The 100 most-cited articles in Scientific Reports, 2019

Abstract Polycyclic aromatic compounds (PACs) are known due to their mutagenic activity. Among them, 2-nitrobenzanthrone (2-NBA) and 3-nitrobenzanthrone (3-NBA) are considered as two of the most potent mutagens found in atmospheric particles. In the present study 2-NBA, 3-NBA and selected PAHs and Nitro-PAHs were determined in fine particle samples (PM 2.5) collected in a bus station and an outdoor site. The fuel used by buses was a diesel-biodiesel (96:4) blend and light-duty vehicles run with any ethanol-to-gasoline proportion. The concentrations of 2-NBA and 3-NBA were, on average, under 14.8 µg g −1 and 4.39 µg g −1 , respectively. In order to access the main sources and formation routes of these compounds, we performed ternary correlations and multivariate statistical analyses. The main sources for the studied compounds in the bus station were diesel/biodiesel exhaust followed by floor resuspension. In the coastal site, vehicular emission, photochemical formation and wood combustion were the main sources for 2-NBA and 3-NBA as well as the other PACs. Incremental lifetime cancer…

Community detection is often used to understand the structure of large and complex networks. One of the most popular algorithms for uncovering community structure is the so-called Louvain algorithm. We show that this algorithm has a major defect that largely went unnoticed until now: the Louvain algorithm may yield arbitrarily badly connected communities. In the worst case, communities may even be disconnected, especially when running the algorithm iteratively. In our experimental analysis, we observe that up to 25% of the communities are badly connected and up to 16% are disconnected. To address this problem, we introduce the Leiden algorithm. We prove that the Leiden algorithm yields communities that are guaranteed to be connected. In addition, we prove that, when the Leiden algorithm is applied iteratively, it converges to a partition in which all subsets of all communities are locally optimally assigned. Furthermore, by relying on a fast local move approach, the Leiden algorithm runs faster than the Louvain algorithm. We demonstrate the performance of the Leiden algorithm for…

The vertebrate gene repertoire is characterized by "cryptic" genes whose identification has been hampered by their absence from the genomes of well-studied species. One example is the Bmp16 gene, a paralog of the developmental key genes Bmp2 and -4. We focus on the Bmp2/4/16 group of genes to study the evolutionary dynamics following gen(om)e duplications with special emphasis on the poorly studied Bmp16 gene. We reveal the presence of Bmp16 in chondrichthyans in addition to previously reported teleost fishes and reptiles. Using comprehensive, vertebrate-wide gene sampling, our phylogenetic analysis complemented with synteny analyses suggests that Bmp2, -4 and -16 are remnants of a gene quartet that originated during the two rounds of whole-genome duplication (2R-WGD) early in vertebrate evolution. We confirm that Bmp16 genes were lost independently in at least three lineages (mammals, archelosaurs and amphibians) and report that they have elevated rates of sequence evolution. This finding agrees with their more "flexible" deployment during development; while Bmp16 has limited…

Functional genomics assays based on high-throughput sequencing greatly expand our ability to understand the genome. Here, we define the ENCODE blacklist- a comprehensive set of regions in the human, mouse, worm, and fly genomes that have anomalous, unstructured, or high signal in next-generation sequencing experiments independent of cell line or experiment. The removal of the ENCODE blacklist is an essential quality measure when analyzing functional genomics data.

Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model…

Spending time in natural environments can benefit health and well-being, but exposure-response relationships are under-researched. We examined associations between recreational nature contact in the last seven days and self-reported health and well-being. Participants (n = 19,806) were drawn from the Monitor of Engagement with the Natural Environment Survey (2014/15-2015/16); weighted to be nationally representative. Weekly contact was categorised using 60 min blocks. Analyses controlled for residential greenspace and other neighbourhood and individual factors. Compared to no nature contact last week, the likelihood of reporting good health or high well-being became significantly greater with contact ≥120 mins (e.g. 120-179 mins: ORs [95%CIs]: Health = 1.59 [1.31-1.92]; Well-being = 1.23 [1.08-1.40]). Positive associations peaked between 200-300 mins per week with no further gain. The pattern was consistent across key groups including older adults and those with long-term health issues. It did not matter how 120 mins of contact a week was achieved (e.g. one long vs. several shorter…

For forty years, there has been a widely held belief that over 2,000 years ago the Chinese Qin developed an advanced chromate conversion coating technology (CCC) to prevent metal corrosion. This belief was based on the detection of chromium traces on the surface of bronze weapons buried with the Chinese Terracotta Army, and the same weapons' very good preservation. We analysed weapons, lacquer and soils from the site, and conducted experimental replications of CCC and accelerated ageing. Our results show that surface chromium presence is correlated with artefact typology and uncorrelated with bronze preservation. Furthermore we show that the lacquer used to cover warriors and certain parts of weapons is rich in chromium, and we demonstrate that chromium on the metals is contamination from nearby lacquer after burial. The chromium anti-rust treatment theory should therefore be abandoned. The good metal preservation probably results from the moderately alkaline pH and very small particle size of the burial soil, in addition to bronze composition.

The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging problems. Here, we develop a deep learning algorithm that can accurately detect breast cancer on screening mammograms using an "end-to-end" training approach that efficiently leverages training datasets with either complete clinical annotation or only the cancer status (label) of the whole image. In this approach, lesion annotations are required only in the initial training stage, and subsequent stages require only image-level labels, eliminating the reliance on rarely available lesion annotations. Our all convolutional network method for classifying screening mammograms attained excellent performance in comparison with previous methods. On an independent test set of digitized film mammograms from the Digital Database for Screening Mammography (CBIS-DDSM), the best single model achieved a per-image AUC of 0.88, and four-model averaging improved the AUC to 0.91 (sensitivity: 86.1%, specificity: 80.1%). On an independent test set of…

The intensity of the heaviest extreme precipitation events is known to increase with global warming. How often such events occur in a warmer world is however less well established, and the combined effect of changes in frequency and intensity on the total amount of rain falling as extreme precipitation is much less explored, in spite of potentially large societal impacts. Here, we employ observations and climate model simulations to document strong increases in the frequencies of extreme precipitation events occurring on decadal timescales. Based on observations we find that the total precipitation from these intense events almost doubles per degree of warming, mainly due to changes in frequency, while the intensity changes are relatively weak, in accordance to previous studies. This shift towards stronger total precipitation from extreme events is seen in observations and climate models, and increases with the strength - and hence the rareness - of the event. Based on these results, we project that if historical trends continue, the most intense precipitation events observed today…

Abstract Mechanistic hypotheses about airborne infectious disease transmission have traditionally emphasized the role of coughing and sneezing, which are dramatic expiratory events that yield both easily visible droplets and large quantities of particles too small to see by eye. Nonetheless, it has long been known that normal speech also yields large quantities of particles that are too small to see by eye, but are large enough to carry a variety of communicable respiratory pathogens. Here we show that the rate of particle emission during normal human speech is positively correlated with the loudness (amplitude) of vocalization, ranging from approximately 1 to 50 particles per second (0.06 to 3 particles per cm 3 ) for low to high amplitudes, regardless of the language spoken (English, Spanish, Mandarin, or Arabic). Furthermore, a small fraction of individuals behaves as “speech superemitters,” consistently releasing an order of magnitude more particles than their peers. Our data demonstrate that the phenomenon of speech superemission cannot be fully explained either by the phonic…

Abstract In this study, we investigated lipopolysaccharide (LPS)-induced cognitive impairment and neuroinflammation in C57BL/6J mice by using behavioral tests, immunofluorescence, enzyme-linked immunosorbent assay (ELISA) and Western blot. We found that LPS treatment leads to sickness behavior and cognitive impairment in mice as shown in the Morris water maze and passive avoidance test, and these effects were accompanied by microglia activation (labeled by ionized calcium binding adaptor molecule-1, IBA-1) and neuronal cell loss (labeled by microtubule-associated protein 2, MAP-2) in the hippocampus. The levels of interleukin-4 (IL-4) and interleukin-10 (IL-10) in the serum and brain homogenates were reduced by the LPS treatment, while the levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), prostaglandin E2 (PGE 2 ) and nitric oxide (NO) were increased. In addition, LPS promoted the expression of cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) in the brain homogenates. The Western blot analysis showed that the nuclear factor kappa B (NF-κB)…

Humans interact with the oceans in diverse and profound ways. The scope, magnitude, footprint and ultimate cumulative impacts of human activities can threaten ocean ecosystems and have changed over time, resulting in new challenges and threats to marine ecosystems. A fundamental gap in understanding how humanity is affecting the oceans is our limited knowledge about the pace of change in cumulative impact on ocean ecosystems from expanding human activities - and the patterns, locations and drivers of most significant change. To help address this, we combined high resolution, annual data on the intensity of 14 human stressors and their impact on 21 marine ecosystems over 11 years (2003-2013) to assess pace of change in cumulative impacts on global oceans, where and how much that pace differs across the ocean, and which stressors and their impacts contribute most to those changes. We found that most of the ocean (59%) is experiencing significantly increasing cumulative impact, in particular due to climate change but also from fishing, land-based pollution and shipping. Nearly all…

Microplastic pollution caused by washing processes of synthetic textiles has recently been assessed as the main source of primary microplastics in the oceans. Therefore, understanding the effective contribution of the washing process of synthetic clothes to this environmental problem, is of great importance. In this study, wash trials at real scale were performed on commercial clothes by using a household washing machine in order to gain reliable data about the release of microplastics, and to identify possible influences of textile characteristics on the release. The wastewater was collected and filtered through subsequent filters with decreasing porosity, and the amount and dimensions of microfibres were determined. Microfibre release was analysed in relation to the nature and characteristics of the washed clothes. Results showed that microfibres released during washing range from 124 to 308 mg for kg of washed fabric depending from the type of washed garment that corresponds to a number of microfibres ranging from 640,000 to 1,500,000. Some textile characteristics, such as the…

Abstract Humans are potentially exposed to microplastics through food, drink, and air. The first two pathways have received quite some scientific attention, while little is known about the latter. We address the exposure of humans to indoor airborne microplastics using a Breathing Thermal Manikin. Three apartments were investigated, and samples analysed through FPA-µFTIR-Imaging spectroscopy followed by automatic analyses down to 11 µm particle size. All samples were contaminated with microplastics, with concentrations between 1.7 and 16.2 particles m −3 . Synthetic fragments and fibres accounted, on average, for 4% of the total identified particles, while nonsynthetic particles of protein and cellulose constituted 91% and 4%, respectively. Polyester was the predominant synthetic polymer in all samples (81%), followed by polyethylene (5%), and nylon (3%). Microplastics were typically of smaller size than nonsynthetic particles. As the identified microplastics can be inhaled, these results highlight the potential direct human exposure to microplastic contamination via indoor air.

Many studies have reported abnormal gut microbiota in individuals with Autism Spectrum Disorders (ASD), suggesting a link between gut microbiome and autism-like behaviors. Modifying the gut microbiome is a potential route to improve gastrointestinal (GI) and behavioral symptoms in children with ASD, and fecal microbiota transplant could transform the dysbiotic gut microbiome toward a healthy one by delivering a large number of commensal microbes from a healthy donor. We previously performed an open-label trial of Microbiota Transfer Therapy (MTT) that combined antibiotics, a bowel cleanse, a stomach-acid suppressant, and fecal microbiota transplant, and observed significant improvements in GI symptoms, autism-related symptoms, and gut microbiota. Here, we report on a follow-up with the same 18 participants two years after treatment was completed. Notably, most improvements in GI symptoms were maintained, and autism-related symptoms improved even more after the end of treatment. Important changes in gut microbiota at the end of treatment remained at follow-up, including significant…

In an attempt to control the mosquito-borne diseases yellow fever, dengue, chikungunya, and Zika fevers, a strain of transgenically modified Aedes aegypti mosquitoes containing a dominant lethal gene has been developed by a commercial company, Oxitec Ltd. If lethality is complete, releasing this strain should only reduce population size and not affect the genetics of the target populations. Approximately 450 thousand males of this strain were released each week for 27 months in Jacobina, Bahia, Brazil. We genotyped the release strain and the target Jacobina population before releases began for >21,000 single nucleotide polymorphisms (SNPs). Genetic sampling from the target population six, 12, and 27-30 months after releases commenced provides clear evidence that portions of the transgenic strain genome have been incorporated into the target population. Evidently, rare viable hybrid offspring between the release strain and the Jacobina population are sufficiently robust to be able to reproduce in nature. The release strain was developed using a strain originally from Cuba, then…

Over-exploitation of groundwater and marked changes in climate over the years have imposed immense pressure on the global groundwater resources. As demand of potable water increases across the globe for human consumption, agriculture and industrial uses, the need to evaluate the groundwater potential and productivity of aquifers also increases. In the recent years, geographic information system based studies have gained much prominence in groundwater exploration because it is rapid and will provide first - hand information on the resource for further developments. Therefore, the present study has been undertaken with an objective to delineate the groundwater potential of a small tropical river basin located in the western side of the Western Ghats in India as an example. A combination of geographical information system and analytical hierarchical process techniques (AHP) was used in the present study. A total of 12 thematic layers such as Geology, Geomorphology, Land Use/Land Cover, Lineament density, Drainage density, Rainfall, Soil, Slope, Roughness, Topographic Wetness Index,…

Labeled medical imaging data is scarce and expensive to generate. To achieve generalizable deep learning models large amounts of data are needed. Standard data augmentation is a method to increase generalizability and is routinely performed. Generative adversarial networks offer a novel method for data augmentation. We evaluate the use of CycleGAN for data augmentation in CT segmentation tasks. Using a large image database we trained a CycleGAN to transform contrast CT images into non-contrast images. We then used the trained CycleGAN to augment our training using these synthetic non-contrast images. We compared the segmentation performance of a U-Net trained on the original dataset compared to a U-Net trained on the combined dataset of original data and synthetic non-contrast images. We further evaluated the U-Net segmentation performance on two separate datasets: The original contrast CT dataset on which segmentations were created and a second dataset from a different hospital containing only non-contrast CTs. We refer to these 2 separate datasets as the in-distribution and…

Using aqueous cyanobacterial extracts in the synthesis of silver nanoparticle is looked as green, ecofriendly, low priced biotechnology that gives advancement over both chemical and physical methods. In the current study, an aqueous extract of Oscillatoria limnetica fresh biomass was used for the green synthesis of Ag-NPs, since O. limnetica extract plays a dual part in both reducing and stabilizing Oscillatoria-silver nanoparticles (O-AgNPs). The UV-Visible absorption spectrum, Fourier transforms infrared (FT-IR), transmission electron microscopy (TEM) and scanning electron microscope (SEM) were achieved for confirming and characterizing the biosynthesized O-AgNPs. TEM images detected the quasi-spherical Ag-NPs shape with diverse size ranged within 3.30-17.97 nm. FT-IR analysis demonstrated the presence of free amino groups in addition to sulfur containing amino acid derivatives acting as stabilizing agents as well as the presence of either sulfur or phosphorus functional groups which possibly attaches silver. In this study, synthesized Ag-NPs exhibited strong antibacterial…

Exosomes have received significant attention for their role in pathobiological processes and are being explored as a tool for disease diagnosis and management. Consequently, various isolation methods based on different principles have been developed for exosome isolation. Here we compared the efficacy of four kits from Invitrogen, 101Bio, Wako and iZON along with conventional ultracentrifugation-based method for exosome yield, purity and quality. Cell culture supernatant was used as an abundant source of exosomes, and exosome quantity, size-distribution, zeta-potential, marker-expression and RNA/protein quality were determined. The Invitrogen kit gave the highest yield but the preparation showed broader size-distribution likely due to microvesicle co-precipitation and had the least dispersion stability. Other preparations showed <150 nm size range and good stability. Preparation from iZON column; however, had a broader size-distribution in the lower size range suggestive of some impurities of non-vesicular aggregates. RNA quality from all preparations was comparable; however,…

Abstract Maize is a sensitive crop to drought and heat stresses, particularly at the reproductive stages of development. The present study investigated the individual and interactive effects of drought (50% field capacity) and heat (38 °C/30 °C) stresses on morpho-physiological growth, yield, nutrient uptake and oxidative metabolism in two maize hybrids i.e., ‘Xida 889’ and ‘Xida 319’. The stress treatments were applied at tasseling stage for 15 days. Drought, heat and drought + heat stress caused oxidative stress by the over-production of ROS (O 2− , H 2 O 2 , OH − ) and enhanced malondialdehyde contents, which led to reduced photosynthetic components, nutrients uptake and yield attributes. The concurrent occurrence of drought and heat was more severe for maize growth than the single stress. However, both stresses induced the metabolites accumulation and enzymatic and non-enzymatic antioxidants to prevent the oxidative damage. The performance of Xida 899 was more prominent than the Xida 319. The greater tolerance of Xida 889 to heat and drought stresses was attributed to strong…

The blood-brain barrier (BBB) has long limited therapeutic access to brain tumor and peritumoral tissue. In animals, MR-guided focused ultrasound (MRgFUS) with intravenously injected microbubbles can temporarily and repeatedly disrupt the BBB in a targeted fashion, without open surgery. Our objective is to demonstrate safety and feasibility of MRgFUS BBB opening with systemically administered chemotherapy in patients with glioma in a phase I, single-arm, open-label study. Five patients with previously confirmed or suspected high-grade glioma based on imaging underwent the MRgFUS in conjunction with administration of chemotherapy (n = 1 liposomal doxorubicin, n = 4 temozolomide) one day prior to their scheduled surgical resection. Samples of "sonicated" and "unsonicated" tissue were measured for the chemotherapy by liquid-chromatography-mass spectrometry. Complete follow-up was three months. The procedure was well-tolerated, with no adverse clinical or radiologic events related to the procedure. The BBB within the target volume showed radiographic evidence of opening with an…

We present a framework, which we call Molecule Deep Q-Networks (MolDQN), for molecule optimization by combining domain knowledge of chemistry and state-of-the-art reinforcement learning techniques (double Q-learning and randomized value functions). We directly define modifications on molecules, thereby ensuring 100% chemical validity. Further, we operate without pre-training on any dataset to avoid possible bias from the choice of that set. MolDQN achieves comparable or better performance against several other recently published algorithms for benchmark molecular optimization tasks. However, we also argue that many of these tasks are not representative of real optimization problems in drug discovery. Inspired by problems faced during medicinal chemistry lead optimization, we extend our model with multi-objective reinforcement learning, which maximizes drug-likeness while maintaining similarity to the original molecule. We further show the path through chemical space to achieve optimization for a molecule to understand how the model works.

Predicted global figures for plastic debris accumulation in the ocean surface layer range on the order of hundreds of thousands of metric tons, representing only a few percent of estimated annual emissions into the marine environment. The current accepted explanation for this difference is that positively buoyant macroplastic objects do not persist on the ocean surface. Subject to degradation into microplastics, the major part of the mass is predicted to have settled below the surface. However, we argue that such a simple emission-degradation model cannot explain the occurrence of decades-old objects collected by oceanic expeditions. We show that debris circulation dynamics in coastal environments may be a better explanation for this difference. The results presented here suggest that there is a significant time interval, on the order of several years to decades, between terrestrial emissions and representative accumulation in offshore waters. Importantly, our results also indicate that the current generation of secondary microplastics in the global ocean is mostly a result of the…

Plastic waste has been documented in nearly all types of marine environments and has been found in species spanning all levels of marine food webs. Within these marine environments, deep pelagic waters encompass the largest ecosystems on Earth. We lack a comprehensive understanding of the concentrations, cycling, and fate of plastic waste in sub-surface waters, constraining our ability to implement effective, large-scale policy and conservation strategies. We used remotely operated vehicles and engineered purpose-built samplers to collect and examine the distribution of microplastics in the Monterey Bay pelagic ecosystem at water column depths ranging from 5 to 1000 m. Laser Raman spectroscopy was used to identify microplastic particles collected from throughout the deep pelagic water column, with the highest concentrations present at depths between 200 and 600 m. Examination of two abundant particle feeders in this ecosystem, pelagic red crabs (Pleuroncodes planipes) and giant larvaceans (Bathochordaeus stygius), showed that microplastic particles readily flow from the environment…

Abstract We present one of the first case studies demonstrating the use of distributed acoustic sensing deployed on regional unlit fiber-optic telecommunication infrastructure (dark fiber) for broadband seismic monitoring of both near-surface soil properties and earthquake seismology. We recorded 7 months of passive seismic data on a 27 km section of dark fiber stretching from West Sacramento, CA to Woodland, CA, densely sampled at 2 m spacing. This dataset was processed to extract surface wave velocity information using ambient noise interferometry techniques; the resulting V S profiles were used to map both shallow structural profiles and groundwater depth, thus demonstrating that basin-scale variations in hydrological state could be resolved using this technique. The same array was utilized for detection of regional and teleseismic earthquakes and evaluated for long period response using records from the M8.1 Chiapas, Mexico 2017, Sep 8th event. The combination of these two sets of observations conclusively demonstrates that regionally extensive fiber-optic networks can…

Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are used to help diagnose heart disease by recording the heart's activity. However, automated medical-aided diagnosis with computers usually requires a large volume of labeled clinical data without patients' privacy to train the model, which is an empirical problem that still needs to be solved. To address this problem, we propose a generative adversarial network (GAN), which is composed of a bidirectional long short-term memory(LSTM) and convolutional neural network(CNN), referred as BiLSTM-CNN,to generate synthetic ECG data that agree with existing clinical data so that the features of patients with heart disease can be retained. The model includes a generator and a discriminator, where the generator employs the two layers of the BiLSTM networks and the discriminator is based on convolutional neural networks. The 48 ECG records from individuals of the MIT-BIH database were used to train the model. We compared the performance of our model with two other generative models, the recurrent neural network…

Herein, we present the synthesis of mono-dispersed C-QDs via single-step thermal decomposition process using the fennel seeds (Foeniculum vulgare). As synthesized C-QDs have excellent colloidal, photo-stability, environmental stability (pH) and do not require any additional surface passivation step to improve the fluorescence. The C-QDs show excellent PL activity and excitation-independent emission. Synthesis of excitation-independent C-QDs, to the best of our knowledge, using natural carbon source via pyrolysis process has never been achieved before. The effect of reaction time and temperature on pyrolysis provides insight into the synthesis of C-QDs. We used Machine-learning techniques (ML) such as PCA, MCR-ALS, and NMF-ARD-SO in order to provide a plausible explanation for the origin of the PL mechanism of as-synthesized C-QDs. ML techniques are capable of handling and analyzing the large PL data-set, and institutively recommend the best excitation wavelength for PL analysis. Mono-disperse C-QDs are highly desirable and have a range of potential applications in bio-sensing,…

Robotic weed control has seen increased research of late with its potential for boosting productivity in agriculture. Majority of works focus on developing robotics for croplands, ignoring the weed management problems facing rangeland stock farmers. Perhaps the greatest obstacle to widespread uptake of robotic weed control is the robust classification of weed species in their natural environment. The unparalleled successes of deep learning make it an ideal candidate for recognising various weed species in the complex rangeland environment. This work contributes the first large, public, multiclass image dataset of weed species from the Australian rangelands; allowing for the development of robust classification methods to make robotic weed control viable. The DeepWeeds dataset consists of 17,509 labelled images of eight nationally significant weed species native to eight locations across northern Australia. This paper presents a baseline for classification performance on the dataset using the benchmark deep learning models, Inception-v3 and ResNet-50. These models achieved an average…

We applied deep convolutional neural networks (CNNs) to detect periodontal bone loss (PBL) on panoramic dental radiographs. We synthesized a set of 2001 image segments from panoramic radiographs. Our reference test was the measured % of PBL. A deep feed-forward CNN was trained and validated via 10-times repeated group shuffling. Model architectures and hyperparameters were tuned using grid search. The final model was a seven-layer deep neural network, parameterized by a total number of 4,299,651 weights. For comparison, six dentists assessed the image segments for PBL. Averaged over 10 validation folds the mean (SD) classification accuracy of the CNN was 0.81 (0.02). Mean (SD) sensitivity and specificity were 0.81 (0.04), 0.81 (0.05), respectively. The mean (SD) accuracy of the dentists was 0.76 (0.06), but the CNN was not statistically significant superior compared to the examiners (p = 0.067/t-test). Mean sensitivity and specificity of the dentists was 0.92 (0.02) and 0.63 (0.14), respectively. A CNN trained on a limited amount of radiographic image segments showed at least…

Abstract Since the last decades, non-precious metal catalysts (NPMC), especially iron based electrocatalysts show sufficient activity, potentially applicant in oxygen reduction reaction (ORR), however they only withstand considerable current densities at low operating potentials. On the other hand iron based electrocatalysts are not stable at elevated cathode potentials, which is essential for high energy competence, and its remains difficult to deal. Therefore, via this research a simple approach is demonstrated that allows synthesis of nanosize Fe-doped mayenite electride, [Ca24Al28O64]4+·(e−)4 (can also write as, C12A7−xFex:e−, where doping level, x = 1) (thereafter, Fe-doped C12A7:e−), consist of abundantly available elements with gram level powder material production, based on simple citrate sol-gel method. The maximum achieved conductivity of this first time synthesized Fe-doped C12A7:e− composite materials was 249 S/cm. Consequently, Fe-doped C12A7:e− composite is cost-effective, more active and highly durable precious-metal free electrocatalyst, with 1.03 V onset potential,…

The early treatment and rapid closure of acute or chronic wounds is essential for normal healing and prevention of hypertrophic scarring. The use of split thickness autografts is often limited by the availability of a suitable area of healthy donor skin to harvest. Cellular and non-cellular biological skin-equivalents are commonly used as an alternative treatment option for these patients, however these treatments usually involve multiple surgical procedures and associated with high costs of production and repeated wound treatment. Here we describe a novel design and a proof-of-concept validation of a mobile skin bioprinting system that provides rapid on-site management of extensive wounds. Integrated imaging technology facilitated the precise delivery of either autologous or allogeneic dermal fibroblasts and epidermal keratinocytes directly into an injured area, replicating the layered skin structure. Excisional wounds bioprinted with layered autologous dermal fibroblasts and epidermal keratinocytes in a hydrogel carrier showed rapid wound closure, reduced contraction and…

Although stress is an increasing global health problem in cities, urban green spaces can provide health benefits. There is, however, a lack of understanding of the link between physiological mechanisms and qualities of urban green spaces. Here, we compare the effects of visual stimuli (360 degree virtual photos of an urban environment, forest, and park) to the effects of congruent olfactory stimuli (nature and city odours) and auditory stimuli (bird songs and noise) on physiological stress recovery. Participants (N = 154) were pseudo-randomised into participating in one of the three environments and subsequently exposed to stress (operationalised by skin conductance levels). The park and forest, but not the urban area, provided significant stress reduction. High pleasantness ratings of the environment were linked to low physiological stress responses for olfactory and to some extent for auditory, but not for visual stimuli. This result indicates that olfactory stimuli may be better at facilitating stress reduction than visual stimuli. Currently, urban planners prioritise visual…

Abstract Phosphorus (P) is a limiting nutrient for plants and an essential element for all life on Earth. As the resources of phosphate rock are depleting, new management tools for environmentally friendly P fertilizers are needed. In order to achieve this, recent studies have proposed to use biochar, a carbon-rich solid product of thermochemical conversion of biomass with minimal or zero oxygen supply, as slow-release P fertilizer. However, the effects of biochar on plant-available P in soils have been reported to be variable. Therefore, we quantitatively evaluated existing peer-reviewed data using meta-analysis to draw general conclusions. In the present study, we evaluated 108 pairwise comparisons to their response of biochar application on P availability in soils. Our results indicate that biochar can act as a short-, mid-, and long-term P fertilizer with its effect depending on feedstock, pyrolysis temperature and application amount. Overall, the addition of biochar significantly increased the P availability in agricultural soil by a factor of 4.6 (95% confidence interval…

Gelatin methacryloyl (GelMA) is a versatile material for a wide range of bioapplications. There is an intense interest in developing effective chemical strategies to prepare GelMA with a high degree of batch-to-batch consistency and controllability in terms of methacryloyl functionalization and physiochemical properties. Herein, we systematically investigated the batch-to-batch reproducibility and controllability of producing GelMA (target highly and lowly substituted versions) via a one-pot strategy. To assess the GelMA product, several parameters were evaluated, including the degree of methacryloylation, secondary structure, and enzymatic degradation, along with the mechanical properties and cell viability of GelMA hydrogels. The results showed that two types of target GelMA with five batches exhibited a high degree of controllability and reproducibility in compositional, structural, and functional properties owing to the highly controllable one-pot strategy.

Abstract Along the last two centuries, the story of semiconductor materials ranged from a mix of disbelief and frustration to one of the most successful technological achievements ever seen. Such a progress comprised the development of materials and models that, allied to the knowledge provided by spectroscopic techniques, resulted in the (nowadays) omnipresent electronic gadgets. Within this context, optically-based methods were of special importance since, amongst others, they presented details about the electronic states and energy bandgap E gap of semiconductors which, ultimately, decided about their application in devices. Stimulated by these aspects, this work investigated the semiconductors silicon, germanium, and gallium-arsenide in the crystalline (bulk and powder) and amorphous (film) forms. The detailed analysis of the experimental results indicates that accurate E gap values can be obtained by fitting a sigmoid (Boltzmann) function to their corresponding optical absorption spectra. The method is straightforward and, contrary to the traditional approaches to determine E…

Artificial urine has many advantages over human urine for research and educational purposes. By closely mimicking healthy individuals' urine, it may also be important in discovering novel biomarkers. However, up until now, there has not been any specific protocol to prove the similarity in terms of the chemical composition at the molecular level. In this study, a new artificial urine protocol is established to mimics the urine of healthy individuals. The multi-purpose artificial urine (MP-AU) presented here is compared with two other protocols most cited in literature. Furthermore, these three protocols are also compared with samples from 28 healthy young individuals. To do so, attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) is used, according to which MP-AU shows a significantly close similarity with human urine. In formulating MP-AU, the infrared spectra of nine compounds is provided, making possible the band assignment of some absorption bands to certain compounds. Given its properties, the MP-AU protocol introduced here is both economical and…

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is characterized by impairments in social interactions and communication, restricted interests and repetitive behaviors. Several studies report a high prevalence of gastrointestinal (GI) symptoms in autistic individuals. Cumulative evidence reveals that the gut microbiota and its metabolites (especially short-chain fatty acids, SCFAs) play an important role in GI disorders and the pathogenesis of ASD. However, the composition of the gut microbiota and its association with fecal SCFAs and GI symptoms of autistic children remain largely unknown. In the present study, we sequenced the bacterial 16S rRNA gene, detected fecal SCFAs, assessed GI symptoms and analyzed the relationship between the gut microbiome and fecal SCFAs in autistic and neurotypical individuals. The results showed that the compositions of the gut microbiota and SCFAs were altered in ASD individuals. We found lower levels of fecal acetic acid and butyrate and a higher level of fecal valeric acid in ASD subjects. We identified decreased abundances of…

The increased availability of labeled X-ray image archives (e.g. ChestX-ray14 dataset) has triggered a growing interest in deep learning techniques. To provide better insight into the different approaches, and their applications to chest X-ray classification, we investigate a powerful network architecture in detail: the ResNet-50. Building on prior work in this domain, we consider transfer learning with and without fine-tuning as well as the training of a dedicated X-ray network from scratch. To leverage the high spatial resolution of X-ray data, we also include an extended ResNet-50 architecture, and a network integrating non-image data (patient age, gender and acquisition type) in the classification process. In a concluding experiment, we also investigate multiple ResNet depths (i.e. ResNet-38 and ResNet-101). In a systematic evaluation, using 5-fold re-sampling and a multi-label loss function, we compare the performance of the different approaches for pathology classification by ROC statistics and analyze differences between the classifiers using rank correlation. Overall, we…

Combining membrane impermeable DNA-binding stain propidium iodide (PI) with membrane-permeable DNA-binding counterstains is a widely used approach for bacterial viability staining. In this paper we show that PI staining of adherent cells in biofilms may significantly underestimate bacterial viability due to the presence of extracellular nucleic acids (eNA). We demonstrate that gram-positive Staphylococcus epidermidis and gram-negative Escherichia coli 24-hour initial biofilms on glass consist of 76 and 96% PI-positive red cells in situ, respectively, even though 68% the cells of either species in these aggregates are metabolically active. Furthermore, 82% of E. coli and 89% S. epidermidis are cultivable after harvesting. Confocal laser scanning microscopy (CLSM) revealed that this false dead layer of red cells is due to a subpopulation of double-stained cells that have green interiors under red coating layer which hints at eNA being stained outside intact membranes. Therefore, viability staining results of adherent cells should always be validated by an alternative method for…

Abstract The ocean’s chemistry is changing due to the uptake of anthropogenic carbon dioxide (CO 2 ). This phenomenon, commonly referred to as “Ocean Acidification”, is endangering coral reefs and the broader marine ecosystems. In this study, we combine a recent observational seawater CO 2 data product, i.e., the 6 th version of the Surface Ocean CO 2 Atlas (1991–2018, ~23 million observations), with temporal trends at individual locations of the global ocean from a robust Earth System Model to provide a high-resolution regionally varying view of global surface ocean pH and the Revelle Factor. The climatology extends from the pre-Industrial era (1750 C.E.) to the end of this century under historical atmospheric CO 2 concentrations (pre-2005) and the Representative Concentrations Pathways (post-2005) of the Intergovernmental Panel on Climate Change (IPCC)’s 5 th Assessment Report. By linking the modeled pH trends to the observed modern pH distribution, the climatology benefits from recent improvements in both model design and observational data coverage, and is likely to provide…

Abstract Shift work is associated with impaired alertness and performance due to sleep loss and circadian misalignment. This study examined sleep between shift types (day, evening, night), and alertness and performance during day and night shifts in 52 intensive care workers. Sleep and wake duration between shifts were evaluated using wrist actigraphs and diaries. Subjective sleepiness (Karolinska Sleepiness Scale, KSS) and Psychomotor Vigilance Test (PVT) performance were examined during day shift, and on the first and subsequent night shifts (3 rd , 4 th or 5 th ). Circadian phase was assessed using urinary 6-sulphatoxymelatonin rhythms. Sleep was most restricted between consecutive night shifts (5.74 ± 1.30 h), consecutive day shifts (5.83 ± 0.92 h) and between evening and day shifts (5.20 ± 0.90 h). KSS and PVT mean reaction times were higher at the end of the first and subsequent night shift compared to day shift, with KSS highest at the end of the first night. On nights, working during the circadian acrophase of the urinary melatonin rhythm led to poorer outcomes on the KSS…

Extreme climatic events have recently impacted marine ecosystems around the world, including foundation species such as corals and kelps. Here, we describe the rapid climate-driven catastrophic shift in 2014 from a previously robust kelp forest to unproductive large scale urchin barrens in northern California. Bull kelp canopy was reduced by >90% along more than 350 km of coastline. Twenty years of kelp ecosystem surveys reveal the timing and magnitude of events, including mass mortalities of sea stars (2013-), intense ocean warming (2014-2017), and sea urchin barrens (2015-). Multiple stressors led to the unprecedented and long-lasting decline of the kelp forest. Kelp deforestation triggered mass (80%) abalone mortality (2017) resulting in the closure in 2018 of the recreational abalone fishery worth an estimated $44 M and the collapse of the north coast commercial red sea urchin fishery (2015-) worth $3 M. Key questions remain such as the relative roles of ocean warming and sea star disease in the massive purple sea urchin population increase. Science and policy will need to…

The ever decreasing area of forests has lead to environmental and economical challenges and has brought with it a renewed interest in developing methodologies that quantify the extent of deforestation and reforestation. In this study we analyzed the deforested areas of the Apuseni Mountains, which has been under economic pressure in recent years and resulted in widespread deforestation as a means of income. Deforested surface dynamics modeling was based on images contained in the Global Forest Database, provided by the Department of Geographical Sciences at Maryland University between 2000 and 2014. The results of the image particle analysis and modelling were based on Total Area (ha), Count of patches and Average Size whereas deforested area distribution was based on the Local Connected Fractal Dimension, Fractal Fragmentation Index and Tug-of-War Lacunarity as indicators of forest fragmentation or heterogeneity. The major findings of the study indicated a reduction of the tree cover area by 3.8%, an increase in fragmentation of 17.7% and an increase in heterogeneity by 29%, while…

It is critical, but difficult, to catch the small variation in genomic or other kinds of data that differentiates phenotypes or categories. A plethora of data is available, but the information from its genes or elements is spread over arbitrarily, making it challenging to extract relevant details for identification. However, an arrangement of similar genes into clusters makes these differences more accessible and allows for robust identification of hidden mechanisms (e.g. pathways) than dealing with elements individually. Here we propose, DeepInsight, which converts non-image samples into a well-organized image-form. Thereby, the power of convolution neural network (CNN), including GPU utilization, can be realized for non-image samples. Furthermore, DeepInsight enables feature extraction through the application of CNN for non-image samples to seize imperative information and shown promising results. To our knowledge, this is the first work to apply CNN simultaneously on different kinds of non-image datasets: RNA-seq, vowels, text, and artificial.

Abstract In this study, the antimicrobial activity of titanium dioxide (TiO 2 ), zinc oxide (ZnO), and TiO 2 /ZnO nanoparticles supported into 4A zeolite (4A z) was assessed. Based on antimicrobial experiments, minimum inhibitory concentration (MIC 90 ), minimum bactericidal concentration (MBC), fractional inhibitory concentration (FIC) and disc diffusion test were determined after 24 h of contact with the prepared nanocomposites. These results are in agreements with the results of disc diffusion test. During the experiments, the numbers of viable bacterial cells of Staphylococcus aureus , Pseudomonas fluorescens , Listeria monocytogenes and Escherichia coli O 157 :H 7 decreased significantly. The crystallinity and morphology of nanoparticles were investigated by X-ray diffraction patterns (XRD), elemental mapping at the microstructural level by scanning electron microscopy (SEM) with energy dispersive X-ray spectrometry (EDS), and transmission electron microscopy (TEM). As a result, it was demonstrated that TiO 2 /ZnO nanoparticles supported in 4A zeolite could lead to an optimum…

Autophagy is an evolutionarily conserved process across eukaryotes that degrades cargoes like aggregate-prone proteins, pathogens, damaged organelles and macromolecules via delivery to lysosomes. The process involves the formation of double-membraned autophagosomes that engulf the cargoes destined for degradation, sometimes with the help of autophagy receptors like p62, which are themselves autophagy substrates. LC3-II, a standard marker for autophagosomes, is generated by the conjugation of cytosolic LC3-I to phosphatidylethanolamine (PE) on the surface of nascent autophagosomes. As LC3-II is relatively specifically associated with autophagosomes and autolysosomes (in the absence of conditions stimulating LC3-associated phagocytosis), quantification of LC3-positive puncta is considered as a gold-standard assay for assessing the numbers of autophagosomes in cells. Here we find that the endogenous LC3-positive puncta become larger in cells where autophagosome formation is abrogated, and are prominent even when LC3-II is not formed. This occurs even with transient and incomplete…

Biodiesel production from waste cooking oil (WCO) provides an alternative energy means of producing liquid fuels from biomass for various uses. Biodiesel production by recycling WCO and methanol in the presence of calcium oxide (CaO) nano-catalyst offers several benefits such as economic, environmental and waste management. A nano-catalyst of CaO was synthesized by thermal-decomposition method and calcinated at 500 °C followed by characterization using x-ray diffraction (XRD) and scanning electron microscope (SEM) techniques. The XRD results revealed nano-scale crystal sizes at high purity, with a mean particle size of ~29 nm. The SEM images exhibited morphology of irregular shapes and porous structure of the synthesized nanocatalysts. The highest conversion of WCO to biodiesel was estimated to be 96%, at optimized experimental conditions i.e., 50 °C, 1:8 WCO oil to methanol ratio, 1% by weight of catalyst loading rate and 90 minutes reaction time, which is among few highest conversions reported so far. Biodiesel properties were tested according to the American (ASTM D6571) fuel…

The gut microbiota (GM) is related to obesity and other metabolic diseases. To detect GM markers for obesity in patients with different metabolic abnormalities and investigate their relationships with clinical indicators, 1,914 Chinese adults were enrolled for 16S rRNA gene sequencing in this retrospective study. Based on GM composition, Random forest classifiers were constructed to screen the obesity patients with (Group OA) or without metabolic diseases (Group O) from healthy individuals (Group H), and high accuracies were observed for the discrimination of Group O and Group OA (areas under the receiver operating curve (AUC) equal to 0.68 and 0.76, respectively). Furthermore, six GM markers were shared by obesity patients with various metabolic disorders (Bacteroides, Parabacteroides, Blautia, Alistipes, Romboutsia and Roseburia). As for the discrimination with Group O, Group OA exhibited low accuracy (AUC = 0.57). Nonetheless, GM classifications to distinguish between Group O and the obese patients with specific metabolic abnormalities were not accurate (AUC values from 0.59 to…

Though clinical trials for medical applications of dimethyl sulfoxide (DMSO) reported toxicity in the 1960s, later, the FDA classified DMSO in the safest solvent category. DMSO became widely used in many biomedical fields and biological effects were overlooked. Meanwhile, biomedical science has evolved towards sensitive high-throughput techniques and new research areas, including epigenomics and microRNAs. Considering its wide use, especially for cryopreservation and in vitro assays, we evaluated biological effect of DMSO using these technological innovations. We exposed 3D cardiac and hepatic microtissues to medium with or without 0.1% DMSO and analyzed the transcriptome, proteome and DNA methylation profiles. In both tissue types, transcriptome analysis detected >2000 differentially expressed genes affecting similar biological processes, thereby indicating consistent cross-organ actions of DMSO. Furthermore, microRNA analysis revealed large-scale deregulations of cardiac microRNAs and smaller, though still massive, effects in hepatic microtissues. Genome-wide methylation patterns…

The systemic immune-inflammation index (SII) based on peripheral lymphocyte, neutrophil and platelet counts has been considered a good index that reflects the local immune response and systemic inflammation. However, the use of the SII has not been reported in cervical cancer. In this study, Kaplan-Meier survival analysis showed that a high SII was associated with poor prognosis in cervical cancer patients in the primary and validation cohorts. A higher SII had a significant correlation with larger tumours but had no correlation with other clinicopathological parameters. Among all systemic immune indexes, the SII is the only independent prognostic factor for cervical cancer patients. Compared with the area under the curve for the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and monocyte/lymphocyte ratio (MLR), the area for the SII was larger at 3 and 5 years. In addition, the SII still retains it prognostic values across all FIGO stages. The SII can independently predict the overall survival of patients with cervical cancer receiving radical resection and is…

Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by a decline in cognitive functions with no validated disease modifying treatment. It is critical for timely treatment to detect AD in its earlier stage before clinical manifestation. Mild cognitive impairment (MCI) is an intermediate stage between cognitively normal older adults and AD. To predict conversion from MCI to probable AD, we applied a deep learning approach, multimodal recurrent neural network. We developed an integrative framework that combines not only cross-sectional neuroimaging biomarkers at baseline but also longitudinal cerebrospinal fluid (CSF) and cognitive performance biomarkers obtained from the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI). The proposed framework integrated longitudinal multi-domain data. Our results showed that 1) our prediction model for MCI conversion to AD yielded up to 75% accuracy (area under the curve (AUC) = 0.83) when using only single modality of data separately; and 2) our prediction model achieved the best performance with 81% accuracy (AUC =…

A novel eco-friendly procedure was developed to produce safer, stable and highly pure zinc oxide nanoparticles (ZnO NPs) using microalgae Chlorella extract. The ZnO NPs were synthesized simply using zinc nitrate and microalgae Chlorella extract which conducted at ambient conditions. In this recipe, microalgae Chlorella extract acted as the reducing agent and a stabilizing layer on fresh ZnO NPs. UV-visible spectrum was confirmed the formation of ZnO NPs showing an absorption peak at 362 nm. XRD results demonstrated that prepared ZnO NPs has a high-crystalline hexagonal (Wurtzite) structure, with average size about 19.44 nm in diameter. FT-IR spectral analysis indicated an active contribution of algae-derived biomolecules in zinc ions bioreduction. According to SEM and TEM observations, ZnO NPs are well dispersed and has a hexagonal shape with the average size of 20 ± 2.2 nm, respectively. Based on gas chromatography analyses, the optimum 0.01 g/L dosage of ZnO catalyst revealed an effective photocatalytic activity toward the degradation (97%) of Dibenzothiophene (DBT) contaminant as…

Plastic pollution represents a pervasive and increasing threat to marine ecosystems worldwide and there is a need to better understand the extent to which microplastics (<5 mm) are ingested by high trophic-level taxa, such as marine mammals. Here, we perform a comprehensive assessment by examining whole digestive tracts of 50 individuals from 10 species whilst operating strict contamination controls. Microplastics were ubiquitous with particles detected in every animal examined. The relatively low number per animal (mean = 5.5) suggests these particles are transitory. Stomachs, however, were found to contain a greater number than intestines, indicating a potential site of temporary retention. The majority of particles were fibres (84%) while the remaining 16% was fragments. Particles were mainly blue and black (42.5% and 26.4%) in colour and Nylon was the most prevalent (60%) polymer type. A possible relationship was found between the cause of death category and microplastic abundance, indicating that animals that died due to infectious diseases had a slightly higher number of…

Abstract Predicting physical response of an artificially structured material is of particular interest for scientific and engineering applications. Here we use deep learning to predict optical response of artificially engineered nanophotonic devices. In addition to predicting forward approximation of transmission response for any given topology, this approach allows us to inversely approximate designs for a targeted optical response. Our Deep Neural Network (DNN) could design compact (2.6 × 2.6 μm 2 ) silicon-on-insulator (SOI)-based 1 × 2 power splitters with various target splitting ratios in a fraction of a second. This model is trained to minimize the reflection (to smaller than ~ −20 dB) while achieving maximum transmission efficiency above 90% and target splitting specifications. This approach paves the way for rapid design of integrated photonic components relying on complex nanostructures.

Microplastics have become pervasive environmental pollutants in both freshwater and marine ecosystems. The presence of microplastics have been recorded in the tissues of many wild fish species, and laboratory studies have demonstrated that microplastics can exert adverse health effects. To further investigate the biological mechanisms underlying microplastics toxicity we applied an integrated approach, analyzing the effects of microplastics at transcriptomic, histological and behavioral level. Adult zebrafish have been exposed to two concentrations of high-density polyethylene and polystyrene microplastics for twenty days. Transcriptomic results indicate alterations in the expression of immune system genes and the down-regulation of genes correlated with epithelium integrity and lipid metabolism. The transcriptomic findings are supported by tissue alterations and higher occurrence of neutrophils observed in gills and intestinal epithelium. Even the daily rhythm of activity of zebrafish appears to be affected, although the regular pattern of activity is recovered over time.…

The origin of modern disjunct plant distributions in the Brazilian Highlands with strong floristic affinities to distant montane rainforests of isolated mountaintops in the northeast and northern Amazonia and the Guyana Shield remains unknown. We tested the hypothesis that these unexplained biogeographical patterns reflect former ecosystem rearrangements sustained by widespread plant migrations possibly due to climatic patterns that are very dissimilar from present-day conditions. To address this issue, we mapped the presence of the montane arboreal taxa Araucaria, Podocarpus, Drimys, Hedyosmum, Ilex, Myrsine, Symplocos, and Weinmannia, and cool-adapted plants in the families Myrtaceae, Ericaceae, and Arecaceae (palms) in 29 palynological records during Heinrich Stadial 1 Event, encompassing a latitudinal range of 30°S to 0°S. In addition, Principal Component Analysis and Species Distribution Modelling were used to represent past and modern habitat suitability for Podocarpus and Araucaria. The data reveals two long-distance patterns of plant migration connecting south/southeast to…

With every moving day, the aspect that is going to be the most important for modern science and technology is the means to supply sufficient energy for all the scientific applications. As the resource of fossil fuel is draining out fast, an alternative is always required to satisfy the needs of the future world. Limited resources also force to innovate something that can utilise the resource more efficiently. This work is based on a simple synthesis route of biomass derived hard carbon and to exploring the possibility of using it as electrochemical supercapacitors. A cheap, eco-friendly and easily synthesized carbon material is utilized as electrode for electrochemical energy-storage. Four different hard carbons were synthesized from KOH activated banana stem (KHC), phosphoric acid treated banana stem derived carbons (PHC), corn-cob derived hard carbon (CHC) and potato starch derived hard carbons (SHC) and tested as supercapacitor electrodes. KOH-activated hard carbon has provided 479.23 F/g specific capacitance as calculated from its cycle voltammograms. A detailed analysis is done…

Abstract Coastal inundation due to sea level rise (SLR) is projected to displace hundreds of millions of people worldwide over the next century, creating significant economic, humanitarian, and national-security challenges. However, the majority of previous efforts to characterize potential coastal impacts of climate change have focused primarily on long-term SLR with a static tide level, and have not comprehensively accounted for dynamic physical drivers such as tidal non-linearity, storms, short-term climate variability, erosion response and consequent flooding responses. Here we present a dynamic modeling approach that estimates climate-driven changes in flood-hazard exposure by integrating the effects of SLR, tides, waves, storms, and coastal change (i.e. beach erosion and cliff retreat). We show that for California, USA, the world’s 5 th largest economy, over $150 billion of property equating to more than 6% of the state’s GDP and 600,000 people could be impacted by dynamic flooding by 2100; a three-fold increase in exposed population than if only SLR and a static coastline are…

Abstract Although marine plastic pollution has been the focus of several studies, there are still many gaps in our understanding of the concentrations, characteristics and impacts of plastics in the oceans. This study aimed to quantify and characterize plastic debris in oceanic surface waters of the Antarctic Peninsula. Sampling was done through surface trawls, and mean debris concentration was estimated at 1,794 items.km −2 with an average weight of 27.8 g.km −2 . No statistical difference was found between the amount of mesoplastics (46%) and microplastics (54%). We found hard and flexible fragments, spheres and lines, in nine colors, composed mostly of polyurethane, polyamide, and polyethylene. An oceanographic dispersal model showed that, for at least seven years, sampled plastics likely did not originate from latitudes lower than 58°S. Analysis of epiplastic community diversity revealed bacteria, microalgae, and invertebrate groups adhered to debris. Paint fragments were present at all sampling stations and were approximately 30 times more abundant than plastics. Although paint…

Abstract In this study, we demonstrated a blue phosphorescent organic light-emitting diode (BPOLED) based on a host with two carbazole and one trizole (2CbzTAZ) moiety, 9,9′-(2-(4,5-diphenyl-4H-1,2,4-triazol-3-yl)-1,3-phenylene)bis(9H-carbazole), that exhibits bipolar transport characteristics. Compared with the devices with a carbazole host (N,N’-dicarbazolyl-3,5-benzene, (mCP)), triazole host (3-(biphenyl-4-yl)-5-(4-tert-butylphenyl)-4-phenyl-4H-1,2,4-triazole, (TAZ)), or a physical mixture of mCP:TAZ, which exhibit hole, electron, and bipolar transport characteristics, respectively, the BPOLED with the bipolar 2CbzTAZ host exhibited the lowest driving voltage (6.55 V at 10 mA/cm2), the highest efficiencies (maximum current efficiency of 52.25 cd/A and external quantum efficiency of 23.89%), and the lowest efficiency roll-off, when doped with bis[2-(4,6-difluorophenyl)pyridinato-C2,N](picolinato)iridium(III) (FIrpic) as blue phosphor. From analyses of light leakage of the emission spectra of electroluminescence, transient electroluminescence, and partially doped OLEDs, it was…

Abstract Solar energy has the potential to offset a significant fraction of non-renewable electricity demands globally, yet it may occupy extensive areas when deployed at this level. There is growing concern that large renewable energy installations will displace other land uses. Where should future solar power installations be placed to achieve the highest energy production and best use the limited land resource? The premise of this work is that the solar panel efficiency is a function of the location’s microclimate within which it is immersed. Current studies largely ignore many of the environmental factors that influence Photovoltaic (PV) panel function. A model for solar panel efficiency that incorporates the influence of the panel’s microclimate was derived from first principles and validated with field observations. Results confirm that the PV panel efficiency is influenced by the insolation, air temperature, wind speed and relative humidity. The model was applied globally using bias-corrected reanalysis datasets to map solar panel efficiency and the potential for solar power…

Earthquake signal detection is at the core of observational seismology. A good detection algorithm should be sensitive to small and weak events with a variety of waveform shapes, robust to background noise and non-earthquake signals, and efficient for processing large data volumes. Here, we introduce the Cnn-Rnn Earthquake Detector (CRED), a detector based on deep neural networks. CRED uses a combination of convolutional layers and bi-directional long-short-term memory units in a residual structure. It learns the time-frequency characteristics of the dominant phases in an earthquake signal from three component data recorded on individual stations. We train the network using 500,000 seismograms (250k associated with tectonic earthquakes and 250k identified as noise) recorded in Northern California. The robustness of the trained model with respect to the noise level and non-earthquake signals is shown by applying it to a set of semi-synthetic signals. We also apply the model to one month of continuous data recorded at Central Arkansas to demonstrate its efficiency, generalization, and…

Abstract The purpose of this study was the preparation, characterization and application of high-performance activated carbons (ACs) derived from oily sludge through chemical activation by KOH. The produced ACs were characterized using iodine number, N 2 adsorption-desorption, Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The activated carbon prepared under optimum conditions showed a predominantly microporous structure with a BET surface area of 2263 m 2 g −1 , a total pore volume of 1.37 cm 3 g −1 and a micro pore volume of 1.004 cm 3 g −1 . The kinetics and equilibrium adsorption data of phenol fitted well to the pseudo second order model (R 2 = 0.99) and Freundlich isotherm (R 2 = 0.99), respectively. The maximum adsorption capacity based on the Langmuir model (434 mg g −1 ) with a relatively fast adsorption rate (equilibrium time of 30 min) was achieved under an optimum pH value of 6.0. Thermodynamic parameters were negative and showed that adsorption of phenol onto the activated carbon was feasible, spontaneous and exothermic.…

Automated diagnosis of tuberculosis (TB) from chest X-Rays (CXR) has been tackled with either hand-crafted algorithms or machine learning approaches such as support vector machines (SVMs) and convolutional neural networks (CNNs). Most deep neural network applied to the task of tuberculosis diagnosis have been adapted from natural image classification. These models have a large number of parameters as well as high hardware requirements, which makes them prone to overfitting and harder to deploy in mobile settings. We propose a simple convolutional neural network optimized for the problem which is faster and more efficient than previous models but preserves their accuracy. Moreover, the visualization capabilities of CNNs have not been fully investigated. We test saliency maps and grad-CAMs as tuberculosis visualization methods, and discuss them from a radiological perspective.

In Africa, livestock production currently accounts for about 30% of the gross value of agricultural production. However, production is struggling to keep up with the demands of expanding human populations, the rise in urbanization and the associated shifts in diet habits. High costs of feed prevent the livestock sector from thriving and to meet the rising demand. Insects have been identified as potential alternatives to the conventionally used protein sources in livestock feed due to their rich nutrients content and the fact that they can be reared on organic side streams. Substrates derived from organic by-products are suitable for industrial large-scale production of insect meal. Thus, a holistic comparison of the nutritive value of Black Soldier Fly larvae (BSFL) reared on three different organic substrates, i.e. chicken manure (CM), brewers' spent grain (SG) and kitchen waste (KW), was conducted. BSFL samples reared on every substrate were collected for chemical analysis after the feeding process. Five-hundred (500) neonatal BSFL were placed in 23 × 15 cm metallic trays on the…

Abstract In the present work, sustainable nanomaterials, cellulose, and spherical cellulose nanocrystals (SCNCs) were isolated from the non-edible parts of jackfruit ( Artocarpus heterophyllus) . Of the three different methods tested, sodium chlorite treatment produced the highest yield of cellulose, 20.08 ± 0.05% w/w (dry weight). Peaks observed in CP/MAS 13 C NMR spectrum and FTIR frequencies revealed the presence of α-cellulose and absence of other biomass fractions like hemicellulose and lignin. XRD analysis showed a high crystallinity of 83.42%. An appearance of a sharp endothermal peak at 323 °C in DSC and decomposition patterns between 310–420 °C of TGA confirms the presence of cellulose. Further, Sulphuric acid hydrolysis was employed to produce SCNCs and examined by TEM for the morphology and by HPLC for the presence of glucose.

Abstract Onchocerciasis is a parasitic disease with high socio-economic burden particularly in sub-Saharan Africa. The elimination plan for this disease has faced numerous challenges. A multi-epitope prophylactic/therapeutic vaccine targeting the infective L3 and microfilaria stages of the parasite’s life cycle would be invaluable to achieve the current elimination goal. There are several observations that make the possibility of developing a vaccine against this disease likely. For example, despite being exposed to high transmission rates of infection, 1 to 5% of people have no clinical manifestations of the disease and are thus considered as putatively immune individuals. An immuno-informatics approach was applied to design a filarial multi-epitope subunit vaccine peptide consisting of linear B-cell and T-cell epitopes of proteins reported to be potential novel vaccine candidates. Conservation of the selected proteins and predicted epitopes in other parasitic nematode species suggests that the generated chimera could be helpful for cross-protection. The 3D structure was predicted,…

Abstract The plant growth promoting rhizobacteria (PGPR) and plant growth regulators (PGRs) can be applied to improve the growth and productivity of plants, with potential to be used for genetic improvement of drought tolerance. However, for genetic improvement to be achieved, a solid understanding of the physiological and biochemical changes in plants induced by PGPR and PGR is required. The present study was carried out to investigate the role of PGPR and PGRs on the physiology and biochemical changes in chickpea grown under drought stress conditions and their association with drought tolerance. The PGPR, isolated from the rhizosphere of chickpea, were characterized on the basis of colony morphology and biochemical characters. They were also screened for the production of indole-3-acetic acid (IAA), hydrogen cyanide (HCN), ammonia (NH3), and exopolysaccharides (EPS) production. The isolated PGPR strains, named P1, P2, and P3, were identified by16S-rRNAgene sequencing asBacillus subtilis,Bacillus thuringiensis, andBacillus megaterium, respectively. The seeds of two chickpea…

We characterized the vaginal ecosystem during common infections of the female genital tract, as vulvovaginal candidiasis (VVC, n = 18) and Chlamydia trachomatis infection (CT, n = 20), recruiting healthy (HC, n = 21) and bacterial vaginosis-affected (BV, n = 20) women as references of eubiosis and dysbiosis. The profiles of the vaginal microbiome and metabolome were studied in 79 reproductive-aged women, by means of next generation sequencing and proton based-nuclear magnetic resonance spectroscopy. Lactobacillus genus was profoundly depleted in all the genital infections herein considered, and species-level analysis revealed that healthy vaginal microbiome was dominated by L. crispatus. In the shift from HC to CT, VVC, and BV, L. crispatus was progressively replaced by L. iners. CT infection and VVC, as well as BV condition, were mainly characterised by anaerobe genera, e.g. Gardnerella, Prevotella, Megasphaera, Roseburia and Atopobium. The changes in the bacterial communities occurring during the genital infections resulted in significant alterations in the vaginal metabolites…

With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have improved, but at the cost of increased treatment plan complexity and planning time. The accurate prediction of dose distributions would alleviate this issue by guiding clinical plan optimization to save time and maintain high quality plans. We have modified a convolutional deep network model, U-net (originally designed for segmentation purposes), for predicting dose from patient image contours of the planning target volume (PTV) and organs at risk (OAR). We show that, as an example, we are able to accurately predict the dose of intensity-modulated radiation therapy (IMRT) for prostate cancer patients, where the average Dice similarity coefficient is 0.91 when comparing the predicted vs. true isodose volumes between 0% and 100% of the prescription dose. The average value of the absolute differences in [max, mean] dose is found to be under 5% of the prescription dose, specifically for each structure is [1.80%, 1.03%](PTV), [1.94%, 4.22%](Bladder), [1.80%, 0.48%](Body), [3.87%, 1.79%](L…

Currently, most real-world time series datasets are multivariate and are rich in dynamical information of the underlying system. Such datasets are attracting much attention; therefore, the need for accurate modelling of such high-dimensional datasets is increasing. Recently, the deep architecture of the recurrent neural network (RNN) and its variant long short-term memory (LSTM) have been proven to be more accurate than traditional statistical methods in modelling time series data. Despite the reported advantages of the deep LSTM model, its performance in modelling multivariate time series (MTS) data has not been satisfactory, particularly when attempting to process highly non-linear and long-interval MTS datasets. The reason is that the supervised learning approach initializes the neurons randomly in such recurrent networks, disabling the neurons that ultimately must properly learn the latent features of the correlated variables included in the MTS dataset. In this paper, we propose a pre-trained LSTM-based stacked autoencoder (LSTM-SAE) approach in an unsupervised learning fashion…

Even though it is known that urbanization affects rainfall, studies vary regarding the magnitude and location of rainfall change. To develop a comprehensive understanding of rainfall modification due to urbanization, a systematic meta-analysis is undertaken. The initial search identified over 2000 papers of which 489 were carefully analyzed. From these papers, 85 studies from 48 papers could be used in a quantitative meta-analysis assessment. Results were analyzed for case studies versus climatological assessments, observational versus modeling studies and for day versus night. Results highlight that urbanization modifies rainfall, such that mean precipitation is enhanced by 18% downwind of the city, 16% over the city, 2% on the left and 4% on the right with respect to the storm direction. The rainfall enhancement occurred approximately 20-50 km from the city center. Study results help develop a more complete picture of the role of urban processes in rainfall modification and highlight that rainfall increases not only downwind of the city but also over the city. These findings have…

In this study, using three types of resins (each with unique material properties) as a matrix, and carbon black (CB) as a conductive additive, conductive fibres were fabricated through a melt-spinning process. An examination of the electrical conductivity revealed that a CB/polyethylene terephthalate (PET) composite had a low percolation value of 0.58 wt%, and thus the highest conductivity of the three resin types. These results indicate that CB/PET fibres could be used to manufacture antistatic fabrics.

emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and Europe. Europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and East Asia. The uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a…

We propose using faster regions with convolutional neural network features (faster R-CNN) in the TensorFlow tool package to detect and number teeth in dental periapical films. To improve detection precisions, we propose three post-processing techniques to supplement the baseline faster R-CNN according to certain prior domain knowledge. First, a filtering algorithm is constructed to delete overlapping boxes detected by faster R-CNN associated with the same tooth. Next, a neural network model is implemented to detect missing teeth. Finally, a rule-base module based on a teeth numbering system is proposed to match labels of detected teeth boxes to modify detected results that violate certain intuitive rules. The intersection-over-union (IOU) value between detected and ground truth boxes are calculated to obtain precisions and recalls on a test dataset. Results demonstrate that both precisions and recalls exceed 90% and the mean value of the IOU between detected boxes and ground truths also reaches 91%. Moreover, three dentists are also invited to manually annotate the test dataset…

Computational quantum technologies are entering a new phase in which noisy intermediate-scale quantum computers are available, but are still too small to benefit from active error correction. Even with a finite coherence budget to invest in quantum information processing, noisy devices with about 50 qubits are expected to experimentally demonstrate quantum supremacy in the next few years. Defined in terms of artificial tasks, current proposals for quantum supremacy, even if successful, will not help to provide solutions to practical problems. Instead, we believe that future users of quantum computers are interested in actual applications and that noisy quantum devices may still provide value by approximately solving hard combinatorial problems via hybrid classical-quantum algorithms. To lower bound the size of quantum computers with practical utility, we perform realistic simulations of the Quantum Approximate Optimization Algorithm and conclude that quantum speedup will not be attainable, at least for a representative combinatorial problem, until several hundreds of qubits are…

The northern Gulf of Mexico (GoM) is a region strongly influenced by river discharges of freshwater and nutrients, which promote a highly productive coastal ecosystem that host commercially valuable marine species. A variety of climate and weather processes could potentially influence the river discharges into the northern GoM. However, their impacts on the coastal ecosystem remain poorly described. By using a regional ocean-biogeochemical model, complemented with satellite and in situ observations, here we show that El Niño - Southern Oscillation (ENSO) is a main driver of the interannual variability in salinity and plankton biomass during winter and spring. Composite analysis of salinity and plankton biomass anomalies shows a strong asymmetry between El Niño and La Niña impacts, with much larger amplitude and broader areas affected during El Niño conditions. Further analysis of the model simulation reveals significant coastal circulation anomalies driven by changes in salinity and winds. The coastal circulation anomalies in turn largely determine the spatial extent and…

Abstract Recent work has disclosed the critical role played by enamel peptides in sex classification of old skeletal remains. In particular, protein AMELY (amelogenin isoform Y) is present in the enamel dental tissue of male individuals only, while AMELX (isoform X) can be found in both sexes. AMELY can be easily detected by LC-MS/MS in the ion extracted chromatograms of the SM (ox) IRPPY peptide (monoisotopic [M + 2 H] +2 mass = 440.2233 m/z ). In this paper, we exploited the dimorphic features of the amelogenin protein to determine the sex of the so-called ‘Lovers of Modena’, two Late Antique individuals whose skeletons were intentionally buried hand-in-hand. Upon discovery, mass media had immediately assumed they were a male-female couple, even if bad preservation of the bones did not allow an effective sex classification. We were able to extract proteins from the dental enamel of both individuals (~1600 years old) and to confidently classify them as males. Results were compared to 14 modern and archaeological control samples, confirming the reliability of the ion chromatogram…

Polypyrrole (PPy) nanorods (NRs) and nanoparticles (NPs) are synthesized via electrochemical and chemical methods, respectively, and tested upon ammonia exposure using Raman and X-ray photoelectron spectroscopy (XPS). Characterization of both nanomaterials via Raman spectroscopy demonstrates the formation of PPy, displaying vibration bands consistent with the literature. Additionally, XPS reveals the presence of neutral PPy species as major components in PPy NRs and PPy NPs, and other species including polarons and bipolarons. Raman and XPS analysis after ammonia exposure show changes in the physical/chemical properties of PPy, confirming the potential of both samples for ammonia sensing. Results demonstrate that the electrochemically synthesized NRs involve both proton and electron transfer mechanisms during ammonia exposure, as opposed to the chemically synthesized NPs, which show a mechanism dominated by electron transfer. Thus, the different detection mechanisms in PPy NRs and PPy NPs appear to be connected to the particular morphological and chemical composition of each film.…

A record 500,000 hectares burned in Portugal during the extreme wildfire season of 2017, with more than 120 human lives lost. Here we analyse the climatic factors responsible for the burned area (BA) from June to October series in Portugal for the period 1980-2017. Superposed onto a substantially stationary trend on BA data, strong oscillations on shorter time scales were detected. Here we show that they are significantly affected by the compound effect of summer (June-July-August) drought and high temperature conditions during the fire season. Drought conditions were calculated using the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSI). Then the extent to which the burned area has diverged from climate-expected trends was assessed. Our results indicate that in the absence of other drivers, climate change would have led to higher BA values. In addition, the 2017 extreme fire season is well captured with the model forced with climate drivers only, suggesting that the extreme fire…

, normal or impaired glucose metabolism), associations between SCFA (faecal and fasting circulating) and circulating metabolites, substrate oxidation and IS were investigated. In a subgroup (n = 93), IS was determined using a hyperinsulinemic-euglycemic clamp. Data were analyzed using multiple linear regression analysis adjusted for sex, age and BMI. Fasting circulating acetate, propionate and butyrate concentrations were positively associated with fasting GLP-1 concentrations. Additionally, circulating SCFA were negatively related to whole-body lipolysis (glycerol), triacylglycerols and free fatty acids levels (standardized (std) β adjusted (adj) -0.190, P = 0.023; std β adj -0.202, P = 0.010; std β adj -0.306, P = 0.001, respectively). Circulating acetate and propionate were, respectively, negatively and positively correlated with IS (M-value: std β adj -0.294, P < 0.001; std β adj 0.161, P = 0.033, respectively). We show that circulating rather than faecal SCFA were associated with GLP-1 concentrations, whole-body lipolysis and peripheral IS in humans. Therefore, circulating SCFA…

Adoption of no-till management on croplands has become a controversial approach for storing carbon in soil due to conflicting findings. Yet, no-till is still promoted as a management practice to stabilize the global climate system from additional change due to anthropogenic greenhouse gas emissions, including the 4 per mille initiative promoted through the UN Framework Convention on Climate Change. We evaluated the body of literature surrounding this practice, and found that SOC storage can be higher under no-till management in some soil types and climatic conditions even with redistribution of SOC, and contribute to reducing net greenhouse gas emissions. However, uncertainties tend to be large, which may make this approach less attractive as a contributor to stabilize the climate system compared to other options. Consequently, no-till may be better viewed as a method for reducing soil erosion, adapting to climate change, and ensuring food security, while any increase in SOC storage is a co-benefit for society in terms of reducing greenhouse gas emissions.

The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient's outcome since it assumes that the outcome is a linear combination of covariates. In this retrospective study including 255 patients suitable for analysis who underwent surgical treatment in our department from 2000 to 2017, we applied a deep learning-based survival prediction method in oral squamous cell carcinoma (SCC) patients and validated its performance. Survival prediction using DeepSurv, a deep learning based-survival prediction algorithm, was compared with random survival forest (RSF) and the Cox proportional hazard model (CPH). DeepSurv showed the best performance among the three models, the c-index of the training and testing sets reaching 0.810 and 0.781, respectively, followed by RSF (0.770/0.764), and CPH (0.756/0.694). The performance of DeepSurv steadily improved with added features. Thus, deep learning-based survival prediction may improve prediction accuracy and guide clinicians both in choosing…

The prevalence of many chronic diseases has increased over the last decades. It has been postulated that dysbiosis driven by environmental factors such as antibiotic use is shifting the microbiome in ways that increase inflammation and the onset of chronic disease. Dysbiosis can be defined through the loss or gain of bacteria that either promote health or disease, respectively. Here we use multiple independent datasets to determine the nature of dysbiosis for a cluster of chronic diseases that includes urinary stone disease (USD), obesity, diabetes, cardiovascular disease, and kidney disease, which often exist as co-morbidities. For all disease states, individuals exhibited a statistically significant association with antibiotics in the last year compared to healthy counterparts. There was also a statistically significant association between antibiotic use and gut microbiota composition. Furthermore, each disease state was associated with a loss of microbial diversity in the gut. Three genera, Bacteroides, Prevotella, and Ruminococcus, were the most common dysbiotic taxa in terms of…

Detecting changes in climate is a prerequisite for a better understanding of the climate and developing adaptation and mitigation measures at a regional and local scale. In this study long-term trends in rainfall and maximum and minimum temperature (T-max and T-min) were analysed on seasonal and annual time scales for East Africa. High resolution gridded rainfall (1981-2016) and temperature (1979-2010) data from international databases like the Climate Hazards Group are used. Long-term seasonal trend analysis shows a non-significant (except for small areas), decreasing (increasing) trend in rainfall in eastern (western) parts of Ethiopia and Kenya and a decreasing trend in large parts of Tanzania during the long rainy season. On the other hand, a non-significant increasing trend in large parts of the region is observed during the short rain season. With regard to annual trends, results largely confirm seasonal analyses: only a few significant trends in rainfall, but significant increasing trends in T-max (up to 1.9 °C) and T-min (up to 1.2 °C) for virtually the whole region. Our…

Recently, deep-learning-based approaches have been proposed for the classification of neuroimaging data related to Alzheimer's disease (AD), and significant progress has been made. However, end-to-end learning that is capable of maximizing the impact of deep learning has yet to receive much attention due to the endemic challenge of neuroimaging caused by the scarcity of data. Thus, this study presents an approach meant to encourage the end-to-end learning of a volumetric convolutional neural network (CNN) model for four binary classification tasks (AD vs. normal control (NC), progressive mild cognitive impairment (pMCI) vs. NC, stable mild cognitive impairment (sMCI) vs. NC and pMCI vs. sMCI) based on magnetic resonance imaging (MRI) and visualizes its outcomes in terms of the decision of the CNNs without any human intervention. In the proposed approach, we use convolutional autoencoder (CAE)-based unsupervised learning for the AD vs. NC classification task, and supervised transfer learning is applied to solve the pMCI vs. sMCI classification task. To detect the most important…

Studying transitions in and out of the altered state of consciousness caused by intravenous (IV) N,N-Dimethyltryptamine (DMT - a fast-acting tryptamine psychedelic) offers a safe and powerful means of advancing knowledge on the neurobiology of conscious states. Here we sought to investigate the effects of IV DMT on the power spectrum and signal diversity of human brain activity (6 female, 7 male) recorded via multivariate EEG, and plot relationships between subjective experience, brain activity and drug plasma concentrations across time. Compared with placebo, DMT markedly reduced oscillatory power in the alpha and beta bands and robustly increased spontaneous signal diversity. Time-referenced and neurophenomenological analyses revealed close relationships between changes in various aspects of subjective experience and changes in brain activity. Importantly, the emergence of oscillatory activity within the delta and theta frequency bands was found to correlate with the peak of the experience - particularly its eyes-closed visual component. These findings highlight marked changes in…

Iran is experiencing unprecedented climate-related problems such as drying of lakes and rivers, dust storms, record-breaking temperatures, droughts, and floods. Here, we use the ensemble of five high-resolution climate models to project maximum and minimum temperatures and rainfall distribution, calculate occurrences of extreme temperatures (temperatures above and below the historical 95th and 5th percentiles, respectively), analyze compound of precipitation and temperature extremes, and determine flooding frequencies across the country. We found that compared to the period of 1980-2004, in the period of 2025-2049, Iran is likely to experience more extended periods of extreme maximum temperatures in the southern part of the country, more extended periods of dry (for ≥120 days: precipitation <2 mm, Tmax ≥30 °C) as well as wet (for ≤3 days: total precipitation ≥110 mm) conditions, and higher frequency of floods. Overall, the combination of these results projects a climate of extended dry periods interrupted by intermittent heavy rainfalls, which is a recipe for increasing the chances…

Chronic alcohol use is associated with cognitive decline that impedes behavioral change during rehabilitation. Despite this, addiction therapy does not address cognitive deficits, and there is poor understanding regarding the mechanisms that underlie this decline. We established a rodent model of chronic voluntary alcohol use to measure ensuing cognitive effects and underlying pathology. Rats had intermittent access to alcohol or an isocaloric solution in their home cage under voluntary 2-bottle choice conditions. In Experiments 1 and 2 cognition was assessed using operant touchscreen chambers. We examined performance in a visual discrimination and reversal task (Experiment 1), and a 5-choice serial reaction time task (Experiment 2). For Experiment 3, rats were perfused immediately after cessation of alcohol access period, and volume, cell density and microglial populations were assessed in the prefrontal cortex and striatum. Volume was assessed using the Cavalieri probe, while cell and microglial counts were estimated using unbiased stereology with an optical fractionator.…

Independent and combined drought and heat stress negatively affect wheat yield and physiology. The present study was aimed to quantify effects of Drought [D], heat [H] and combined heat and drought [HD] during reproductive stage on wheat yield and to identify physio-biochemical traits which were strongly associated with improved yield and tolerance of wheat under stressful conditions. One hundred and eight elite diverse wheat genotypes were exposed to [H], [D] and [HD] treatments from heading till maturity. Grain yield was reduced by 56.47%, 53.05% and 44.66% under [HD], [H] and [D] treatment, respectively. The [HD] treatment affects the grain yield by reducing metabolism and mobilization of reserves to developing grains and leaves. Disintegration of membrane structure, chlorophyll and protein molecules was higher under [H] stress than [D] stress while water status of genotypes and sink strength was more affected by [D] than [H] stress. Multivariate analysis showed a strong correlation of chlorophyll content before and after anthesis, water-soluble carbohydrates (WSC), proline…

Abstract Pinus pinaster bark, an abundant by-product from the timber industry, has been studied as a potential low-cost adsorbent for the removal of Congo red (CR) dye from wastewaters. Surface morphological and physico-chemical characteristics of pine bark were analysed using Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), determination of the point of zero charge (pH PZC ) and elemental analysis. Assays were performed to determine the wavelength for the maximum absorbance and the stability with time of CR solutions depending on concentration and/or pH, which resulted to be a very significant parameter. Adsorption studies were conducted on batch mode to study the effect of contact time (till 7 days), pH (2–9), adsorbent dosage (1–10 g L −1 ) and temperature (25–60 °C). The bark adsorption capacity at equilibrium varied between 0.3 and 1.6 mg g −1 and the equilibrium adsorption percentage between 23.4 and 100% depending on adsorbent dosage, temperature and pH at an initial CR concentration of 5 mg L −1 . Kinetic data for the removal of CR by pine…

Abstract Drought episodes decrease plant growth and productivity, which in turn cause high economic losses. Plants naturally sense and respond to water stress by activating specific signalling pathways leading to physiological and developmental adaptations. Genetically engineering genes that belong to these pathways might improve the drought tolerance of plants. The abscisic acid (ABA)-responsive element binding protein 1/ABRE binding factor (AREB1/ABF2) is a key positive regulator of the drought stress response. We investigated whether the CRISPR activation (CRISPRa) system that targets AREB1 might contribute to improve drought stress tolerance in Arabidopsis. Arabidopsis histone acetyltransferase 1 (AtHAT1) promotes gene expression activation by switching chromatin to a relaxed state. Stable transgenic plants expressing chimeric dCas9 HAT were first generated. Then, we showed that the CRISPRa dCas9 HAT mechanism increased the promoter activity controlling the β-glucuronidase ( GUS ) reporter gene. To activate the endogenous promoter of AREB1 , the CRISPRa dCas9 HAT system was set…

Classification of histologic patterns in lung adenocarcinoma is critical for determining tumor grade and treatment for patients. However, this task is often challenging due to the heterogeneous nature of lung adenocarcinoma and the subjective criteria for evaluation. In this study, we propose a deep learning model that automatically classifies the histologic patterns of lung adenocarcinoma on surgical resection slides. Our model uses a convolutional neural network to identify regions of neoplastic cells, then aggregates those classifications to infer predominant and minor histologic patterns for any given whole-slide image. We evaluated our model on an independent set of 143 whole-slide images. It achieved a kappa score of 0.525 and an agreement of 66.6% with three pathologists for classifying the predominant patterns, slightly higher than the inter-pathologist kappa score of 0.485 and agreement of 62.7% on this test set. All evaluation metrics for our model and the three pathologists were within 95% confidence intervals of agreement. If confirmed in clinical practice, our model can…

Seasonal drought is a major threat to rice production. However, the sensitivity of rice to drought stress (DS) at different growth periods remains unclear. The objective of this study was to reveal the different impacts of DS at the flowering stage on rice physiological traits, grain yield, and quality. Field experiments were conducted with two rice cultivars, Yangliangyou 6 (YLY6) and Hanyou 113 (HY113) under two water treatments (traditional flooding (CK) and DS at flowering stage) in 2013 and 2014. Compared with CK, grain yield (GY) under DS was significantly reduced by 23.2% for YLY6 and 24.0% for HY113 while instantaneous water use efficiency (IWUE) was significantly increased by 39% for YLY6 and 37% for HY113, respectively. All physiological traits were significantly decreased under DS and physiological activities did not revert to normal levels at grain filling stage. There was no significant effect on the appearance and nutritional quality except for the significant increase in chalky kernel and chalkiness under DS. Our data suggest that drought stress at flowering stage has…

Gold nanoparticles (AuNPs) have been extensively used as nanomaterials for theranostic applications due to their multifunctional characteristics in therapeutics, imaging, and surface modification. In this study, the unique functionalities of exosome-derived membranes were combined with synthetic AuNPs for targeted delivery to brain cells. Here, we report the surface modification of AuNPs with brain-targeted exosomes derived from genetically engineered mammalian cells by using the mechanical method or extrusion to create these novel nanomaterials. The unique targeting properties of the AuNPs after fabrication with the brain-targeted exosomes was demonstrated by their binding to brain cells under laminar flow conditions as well as their enhanced transport across the blood brain barrier. In a further demonstration of their ability to target brain cells, in vivo bioluminescence imaging revealed that targeted-exosome coated AuNPs accumulated in the mouse brain after intravenous injection. The surface modification of synthetic AuNPs with the brain-targeted exosome demonstrated in this…

As environmental DNA (eDNA) studies have grown in popularity for use in ecological applications, it has become clear that their results differ in significant ways from those of traditional, non-PCR-based surveys. In general, eDNA studies that rely on amplicon sequencing may detect hundreds of species present in a sampled environment, but the resulting species composition can be idiosyncratic, reflecting species' true biomass abundances poorly or not at all. Here, we use a set of simulations to develop a mechanistic understanding of the processes leading to the kinds of results common in mixed-template PCR-based (metabarcoding) studies. In particular, we focus on the effects of PCR cycle number and primer amplification efficiency on the results of diversity metrics in sequencing studies. We then show that proportional indices of amplicon reads capture trends in taxon biomass with high accuracy, particularly where amplification efficiency is high (median correlation up to 0.97). Our results explain much of the observed behavior of PCR-based studies, and lead to recommendations for…

Abstract On Dec. 22, 2018, at approximately 20:55–57 local time, Anak Krakatau volcano, located in the Sunda Straits of Indonesia, experienced a major lateral collapse during a period of eruptive activity that began in June. The collapse discharged volcaniclastic material into the 250 m deep caldera southwest of the volcano, which generated a tsunami with runups of up to 13 m on the adjacent coasts of Sumatra and Java. The tsunami caused at least 437 fatalities, the greatest number from a volcanically-induced tsunami since the catastrophic explosive eruption of Krakatau in 1883 and the sector collapse of Ritter Island in 1888. For the first time in over 100 years, the 2018 Anak Krakatau event provides an opportunity to study a major volcanically-generated tsunami that caused widespread loss of life and significant damage. Here, we present numerical simulations of the tsunami, with state-of the-art numerical models, based on a combined landslide-source and bathymetric dataset. We constrain the geometry and magnitude of the landslide source through analyses of pre- and post-event…

Recently, the concerns about micro- and nano-plastics (NPs) toxicity have been increasing constantly, however the investigations are quiet meager. The present study provides evidences on the toxicological prospectives of virgin-, coronated- and isolated-NPs on human blood cells and Allium cepa root tip, respectively. Several plasma proteins displayed strong affinity towards NPs and produced multi-layered corona of 13 nm to 600 nm size. The coronated-NPs often attracted each other via non-specific protein-protein attraction which subsequently induced protein-induced coalescence in NPs. In the protein point of view, the interaction caused conformational changes and denaturation of protein thereby turned it as bio-incompatible. The coronated-NPs with increased protein confirmation changes caused higher genotoxic and cytotoxic effect in human blood cells than the virgin-NPs. On the other hand, virgin-NPs and the NPs isolated from facial scrubs hindered the root growth and caused chromosome aberration (ring formation, C-mitotic and chromosomal breaks, etc.) in root of Allium cepa. At the…

Immersive virtual reality has become increasingly popular to improve the assessment and treatment of health problems. This rising popularity is likely to be facilitated by the availability of affordable headsets that deliver high quality immersive experiences. As many health problems are more prevalent in older adults, who are less technology experienced, it is important to know whether they are willing to use immersive virtual reality. In this study, we assessed the initial attitude towards head-mounted immersive virtual reality in 76 older adults who had never used virtual reality before. Furthermore, we assessed changes in attitude as well as self-reported cybersickness after a first exposure to immersive virtual reality relative to exposure to time-lapse videos. Attitudes towards immersive virtual reality changed from neutral to positive after a first exposure to immersive virtual reality, but not after exposure to time-lapse videos. Moreover, self-reported cybersickness was minimal and had no association with exposure to immersive virtual reality. These results imply that the…