TMEM16A regulates satellite cell mediated skeletal muscle regeneration by ensuring a moderate level of caspase 3 activity.

It has been documented that caspase 3 activity is necessary for skeletal muscle regeneration, but how its activity is regulated is largely unknown. Our previous report shows that intracellular TMEM16A, a calcium activated chloride channel, significantly regulates caspase 3 activity in myoblasts during skeletal muscle development. By using a mouse line with satellite cell (SC)-specific deletion of TMEM16A, we examined the role of TMEM16A in regulating caspase 3 activity in SC (or SC-derived myoblast) as well as skeletal muscle regeneration. The mutant animals displayed apparently impaired regeneration capacity in adult muscle along with enhanced ER stress and elevated caspase 3 activity in Tmem16a-/- SC derived myoblasts. Blockade of either excessive ER stress or caspase 3 activity by small molecules significantly restored the inhibited myogenic differentiation of Tmem16a-/- SCs, indicating that excessive caspase 3 activity resulted from TMEM16A deletion contributes to the impaired muscle regeneration and the upstream regulator of caspase 3 was ER stress. Our results revealed an essential role of TMEM16A in satellite cell mediated skeletal muscle regeneration by ensuring a moderate level of caspase 3 activity.

The global burden and trend of Clostridioides difficile and its association with world antibiotic consumption, 1990-2019.

Background: To estimate the global trends and disease burden of Clostridioides difficile infection (CDI) and its correlation with worldwide antibiotic consumption. Methods: Clostridioides difficile infection and antibiotic consumption data were retrieved from the Global Burden of Disease 2019, ResistanceMap-AntibiocUse, Food and Drug Administration (FDA) Adverse Event Reporting System, and Global Antimicrobial Resistance and Use Surveillance System. Jointpoint regression and age-period-cohort model were developed to show the global trends and burden of CDI. Correlation tests were calculated to explore the relationship between CDI and antibiotics. Results: Globally, CDI is the most significant one with a high-rocketing burden increase rate among 13 pathogens causing diarrheal deaths and disability-adjusted life years (DALYs). The age-standardised death rate (ASDR) increased from 0.19 in 1990 to 0.43 in 2019, in which the elderly and females are at higher risk. A rapid increase in ASDR in high to middle sociodemographic index (SDI) regions such as North America (average annual percentage change (AAPC) = 7.71%), Andean (AAPC = 7.82%), and Southern Latin America (AAPC = 11.08%) was identified. Antibiotic consumption has a significant positive correlation with CDI with different risk stratifications. Conclusions: The global burden of CDI has continuously increased for the past 30 years, especially in high to middle-SDI regions. World antibiotic consumption showed a strong positive correlation with CDI with different risk stratification. More effective prevention and control measures should be implemented in these critical regions, with a specific emphasis on vulnerable populations, to mitigate the spread of epidemics.

Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework.

The causes of traffic violations by elderly drivers are different from those of other age groups. To reduce serious traffic violations that are more likely to cause serious traffic crashes, this study divided the severity of traffic violations into three levels (i.e., slight, ordinary, severe) based on point deduction, and explore the patterns of serious traffic violations (i.e., ordinary, severe) using multi-source data. This paper designed an interpretable machine learning framework, in which four popular machine learning models were enhanced and compared. Specifically, adaptive synthetic sampling method was applied to overcome the effects of imbalanced data and improve the prediction accuracy of minority classes (i.e., ordinary, severe); multi-objective feature selection based on NSGA-II was used to remove the redundant factors to increase the computational efficiency and make the patterns discovered by the explainer more effective; Bayesian hyperparameter optimization aimed to obtain more effective hyperparameters combination with fewer iterations and boost the model adaptability. Results show that the proposed interpretable machine learning framework can significantly improve and distinguish the performance of four popular machine learning models and two post-hoc interpretation methods. It is found that six of the top ten important factors belong to multi-scale built environment attributes. By comparing the results of feature contribution and interaction effects, some findings can be summarized: ordinary and severe traffic violations have some identical influencing factors and interactive effects; have the same influencing factors or the same combinations of influencing factors, but the values of the factors are different; have some unique influencing factors and unique combinations of influencing factors.

Recreational ball games are effective in improving social communication impairments among preschoolers diagnosed with autism spectrum disorder: a multi-arm controlled study.

BACKGROUND: This study aimed to compare the effects of two 12-week training intervention experimental ball games combined with standard behavioral rehabilitation against a control group solely utilizing standard behavioral rehabilitation on social communication impairments (SCI) in preschool children with Autism Spectrum Disorder (ASD). METHODS: A multi-arm controlled study design was implemented, involving 41 children diagnosed with ASD (mean age: 4.99 ± 0.76 years). 41 participants were randomized assigned to two experimental groups and a control group, The experimental group carried out ball combination training program group (BCTP) and mini-basketball training program group (MBTP) on the basis of routine behavioral rehabilitation, which underwent 12-week training interventions 5 times a week. The control group (n = 14) received only standard behavioral rehabilitation. Evaluations were conducted before and after interventions using the Social Responsiveness Scale, Second Edition (SRS-2). RESULTS: The results suggest that both 12-week interventions, BCTP, and MBTP, led to significant improvements in social communication impairment among children with ASD (p < 0.05). Despite enhancing the overall scores on the SRS-2, these interventions displayed varying impacts across different sub-dimensions. BCTP primarily exhibited significant enhancements in social awareness and behavior pattern (p < 0.05), whereas MBTP significantly improved social cognition and social communication (p < 0.05). Both interventions showed slight improvements in social motivation. CONCLUSIONS: The utilization of recreational ball games has showed to be effective in decreasing the impairment levels of children with ASD, while the control group experienced a worsening of outcomes. This suggests that irrespective of the specific ball game strategy employed, both can be employed on a weekly basis to complement standard behavioral rehabilitation and enhance the ability to improve the quality of life for children diagnosed with ASD. TRIAL REGISTRATION: The trial is retrospectively registered on the Chinese Clinical Trial Registry (ChiCTR1900024973;August 5, 2019).

Research trends and hotspot evolution of exercise-regulated myokines: a bibliometric analysis from 2003 to 2023.

Background: The lack of physical activity is a common issue in modern society and is considered a major risk factor for various chronic non-communicable diseases. Bioactive factors secreted by skeletal muscle during exercise play a crucial role in inter-organ interactions. Since the concept of "myokines" was proposed in 2004, hundreds of regulatory myokines have been identified. Visual analysis of research on exercise-regulated myokines is significant to explore research hotspots and frontiers in this field. Methods: Research literature on exercise-regulated myokines from 2003 to 2023 in the "Web of Science" database was used as the data source. Knowledge maps were drawn using "VOS Viewer, CiteSpace, and R-bibliometrix" software. Results: A total of 1,405 papers were included, showing a fluctuating yet slow growth in annual publications. The United States and China led in the number of publications and collaboration networks. Harvard University ranked first with 120 publications. CIBER (centrality 0.16) and the University of California System (centrality 0.16) were pivotal in advancing this field. PEDERSEN BK led author rankings with 41 publications and 1,952 citations. FRONTIERS IN PHYSIOLOGY ranked first among journals with 64 publications and the highest g-index (39), while PLoS One had the highest h-index (25) and most citations (2,599). Key co-cited reference clusters included #1 skeletal muscle dysfunction, #2 obesity, #6 ASCs, and #7 adaptive immunocytes. Pontus Boström's paper had a notable citation burst intensity of 77.37. High-frequency keywords were "exercise" (509), "skeletal muscle" (452), and "expression" (293), with long-term keywords such as #0 irisin, #2 insulin resistance, #3 transcription, and #6 physical activity. Recently, keywords like "physical exercise," "resistance exercise," "aerobic exercise," "insulin," and "oxidative stress" have emerged. Conclusion: Research in the field of exercise-regulated myokines shows an overall upward trend. The focus areas include myokines mediated by different types of exercise, the interaction of irisin-mediated muscle with other organs, and the important role of myokine-mediated oxidative stress in exercise simulation.

Polyphenols-based intelligent oral barrier membranes for periodontal bone defect reconstruction.

Periodontitis-induced periodontal bone defects significantly impact patients' daily lives. The guided tissue regeneration and guided bone regeneration techniques, which are based on barrier membranes, have brought hope for the regeneration of periodontal bone defects. However, traditional barrier membranes lack antimicrobial properties and cannot effectively regulate the complex oxidative stress microenvironment in periodontal bone defect areas, leading to unsatisfactory outcomes in promoting periodontal bone regeneration. To address these issues, our study selected the collagen barrier membrane as the substrate material and synthesized a novel barrier membrane (PO/4-BPBA/Mino@COL, PBMC) with an intelligent antimicrobial coating through a simple layer-by-layer assembly method, incorporating reactive oxygen species (ROS)-scavenging components, commercial dual-functional linkers and antimicrobial building blocks. Experimental results indicated that PBMC exhibited good degradability, hydrophilicity and ROS-responsiveness, allowing for the slow and controlled release of antimicrobial drugs. The outstanding antibacterial, antioxidant and biocompatibility properties of PBMC contributed to resistance to periodontal pathogen infection and regulation of the oxidative balance, while enhancing the migration and osteogenic differentiation of human periodontal ligament stem cells. Finally, using a rat periodontal bone defect model, the therapeutic effect of PBMC in promoting periodontal bone regeneration under infection conditions was confirmed. In summary, the novel barrier membranes designed in this study have significant potential for clinical application and provide a reference for the design of future periodontal regenerative functional materials.

Radiometric thermometry of point targets based on dual-band infrared imaging.

The observation area of a point target, which is usually inaccessible, is a necessary condition when utilizing the conventional single-band infrared radiometric thermometry method, as the image gray level inevitably undergoes dispersion. Otherwise, significant errors will be generated, seriously affecting the applicability of infrared radiometric thermometry for distant point targets in the external field. To address the above issue, the infrared radiometric thermometry method for point targets has been researched. A point target radiometric thermometry method based on dual-band infrared imaging is proposed, which can effectively measure radiance and temperature when the area of the point target is unknown. The experimental results show that, compared with conventional single-band algorithms, the proposed dual-band point target thermometry algorithm has a maximum error of 11.18°C under the condition of unknown area, which can meet the needs of infrared radiometric thermometry of point targets at long distances in the external field.

The effect of multi-component exercise on cognition function in patients with diabetes: A systematic review and meta-analysis.

BACKGROUND: This meta-analysis investigated the influence of exercise on cognitive function in people living with diabetes. METHODS: Stringent criteria for literature inclusion and exclusion were defined. Searches were conducted across four English databases to gather randomized controlled trials investigating exercise interventions for cognitive function in people living with diabetes. Outcome indicators from 1193 subjects across 12 articles were analyzed using RevMan 5.4 software. RESULTS: Exercise intervention demonstrated the ability to mitigate cognitive decline in people living with diabetes, with a combined effect size (standardized mean difference) of 0.91, 95% CI: 0.28, 1.54, P < 0.00001. The intervention effect showed significant modulation by intervention content (I2 = 95%), intervention duration (I2 = 95%), intervention frequency (I2 = 95%), and intervention cycle (I2 = 96%). Among these factors, multi-component exercise, sessions >40 minutes, exercise frequency >4 times per week, and sustained exercise for >6 months were paramount, all with P < 0.05. CONCLUSION: Exercise intervention emerges as a viable strategy for delaying cognitive decline in people living with diabetes. Its efficacy is subject to modulation by various variables. Optimal intervention includes multi-component exercise, individual sessions lasting 40-60 minutes, exercising >4 times a week, and continuous exercise for over 6 months.

SOCS modulates JAK-STAT pathway as a novel target to mediate the occurrence of neuroinflammation: Molecular details and treatment options.

SOCS (Suppressor of Cytokine Signalling) proteins are intracellular negative regulators that primarily modulate and inhibit cytokine-mediated signal transduction, playing a crucial role in immune homeostasis and related inflammatory diseases. SOCS act as inhibitors by regulating the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway, thereby intervening in the pathogenesis of inflammation and autoimmune diseases. Recent studies have also demonstrated their involvement in central immunity and neuroinflammation, showing a dual functionality. However, the specific mechanisms of SOCS in the central nervous system remain unclear. This review thoroughly elucidates the specific mechanisms linking the SOCS-JAK-STAT pathway with the inflammatory manifestations of neurodegenerative diseases. Based on this, it proposes the theory that SOCS proteins can regulate the JAK-STAT pathway and inhibit the occurrence of neuroinflammation. Additionally, this review explores in detail the current therapeutic landscape and potential of targeting SOCS in the brain via the JAK-STAT pathway for neuroinflammation, offering insights into potential targets for the treatment of neurodegenerative diseases.

Effects of mini-basketball training program on social communication impairments and regional homogeneity of brain functions in preschool children with autism spectrum disorder.

BACKGROUND: Social communication impairments (SCI) is a core symptom of autism spectrum disorder (ASD) and is marked by challenges in social interaction. Although physical exercise has been shown to improve SCI, this finding has not been supported by comprehensive scientific evidence. Existing research has established a strong link between the SCI in children with ASD and abnormalities in regional homogeneity (ReHo). Therefore, investigating the effects of physical exercise on SCI and Reho in patients with ASD may help to elucidate the neurological mechanisms involved. METHODS: The present study included 30 preschool children diagnosed with ASD, with 15 participants in each group (experimental and control). The experimental group underwent a 12-week mini-basketball training program (MBTP) based on routine behavioral rehabilitation, while the control group only received routine behavioral rehabilitation. The Social Responsiveness Scale-Second Edition (SRS-2) was employed to assess SCI in both groups. Resting-state functional magnetic resonance imaging technology was used to evaluate ReHo in both groups. RESULTS: After 12-week of MBTP, significant group × time interactions were observed between the experimental and control groups in total SRS-2 scores (F = 14.514, p < 0.001, ηp2 = 0.341), as well as in the domains of social cognition (F = 15.620, p < 0.001, ηp2 = 0.358), social communication (F = 12.460, p < 0.01, ηp2 = 0.308), and autistic mannerisms (F = 9.970, p < 0.01, ηp2 = 0.263). No statistical difference was found in the scores for the social awareness subscale and social motivation subscale in the group × time interaction (all p > 0.05). The experimental group exhibited increased ReHo in the right Cerebellum_Crus1 and right parahippocampal gyrus, coupled with decreased ReHo in the left middle frontal gyrus (orbital part), left superior frontal gyrus (dorsolateral), left postcentral gyrus, and right superior parietal gyrus. Furthermore, a decrease in ReHo in the left postcentral gyrus positively correlated with changes in social communication scores in SCI behaviors (p < 0.05). CONCLUSIONS: Our study underscores the effectiveness of a 12-week MBTP in ameliorating SCI and abnormalities in ReHo among preschool children with ASD. TRIAL REGISTRATION: The trial is retrospectively registered on the Chinese Clinical Trial Registry (ChiCTR1900024973; August 5, 2019).

The effects of football juggling learning on executive function and brain functional connectivity.

This study aimed to explore the relationship between motor skill learning and executive function (EF), with an emphasis on the potential effects of football juggling learning. A randomized controlled trial involving 111 participants aged 17-19 years was conducted. Participants were randomly assigned to either the football juggling learning (FJL) group or a control group. The FJL group underwent 70 sessions of football juggling learning, while the control group engaged in their normal daily activities without any exercise intervention during the same time frame. Both groups were assessed for EF performance and underwent functional magnetic resonance imaging (fMRI) scans before and after the experiment. The executive function test included three tasks, namely, inhibition, working memory, and shifting. The results showed significant improvement in inhibition and shifting in both groups, and the FJL group showed greater improvement in these aspects of EF compared to the control group. Additionally, in comparison to the control group, the FJL group exhibited increased functional connectivity within the frontal, temporal, and cerebellar regions from the pre-test to the post-test. Notably, enhanced functional connectivity between the right superior temporal gyrus (posterior division) and left cerebellum 6 was identified in the FJL group and was associated with improved EF performance induced by football juggling learning. These findings shed light on the potential causal relationship between motor skill learning, EF, and brain plasticity. Importantly, our study provides preliminary evidence supporting the use of motor skill learning, such as football juggling, as a potential avenue for cognitive enhancement.

Living, Heat-Killed Limosilactobacillus mucosae and Its Cell-Free Supernatant Differentially Regulate Colonic Serotonin Receptors and Immune Response in Experimental Colitis.

Lactobacillus species have been shown to alleviate gut inflammation and oxidative stress. However, the effect of different lactobacilli components on gut inflammation has not been well studied. This study aims to identify the differences in the effect and mechanisms of different forms and components of Limosilactobacillus mucosae (LM) treatment in the alleviation of gut inflammation using a colitis mouse model that is induced by dextran sodium sulfate (DSS). Seventy-two C57BL/6 mice were divided into six groups: control, DSS, live LM+DSS (LM+DSS), heat-killed LM+DSS (HKLM+DSS), LM cell-free supernatant + DSS (LMCS+DSS), and MRS medium + DSS (MRS+DSS). The mice were treated with different forms and components of LM for two weeks before DSS treatment. After that, the mice were sacrificed for an assessment of their levels of inflammatory cytokines, serotonin (5-HT) receptors (HTRs), and tryptophan metabolites. The results showed that, compared to other treatments, LMCS was more effective (p < 0.05) in the alleviation of DSS-induced body weight loss and led to an increase in the disease activity index score. All three forms and components of LM increased (p < 0.05) the levels of indole-3-acetic acid but reduced (p < 0.05) the levels of 5-HT in the colon. HKLM or LMCS reduced (p < 0.05) the percentages of CD3+CD8+ cytotoxic T cells but increased (p < 0.05) the percentages of CD3+CD4+ T helper cells in the spleen. LM or HKLM increased (p < 0.05) abundances of CD4+Foxp3+ regulatory T cells in the spleen. The LM and LMCS treatments reduced (p < 0.05) the expression of the pro-inflammatory cytokines Il6 and Il17a. The mice in the HKLM+DSS group had higher (p < 0.05) mRNA levels of the anti-inflammatory cytokine Il10, the cell differentiation and proliferation markers Lgr5 and Ki67, the 5-HT degradation enzyme Maoa, and HTRs (Htr1a, Htr2a, and Htr2b) in the colon. All three forms and components of LM reduced the phosphorylation of STAT3. The above findings can help to optimize the functionality of probiotics and develop new dietary strategies that aid in the maintenance of a healthy gut.

How do drunk-driving events escalate into drunk-driving crashes? An empirical analysis of Beijing from a spatiotemporal perspective.

Drunk-driving events often escalate into drunk-driving crashes, however, the contributing factors of this progression remain elusive. To mitigate the likelihood of crashes stemming from drunk-driving events, this paper introduces the notion of 'the severity of drunk-driving event' and examines the complex relationship between the severity and its contributing factors, considering spatiotemporal heterogeneity. The study utilizes a Geographically and Temporally Weighted Binary Logistic Regression (GTWBLR) model to conduct spatiotemporal analysis based on police-reported drunk-driving events in Beijing, China. The results show that most factors passed the non-stationary test, indicating their effects on the severity of drunk-driving event vary significantly across different spatial and temporal domains. Notably, during non-workday, drunk-driving events in northeast of Beijing are more likely to escalate into crashes. Furthermore, severe weather during winter in the northwest of Beijing is associated with high risk of drunk-driving crashes. Based on these insights, the authorities can strengthen drunk-driving checks in the northeast region of Beijing, particularly during non-workdays. And it is crucial to promptly clear accumulated snow on the roads during severe winter weather to improve road safety. These insights and recommendations are highly valuable for reducing the risk of drunk-driving crashes.

Understanding key contributing factors on the severity of traffic violations by elderly drivers: a hybrid approach of latent class analysis and XGBoost based SHAP.

Traffic violation is one of the leading causes of traffic crashes. In the context of global aging, it is important to study traffic violations by elderly drivers for improving traffic safety in preparation for a worldwide aging population. In this study, a hybrid approach of Latent Class Analysis (LCA) and XGBoost based SHAP is proposed to identify hidden clusters and to understand the key contributing factors on the severity of traffic violations by elderly drivers, based on the police-reported traffic violation dataset of Beijing (China). First, LCA is applied to segment the dataset into several latent homogeneous clusters, then XGBoost based SHAP is established on each cluster to identify feature contributions and the interaction effects of the key contributing factors on the severity of traffic violations by elderly drivers. Two comparison groups were set up to analyze factors, which are responsible for the different severities of traffic violations. The results show that elderly drivers can be classified into four groups by age, urban or not, license, and season; factors such as less annual number of traffic violations, national & provincial highway, night and winter are key contributing factors for higher severity of traffic violations, which are consistent with common cognition; key contributing factors for all clusters are similar but not identical, for example, more annual number of traffic violations contribute to more severe violation for all clusters except for Cluster 2; some factors which are not key contributing factors may affect the severity of traffic violations when they are combined with other factors, for example, the combination of lower annual number of traffic violations and county & township highway contributes to more severe violation for Cluster 1. These findings can help government to formulate targeted countermeasures to decrease the severity of traffic violations by specific elderly groups and improve road service for the driving population.

A novel amidine-based fluorescent probe TPE-4+ for rapid detection of anionic surfactant sodium dodecyl sulfate.

An accurate, fast, and simple surfactant detection method is of great significance for monitoring surfactants pollution. Sodium dodecyl sulfate (SDS) is one of the most commonly used anionic surfactants and has been listed as an important monitoring pollutant for surfactant residues. Herein, a novel fluorescent probe named TPE-4+ with four amidines as the recognition functional group and tetraphenylethene as the fluorophore was fabricated. Due to the special intramolecular environment, the probe showed selectively identification towards SDS which made an aggregation induced fluorescence enhencement. Under the optimum conditions, the fluorescence enhencement of TPE-4+ is linearly related to the concentration of SDS in the range of 5.0-60.0 µM with limit of detection (LOD) of 0.010 µM and limit of quantification (LOQ) of 0.034 µM. Relative to the reported methods, the probe in our work showed better selectivity and sensitivity. The proposed method was successfully applied for the SDS determination of disinfecting bowls.

Diagnosing autism severity associated with physical fitness and gray matter volume in children with autism spectrum disorder: Explainable machine learning method.

PURPOSE: This study aimed to investigate the relationship between physical fitness, gray matter volume (GMV), and autism severity in children with autism spectrum disorder (ASD). Besides, we sought to diagnose autism severity associated with physical fitness and GMV using machine learning methods. METHODS: Ninety children diagnosed with ASD underwent physical fitness tests, magnetic resonance imaging scans, and autism severity assessments. Diagnosis models were established using extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), and decision tree (DT) algorithms. Hyperparameters were optimized through the grid search cross-validation method. The shapley additive explanation (SHAP) method was employed to explain the diagnosis results. RESULTS: Our study revealed associations between muscular strength in physical fitness and GMV in specific brain regions (left paracentral lobule, bilateral thalamus, left inferior temporal gyrus, and cerebellar vermis I-II) with autism severity in children with ASD. The accuracy (95 % confidence interval) of the XGB, RF, SVM, and DT models were 77.9 % (77.3, 78.6 %), 72.4 % (71.7, 73.2 %), 71.9 % (71.1, 72.6 %), and 66.9 % (66.2, 67.7 %), respectively. SHAP analysis revealed that muscular strength and thalamic GMV significantly influenced the decision-making process of the XGB model. CONCLUSION: Machine learning methods can effectively diagnose autism severity associated with physical fitness and GMV in children with ASD. In this respect, the XGB model demonstrated excellent performance across various indicators, suggesting its potential for diagnosing autism severity.

Predicting academic achievement from the collaborative influences of executive function, physical fitness, and demographic factors among primary school students in China: ensemble learning methods.

BACKGROUND: Elevated levels of executive function and physical fitness play a pivotal role in shaping future quality of life. However, few studies have examined the collaborative influences of physical and mental health on academic achievement. This study aims to investigate the key factors that collaboratively influence primary school students' academic achievement from executive function, physical fitness, and demographic factors. Additionally, ensemble learning methods are employed to predict academic achievement, and their predictive performance is compared with individual learners. METHODS: A cluster sampling method was utilized to select 353 primary school students from Huai'an, China, who underwent assessments for executive function, physical fitness, and academic achievement. The recursive feature elimination cross-validation method was employed to identify key factors that collaboratively influence academic achievement. Ensemble learning models, utilizing eXtreme Gradient Boosting and Random Forest algorithms, were constructed based on Bagging and Boosting methods. Individual learners were developed using Support Vector Machine, Decision Tree, Logistic Regression, and Linear Discriminant Analysis algorithms, followed by the establishment of a Stacking ensemble learning model. RESULTS: Our findings revealed that sex, body mass index, muscle strength, cardiorespiratory function, inhibition, working memory, and shifting were key factors influencing the academic achievement of primary school students. Moreover, ensemble learning models demonstrated superior predictive performance compared to individual learners in predicting academic achievement among primary school students. CONCLUSIONS: Our results suggest that recognizing sex differences and emphasizing the simultaneous development of cognition and physical well-being can positively impact the academic development of primary school students. Ensemble learning methods warrant further attention, as they enable the establishment of an accurate academic early warning system for primary school students.

Pooled CRISPR Screening Identifies P-Bodies as Repressors of Cancer Epithelial-Mesenchymal Transition.

Epithelial-mesenchymal transition (EMT) is a fundamental cellular process frequently hijacked by cancer cells to promote tumor progression, especially metastasis. EMT is orchestrated by a complex molecular network acting at different layers of gene regulation. In addition to transcriptional regulation, posttranscriptional mechanisms may also play a role in EMT. Here, we performed a pooled CRISPR screen analyzing the influence of 1,547 RNA-binding proteins on cell motility in colon cancer cells and identified multiple core components of P-bodies (PB) as negative modulators of cancer cell migration. Further experiments demonstrated that PB depletion by silencing DDX6 or EDC4 could activate hallmarks of EMT thereby enhancing cell migration in vitro as well as metastasis formation in vivo. Integrative multiomics analysis revealed that PBs could repress the translation of the EMT driver gene HMGA2, which contributed to PB-meditated regulation of EMT. This mechanism is conserved in other cancer types. Furthermore, endoplasmic reticulum stress was an intrinsic signal that induced PB disassembly and translational derepression of HMGA2. Taken together, this study has identified a function of PBs in the regulation of EMT in cancer. SIGNIFICANCE: Systematic investigation of the influence of posttranscriptional regulation on cancer cell motility established a connection between P-body-mediated translational control and EMT, which could be therapeutically exploited to attenuate metastasis formation.

Hyperbolic exciton polaritons in a van der Waals magnet.

Exciton polaritons are quasiparticles of photons coupled strongly to bound electron-hole pairs, manifesting as an anti-crossing light dispersion near an exciton resonance. Highly anisotropic semiconductors with opposite-signed permittivities along different crystal axes are predicted to host exotic modes inside the anti-crossing called hyperbolic exciton polaritons (HEPs), which confine light subdiffractionally with enhanced density of states. Here, we show observational evidence of steady-state HEPs in the van der Waals magnet chromium sulfide bromide (CrSBr) using a cryogenic near-infrared near-field microscope. At low temperatures, in the magnetically-ordered state, anisotropic exciton resonances sharpen, driving the permittivity negative along one crystal axis and enabling HEP propagation. We characterize HEP momentum and losses in CrSBr, also demonstrating coupling to excitonic sidebands and enhancement by magnetic order: which boosts exciton spectral weight via wavefunction delocalization. Our findings open new pathways to nanoscale manipulation of excitons and light, including routes to magnetic, nonlocal, and quantum polaritonics.