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Abstract Single cell ATAC-seq (scATAC-seq) experimental designs have become increasingly complex, with multiple factors that might affect chromatin accessibility, including genotype, cell type, tissue of origin, sample location, batch, etc., whose compound effects are difficult to test by existing methods. In addition, current scATAC-seq data present statistical difficulties due to their sparsity and variations in individual sequence capture. To address these problems, we present a zero-adjusted statistical model, Probability model of Accessible Chromatin of Single cells (PACS), that allows complex hypothesis testing of accessibility-modulating factors while accounting for sparse and incomplete data. For differential accessibility analysis, PACS controls the false positive rate and achieves a 17% to 122% higher power on average than existing tools. We demonstrate the effectiveness of PACS through several analysis tasks, including supervised cell type annotation, compound hypothesis testing, batch effect correction, and spatiotemporal modeling. We apply PACS to datasets from various tissues and show its ability to reveal previously undiscovered insights in scATAC-seq data.

Neighborhood rough set is considered an essential approach for dealing with incomplete data and inexact knowledge representation, and it has been widely applied in feature selection. The Gini index is an indicator used to evaluate the impurity of a dataset and is also commonly employed to measure the importance of features in feature selection. This article proposes a novel feature selection methodology based on these two concepts. In this methodology, we present the neighborhood Gini index and the neighborhood class Gini index and then extensively discuss their properties and relationships with attributes. Subsequently, two forward greedy feature selection algorithms are developed using these two metrics as a foundation. Finally, to comprehensively evaluate the performance of the algorithm proposed in this article, comparative experiments were conducted on 16 UCI datasets from various domains, including industry, food, medicine, and pharmacology, against four classical neighborhood rough set-based feature selection algorithms. The experimental results indicate that the proposed algorithm improves the average classification accuracy on the 16 datasets by over 6%, with improvements exceeding 10% in five. Furthermore, statistical tests reveal no significant differences between the proposed algorithm and the four classical neighborhood rough set-based feature selection algorithms. However, the proposed algorithm demonstrates high stability, eliminating most redundant or irrelevant features effectively while enhancing classification accuracy. In summary, the algorithm proposed in this article outperforms classical neighborhood rough set-based feature selection algorithms.

Abstract The transcription factor hepatocyte nuclear factor 1β (HNF-1β) is essential for normal development of the kidney and other epithelial organs. In the developing mouse kidney, HNF-1β is required for the differentiation and patterning of immature nephrons and branching morphogenesis of the ureteric bud (UB). Here, we used ChIP-sequencing (ChIP-seq) and RNA sequencing (RNA-seq) to identify genes that are regulated by HNF-1β in embryonic mouse kidneys. ChIP-seq revealed that HNF-1β binds to 8284 sites in chromatin from E14.5 mouse kidneys. Comparison with previous ATAC-seq and histone modification studies showed that HNF-1β binding peaks colocalized with open chromatin and epigenetic marks of transcriptional activation (H3K27 acetylation, H3K4 trimethylation, H3K4 monomethylation), indicating that the binding sites were functional. To investigate the relationship between HNF-1β binding and HNF-1β-dependent gene regulation, RNA-seq was performed on UB cells purified from wild-type and HNF-1β mutant embryonic kidneys. A total of 1632 genes showed reduced expression in HNF-1β-deficient UB cells, and 485 genes contained nearby HNF-1β binding sites indicating that they were directly activated by HNF-1β. Conversely, HNF-1β directly repressed the expression of 526 genes in the UB. Comparison with snATAC-seq analysis of UB-derived cells showed that both HNF-1β-dependent activation and repression correlated with chromatin accessibility. Pathway analysis revealed that HNF-1β binds near 68 axon guidance genes in the developing kidney. RNA-seq analysis showed that Nrp1, Sema3c, Sema3d, Sema6a, and Slit2 were activated by HNF-1β, whereas Efna1, Epha3, Epha4, Epha7, Ntn4, Plxna2, Sema3a, Sema4b, Slit3, Srgap1, Unc5c and Unc5d were repressed by HNF-1β. RNAscope in situ hybridization showed that Nrp1, Sema3c, Sema3d, Sema6a, and Slit2 were expressed in wild-type UB and were dysregulated in HNF-1β mutant UB. These studies show that HNF-1β directly regulates the expression of multiple axon guidance genes in the developing mouse kidney. Dysregulation of axon guidance genes may underlie kidney defects in HNF-1β mutant mice.

Abstract We consider an increasingly popular study design where single-cell RNA-seq data are collected from multiple individuals and the question of interest is to find genes that are differentially expressed between two groups of individuals. Towards this end, we propose a statistical method named IDEAS (individual level differential expression analysis for scRNA-seq). For each gene, IDEAS summarizes its expression in each individual by a distribution and then assesses whether these individual-specific distributions are different between two groups of individuals. We apply IDEAS to assess gene expression differences of autism patients versus controls and COVID-19 patients with mild versus severe symptoms.

Human-wildlife conflict is rapidly evolving in response to significant ecological, social, and economic changes affecting society globally. Developing objective and acceptable resolution strategies is challenging because of divergence in perceptions and understandings of human-wildlife conflict between urban and rural populations, and this disparity is increasing with rapid urbanization. In this study, we explore preferences for wild boar conflict management in China using a mixed methods approach of a survey, choice experiments, and interviews. We found that significant differences in the preferences of wild boar management exist between rural and urban residents. The majority of rural residents preferred hunting whereas most urban residents in cities remote from the conflict preferred non-hunting measures. However, we found that economic cost played an important role in influencing public preferences for management measures. The urban population had positive preferences for hunting if they were required to pay an environmental tax to compensate farmers for crop damage when asked to consider their preferred management strategy package. We consider that the current management of hunting wild boar in China requires improvement, and we argue that China should adjust the current hunting management policy to take into account the benefits of wild boar population control and the economic development of the surrounding rural areas.

BackgroundA single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout from digital health interventions for smoking cessation, specifically, users who logged in during the first week of the intervention and had little to no activity thereafter. These users also had a substantially lower smoking cessation rate with our iCanQuit smoking cessation app compared with users who used the app for longer periods. ObjectiveThis study aimed to explore whether log-in count data, using standard statistical methods, can precisely predict whether an individual will become an iCanQuit early dropout while validating the approach using other statistical methods and randomized trial data from 3 other digital interventions for smoking cessation (combined randomized N=4529). MethodsStandard logistic regression models were used to predict early dropouts for individuals receiving the iCanQuit smoking cessation intervention app, the National Cancer Institute QuitGuide smoking cessation intervention app, the WebQuit.org smoking cessation intervention website, and the Smokefree.gov smoking cessation intervention website. The main predictors were the number of times a participant logged in per day during the first 7 days following randomization. The area under the curve (AUC) assessed the performance of the logistic regression models, which were compared with decision trees, support vector machine, and neural network models. We also examined whether 13 baseline variables that included a variety of demographics (eg, race and ethnicity, gender, and age) and smoking characteristics (eg, use of e-cigarettes and confidence in being smoke free) might improve this prediction. ResultsThe AUC for each logistic regression model using only the first 7 days of log-in count variables was 0.94 (95% CI 0.90-0.97) for iCanQuit, 0.88 (95% CI 0.83-0.93) for QuitGuide, 0.85 (95% CI 0.80-0.88) for WebQuit.org, and 0.60 (95% CI 0.54-0.66) for Smokefree.gov. Replacing logistic regression models with more complex decision trees, support vector machines, or neural network models did not significantly increase the AUC, nor did including additional baseline variables as predictors. The sensitivity and specificity were generally good, and they were excellent for iCanQuit (ie, 0.91 and 0.85, respectively, at the 0.5 classification threshold). ConclusionsLogistic regression models using only the first 7 days of log-in count data were generally good at predicting early dropouts. These models performed well when using simple, automated, and readily available log-in count data, whereas including self-reported baseline variables did not improve the prediction. The results will inform the early identification of people at risk of early dropout from digital health interventions with the goal of intervening further by providing them with augmented treatments to increase their retention and, ultimately, their intervention outcomes.

Identifying causal variants and genes is an essential step in interpreting GWAS loci. Here, the authors investigate a kidney disease GWAS locus with functional genomics data, CRISPR editing and mouse experiments to identify DPEP1 and CHMP1A as putative kidney disease genes via ferroptosis.

Epigenetic and transcriptional dynamics are critical for both tissue homeostasis and injury response in the kidney. Leveraging a single cell multiomics atlas of the developing mouse kidney, the authors reveal key events in chromatin regulation and gene expression dynamics during postnatal development.

BackgroundLittle is known about how individuals engage over time with smartphone app interventions and whether this engagement predicts health outcomes. ObjectiveIn the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership. MethodsFunctional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app. ResultsFor iCanQuit, participants were clustered into 3 groups: “1-week users” (610/1069, 57.06%), “4-week users” (303/1069, 28.34%), and “26-week users” (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), whereas 26-week users had 397% higher odds (56% vs 23%; OR 4.97, 95% CI 3.31-7.52; P

Radiation causes a collapse of bone marrow cells and elimination of microvasculature. To understand how bone marrow recovers after radiation, we focused on mesenchymal lineage cells that provide a supportive microenvironment for hematopoiesis and angiogenesis in bone. We recently discovered a nonproliferative subpopulation of marrow adipogenic lineage precursors (MALPs) that express adipogenic markers with no lipid accumulation. Single-cell transcriptomic analysis revealed that MALPs acquire proliferation and myofibroblast features shortly after radiation. Using an adipocyte-specific Adipoq-Cre, we validated that MALPs rapidly and transiently expanded at day 3 after radiation, coinciding with marrow vessel dilation and diminished marrow cellularity. Concurrently, MALPs lost most of their cell processes, became more elongated, and highly expressed myofibroblast-related genes. Radiation activated mTOR signaling in MALPs that is essential for their myofibroblast conversion and subsequent bone marrow recovery at day 14. Ablation of MALPs blocked the recovery of bone marrow vasculature and cellularity, including hematopoietic stem and progenitors. Moreover, VEGFa deficiency in MALPs delayed bone marrow recovery after radiation. Taken together, our research demonstrates a critical role of MALPs in mediating bone marrow repair after radiation injury and sheds light on a cellular target for treating marrow suppression after radiotherapy.

Recent genetic data can offer important insights into the roles of lipoprotein subfractions and particle sizes in preventing coronary artery disease (CAD), as previous observational studies have often reported conflicting results. We used the LD score regression to estimate the genetic correlation of 77 subfraction traits with traditional lipid profile and identified 27 traits that may represent distinct genetic mechanisms. We then used Mendelian randomization (MR) to estimate the causal effect of these traits on the risk of CAD. In univariable MR, the concentration and content of medium high-density lipoprotein (HDL) particles showed a protective effect against CAD. The effect was not attenuated in multivariable analyses. Multivariable MR analyses also found that small HDL particles and smaller mean HDL particle diameter may have a protective effect. We identified four genetic markers for HDL particle size and CAD. Further investigations are needed to fully understand the role of HDL particle size.

Bone marrow mesenchymal lineage cells are a heterogeneous cell population involved in bone homeostasis and diseases such as osteoporosis. While it is long postulated that they originate from mesenchymal stem cells, the true identity of progenitors and their in vivo bifurcated differentiation routes into osteoblasts and adipocytes remain poorly understood. Here, by employing large scale single cell transcriptome analysis, we computationally defined mesenchymal progenitors at different stages and delineated their bi-lineage differentiation paths in young, adult and aging mice. One identified subpopulation is a unique cell type that expresses adipocyte markers but contains no lipid droplets. As non-proliferative precursors for adipocytes, they exist abundantly as pericytes and stromal cells that form a ubiquitous 3D network inside the marrow cavity. Functionally they play critical roles in maintaining marrow vasculature and suppressing bone formation. Therefore, we name them marrow adipogenic lineage precursors (MALPs) and conclude that they are a newly identified component of marrow adipose tissue.

A unique self-standing membrane composed of hierarchical thermoplastic polyurethane (TPU)/polyacrylonitrile (PAN) fibers is prepared by the electrospinning technique, followed by a simple dip-coating process. Fe3O4 nanoparticles are uniformly anchored on TPU/PAN fibers during the electrospinning process, enabling the membrane to achieve effective electromagnetic interference shielding (EMI SE) performance. Such a hybrid membrane has a high magnetization of 18.9 emu/g. When MXene (Ti3C2Tx) layers are further loaded on the TPU/PAN/Fe3O4NPs hybrid membrane, its EMI SE performance in the X band can exceed 30 dB due to the hydrogen bonds generated between the macromolecular chain of PAN and the functional group (Tx) on the surface of MXene. Simultaneously, the interfacial attraction between MXene and the TPU/PAN/Fe3O4NPs substrate is enhanced. The EMI SE mechanism of the hybrid membrane indicates that this film has great potential in the fields of wearable devices and flexible materials.

The widespread dissemination of information related to wildlife utilization in new online media and traditional media undoubtedly impacts societal conservation concepts and attitudes, thus triggering public discussions on the relationship between conservation and utilization. A study on how public attitudes and concepts are affected by the related information on wildlife utilization is helpful to implement the scientific wildlife conservation and management strategies, and to propose targeted measures to optimize the information environment. We designed the questionnaire to investigate the public’s awareness and agreement with related information on wildlife utilization so as to measure how information with different dissemination channels, source types, and content orientation influenced the public’s concept of wildlife conservation and utilization. The questionnaire was distributed in seven major geographical regions throughout China. Out of a total of 1645 questionnaires that were collected, 1294 questionnaires were valid, with an effective rate of 78.7%. Results show that respondents had the greatest awareness of information on preventing unsustainable and illegal utilization, and the lowest awareness of information on promoting unsustainable utilization, and that awareness of information that against utilization was higher than that of information which supported sustainable utilization. At the same time, respondents showed the greatest agreement for information on preventing unsustainable utilization and the lowest agreement for information on promoting unsustainable utilization; also, their agreement with information that against utilization was higher than that for information which supported sustainable use. Respondents had a high level of awareness of information on wildlife related to COVID-19 provided by experts. Gender, age, the level of development of the city in which they live, education, vegetarianism, and religious beliefs all affected respondents’ agreement with related information on wildlife utilization. This research suggests that the publicity and education of scientific conservation methods should be emphasized in the future conservation education. In addition, scholars in the field of wildlife research should assume the role of ‘influencer’ and give full play to the scientific guidance of public opinion.

Sustainable wildlife management (SWM) is based on a synergy of traditional/local knowledge, advances in scientific knowledge, and fast-evolving economic and social circumstances. A widely accepted cornerstone of SWM globally is that conservation and utilization need to be effectively integrated, emphasizing the benefits humans can derive from biodiversity, thereby further encouraging people to protect and value wildlife though its management. However, with demand from biological resources growing at an unprecedented rate and the emergence of social media, conservationists must respond quickly to new challenges and conflicts associated with species management and public policy. For example, the rise of the “Compassionate Conservation” (CC) movement, fueled by social marketing and media, which promotes the welfare of individual animals, has introduced a set of challenges for conventional conservation management as it opposes most or all forms of wildlife utilization and hunting. CC advocates are increasingly influential at global and national policy levels; hence, it is imperative that conservationists are informed and aware of the future challenges from a rapidly changing global society. In this paper, we report the findings of a large semi-structured questionnaire in China which investigated the attitude of the urban public toward sustainable wildlife management (SWM) and wildlife conservation across a range of issues and identified the key socio-economic and demographic factor drivers for those attitudes. The survey was conducted from November 2018 to October 2020, across 15 cities randomly selected among China’s seven administrative geographic regions. The survey was initially conducted through face-to-face interviews, but later, due to COVID-19 restrictions, was completed via online questionnaires. A Likert seven-point scale method was used to score the public’s degree of agreement or disagreement for each question; a multivariate stepwise linear regression method was used to analyze whether the overall attitude of the respondents toward SWM and wildlife conservation was affected by their demographic characteristics; and a classification and regression tree (CART) was used to conduct an in-depth analysis of the issues with negative scores in the questionnaire, so as to understand how the respondents’ demographic characteristics affected the public’s attitude about such issues, which could supplement results obtained from the multivariate stepwise linear regression analysis. The results show that the public are broadly supportive of SWM, but only moderately so. On issues of “Animal Welfare and Rights,” “Wildlife Utilization and Captive Breeding,” and “Trophy Hunting”, the core concerns of the “Compassionate Conservation” movement and the overall public view are more antagonistic to conventional SWM. We also find specific demographic characteristics significantly influence attitudes about SWM, with vegetarians, those with religious beliefs, and with lower educational standards demonstrating weaker support for SWM. For younger people, “Animal Welfare and Rights” is a special concern, hence, we identify this as a key issue to be addressed for SWM and conservation in the future. Our research suggests that conservation organisations may need to adapt their management aims and practices to avoid direct conflict with the rising tide of animal rights sentiment, especially among the young. Furthermore, significant investment will be required to promote science-based conservation in social marketing on all social media platforms to help educate and engage the public with the science behind conservation management.

Wildlife conservation and management has become a very complex public policy issue in China as concerns over on animal welfare and empathy for animals have grown. Science-based conservation strategies that are oriented toward sustainable wildlife management (SWM) are under threat as these new attitudes and values emerge and take hold. This study accesses the attitudes of college students towards SWM and wildlife conservation, and investigates demographic characteristics influencing their attitudes in China, a country that is traditionally associated with consumptive use of wildlife and SWM, but where new ideas about wildlife conservation are emerging. From October 2018 to April 2019, nine universities (including “Double First-Class” universities, first-tier universities, second-tier universities), and four three-year colleges in China were selected as survey locations, and face-to-face interviews were conducted with 1991 students. A total of 1977 questionnaires were recovered, of which 1739 were valid, with a completion rate of 88%. A Likert seven-point scale method was used to score students’ attitudes, and a classification and regression tree (CART) was used to analyze whether their attitudes were affected by their demographic characteristics. The results show that although students are broadly supportive of the theory of SWM, some are deeply antagonistic about on SWM on issues that arouse strong emotions such as “Animal Welfare and Rights” and “Trophy Hunting”. Demographic characteristics of students affect their degree of support for the SWM with support for SWM lower among vegetarians, freshmen, and students who have taken environmental protection electives. This research suggests that the theory of SWM requires to be refreshed and adapted to appeal to the younger generation of Chinese students, with SWM principles integrated into the environmental education programs of universities and three-year colleges. More attention should also be attached to media publicity by the government about wildlife conservation so as to enhance awareness of the need for SWM.

While titanium components manufactured by additive manufacturing have been widely used in direct molding of complex components, their performance is strongly affected by existing internal flaws generated in the unique manufacturing process. Thus, how to efficiently and accurately characterize geometrical characteristics of internal flaws is critical for enhancing applications of additive manufactured titanium components. In the present work, an effective non-destructive method by using phased array ultrasonic testing is proposed to characterize sub-millimeter artificial deep bottom holes in additive manufactured TC18 titanium block. Specifically, a phased array ultrasonic testing platform integrated with total focusing method-based post-processing algorithm is established. Flat bottom holes with a diameter of 0.8 mm and a depth of 5.0 mm in 55 mm-sized cube titanium block are detected using both linear and annular array transducers. Experimental results show that pre-existing holes can be characterized by both linear and annular transducers, in despite of accompanied high acoustic attenuation. Furthermore, the annular phased array ultrasonic testing has higher detection accuracy and resolution than the linear phased array one, for its stronger capability of sound field focusing. More importantly, the annular phased array ultrasonic testing shows similar high testing accuracy in different relative orientations between forming orientation of the titanium component and sound wave propagation direction. These findings provide an effective strategy for the non-destructive ultrasonic testing of titanium components by additive manufacturing.

While particulate-reinforced metal matrix composites are composed of two phase materials with dramatically different physical and mechanical properties, sound wave-particle interactions play an important role in their ultrasonic inspection tests. In the present work, we investigate the sound wave-particle interactions in silicon carbide (SiC) particle-reinforced aluminum (Al) matrix composites under the pulse-echo mode ultrasonic inspection by means of finite element simulations. Be consistent with experimentally observed real microstructures, the simulated SiC particles have polygon shapes and are randomly dispersed in the Al matrix. In particular, the sound wave-particle interactions are revealed, and their correlations with the A-scan signals are investigated. Furthermore, the effects of extrinsic pulse frequency and intrinsic SiC particle size on the ultrasonic inspection of the composites are addressed. Simulation results indicate that the interference of sound waves with heterogeneous SiC particles leads to more pronounced deflection, scattering and conversion of sound waves than the pure Al matrix, which in turn result in higher attenuation of sound waves in SiCp/Al composites. It is also found that the sound wave-particle interactions have a strong dependence on both pulse frequency and particle size.

In this case report, we will discuss a 74-year-old female who presented with a chief complaint of abdominal pain, bloating, anorexia, and nausea for four days which preceded after catheter ablation and anhydrous ethanol infusion vein of Marshall (VOM) one month prior. She was admitted and treated as a general patient in the general ward. After hospital admission, a pericardiocentesis was guided by B-scan ultrasonography, resulting in the extraction of 20ml of pericardial effusion, followed by catheterization for drainage. The key takeaway in this report is that anhydrous ethanol infusion VOM may not always be without risks. Hence, during the procedure, it is imperative to carefully administer the appropriate volume of anhydrous ethanol into the VOM to prevent vessel damage and associated complications. [ABSTRACT FROM AUTHOR]