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MetaDAVis: An R shiny application for metagenomic data analysis and visualization
The human microbiome exerts tremendous influence on maintaining a balance between human health and disease. High-throughput sequencing has enabled the study of microbial communities at an unprecedented resolution. Generation of massive amounts of sequencing data has also presented novel challenges to analyzing and visualizing data to make biologically relevant interpretations. We have developed an interactive Metagenome Data Analysis and Visualization (MetaDAVis) tool for 16S rRNA as well as the whole genome sequencing data analysis and visualization to address these challenges using an R Shiny application. MetaDAVis can perform six different types of analyses that include: i) Taxonomic abundance distribution; ii) Alpha and beta diversity analyses; iii) Dimension reduction tasks using PCA, t-SNE, and UMAP; iv) Correlation analysis using taxa- or sample-based data; v) Heatmap generation; and vi) Differential abundance analysis. MetaDAVis creates interactive and dynamic figures and tables from multiple methods enabling users to easily understand their data using different variables. Our program is user-friendly and easily customizable allowing those without any programming background to perform comprehensive data analyses using a standalone or web-based interface.
Erratum: “Sequence dependence of critical properties for two-letter chains” [J. Chem. Phys. 160, 234902 (2024)]
A new growing degree-day phenology model for wheat stem sawfly (Hymenoptera: Cephidae) in Colorado wheat fields
Wheat stem sawfly (WSS), Cephus cinctus (Hymenoptera: Cephidae), is a native grass-feeding insect and one of the most important pests of wheat in North America. Yield losses from WSS can be due to stem boring and/or stem cutting which causes plants to lodge. Current methods, such as solid stem varieties and insecticides, do not effectively control WSS. A better understanding of WSS emergence, population size, and related environmental factors is critical to building efficient and effective integrated pest management (IPM) strategies for this pest. In this study, wheat fields were sampled for adult WSS from mid-April to the end of June between 2011 and 2023 in several field sites in two locations in Colorado. This multi-year data created a phenology model that predicts adult WSS emergence and population peak based on growing degree-day (GDD). The inter-annual variability in emergence timing based on calendar date was substantially reduced when using a GDD model with a base temperature of 10°C, an upper threshold of 30°C, and a biofix of Jan 1. The model predicted initial WSS emergence at 148 GDD, population peak at 224 GDD, and decline at 354 GDD. We also modeled the effects of environmental factors on mean WSS populations at each field site, finding that higher WSS populations are associated with longer emergence periods, less precipitation before emergence, milder temperatures during emergence, and milder maximum temperatures before and during emergence. By analyzing multiple years of comprehensive phenology data, we provide robust models to guide adult WSS forecasting and monitoring for the first time. Further, this data will aid in decision-making related to timely and effective management strategies to suppress populations of WSS.
Optical-cavity manipulation strategies of singlet fission systems mediated by conical intersections: Insights from fully quantum simulations
We offer a theoretical perspective on simulation and engineering of polaritonic conical-intersection-driven singlet-fission (SF) materials. We begin by examining fundamental models, including Tavis–Cummings and Holstein–Tavis–Cummings Hamiltonians, exploring how disorder, non-Hermitian effects, and finite temperature conditions impact their dynamics, setting the stage for studying conical intersections and their crucial role in SF. Using rubrene as an example and applying the numerically accurate Davydov Ansatz methodology, we derive dynamic and spectroscopic responses of the system and demonstrate key mechanisms capable of SF manipulation, viz. cavity-induced enhancement/weakening/suppression of SF, population localization on the singlet state via engineering cavity-mode excitation, polaron/polariton decoupling, and collective enhancement of SF. We outline unsolved problems and challenges in the field and share our views on the development of the future lines of research. We emphasize the significance of careful modeling of cascades of polaritonic conical intersections in high excitation manifolds and envisage that collective geometric phase effects may remarkably affect the SF dynamics and yield. We argue that the microscopic interpretation of the main regulatory mechanisms of polaritonic conical-intersection-driven SF can substantially deepen our understanding of this process, thereby providing novel ideas and solutions for improving conversion efficiency in photovoltaics.
AgrC biotinylation inhibits Staphylococcus aureus infection
Staphylococcus aureus (S. aureus) is a leading cause of nosocomial infections, particularly among antibiotic-resistant strains. S. aureus virulence is governed by the accessory gene regulator (Agr) quorum sensing (QS) system, which relies on AgrC, a two-component histidine kinase, to detect secreted auto-inducing peptides (AIPs). Emerging evidence highlights the potential of inhibiting the interaction between AgrC and AIPs as a promising therapeutic strategy. Given the limited clinic methods in inhibiting AgrC, we hereby report a novel method utilizing TurboID, an engineered biotin ligase, to inhibit Agr C on S. aureus via its biotinylation. To achieve this goal, a fusion protein named TurboID-AgrD1−2 (Agr-ID) was designed to include an AgrC binding domain (AgrID1−2) and a catalytic domain (TurboID) for AgrC biotinylation. By incubating with Alexa Fluor 647-conjugated streptavidin, the biotinylated AgrC on S. aureus was successfully visualized through fluorescence microscopy with 100x objective. We further confirmed the specific biotinylation of AgrC using Western Blotting, and biotinylated AgrC resulted in inhibiting the growth of S. aureus strains, including S. aureus 25923, S. aureus 43300, and S. aureus 6538 (MRSA). The downstream biological effect of AgrC biotinylation exhibited decreased virulence protein generation as monitored by the lower presence of apoptotic HEK 293T cells after incubating with S. aureus cell lysates and supernatant. The impaired colonizing features from biotinylated S. aureus 6538 were investigated by calculating the decreased ratio of cell death versus live HeLa cells. By further investigating the efficiency of the immune clearance of biotinylated S. aureus by mouse macrophages, we observed the enhanced uptake of S. aureus by murine macrophages in vivo. Overall, our work reveals that the biotinylation of AgrC can inhibit the growth and toxicity of S. aureus while simultaneously promoting the clearance of biotinylated S. aureus via macrophage phagocytosis.
Flexocatalysis: Regulating peroxymonosulfate activation by flexoelectricity
Challenges related to energy shortages and environmental pollution are driving extensive research in catalysis. Flexocatalysis, which extends flexoelectricity to mechanocatalysis, is a promising mechanism for catalytic processes. Owing to its size-dependent effects, flexoelectricity has become particularly significant and plays a dominant regulatory role in chemical reactions within nanocatalysis. In this study, we integrated flexocatalysis with peroxymonosulfate (PMS) activation for efficient water purification. The simulation results show that flexoelectric polarization can induce a strong flexoelectric field in δ-MnO2 nanosheets. This built-in electric field subsequently drives the migration of electrons and holes to the reaction interface, thereby activating PMS and promoting rapid generation of reactive species for the degradation of organic pollutants. At low concentrations of flexoelectric catalysts, we achieved excellent degradation efficiency that was 6.6 times greater than that obtained through the thermal activation of PMS. This study demonstrated that flexoelectricity can function as a switch for PMS activation and offers a promising approach for sustainable water remediation.
Layer-specific residual strains in human carotid arteries revealed under layer separation
Residual stresses are considered as a significant factor influencing the stress-states in arteries. These stresses are typically observed through opening angle of a radially cut artery segment, often regarded as a primary descriptor of their stress-free state. However, the experimental evidence regarding the stress-free states of different artery layers is scarce. In this study, two experimental protocols, each employing different layer-separating sequences, were performed on 17 human common carotid arteries; the differences between both protocols were found statistically insignificant. While the media exhibited opening behaviour (reduced curvature), a contrasting trend was observed for the adventitia curvature, indicating its closing behaviour. In addition to the different bending effect, length changes of both layers after separation were observed, namely shortening of the adventitia and elongation of the media. The results point out that not all the residual stresses are released after a radial cut but a significant portion of them is released only after the layer separation. Considering the different mechanical properties of layers, this may significantly change the stress distribution in arterial wall and should be considered in its biomechanical models.
Automated mapping of land cover in Google Earth Engine platform using multispectral Sentinel-2 and MODIS image products
Land cover mapping often utilizes supervised classification, which can have issues with insufficient sample size and sample confusion, this study assessed the accuracy of a fast and reliable method for automatic labeling and collection of training samples. Based on the self-programming in Google Earth Engine (GEE) cloud-based platform, a large and reliable training dataset of multispectral Sentinel-2 image was extracted automatically across the study area from the existing MODIS land cover product. To enhance confidence in high-quality training class labels, homogeneous 20 m Sentinel-2 pixels within each 500 m MODIS pixel were selected and a minority of heterogeneous 20 m pixels were removed based on calculations of spectral centroid and Euclidean distance. Further, the quality control and spatial filter were applied for all land cover classes to generate a reliable and representative training dataset that was subsequently applied to train the Classification and Regression Tree (CART), Random Forest (RF), and Support Vector Machine (SVM) classifiers. The results shows that the main land cover types in the study area as distinguished by three different classifiers were Evergreen Broadleaf Forests, Mixed Forests, Woody Savannas, and Croplands. In the training and validation samples, the numbers of correctly classified pixels under the CART without computationally intensive were more than those for the RF and SVM classifiers. Moreover, the user’s and producer’s accuracies, overall accuracy and kappa coefficient of the CART classifier were the best, indicating the CART classifier was more suitable to this automatic workflow for land cover mapping. The proposed method can automatically generate a large number of reliable and accurate training samples in a timely manner, which is promising for future land cover mapping in a large-scale region.
Factors influencing colorectal cancer screening decisions among Saudi women: A qualitative study
Background Colorectal cancer (CRC) is a major global health challenge and one of the most prevalent cancers in Saudi Arabia. Studies show that young Saudi women are often diagnosed with CRC at more advanced stages, leading to poorer prognoses. Despite the recent launch of the first Saudi national CRC screening program, public awareness and acceptance of CRC screening (CRCS) remain limited. Methods We conducted semi-structured interviews with 17 women aged 40 or older to explore their awareness, views, and attitudes toward CRC and CRCS. Data were analyzed using reflexive thematic analysis, and the Social Ecological Model was applied to guide the structuring and organization of the developed themes. Results We identified a multifaceted interplay of knowledge, beliefs, and social-cultural factors influencing CRCS decisions among Saudi women. Although there was a general awareness of CRC, understanding of risk factors, signs, and symptoms was limited. Many participants adopted a reactive approach to screening, prompted by symptom manifestation or family history, rather than preventive health measures. Concerns such as fear of a cancer diagnosis and discomfort with the stool sample collection process hindered screening participation. Social support from family and community, and physician recommendations were crucial in encouraging screening uptake. Logistic and digital literacy challenges in accessing health services were noted for older adults. Participants stressed the need for increased CRC awareness, equitable access to screening services, and reminders to improve CRCS participation. Conclusion Factors influencing CRCS uptake among Saudi women are complex and multifaceted. Comprehensive and tailored health promotion interventions that meet community needs are essential. Further research is needed to develop and evaluate the effectiveness of these interventions in increasing screening uptake.
A protocol for an experimental investigation of the effects of pain-related interpretation bias modification on interpretation of ambiguous somatosensory and linguistic stimuli in healthy individuals
Researchers are increasingly exploring the existence and potential implications of pain-related cognitive biases in clinical and non-clinical populations, using a range of paradigms and stimuli to test theoretical predictions and refine models. One avenue of investigation explores the implications of biased pain-related interpretations in pain-free individuals, which may shed light on processes of transition from a pain-free state to acute pain, and acute pain to chronic pain. The primary aim of the main study detailed in this protocol is to investigate the effects of pain-related cognitive bias modification for interpretation (CBM-I) on the interpretation of ambiguous somatosensory stimuli. When deciding the point at which to report their level of pain threshold and tolerance, participants must by necessity interpret somatosensory sensations. Sensations around the pain threshold are likely to be ambiguously painful, sometimes interpreted as painful and sometimes not, which has been proposed as a zone of uncertainty. A pilot study was first conducted to test whether the proposed experimental design is feasible and appropriate, and to ascertain study effect sizes. Eighteen healthy participants were randomised to complete either benign CBM-I (trained towards neutral interpretations of ambiguous scenarios; n = 9) or pain CBM-I (trained towards pain-related interpretations of ambiguous scenarios; n = 9). The Ambiguous Scenarios Task was used to train interpretation biases, and a novel Interpretation of Somatosensory Sensations Assessment was used to explore interpretation of ambiguous somatosensory sensations around the individual’s pain threshold. Participants receiving pain CBM-I, compared to those receiving benign CBM-I, had higher pain-related interpretation bias scores on the test phase of the Ambiguous Scenarios Task with a large effect size, and showed higher intensity and unpleasantness ratings on the Interpretation of Somatosensory Sensations Assessment typically with medium to large effect sizes. These paradigms are suitable for a full-scale investigation. Modifications made to the experimental design based on insights from the pilot study are discussed. This research extends beyond pain patient populations to researchers and clinicians working with other conditions, especially anxiety and mood disorders where patients may misinterpret or catastrophize ambiguous bodily sensations.
Attention Allocation for Dysphoric Information in Adults with Depression Symptoms Using Eye-tracking and Mouse-tracking
Biased attention for dysphoric stimuli is thought to maintain depression, but poor measurement has limited prior tests of this hypothesis. The current study examined the association between biased attention for dysphoric information and depression using a novel free viewing attention bias task combined with measuring line of visual gaze via eye tracking or a behavioral proxy for line of visual gaze via mouse tracking in three samples of college students using in-person eye-tracking (Experiment 1, N = 129) and remotely collected mouse-tracking (Experiment 2, N = 79; Experiment 3, N = 154). Mixed effects regression analyses revealed that depression severity was significantly associated with greater attention for dysphoric stimuli in Experiments 1 and 2, but not Experiment 3. Results suggest that depression severity is associated with attention for dysphoric information (although findings from Experiment 3 temper this conclusion) and that eye- and mouse-tracking may be good options for measuring attention bias in depression. Additional work using longitudinal research designs seems warranted to further examine the relationship between attention bias for dysphoric information and the maintenance of depression.
Spatial monitoring of open caissons via computer vision approach
Sustainable hydrophobic bio-based adsorbent from modified sphagnum moss for efficient oil-water separation
Separation of thoracic and abdominal measurements in neonatal vital sign monitoring using radar vision fusion system
Research on intelligent identification of microscopic substances in shale scanning electron microscope images based on deep learning theory
Association between organophosphate esters exposure and the prevalence of hyperuricemia in US adults from NHANES 2011–2016
Magnetic properties and entanglement in antiferromagnetic interactions in copper(II) dinuclear and trinuclear complexes
Theoretical research and system design of ship navigation guidance for local temporary prohibited navigation area
Exploring the injury severity of unlicensed powered two- and three-wheeler drivers in two-vehicle crashes in China
Abstract Large presence of unlicensed powered two- and three-wheeler (PTW) drivers in China pose a significant threat to road safety. In this study, a customized Deep Forest Model (DF-ptw) is constructed to investigate the effect of unlicensed PTW drivers on crash severity in two-vehicle crashes, using a recent 3-year historical crash data. SHapley Additive explanation (SHAP) and Partial Dependence Plot (PDP) analysis reveal that unlicensed motorcyclists are significantly more likely to suffer serious injuries in two-vehicle crashes compared to unlicensed auto-rickshaw drivers. Additionally, factors such as drunk driving, fatigued driving, and being an unlicensed driver over the age of 53 notably elevate the risk of serious injury or death, with unlicensed motorcyclists being disproportionately affected. Moreover, self-employed unlicensed PTW drivers face a higher probability of serious injury or fatality in crashes compared to farmers, blue-collar, and white-collar workers. Unlicensed PTW drivers are also more susceptible to severe or fatal injuries on national and provincial roads, in low visibility conditions, during late-night hours, on non-separated roads, and at dusk or dawn. Based on these findings, this study proposes to reduce the frequency and severity of crashes involving unlicensed PTW drivers by focusing on more stringent eligibility checks, increasing safety awareness, and implementing advanced safety measures.