the most important sections for the prediction. Data Science and machine learning (ML) can be very helpful in the prediction of heart attacks in which different risk factors like high blood pressure, high cholesterol, abnormal pulse rate, diabetes, etc... can be considered. The objective of this study is to optimize the prediction of heart disease using ML. Methods: In this paper, we are presenting a machine learning-based heart attack prediction (ML-HAP) method in which the analysis of different risk factors and prediction for heart attacks is done using ML approaches of Support Vector Machines, Logistic Regression, Naïve Bayes and XGBoost. The data of heart disease symptoms has been collected from the UCI ML Repository and analysis has been performed on the data using ML methods. The focus has been on optimizing the prediction on the basis of different parameters. Results: XGBoost…

Atmospheric nitrogen fixation carried out by microorganisms has environmental and industrial importance, related to the increase of soil fertility and productivity. The present work proposes the development of a new high precision system that allows the recognition of amino acid sequences of the nitrogenase enzyme (NifH) as a promising way to improve the identification of diazotrophic bacteria. For this purpose, a database obtained from UniProt built a processed dataset formed by a set of 4911 and 4782 amino acid sequences of the NifH and non-NifH proteins respectively. Subsequently, the feature extraction was developed using two methodologies: (i) k-mers counting and (ii) embedding layers to obtain numerical vectors of the amino acid chains. Afterward, for the embedding layer, the data was crossed by an external trainable convolutional layer, which received a uniform matrix and applied convolution using filters to obtain the feature maps of the model. Finally, a deep neural network was used as the primary model to classify the amino acid sequences as NifH protein or not.…

bit is a collection of small scripts and programs that facilitate many common tasks in bioinformatics. It operates in a Unix-like command-line environment and is comprised of bash and python code. bit is openly available on GitHub, archived with Zenodo, and is conda installable. The package is useful for users who want to do things such as manipulate fasta files, calculate GC content, quickly summarize nucleotide assemblies, easily download assemblies from NCBI just based on accessions, pull amino-acid sequences from GenBank files, calculate Shannon uncertainty for columns in multiple sequence alignments, and more. The source code is hosted on GitHub: github.com/AstrobioMike/bit

Background : Coronavirus disease 2019 (COVID-19) requires mass immunization to control the symptoms and global spread of severe acute respiratory syndrome coronavirus 2. Data from developed countries reported a high prevalence of parental COVID-19 vaccine hesitancy. However, parental vaccine hesitancy data in countries with low and middle income are scarce. The goal of this study was to assess the prevalence of parental vaccine hesitancy and identify subgroups with higher odds of vaccine hesitancy. Methods: A cross-sectional study was conducted on parents of children aged <18 years from October 10, 2021, to October 31, 2021. Parents aged ≥18 years underwent face-to-face interviews in randomly selected places in Bangladesh using a vaccine hesitancy questionnaire. Predictors were identified using binary logistic regression analysis. Results: Data from 2633 eligible parents were analyzed. Overall, 42.8% reported COVID-19 vaccine hesitancy for their youngest child. The final model suggested that children's age, parent's age, religion, occupation, monthly household income, permanent…

The principal’s role as a leader is crucial in improving the teacher performance and student achievement. However, it still remains unknown what kinds of school leadership behaviors that are effective to improve teacher performance and student achievement. This study aims to determine the level of significance of the effect of (1) the quality of principal's leadership behaviors on teacher performance, (2) the quality of principal's leadership behaviors on student achievement, and (3) the teacher performance on student achievement.This study is a quantitative descriptive research. The study population was 317 teachers with 281 teachers as the samples. The data collection technique was carried out through questionnaires, participant observation, and teacher performance appraisals. The data analysis technique used the Structural Equation Modeling (SEM). The results of this study showed a significant (5%) influence between: (1) the quality of the principal's leadership behaviors on the teacher performance where the estimated rate was 0.89 with the value of -t = 3.23> 1.96. The higher…

Background: One of the vital issues in promoting the sustainable tourism industry in developing countries, including Azerbaijan, is the well-grounded selection of tourism sites. Applying traditional approaches as a solution to this task, does not provide a relevant result in all cases in these countries due to local specifics of the tourism, the incompleteness of statistical data, the high-level uncertainty of the internal and external environment, and the questionable reliability of the available information. Methods: Since the statistical data are limited, and conventional formalization tools used for uncertainty description do not consider the reliability degree of the data, it is suggested to make decisions based on the Z-extension of fuzzy logic. A Delphi panel with the expert group is conducted to obtain the information required for the model development. Fuzzy Z-information-based TOPSIS and PROMETHEE methods are applied for the problem solution. Within these approaches Z-number-based procedures of the decision matrix normalization, defining the distance between solutions and…

Abstract In order to automate the genome sequencing pipeline in our laboratory, we programmed a dual-arm anthropomorphic robot, the Robotic Biology Institute’s Maholo LabDroid, to perform organic solvent-based genomic DNA extraction from cell lysates. To the best of our knowledge, this is the first time that automation of phenol-chloroform extraction has been reported. We achieved routine extraction of high molecular weight genomic DNA (>100 kb) from diverse biological samples including algae cultured in sea water, bacteria, whole insects, and human cell lines. The results of pulse-field electrophoresis size analysis and the N50 sequencing metrics of reads obtained from Nanopore MinION runs verified the presence of intact DNA suitable for direct sequencing. We present the workflow that can be used to program similar robots and discuss the problems and solutions we encountered in developing the workflow. The protocol can be adapted to analogous methods such as RNA extraction, and there is ongoing work to incorporate further post-extraction steps such as library construction. This…

Background : Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations. Methods : Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software. Results : This paper described a…

Background : Cybercrime is a fast-growing digital crime and legislation falling behind with the fast-moving advancement of technology. One important factor projected by literature in combating cybercrime is legislation. In order to combat cybercrime, the role of cybercrime legislation is a challenge that has not been clearly studied before. This paper thus aims to recapitulate the literature on cybercrime legislation in combating cybercrime. The literature in this context emphasises on existing studies relating to cybercrime legislation and addressing the importance of adequate and efficient responses in place in order to combat cybercrime efficiently. Methods : This paper finds an extensive literature review using the “Preferred Reporting Items for Systematic Review and Meta-Analysis” method based on legislation to combat cybercrime and explains a systematic analysis of the legislation in most advanced countries in both technology and legal framework. The study was done by selecting keywords, validated by the experts to discover research trends of cybercrime legislation. A search…

Background: Evaluation of the knowledge about stroke in the general population is extremely vital as it prevents stroke development, limits complications, and achieves better quality of life. We assume that the general Lebanese population lacks awareness about stroke and its associated complications. This study aims to evaluate stroke knowledge and determine the factors associated with stroke awareness among the general Lebanese population. Methods: This cross-sectional study assessed respondents’ sociodemographic characteristics and the identification of risk factors, warning signs, stroke consequences, and early response to stroke symptoms. A total of 551 Lebanese adults without a history of stroke filled in an online self-reported questionnaire publicly shared on social applications. Logistic regression analysis was performed to identify the factors associated with poor knowledge of stroke. Results: Among the 551 participants enrolled, 403 (74.2%) were females and 312 (56.7%) were under 30 years of age. Females compared to males and employed compared to unemployed had…

BACKGROUND: Syndemics or synergies of cooccurring epidemics are widely studied across health and social sciences in recent years. METHODS: We conducted a meta-knowledge analysis of articles published between 2001 to 2020 in this growing field of academic scholarship. RESULTS: We found a total of 830 articles authored by 3025 authors, mostly from high-income countries. Publications on syndemics are gradually increasing since 2003, with rapid development in 2013. Each article was cited more than 15 times on average, and most (n = 604) articles were original studies. Syndemics research focused on several areas, including HIV/AIDS, substance abuse, mental health, gender minority stressors, racism, violence, chronic physical and mental disorders, food insecurity, social determinants of health, and coronavirus disease 2019. Moreover, biopsychosocial interactions between multiple health problems were studied across medical, anthropological, public health, and other disciplines of science. CONCLUSIONS: The limited yet rapidly evolving literature on syndemics informs transdisciplinary…

The respiratory tract is a compartmentalised and heterogenous environment. The nasopharynx and sinuses of the upper airways have distinct properties from the lungs and these differences may shape bacterial adaptation and evolution. Upper airway niches act as early colonisation sites for respiratory bacterial pathogens, including those, such as Pseudomonas aeruginosa , that can go on to establish chronic infection of the lungs in people with cystic fibrosis (CF). Despite the importance of upper airway environments in facilitating early adaptation to host environments, currently available in vitro models for study of respiratory infection in CF focus exclusively on the lungs. Furthermore, animal models, widely used to bridge the gap between in vitro systems and the clinical scenario, do not allow the upper and lower airways to be studied in isolation. We have developed a suite of culture media reproducing key features of the upper and lower airways, for the study of bacterial adaptation and evolution in different respiratory environments. For both upper and lower airway-mimicking…

Gene symbols are recognizable identifiers for gene names but are unstable and error-prone due to aliasing, manual entry, and unintentional conversion by spreadsheets to date format. Official gene symbol resources such as HUGO Gene Nomenclature Committee (HGNC) for human genes and the Mouse Genome Informatics project (MGI) for mouse genes provide authoritative sources of valid, aliased, and outdated symbols, but lack a programmatic interface and correction of symbols converted by spreadsheets. We present HGNChelper, an R package that identifies known aliases and outdated gene symbols based on the HGNC human and MGI mouse gene symbol databases, in addition to common mislabeling introduced by spreadsheets, and provides corrections where possible. HGNChelper identified invalid gene symbols in the most recent Molecular Signatures Database (MSigDB 7.0) and in platform annotation files of the Gene Expression Omnibus, with prevalence ranging from ~3% in recent platforms to 30-40% in the earliest platforms from 2002-03. HGNChelper is installable from CRAN.

Background: Vaccine apprehension poses a serious threat to global health. While there has been a tremendous global effort to create a vaccine against coronavirus disease 2019 (COVID-19), little is known about its reception in Iraq. Therefore, we sought to examine COVID-19 vaccine acceptance, hesitation, and related elements in the Iraqi population. Methods: Between the 19th of May and the 22nd of September 2021, a descriptive, cross-sectional web-based survey was conducted employing a quantitative approach. Respondents from both sexes aged 18 years and above who live in Iraq and agreed to participate were included. An anonymized online structured questionnaire was designed based on data from prior research on vaccine hesitation in general, and COVID-19 vaccination reluctance specifically. Results: A total of 1221 eligible participants from various regions in Iraq actively participated in the short web-based questionnaire. The overall acceptance rate of the COVID-19 vaccine was 56.2%, with a greater acceptance rate among younger male participants (p<0.05). Marital status had no…

Background : Caregivers play a central role in post-stroke patients' care. However, the role of and problems managed by caregivers have not been widely studied, particularly in Indonesia. This study aims to explore the roles and problems of caregivers in post- stroke patients’ care. Method : This was a qualitative study. Seven caregivers of post-stroke patients from the homecare clinic of Dr Sardjito General Hospital were purposely selected during January 2017 to June 2018. Focus group discussions were conducted to explore the roles and problems of caregiving. Results : Themes related to caregivers’ roles were: connecting patients with medical personnel and other family members, maintaining patients’ health conditions by fulfilling basic needs and assisting rehabilitation, as well as maintaining patients’ psychological conditions by encouraging conversation, telling jokes, or recreation. On the other hand, themes related to caregivers’ problems were: lack of knowledge caused by education inadequacy, underappreciated and unconcerned family, suboptimal service including limited…

Background : While the PRISMA 2020 statement is intended to guide the reporting of original systematic reviews, updated systematic reviews, and living systematic reviews (LSRs), its explanation and elaboration document notes that additional considerations for updated systematic reviews and LSRs may need to be addressed. This paper reports the protocol for developing an extension of the PRISMA 2020 statement for LSRs. Methods: We will follow the EQUATOR Network’s guidance for developing health research reporting guidelines. We will review the literature to identify possible items of the PRISMA 2020 checklist that need modification, as well as new items that need to be added. Then, we will survey representatives of different stakeholder groups for their views on the proposed modifications of the PRISMA 2020 checklist. We will summarize, present, and discuss the results of the survey in an online meeting, aiming to reach consensus on the content of the LSR extension. We will then draft the checklist, explanation and elaboration for each item, and flow diagram for the PRISMA 2020…

Background: iron and calcium dysmetabolism, with hyperferritinemia, hypoferremia, hypocalcemia and anemia have been documented in the majority of COVID-19 patients at later/worse stages. Furthermore, complementary to ACE2, both sialic acid (SA) molecules and CD147 proved relevant host receptors for SARS-CoV-2 entry, which explains the viral attack to multiple types of cells, including erythrocytes, endothelium and neural tissue. Several authors advocated that cell ferroptosis may be the core and final cell degenerative mechanism. Methods : a literature research was performed in several scientific search engines, such as PubMed Central, Cochrane Library, Chemical Abstract Service. More than 500 articles were retrieved until mid-December 2021, to highlight the available evidence about the investigated issues. Results : based on COVID-19 literature data, we have highlighted a few pathophysiological mechanisms, associated with virus-based cation dysmetabolism, multi-organ attack, mitochondria degeneration and ferroptosis. Our suggested elucidated pathological sequence is: a) spike…

Background : Food labeling is a fundamental educational tool for advocating for public awareness. It emphasizes knowledge of the nutrient content of food and thus directs the choice towards the healthiest food products. This cross-sectional survey aimed to assess the knowledge, attitudes, and practices (KAP) regarding nutrition label use in Lebanon through a valid questionnaire. Methods: Overall, 768 participants (mean age: 30.8 ±12, males: 60.2%) were recruited randomly between February and May 2020. We used word of mouth and social media to recruit our sample population. Results : Social media was the most accessed tool to attain nutrition information by responders (39.8%). More than half the participants expressed positive attitudes to check information related to sugars (66.4%), vitamins (64.9%), total fats (61.7%), proteins (59.1%), and calories (58.7%) on the food label. Expiry date, price, and brand name were the top three considerations while reading food labels. About half (46.5%) reported to “always” look at the food label. Responders reported reading labels related…

Background: The ongoing COVID-19 quarantine restrictions have caused multiple sharp decreases in activities associated with the movement of large masses of people. The economies of regions and cities that are critically dependent on tourist flows related to various segments have suffered. This research aims to provide an economic-mathematical model of smart cities externalities’ impact from the point of view of achieving social and environmental goals Methods: The objective of this study was to develop an algorithm for supporting decision-makers. Methods of mathematical modeling, statistical processing of data received in real-time, as well as methods for finding solutions by expansion into dynamic series are used, and the theory of mathematical games is applied. The theoretical mathematical model presented considers the statistical processing of data provided in real time referring to the performance indicators of megacities. Results: The activities of administrations and governments aimed at maintaining stability over the past two years have been aimed at reducing the negative…

Mass cytometry (CyTOF) has become a method of choice for in-depth characterization of tissue heterogeneity in health and disease, and is currently implemented in multiple clinical trials, where higher quality standards must be met. Currently, preprocessing of raw files is commonly performed in independent standalone tools, which makes it difficult to reproduce. Here, we present an R pipeline based on an updated version of CATALYST that covers all preprocessing steps required for downstream mass cytometry analysis in a fully reproducible way. This new version of CATALYST is based on Bioconductor’s SingleCellExperiment class and fully unit tested. The R-based pipeline includes file concatenation, bead-based normalization, single-cell deconvolution, spillover compensation and live cell gating after debris and doublet removal. Importantly, this pipeline also includes different quality checks to assess machine sensitivity and staining performance while allowing also for batch correction. This pipeline is based on open source R packages and can be easily be adapted to different study…

With the ongoing cost decrease of genotyping and sequencing technologies, accurate and fast phenotyping remains the bottleneck in the utilizing of plant genetic resources for breeding and breeding research. Although cost-efficient high-throughput phenotyping platforms are emerging for specific traits and/or species, manual phenotyping is still widely used and is a time- and money-consuming step. Approaches that improve data recording, processing or handling are pivotal steps towards the efficient use of genetic resources and are demanded by the research community. Therefore, we developed PhenoApp, an open-source Android app for tablets and smartphones to facilitate the digital recording of phenotypical data in the field and in greenhouses. It is a versatile tool that offers the possibility to fully customize the descriptors/scales for any possible scenario, also in accordance with international information standards such as MIAPPE (Minimum Information About a Plant Phenotyping Experiment) and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. Furthermore,…