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Transport and inhibition of the sphingosine-1-phosphate exporter SPNS2
Abstract Sphingosine-1-phosphate (S1P) is a signaling lysolipid critical to heart development, immunity, and hearing. Accordingly, mutations in the S1P transporter SPNS2 are associated with reduced white cell count and hearing defects. SPNS2 also exports the S1P-mimicking FTY720-P (Fingolimod) and thereby is central to the pharmacokinetics of this drug when treating multiple sclerosis. Here, we use a combination of cryo-electron microscopy, immunofluorescence, in vitro binding and in vivo S1P export assays, and molecular dynamics simulations to probe SPNS2’s substrate binding and transport. These results reveal the transporter’s binding mode to its native substrate S1P, the therapeutic FTY720-P, and the reported SPNS2-targeting inhibitor 33p. Further capturing an inward-facing apo state, our structures illuminate the protein’s mechanism for exchange between inward-facing and outward-facing conformations. Finally, using these structural, localization, and S1P transport results, we identify how pathogenic mutations ablate the protein’s export activity and thereby lead to hearing loss.
A facial expression recognition network using hybrid feature extraction
Facial expression recognition faces great challenges due to factors such as face similarity, image quality, and age variation. Although various existing end-to-end Convolutional Neural Network (CNN) architectures have achieved good classification results in facial expression recognition tasks, these network architectures share a common drawback that the convolutional kernel can only compute the correlation between elements of a localized region when extracting expression features from an image. This leads to difficulties for the network to explore the relationship between all the elements that make up a complete expression. In response to this issue, this article proposes a facial expression recognition network called HFE-Net. In order to capture the subtle changes of expression features and the whole facial expression information at the same time, HFE-Net proposed a Hybrid Feature Extraction Block. Specifically, Hybrid Feature Extraction Block consists of parallel Feature Fusion Device and Multi-head Self-attention. Among them, Feature Fusion Device not only extracts the local information in expression features, but also measures the correlation between distant elements in expression features, which helps the network to focus more on the target region while realizing the information interaction between distant features. And Multi-head Self-attention can calculate the correlation between the overall elements in the feature map, which helps the network to extract the overall information of the expression features. We conducted a lot of experiments on four publicly available facial expression datasets and verified that the Hybrid Feature Extraction Block constructed in this paper can improve the network’s recognition ability for facial expressions.
Hydroclimatic extremes threaten groundwater quality and stability
Abstract Heavy precipitation, drought, and other hydroclimatic extremes occur more frequently than in the past climate reference period (1961–1990). Given their strong effect on groundwater recharge dynamics, these phenomena increase the vulnerability of groundwater quantity and quality. Over the course of the past decade, we have documented changes in the composition of dissolved organic matter in groundwater. We show that fractions of ingressing surface-derived organic molecules increased significantly as groundwater levels declined, whereas concentrations of dissolved organic carbon remained constant. Molecular composition changeover was accelerated following 2018’s extreme summer drought. These findings demonstrate that hydroclimatic extremes promote rapid transport between surface ecosystems and groundwaters, thereby enabling xenobiotic substances to evade microbial processing, accrue in greater abundance in groundwater, and potentially compromise the safe nature of these potable water sources. Groundwater quality is far more vulnerable to the impact of recent climate anomalies than is currently recognized, and the molecular composition of dissolved organic matter can be used as a comprehensive indicator for groundwater quality deterioration.
Beyond burnout: A comprehensive investigation of burnout, resilience, and career continuity among Palestinian lawyers in a complex socio-political environment
This article investigates burnout among lawyers and proposes systemic changes to reduce pressure and stress in the legal profession while enhancing resilience among lawyers. The article focuses on factors influencing career continuity among Palestinian lawyers within a socio-politically complex environment. It discusses elements contributing to resilience, including a positive mindset, a strong support system, training, and social support. The study reveals exceptional resilience among Palestinian lawyers. A quantitative cross-sectional study was used; the goals of the study involved 323 participants from different places in Palestine. Data analysis employed Smart PLS4 to build a regression model. Challenging conventional notions, the study provides valuable insights for state strategies, legal firms, educational institutions, and policymakers to address challenges and improve lawyer retention and job satisfaction in an environment marked by unstable economic and political conditions. Additionally, it examines gender-specific career intentions, notably women lawyers displaying a stronger inclination to stay, potentially linked to socio-economic responsibilities. This study contributes significantly to existing literature by providing a unique case study on career continuance determinants within economic and political instability. It sets a precedent for further study and strategic improvements in lawyer retention and job satisfaction within high-stress professions in an economically and politically complex environment.
Anti-proteolytic regulation of KRAS by USP9X/NDRG3 in KRAS-driven cancer development
Parental experience of change following VIPP-SD in families with preschool children with externalizing behavior: A qualitative interview study
Background Insensitive parenting and ineffective disciplinary strategies are known risk factors for child externalizing behavior. The Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) has documented effect in promoting sensitive parenting, but little is known on how VIPP-SD is experienced by parents. This study explores how parents of preschool children with externalizing behaviors experience change following VIPP-SD delivered by trained childcare providers. Methods Individual qualitative semi-structured interviews were conducted with 9 mothers and 2 fathers to explore the parents’ experiences of change following the intervention. Data were analyzed using Braun and Clarke’s reflexive thematic analysis. Results Four themes were generated: 1) “All of her behavior is actually just a result of how she feels, right?”—Enhanced parental understanding, 2) Meeting the child’s needs in comfort and in play, 3) Learning to prevent and manage conflicts is essential–diverse experiences of gains and progress, 4) “I’m actually not a bad parent”–new positive perspectives. Conclusion Parents experienced an enhanced capacity to understand their child and positive development in their parenting behavior, skills and confidence as well as improvements in the parent-child relationship after receiving VIPP-SD. Findings also suggest potential areas for adaptation of VIPP-SD when intervening in families with a child exhibiting externalizing behaviors, as parental experiences of gains related to conflict management varied. Further research on this matter is recommended.
Time-resolved spectroscopy uncovers deprotonation-induced reconstruction in oxygen-evolution NiFe-based (oxy)hydroxides
Non-linear dose-response relationship between uterine artery pulsatility index and risk of preeclampsia in early pregnancy: A secondary analysis based on a nested cohort study
Background Previous studies have shown that higher uterine artery pulsatility index (UtA-PI) values in early pregnancy have predictive value for the risk of preeclampsia (PE). However, the sensitivity and specificity of this marker remain controversial. This study aims to explore further the association between UtA-PI in early pregnancy and the incidence of preeclampsia. Methods A total of 5000 pregnant women who underwent prenatal examination and delivery at the same hospital were included in this nested cohort study. And the PI values of left and right uterine arteries of the subjects were obtained by transabdominal ultrasound using GE color doppler diagnostic device in early pregnancy (11–13 + 6 weeks), and finally the mean value of both was calculated and recorded as UtA-PI. Among them, 60 pregnant women developed preeclampsia and were randomly divided into a screening group (n = 12) and control group (n = 48) and matched with pregnant women who did not develop preeclampsia during the same period to form a subset for subsequent statistical analysis. A weighted multivariate logistic regression model was used to analyze the association between UtA-PI and PE. Additionally, the non-linear relationship between UtA-PI and the incidence of PE was examined using smooth curve fitting and a generalized additive model. Results After adjusting for other variables, UtA-PI values were positively correlated with the incidence of PE, and the relationship showed a non-linear U-shaped relationship (inflection point 1.83). Conclusion Our study showed a significantly increased risk of PE when UtA-PI exceeded 1.83. This provides a basis for clinicians to identify high-risk pregnant women early and implement timely intervention, which helps to reduce maternal and fetal complications and improve health outcomes.
An unusual chiral-at-metal mechanism for BINOL-metal asymmetric catalysis
Difference-Cum-Exponential-type estimators for estimation of finite population mean in survey sampling
Extensive research work has been done for the estimation of population mean using bivariate auxiliary information based on conventional measures. Conventional measures of the auxiliary variables provide suspicious results in the presence of outliers/extreme values. However, non-conventional measures of the auxiliary variables include quartile deviation, mid-range, inter-quartile range, quartile average, tri-mean, Hodge-Lehmann estimator etc. give efficient results in case of extreme values. Unfortunately, non-conventional measures are not used by survey practitioners to enhance the estimation of unknown population parameters using bivariate auxiliary information. In this article, difference-cum-exponential-type estimators for population mean utilizing bivariate auxiliary information based on non-conventional measures under simple and stratified random sampling schemes have been suggested. Mathematical properties such as bias and mean squared error are derived. To support theoretical findings, various real-life applications are used to confirm the superiority of the suggested estimators as compared to the competing estimators under study.
What Trump 2.0 means for science: the likely winners and losers
PHARAOH: A collaborative crowdsourcing platform for phenotyping and regional analysis of histology
Ontology-based construction of embroidery intangible cultural heritage knowledge graph: A case study of Qingyang sachets
The fine-grained mining and construction of semantic associations within multimodal intangible cultural heritage (ICH) resources are crucial for deepening our understanding of their knowledge content and ensuring their systematic protection and transmission in the digital and intelligent era. This paper addresses the urgent need for the digital preservation and transmission of ICH resources. Following a review of current research on Qingyang sachets and ICH, the study introduces an ontology-based approach to constructing a semantic description model for the multimodal digital resources related to Qingyang sachets. By acquiring and processing multimodal resources concerning the craftsmanship and associated customs of Qingyang sachets, the study reorganizes the corresponding textual and visual knowledge. Utilizing knowledge graphs, the research explores multidimensional pathways for delivering knowledge services related to the multimodal digital resources of Qingyang sachets. Empirical research confirms the applicability and feasibility of the proposed semantic association scheme for multimodal ICH digital resources. The findings provide valuable insights for multidimensional organization and integration across scenarios, time periods, and resources within the ICH domain, offering a reference for digital solutions aimed at the systematic protection of ICH.
Uncovering the whole genome silencers of human cells via Ss-STARR-seq
Coupling SAR and optical remote sensing data for soil moisture retrieval over dense vegetation covered areas
Soil moisture is a key parameter for the exchange of substance and energy at the land-air interface, timely and accurate acquisition of soil moisture is of great significance for drought monitoring, water resource management, and crop yield estimation. Synthetic aperture radar (SAR) is sensitive to soil moisture, but the effects of vegetation on SAR signals poses challenges for soil moisture retrieval in areas covered with vegetation. In this study, based on Sentinel-1 SAR and Sentinel-2 optical remote sensing data, a coupling approach was employed to retrieval surface soil moisture over dense vegetated areas. Different vegetation indices were extracted from Sentinel-2 data to establish the vegetation water content (VWC) estimation model, which was integrated with the Water Cloud Model (WCM) to distinguish the contribution of vegetation layer and soil layer to SAR backscattering signals. Subsequently, the Oh model and the Look-Up Table (LUT) algorithm were used for soil moisture retrieval, and the accuracy of the result was compared with the traditional direct retrieval method. The results indicate that, for densely vegetated surfaces, VWC can be better reflected by multiple vegetation indices including NDVI, NDWI2, NDGI and FVI, the R2 and RMSE of VWC estimation result is 0.709 and 0.30 kg·m-2. After vegetation correction, the correlation coefficient increased from 0.659 to 0.802 for the VV polarization, and from 0.398 to 0.509 for the VH polarization. Satisfactory accuracy of soil moisture retrieval result was obtained with the Oh model and the LUT algorithm, VV polarization is found to be more suitable for soil moisture retrieval compared to VH polarization, with an R2 of 0.672 and an RMSE of 0.048m3·m-3, the accuracy is higher than that of the direct retrieval method. The results of the study preliminarily verified the feasibility of the coupling method in soil moisture retrieval over densely veg etated surfaces.
Mitotic chromatin marking governs the segregation of DNA damage
Advancing semantic segmentation: Enhanced UNet algorithm with attention mechanism and deformable convolution
This paper presents a novel method for improving semantic segmentation performance in computer vision tasks. Our approach utilizes an enhanced UNet architecture that leverages an improved ResNet50 backbone. We replace the last layer of ResNet50 with deformable convolution to enhance feature representation. Additionally, we incorporate an attention mechanism, specifically ECA-ASPP (Attention Spatial Pyramid Pooling), in the encoding path of UNet to capture multi-scale contextual information effectively. In the decoding path of UNet, we explore the use of attention mechanisms after concatenating low-level features with high-level features. Specifically, we investigate two types of attention mechanisms: ECA (Efficient Channel Attention) and LKA (Large Kernel Attention). Our experiments demonstrate that incorporating attention after concatenation improves segmentation accuracy. Furthermore, we compare the performance of ECA and LKA modules in the decoder path. The results indicate that the LKA module outperforms the ECA module. This finding highlights the importance of exploring different attention mechanisms and their impact on segmentation performance. To evaluate the effectiveness of the proposed method, we conduct experiments on benchmark datasets, including Stanford and Cityscapes, as well as the newly introduced WildPASS and DensPASS datasets. Based on our experiments, the proposed method achieved state-of-the-art results including mIoU 85.79 and 82.25 for the Stanford dataset, and the Cityscapes dataset, respectively. The results demonstrate that our proposed method performs well on these datasets, achieving state-of-the-art results with high segmentation accuracy.
Nanopore sequencing reveals that DNA replication compartmentalisation dictates genome stability and instability in Trypanosoma brucei
Abstract The Trypanosoma brucei genome is structurally complex. Eleven megabase-sized chromosomes each comprise a transcribed core flanked by silent subtelomeres, housing thousands of Variant Surface Glycoprotein (VSG) genes. Additionally, hundreds of sub-megabase chromosomes contain 177 bp repeats of unknown function, and VSG transcription sites localise to many telomeres. DNA replication dynamics have only been described in the megabase chromosome cores, and in the single active VSG transcription site. Using a Nanopore genome assembly, we show that megabase chromosome subtelomeres display a paucity of replication initiation events relative to the core, correlating with increased instability. In addition, replication of the active VSG transcription site is shown to originate from the telomere, likely causing targeted VSG recombination. Lastly, we provide evidence that the 177 bp repeats act as conserved DNA replication origins, explaining submegabase chromosome stability. Compartmentalized DNA replication therefore explains how T. brucei balances stable genome transmission with localised instability driving immune evasion.
Looking back into the Hepatitis C Virus epidemic dynamics from Unnao, India through phylogenetic approach
Viral hepatitis is a major public health challenge. Hepatitis C Virus (HCV) infection causes the progressive liver damage. A surprisingly high number of individuals tested positive for HCV infection during the Unnao Human Immunodeficiency Virus (HIV) outbreak investigation in 2017–2018 (more than 90% of the people living with HIV were from the Premganj township and Chakmeerapur village of the district in the northern State of Uttar Pradesh). This particular outbreak was attributed to the unsafe use of syringe & needles while seeking treatment, rendering it as an iatrogenic transmission. Earlier investigation towards, phylogenetic characterization revealed the shared ancestry for HCV sequences from the reported outbreak. In this investigation using the HCV sequences reported earlier (n = 67) we have analyzed the transmission linkages and evolutionary dynamics of this HCV outbreak using phylogenetic methods. In current analysis, time-scaled phylogenies indicated that most clusters initiated during 2015–2016. Transmission dynamics highlighted that the outbreak was experiencing an exponential phase during 2016–2017, where reproductive number was observed to be beyond documented values for HCV. Phylogeography revealed that source of the virus was Chakmeerapur and the effective population of Premganj was double the size of that in Chakmeerapur. In summary, we provide the snapshot of epidemic dynamics for HCV outbreak attributed to iatrogenic transmission.