Despite Morocco's reliance on sunflower as an oilseed crop,little is known about its agronomic performance when sown in autumn or early winter.This knowledge gap is critical,as spring-sown varieties have shown dec...Despite Morocco's reliance on sunflower as an oilseed crop,little is known about its agronomic performance when sown in autumn or early winter.This knowledge gap is critical,as spring-sown varieties have shown declining performance in recent years under intensifying climate stress.Therefore,targeted breeding strategies could discover genotypes suitable for autumn or early winter sowing,with cold tolerance as a key selection criterion.Currently,‘Ichraq'is the only autumn-planted sunflower variety officially registered in Morocco,although efforts to release additional tolerant varieties are underway.This study evaluated 31 genotypes(MGB1to MGB31)selected from various environments under autumn planting conditions and conserved in the Moroccan Gene Bank.These genotypes were planted in early winter at a mountainous site known for its pronounced winter cold.Eighteen Morphological,physiological and agronomic parameters including initial vigor,leaf area,seed yield,oil content etc.,were assessed using both univariate and multivariate statistical approaches.Analysis of variance revealed significant genotypic differences across most traits,indicating substantial genetic variation.Notably,seed oil content ranged from 23.28%(MGB26)to 43.88%(MGB5),and seed yield from1400 kg/ha(MGB7)to 5400 kg/ha(MGB8).Principal component analysis(PCA)identified that the first principal component,accounting for over 24%of the total phenotypic variance,exhibits a strong positive loading of yield-related traits and chlorophyll content,while displaying a pronounced negative loading for oil content variables.This opposing gradient indicates a clear trade-off between vegetative productivity and oil accumulation across the evaluated genotypes.Hierarchical cluster analysis resolved the germplasm into two principal clusters with high within-group similarity,each further partitioned into relatively homogeneous subgroups.Notably,several genotypes outperformed the control variety Ichraq,underscoring their potential for autumn or early winter cultivation.Nonetheless,essential multi-environment trials remain to validate their phenotypic stability and to ascertain their value as genetic resources for sunflower breeding programs in Morocco and other Mediterranean agro-ecosystems.展开更多
Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due t...Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due to extreme climatic conditions and facilitate the cultivation of subsequent crops on the same land,thereby enhancing overall agricultural efficiency.In this review,we synthesize current information on flowering time regulation in rapeseed through an integrated analysis of its genetic,hormonal,and environmental dimensions,emphasizing their crosstalk and implications for yield.We consolidate multi-omics evidence from population genetics,functional genomics,and systems biology to create a haplotype-based framework that overcomes the trade-off between flowering time and yield,providing support for the precision breeding of early-maturing cultivars.The insights presented here could inform future research on flowering time regulation and guide strategies for increasing rapeseed productivity.展开更多
The integration of multi-omic liquid biopsies with artificial intelligence(AI)represents a rapidly evolving frontier in early cancer detection,offering the potential to enhance personalized medicine and improve patien...The integration of multi-omic liquid biopsies with artificial intelligence(AI)represents a rapidly evolving frontier in early cancer detection,offering the potential to enhance personalized medicine and improve patient outcomes.This review explores the current state and emerging directions of this approach,focusing on the synergistic value of combining genomics,epigenomics,transcriptomics,proteomics,and metabolomics with AIdriven analytics.We discuss advances in multi-analyte blood tests such as CancerSEEK,which have demonstrated promising multi-cancer detection capabilities in early studies,as well as efforts to integrate liquid biopsy data with imaging modalities to improve diagnostic performance.The review also highlights ongoing challenges,including the need for greater analytical sensitivity,improved specificity for early-stage disease,standardization of workflows,and harmonization with existing screening modalities.We outline the prospective—but still largely investigational—impact of these technologies on cancer management,including early detection,treatment monitoring,and minimal residual disease assessment,along with their potential economic implications.Ultimately,we envision a future in which multi-omic liquid biopsies integrated with AI may contribute to more effective,noninvasive cancer detection strategies,while recognizing that substantial validation,regulatory approval,and health-system integration are required before widespread clinical adoption can occur.展开更多
Background:Health benefits have been reported for many physical activity(PA)interventions for improving fundamental movement skills(FMS)and cognitive function(CF),but the most effective type of PA interventions for em...Background:Health benefits have been reported for many physical activity(PA)interventions for improving fundamental movement skills(FMS)and cognitive function(CF),but the most effective type of PA interventions for emhancing FMS and CF in early childhood remain unknown.Thus,the study aimed to determine the effects of PA interventions in enhancing FMS and CF among young children and to establish the optimal types of PA interventions.Methods:Six electronic databases(PubMed,OVID,SPORTDiscus,Scopus,Web of Science,and Cochrane)were searched for studies from inception to March 17,2024.Randomized controlled trials(RCTs)were included in this study if they reported outcomes related to FMS,CF,or both associated with PA interventions.Effect sizes were calculated and performed as Hedges'g.The hierarchy of competing interventions was established using the surface under the cumulative ranking curve(SUCRA).Risk of bias was independently assessed using the Cochrane Riskof-Bias 2.Results:This analysis included 38 studies with 5237 young children,with sample sizes ranging from 32 to 897 participants.The types of PA interventions analyzed included active play/free play/unstructured PA(AP),general structured PA(GSPA),FMS-targeted PA programs(FMSprograms),cognitively-engaging PA programs(CPA),multilevel PA interventions(MPA),and exergaming.PA interventions had a large,pooled effect size for total FMS(g=0.96;95%CI:0.45-1.46;p<0.01;I^(2)=94%).For CF,a small-to-moderate pooled effect size was found(g=0.39;95%CI:0.18-0.60;p<0.01;I^(2)=88%).PA interventions longer than 3 months showed fewer benefits for FMS(p<0.01).The network meta-analysis showed that FMS-programs(standardized mean difference((SMD)=1.55,95%CI:0.98-2.11,SUCRA=98.3%)and GSPA(SMD=0.94,95%CI:0.05-1.85,SUCRA=69.8%)significantly improved total FMS compared to AP.For locomotor skills(LMS),exergaming ranked highest(SUCRA=79.3%),followed by FMS-programs(75.9%)and GSPA(61.6%).However,despite its top ranking,exergaming's effect estimate was not statistically significant(SMD=1.38,95%CI:-0.08 to 2.85).For object control skills(OCS),exergaming again ranked highest(SUCRA=91.9%)and showed the largest significant effect(SMD=2.38,95%CI:0.96-3.80),followed by FMS-programs(SUCRA=78.5%)and GSPA(SUCRA=53.7%).FMS-programs,GSPA,MPA,and UC also significantly improved OCS compared to AP.While no significant differences were observed across PA interventions for most CF domains,exergaming had a significant positive effect on working memory(SMD=1.41,95%CI:0.07-2.75).The certainty of evidence varied from low to moderate.Conclusion:These findings emphasize the importance of PA interventions in improving FMS and CF in early childhood.FMS-programs and GSPA appear to be the most effective approaches for enhancing total FMS,while exergaming showed the highest ranking for LMS and OCS,with a significant impact on OCS but uncertainty in LMS improvements.Additionally,exergaming had a positive effect on working memory,suggesting its potential cognitive benefits.展开更多
Background:Early Hearing Detection and Intervention(EHDI)plays a critical role in improving language,cognitive,and socio-emotional outcomes for infants with hearing loss.In Nigeria,however,EHDI implementation remains ...Background:Early Hearing Detection and Intervention(EHDI)plays a critical role in improving language,cognitive,and socio-emotional outcomes for infants with hearing loss.In Nigeria,however,EHDI implementation remains limited by fragmented service delivery,uneven technological capacity,and sociocultural factors that delay timely diagnosis.This study explored the perspectives of paediatric audiologists and parents to provide a comprehensive understanding of the opportunities and challenges influencing early hearing care across diverse Nigerian settings.Methods:A mixed-methods design was employed across audiology facilities selected systematically from four Nigerian geopolitical zones.Twenty-five paediatric audiologists and twenty-three parents of children with congenital hearing loss participated.Quantitative data were collected using a structured questionnaire assessing awareness,diagnostic access,and intervention experiences.Qualitative data were obtained through semi-structured interviews and two focus group discussions.Thematic analysis followed Braun and Clarke's six-step framework,with dual coding,external auditing,and member validation to enhance credibility.Results:Quantitative findings demonstrated broad agreement on the diagnostic value of otoacoustic emissions(OAEs)and automated auditory brainstem responses(AABRs),the developmental benefits of early intervention,and the importance of active parental involvement.However,respondents identified persistent barriers including high costs of screening and therapy,poor public awareness of early hearing loss symptoms,and a critical shortage of trained personnel,and unequal distribution of diagnostic tools,particularly in rural and northern regions.Thematic analysis further underscored disparities in diagnostic capacity,sociocultural interpretations of deafness that delay clinical consultation,and economic constraints that hinder continuity of care.While families who accessed early intervention reported improved communication,social engagement,and learning readiness in their children,systemic gaps continue to limit widespread success.Conclusions:Despite growing technological capacity and awareness of EHDI benefits,significant structural,financial,and sociocultural challenges continue to impede timely diagnosis and intervention in Nigeria.Strengthening national policies,ensuring equitable distribution of diagnostic tools,expanding professional training,subsidising services,implementing culturally sensitive awareness campaigns and integration of Universal Newborn Hearing Screening into routine postnatal care are essential to improving outcomes for deaf infants.展开更多
BACKGROUND Inappropriate selection of patients with early gastric cancer(EGC)for endoscopic submucosal dissection(ESD)may lead to non-curative resection,necessitating additional gastrectomy.Conversely,inappropriate se...BACKGROUND Inappropriate selection of patients with early gastric cancer(EGC)for endoscopic submucosal dissection(ESD)may lead to non-curative resection,necessitating additional gastrectomy.Conversely,inappropriate selection for gastrectomy may result in overtreatment,adversely affecting patients’quality of life.Few have systematically evaluated the concordance between therapeutic indications under current Japanese guidelines and pathological criteria in EGC.To minimize noncurative resection risks while sparing unnecessary surgery for low-risk patients’,we specifically assess the suitability of Japanese guidelines in non-Japanese populations.This work aims to optimize clinical practice by refining endoscopic treatment criteria for adoption beyond Japan.AIM To evaluate EGC clinical decision accuracy by comparing therapeutic indication with postoperative pathological criteria and analyzing factors influencing discrepancies.METHODS A retrospective analysis was conducted on 796 EGC cases diagnosed at Peking University Third Hospital between January 2010 and December 2022.Cases were categorized into three groups:Same-estimated(preoperative therapeutic indication with postoperative pathological criteria matched),underestimated(preoperative ESD indication but postoperative surgical criteria),and overestimated(preoperative surgical indication but postoperative ESD criteria).The rate of discrepancy and associated risk factors were assessed.RESULTS The accuracy rates of preoperative evaluation for ESD and gastrectomy indications were 73.0%(321/430)and 76.0%(278/366),respectively.The overall discrepancy rate was 25.6%(204/796).Multivariate analysis identified tumor location in the upper-third stomach(odds ratio=2.158,95%confidence interval:1.373-3.390,P=0.001)was significantly associated with a higher likelihood of being underestimated and undifferentiated histologic type on preoperative biopsy(odds ratio=2.005,95%confidence interval:1.036-3.879,P=0.039)was more likely to be overestimated.Significant differences were observed in tumor diameter(P<0.001),depth of infiltration(P<0.001),ulcerative findings(P<0.001),and histologic type(P<0.001)between preoperative and postoperative evaluations.CONCLUSION The accuracy of preoperative EGC indications is 74.4%.Upper-third stomach and undifferentiated histology are primary discrepancy predictors.Upper-third tumors are prone to underestimation,while undifferentiated tumors are prone to overestimation.展开更多
This article reviews research advances in the application of early enteral nutrition(EEN)in elderly patients with severe acute pancreatitis(SAP).Elderly SAP patients are associated with higher mor tality rates due to ...This article reviews research advances in the application of early enteral nutrition(EEN)in elderly patients with severe acute pancreatitis(SAP).Elderly SAP patients are associated with higher mor tality rates due to age-related immune dysfunction,whereas EEN has been demonstrated to improve clinical prognosis,reduce infection and complication rates,and shor ten hospital stays.However,ongoing debates exist regarding the optimal timing,route selection,and complication management of EEN.Through a systematic review of the literature,this study synthesizes current evidence on EEN in elderly SAP populations,critically examines unresolved clinical controversies,and proposes future research priorities to inform evidence-based practice.展开更多
BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking rec...BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking recovery.OBJECTIVE:To determine whether early suspension-protected training with a personal assistant machine for stroke patients enhances walking ability and prevents muscle spasms.METHODS:Thirty-two early-stage stroke patients from Shenzhen University General Hospital and the China Rehabilitation Research Center were randomly assigned to the experimental group(n=16)and the control group(n=16).Both groups underwent 4 weeks of gait training under the suspension protection system for 30 minutes daily,5 days a week.The experimental group used the personal assistant machine during training.Three-dimensional gait analysis(using the Cortex motion capture system),Brunnstrom staging,Fugl-Meyer Assessment for lower limb motor function,Fugl-Meyer balance function,and the modified Ashworth Scale were evaluated within 1 week before the intervention and after 4 weeks of intervention.RESULTS AND CONCLUSION:After the 4-week intervention,all outcome measures showed significant changes in each group.The experimental group had a small but significant increase in the modified Ashworth Scale score(P<0.05,d=|0.15|),while the control group had a large significant increase(P<0.05,d=|1.48|).The experimental group demonstrated greater improvements in walking speed(16.5 to 38.44 cm/s,P<0.05,d=|4.01|),step frequency(46.44 to 64.94 steps/min,P<0.05,d=|2.32|),stride length(15.50 to 29.81 cm,P<0.05,d=|3.44|),and peak hip and knee flexion(d=|1.82|to|2.17|).After treatment,the experimental group showed significantly greater improvements than the control group in walking speed(38.44 vs.26.63 cm/s,P<0.05,d=|2.75|),stride length,peak hip and knee flexion(d=|1.31|to|1.45|),step frequency(64.94 vs.59.38 steps/min,P<0.05,d=|0.85|),and a reduced support phase(bilateral:24.31%vs.28.38%,P<0.05,d=|0.88|;non-paretic:66.19%vs.70.13%,P<0.05,d=|0.94|).For early hemiplegia,personal assistant machine-assisted gait training under the suspension protection system helps establish a correct gait pattern,prevents muscle spasms,and improves motor function.展开更多
Objective:To analyze the improvement effect of early postoperative rehabilitation training on balance ability and quality of life in elderly patients with hip fracture.Methods:A total of 50 elderly patients with hip f...Objective:To analyze the improvement effect of early postoperative rehabilitation training on balance ability and quality of life in elderly patients with hip fracture.Methods:A total of 50 elderly patients with hip fracture admitted to our hospital from January 2023 to January 2024 were selected and divided into the observation group(25 cases)and the control group(25 cases)by random number table method.The control group received routine nursing,while the observation group received early rehabilitation training on the basis of routine nursing.The balance ability(Berg Balance Scale,BBS)and quality of life(SF-36)of the two groups were compared.Results:The BBS scores of the observation group at all postoperative time points were significantly higher than those of the control group(p<0.05),and the quality-of-life scores of the observation group were also significantly higher than those of the control group(p<0.05).Conclusion:Early postoperative rehabilitation training for elderly patients with hip fracture can improve their balance ability,enhance their quality of life,and reduce the incidence of postoperative complications,which is worthy of clinical promotion.展开更多
The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Lap...With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.展开更多
Amylose content(AC)is a key determinant of rice eating and cooking quality(ECQ).Lower AC is generally associated with improved palatability and is therefore a desirable trait in rice breeding;however,effective manipul...Amylose content(AC)is a key determinant of rice eating and cooking quality(ECQ).Lower AC is generally associated with improved palatability and is therefore a desirable trait in rice breeding;however,effective manipulation of AC remains a challenge.In this study,we identified AC6,a novel endosperm-specific early nodulin-like(ENODL)gene,belonging to a 32-member ENODL family.Using CRISPR/Cas9 technology,we generated an ac6 knockout allele,which exhibited a significant decrease in AC and produced improved ECQ without compromising grain appearance or yield.Subcellular localization analysis demonstrated that AC6 is a plastid-localized protein that likely regulates AC by interacting with the Waxy(Wx)protein.Moreover,expression of starch metabolism-related genes was markedly altered in developing ac6 endosperm.Our study highlights AC6 as a novel target gene for engineering rice germplasm with enhanced ECQ.展开更多
0 INTRODUCTION Due to the sudden and highly destructive nature of slope rock collapse,developing effective early warning systems has become an urgent challenge in geotechnical engineering(Cai and Detournay,2024;Loew e...0 INTRODUCTION Due to the sudden and highly destructive nature of slope rock collapse,developing effective early warning systems has become an urgent challenge in geotechnical engineering(Cai and Detournay,2024;Loew et al.,2017).Traditional monitoring methods primarily target the acceleration stage preceding disasters(such as displacement monitoring for landslides and debris flows),which is effective for early warning of plastic collapse disasters but often inadequate for brittle failure modes(Walter et al.,2019;Chao et al.,2018;Crosta et al.,2017).展开更多
Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and earl...Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and early warning of distribution transformers,integrating Sample Ensemble Learning(SEL)with a Self-Optimizing Support Vector Machine(SO-SVM).The SEL technique enhances data diversity and mitigates class imbalance,while SO-SVM adaptively tunes its hyperparameters to improve classification accuracy.A comprehensive transformer model was developed in MATLAB/Simulink to simulate diverse fault scenarios,including inter-turn winding faults,core saturation,and thermal aging.Feature vectors were extracted from voltage,current,and temperature measurements to train and validate the proposed hybrid model.Quantitative analysis shows that the SEL–SO-SVM framework achieves a classification accuracy of 97.8%,a precision of 96.5%,and an F1-score of 97.2%.Beyond classification,the model effectively identified incipient faults,providing an early warning lead time of up to 2.5 s before significant deviations in operational parameters.This predictive capability underscores its potential for preventing catastrophic transformer failures and enabling timely maintenance actions.The proposed approach demonstrates strong applicability for enhancing the reliability and operational safety of distribution transformers in simulated environments,offering a promising foundation for future real-time and field-level implementations.展开更多
Parkinson’s disease remains a major clinical issue in terms of early detection,especially during its prodromal stage when symptoms are not evident or not distinct.To address this problem,we proposed a new deep learni...Parkinson’s disease remains a major clinical issue in terms of early detection,especially during its prodromal stage when symptoms are not evident or not distinct.To address this problem,we proposed a new deep learning 2-based approach for detecting Parkinson’s disease before any of the overt symptoms develop during their prodromal stage.We used 5 publicly accessible datasets,including UCI Parkinson’s Voice,Spiral Drawings,PaHaW,NewHandPD,and PPMI,and implemented a dual stream CNN–BiLSTM architecture with Fisher-weighted feature merging and SHAP-based explanation.The findings reveal that the model’s performance was superior and achieved 98.2%,a F1-score of 0.981,and AUC of 0.991 on the UCI Voice dataset.The model’s performance on the remaining datasets was also comparable,with up to a 2–7 percent betterment in accuracy compared to existing strong models such as CNN–RNN–MLP,ILN–GNet,and CASENet.Across the evidence,the findings back the diagnostic promise of micro-tremor assessment and demonstrate that combining temporal and spatial features with a scatter-based segment for a multi-modal approach can be an effective and scalable platform for an“early,”interpretable PD screening system.展开更多
Early life stress correlates with a higher prevalence of neurological disorders,including autism,attention-deficit/hyperactivity disorder,schizophrenia,depression,and Parkinson's disease.These conditions,primarily...Early life stress correlates with a higher prevalence of neurological disorders,including autism,attention-deficit/hyperactivity disorder,schizophrenia,depression,and Parkinson's disease.These conditions,primarily involving abnormal development and damage of the dopaminergic system,pose significant public health challenges.Microglia,as the primary immune cells in the brain,are crucial in regulating neuronal circuit development and survival.From the embryonic stage to adulthood,microglia exhibit stage-specific gene expression profiles,transcriptome characteristics,and functional phenotypes,enhancing the susceptibility to early life stress.However,the role of microglia in mediating dopaminergic system disorders under early life stress conditions remains poorly understood.This review presents an up-to-date overview of preclinical studies elucidating the impact of early life stress on microglia,leading to dopaminergic system disorders,along with the underlying mechanisms and therapeutic potential for neurodegenerative and neurodevelopmental conditions.Impaired microglial activity damages dopaminergic neurons by diminishing neurotrophic support(e.g.,insulin-like growth factor-1)and hinders dopaminergic axon growth through defective phagocytosis and synaptic pruning.Furthermore,blunted microglial immunoreactivity suppresses striatal dopaminergic circuit development and reduces neuronal transmission.Furthermore,inflammation and oxidative stress induced by activated microglia can directly damage dopaminergic neurons,inhibiting dopamine synthesis,reuptake,and receptor activity.Enhanced microglial phagocytosis inhibits dopamine axon extension.These long-lasting effects of microglial perturbations may be driven by early life stress–induced epigenetic reprogramming of microglia.Indirectly,early life stress may influence microglial function through various pathways,such as astrocytic activation,the hypothalamic–pituitary–adrenal axis,the gut–brain axis,and maternal immune signaling.Finally,various therapeutic strategies and molecular mechanisms for targeting microglia to restore the dopaminergic system were summarized and discussed.These strategies include classical antidepressants and antipsychotics,antibiotics and anti-inflammatory agents,and herbal-derived medicine.Further investigations combining pharmacological interventions and genetic strategies are essential to elucidate the causal role of microglial phenotypic and functional perturbations in the dopaminergic system disrupted by early life stress.展开更多
Vitamin D deficiency(VDD)represents a significant nutritional concern among children and adolescents.The estimated prevalence of VDD in China is 46.8%in this population^([1]).VDD during childhood and adolescence has b...Vitamin D deficiency(VDD)represents a significant nutritional concern among children and adolescents.The estimated prevalence of VDD in China is 46.8%in this population^([1]).VDD during childhood and adolescence has been associated with the onset of various conditions,including acute respiratory infections,asthma,atopic dermatitis,and food allergies^([2]).Multiple factors,including age,sun exposure,adiposity,and genetics,influence vitamin D levels^([2,3]).Increasing attention has been directed toward understanding the environmental determinants that may influence vitamin D status.Given the potential of metallic pollutants to disrupt endocrine function and their ubiquity in the environment,investigating the effects of metal exposure on human vitamin D status,particularly in vulnerable populations,is imperative.展开更多
Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning sy...Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.展开更多
Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are...Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.展开更多
文摘Despite Morocco's reliance on sunflower as an oilseed crop,little is known about its agronomic performance when sown in autumn or early winter.This knowledge gap is critical,as spring-sown varieties have shown declining performance in recent years under intensifying climate stress.Therefore,targeted breeding strategies could discover genotypes suitable for autumn or early winter sowing,with cold tolerance as a key selection criterion.Currently,‘Ichraq'is the only autumn-planted sunflower variety officially registered in Morocco,although efforts to release additional tolerant varieties are underway.This study evaluated 31 genotypes(MGB1to MGB31)selected from various environments under autumn planting conditions and conserved in the Moroccan Gene Bank.These genotypes were planted in early winter at a mountainous site known for its pronounced winter cold.Eighteen Morphological,physiological and agronomic parameters including initial vigor,leaf area,seed yield,oil content etc.,were assessed using both univariate and multivariate statistical approaches.Analysis of variance revealed significant genotypic differences across most traits,indicating substantial genetic variation.Notably,seed oil content ranged from 23.28%(MGB26)to 43.88%(MGB5),and seed yield from1400 kg/ha(MGB7)to 5400 kg/ha(MGB8).Principal component analysis(PCA)identified that the first principal component,accounting for over 24%of the total phenotypic variance,exhibits a strong positive loading of yield-related traits and chlorophyll content,while displaying a pronounced negative loading for oil content variables.This opposing gradient indicates a clear trade-off between vegetative productivity and oil accumulation across the evaluated genotypes.Hierarchical cluster analysis resolved the germplasm into two principal clusters with high within-group similarity,each further partitioned into relatively homogeneous subgroups.Notably,several genotypes outperformed the control variety Ichraq,underscoring their potential for autumn or early winter cultivation.Nonetheless,essential multi-environment trials remain to validate their phenotypic stability and to ascertain their value as genetic resources for sunflower breeding programs in Morocco and other Mediterranean agro-ecosystems.
基金supported by the National Key Research and Development Program of China(2022YFD1200400)the National Natural Science Foundation of China(32272111)+4 种基金Special fund for youth team of the Southwest Universities(SWU-XJPY202306)Chongqing Natural Science Foundation(CSTB2024NSCQLZX0012)Modern Agro-industry Technology Research System(CARS-12)Chongqing Modern Agricultural Industry Technology System(COMAITS202504)Biological Breeding-National Science and Technology Major Project(2022ZD04008).We sincerely appreciate the Plant Editors team for English language editing of the manuscript,which significantly improved its clarity and overall quality.
文摘Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due to extreme climatic conditions and facilitate the cultivation of subsequent crops on the same land,thereby enhancing overall agricultural efficiency.In this review,we synthesize current information on flowering time regulation in rapeseed through an integrated analysis of its genetic,hormonal,and environmental dimensions,emphasizing their crosstalk and implications for yield.We consolidate multi-omics evidence from population genetics,functional genomics,and systems biology to create a haplotype-based framework that overcomes the trade-off between flowering time and yield,providing support for the precision breeding of early-maturing cultivars.The insights presented here could inform future research on flowering time regulation and guide strategies for increasing rapeseed productivity.
文摘The integration of multi-omic liquid biopsies with artificial intelligence(AI)represents a rapidly evolving frontier in early cancer detection,offering the potential to enhance personalized medicine and improve patient outcomes.This review explores the current state and emerging directions of this approach,focusing on the synergistic value of combining genomics,epigenomics,transcriptomics,proteomics,and metabolomics with AIdriven analytics.We discuss advances in multi-analyte blood tests such as CancerSEEK,which have demonstrated promising multi-cancer detection capabilities in early studies,as well as efforts to integrate liquid biopsy data with imaging modalities to improve diagnostic performance.The review also highlights ongoing challenges,including the need for greater analytical sensitivity,improved specificity for early-stage disease,standardization of workflows,and harmonization with existing screening modalities.We outline the prospective—but still largely investigational—impact of these technologies on cancer management,including early detection,treatment monitoring,and minimal residual disease assessment,along with their potential economic implications.Ultimately,we envision a future in which multi-omic liquid biopsies integrated with AI may contribute to more effective,noninvasive cancer detection strategies,while recognizing that substantial validation,regulatory approval,and health-system integration are required before widespread clinical adoption can occur.
文摘Background:Health benefits have been reported for many physical activity(PA)interventions for improving fundamental movement skills(FMS)and cognitive function(CF),but the most effective type of PA interventions for emhancing FMS and CF in early childhood remain unknown.Thus,the study aimed to determine the effects of PA interventions in enhancing FMS and CF among young children and to establish the optimal types of PA interventions.Methods:Six electronic databases(PubMed,OVID,SPORTDiscus,Scopus,Web of Science,and Cochrane)were searched for studies from inception to March 17,2024.Randomized controlled trials(RCTs)were included in this study if they reported outcomes related to FMS,CF,or both associated with PA interventions.Effect sizes were calculated and performed as Hedges'g.The hierarchy of competing interventions was established using the surface under the cumulative ranking curve(SUCRA).Risk of bias was independently assessed using the Cochrane Riskof-Bias 2.Results:This analysis included 38 studies with 5237 young children,with sample sizes ranging from 32 to 897 participants.The types of PA interventions analyzed included active play/free play/unstructured PA(AP),general structured PA(GSPA),FMS-targeted PA programs(FMSprograms),cognitively-engaging PA programs(CPA),multilevel PA interventions(MPA),and exergaming.PA interventions had a large,pooled effect size for total FMS(g=0.96;95%CI:0.45-1.46;p<0.01;I^(2)=94%).For CF,a small-to-moderate pooled effect size was found(g=0.39;95%CI:0.18-0.60;p<0.01;I^(2)=88%).PA interventions longer than 3 months showed fewer benefits for FMS(p<0.01).The network meta-analysis showed that FMS-programs(standardized mean difference((SMD)=1.55,95%CI:0.98-2.11,SUCRA=98.3%)and GSPA(SMD=0.94,95%CI:0.05-1.85,SUCRA=69.8%)significantly improved total FMS compared to AP.For locomotor skills(LMS),exergaming ranked highest(SUCRA=79.3%),followed by FMS-programs(75.9%)and GSPA(61.6%).However,despite its top ranking,exergaming's effect estimate was not statistically significant(SMD=1.38,95%CI:-0.08 to 2.85).For object control skills(OCS),exergaming again ranked highest(SUCRA=91.9%)and showed the largest significant effect(SMD=2.38,95%CI:0.96-3.80),followed by FMS-programs(SUCRA=78.5%)and GSPA(SUCRA=53.7%).FMS-programs,GSPA,MPA,and UC also significantly improved OCS compared to AP.While no significant differences were observed across PA interventions for most CF domains,exergaming had a significant positive effect on working memory(SMD=1.41,95%CI:0.07-2.75).The certainty of evidence varied from low to moderate.Conclusion:These findings emphasize the importance of PA interventions in improving FMS and CF in early childhood.FMS-programs and GSPA appear to be the most effective approaches for enhancing total FMS,while exergaming showed the highest ranking for LMS and OCS,with a significant impact on OCS but uncertainty in LMS improvements.Additionally,exergaming had a positive effect on working memory,suggesting its potential cognitive benefits.
文摘Background:Early Hearing Detection and Intervention(EHDI)plays a critical role in improving language,cognitive,and socio-emotional outcomes for infants with hearing loss.In Nigeria,however,EHDI implementation remains limited by fragmented service delivery,uneven technological capacity,and sociocultural factors that delay timely diagnosis.This study explored the perspectives of paediatric audiologists and parents to provide a comprehensive understanding of the opportunities and challenges influencing early hearing care across diverse Nigerian settings.Methods:A mixed-methods design was employed across audiology facilities selected systematically from four Nigerian geopolitical zones.Twenty-five paediatric audiologists and twenty-three parents of children with congenital hearing loss participated.Quantitative data were collected using a structured questionnaire assessing awareness,diagnostic access,and intervention experiences.Qualitative data were obtained through semi-structured interviews and two focus group discussions.Thematic analysis followed Braun and Clarke's six-step framework,with dual coding,external auditing,and member validation to enhance credibility.Results:Quantitative findings demonstrated broad agreement on the diagnostic value of otoacoustic emissions(OAEs)and automated auditory brainstem responses(AABRs),the developmental benefits of early intervention,and the importance of active parental involvement.However,respondents identified persistent barriers including high costs of screening and therapy,poor public awareness of early hearing loss symptoms,and a critical shortage of trained personnel,and unequal distribution of diagnostic tools,particularly in rural and northern regions.Thematic analysis further underscored disparities in diagnostic capacity,sociocultural interpretations of deafness that delay clinical consultation,and economic constraints that hinder continuity of care.While families who accessed early intervention reported improved communication,social engagement,and learning readiness in their children,systemic gaps continue to limit widespread success.Conclusions:Despite growing technological capacity and awareness of EHDI benefits,significant structural,financial,and sociocultural challenges continue to impede timely diagnosis and intervention in Nigeria.Strengthening national policies,ensuring equitable distribution of diagnostic tools,expanding professional training,subsidising services,implementing culturally sensitive awareness campaigns and integration of Universal Newborn Hearing Screening into routine postnatal care are essential to improving outcomes for deaf infants.
基金Supported by China Health&Medical Development Foundation,No.M2021551.
文摘BACKGROUND Inappropriate selection of patients with early gastric cancer(EGC)for endoscopic submucosal dissection(ESD)may lead to non-curative resection,necessitating additional gastrectomy.Conversely,inappropriate selection for gastrectomy may result in overtreatment,adversely affecting patients’quality of life.Few have systematically evaluated the concordance between therapeutic indications under current Japanese guidelines and pathological criteria in EGC.To minimize noncurative resection risks while sparing unnecessary surgery for low-risk patients’,we specifically assess the suitability of Japanese guidelines in non-Japanese populations.This work aims to optimize clinical practice by refining endoscopic treatment criteria for adoption beyond Japan.AIM To evaluate EGC clinical decision accuracy by comparing therapeutic indication with postoperative pathological criteria and analyzing factors influencing discrepancies.METHODS A retrospective analysis was conducted on 796 EGC cases diagnosed at Peking University Third Hospital between January 2010 and December 2022.Cases were categorized into three groups:Same-estimated(preoperative therapeutic indication with postoperative pathological criteria matched),underestimated(preoperative ESD indication but postoperative surgical criteria),and overestimated(preoperative surgical indication but postoperative ESD criteria).The rate of discrepancy and associated risk factors were assessed.RESULTS The accuracy rates of preoperative evaluation for ESD and gastrectomy indications were 73.0%(321/430)and 76.0%(278/366),respectively.The overall discrepancy rate was 25.6%(204/796).Multivariate analysis identified tumor location in the upper-third stomach(odds ratio=2.158,95%confidence interval:1.373-3.390,P=0.001)was significantly associated with a higher likelihood of being underestimated and undifferentiated histologic type on preoperative biopsy(odds ratio=2.005,95%confidence interval:1.036-3.879,P=0.039)was more likely to be overestimated.Significant differences were observed in tumor diameter(P<0.001),depth of infiltration(P<0.001),ulcerative findings(P<0.001),and histologic type(P<0.001)between preoperative and postoperative evaluations.CONCLUSION The accuracy of preoperative EGC indications is 74.4%.Upper-third stomach and undifferentiated histology are primary discrepancy predictors.Upper-third tumors are prone to underestimation,while undifferentiated tumors are prone to overestimation.
基金supported by the Scientific Research Project of the Health Commission of Shanxi Province(No.2024003)。
文摘This article reviews research advances in the application of early enteral nutrition(EEN)in elderly patients with severe acute pancreatitis(SAP).Elderly SAP patients are associated with higher mor tality rates due to age-related immune dysfunction,whereas EEN has been demonstrated to improve clinical prognosis,reduce infection and complication rates,and shor ten hospital stays.However,ongoing debates exist regarding the optimal timing,route selection,and complication management of EEN.Through a systematic review of the literature,this study synthesizes current evidence on EEN in elderly SAP populations,critically examines unresolved clinical controversies,and proposes future research priorities to inform evidence-based practice.
文摘BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking recovery.OBJECTIVE:To determine whether early suspension-protected training with a personal assistant machine for stroke patients enhances walking ability and prevents muscle spasms.METHODS:Thirty-two early-stage stroke patients from Shenzhen University General Hospital and the China Rehabilitation Research Center were randomly assigned to the experimental group(n=16)and the control group(n=16).Both groups underwent 4 weeks of gait training under the suspension protection system for 30 minutes daily,5 days a week.The experimental group used the personal assistant machine during training.Three-dimensional gait analysis(using the Cortex motion capture system),Brunnstrom staging,Fugl-Meyer Assessment for lower limb motor function,Fugl-Meyer balance function,and the modified Ashworth Scale were evaluated within 1 week before the intervention and after 4 weeks of intervention.RESULTS AND CONCLUSION:After the 4-week intervention,all outcome measures showed significant changes in each group.The experimental group had a small but significant increase in the modified Ashworth Scale score(P<0.05,d=|0.15|),while the control group had a large significant increase(P<0.05,d=|1.48|).The experimental group demonstrated greater improvements in walking speed(16.5 to 38.44 cm/s,P<0.05,d=|4.01|),step frequency(46.44 to 64.94 steps/min,P<0.05,d=|2.32|),stride length(15.50 to 29.81 cm,P<0.05,d=|3.44|),and peak hip and knee flexion(d=|1.82|to|2.17|).After treatment,the experimental group showed significantly greater improvements than the control group in walking speed(38.44 vs.26.63 cm/s,P<0.05,d=|2.75|),stride length,peak hip and knee flexion(d=|1.31|to|1.45|),step frequency(64.94 vs.59.38 steps/min,P<0.05,d=|0.85|),and a reduced support phase(bilateral:24.31%vs.28.38%,P<0.05,d=|0.88|;non-paretic:66.19%vs.70.13%,P<0.05,d=|0.94|).For early hemiplegia,personal assistant machine-assisted gait training under the suspension protection system helps establish a correct gait pattern,prevents muscle spasms,and improves motor function.
基金Chongqing Education Science Planning Project.Project Name:Research on Talent Training of Community Rehabilitation Major in Higher Vocational Colleges Based on OBE Concept(Project No.:K23ZG3420222)。
文摘Objective:To analyze the improvement effect of early postoperative rehabilitation training on balance ability and quality of life in elderly patients with hip fracture.Methods:A total of 50 elderly patients with hip fracture admitted to our hospital from January 2023 to January 2024 were selected and divided into the observation group(25 cases)and the control group(25 cases)by random number table method.The control group received routine nursing,while the observation group received early rehabilitation training on the basis of routine nursing.The balance ability(Berg Balance Scale,BBS)and quality of life(SF-36)of the two groups were compared.Results:The BBS scores of the observation group at all postoperative time points were significantly higher than those of the control group(p<0.05),and the quality-of-life scores of the observation group were also significantly higher than those of the control group(p<0.05).Conclusion:Early postoperative rehabilitation training for elderly patients with hip fracture can improve their balance ability,enhance their quality of life,and reduce the incidence of postoperative complications,which is worthy of clinical promotion.
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
基金supported by National Key Research and Development Program of China(No.2023YFC2507406)National Natural Science Foundation of China(No.82300646)+6 种基金Beijing Natural Science Foundation(No.7232334)Beijing Municipal Administration of Hospitals Incubating Program(No.PX2024002,PX2020001)Capital Fund for Health Development Scientific Research(No.2024-2-2028)Beijing Municipal Science&Technology Commission AI+Health Collaborative Innovation Cultivation Project(No.Z241100007724004)Research Ward Excellence Program of Beijing Municipal Health Commission(No.BRWEP2024W162020100,BRWEP2024W162020112,BRWEP2024W162020114)Excellent Plan for Capital Medicine Scientific and Technological Innovation Achievement Transformation Promotion Plan(No.YC202401QX0824)Clinical Scientific Research Fund of Beijing Integrated Medical Association[No.ZHKY-2025-1869(B012)]。
文摘With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.
基金supported by the Government of Jiangsu Province,China(Grant Nos.23KJA210001,BE2023331,KYCX21_3247,and BE2021334)the National Natural Science Foundation of China(Grant Nos.31971914 and 32472072).
文摘Amylose content(AC)is a key determinant of rice eating and cooking quality(ECQ).Lower AC is generally associated with improved palatability and is therefore a desirable trait in rice breeding;however,effective manipulation of AC remains a challenge.In this study,we identified AC6,a novel endosperm-specific early nodulin-like(ENODL)gene,belonging to a 32-member ENODL family.Using CRISPR/Cas9 technology,we generated an ac6 knockout allele,which exhibited a significant decrease in AC and produced improved ECQ without compromising grain appearance or yield.Subcellular localization analysis demonstrated that AC6 is a plastid-localized protein that likely regulates AC by interacting with the Waxy(Wx)protein.Moreover,expression of starch metabolism-related genes was markedly altered in developing ac6 endosperm.Our study highlights AC6 as a novel target gene for engineering rice germplasm with enhanced ECQ.
基金supported by the National Key R&D Program of China(No.2023YFC3081400)the National Natural Science Foundation of China(No.41702371)+3 种基金the Open Fund Project of State Key Laboratory of Mining Response and Disaster Prevention in Deep Coal Mines(No.SKLMRDPC22KF13)the Supported by State key Laboratory of Mining Disaster Prevention and Control(Shandong University of Science and Technology),Ministry of Education(No.DPEPM202502)the Open Fund Research Project Supported by State Key Laboratory of Strata Intelligent Control and Green Mining Co-founded by Shandong Province and the Ministry of Science and Technology(No.SICGM202503)the Fund of Chongqing Key Laboratory of Facility Damage Mechanism and Protection in Highland Mountain Environment(No.LQ24KFJJ09)。
文摘0 INTRODUCTION Due to the sudden and highly destructive nature of slope rock collapse,developing effective early warning systems has become an urgent challenge in geotechnical engineering(Cai and Detournay,2024;Loew et al.,2017).Traditional monitoring methods primarily target the acceleration stage preceding disasters(such as displacement monitoring for landslides and debris flows),which is effective for early warning of plastic collapse disasters but often inadequate for brittle failure modes(Walter et al.,2019;Chao et al.,2018;Crosta et al.,2017).
文摘Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and early warning of distribution transformers,integrating Sample Ensemble Learning(SEL)with a Self-Optimizing Support Vector Machine(SO-SVM).The SEL technique enhances data diversity and mitigates class imbalance,while SO-SVM adaptively tunes its hyperparameters to improve classification accuracy.A comprehensive transformer model was developed in MATLAB/Simulink to simulate diverse fault scenarios,including inter-turn winding faults,core saturation,and thermal aging.Feature vectors were extracted from voltage,current,and temperature measurements to train and validate the proposed hybrid model.Quantitative analysis shows that the SEL–SO-SVM framework achieves a classification accuracy of 97.8%,a precision of 96.5%,and an F1-score of 97.2%.Beyond classification,the model effectively identified incipient faults,providing an early warning lead time of up to 2.5 s before significant deviations in operational parameters.This predictive capability underscores its potential for preventing catastrophic transformer failures and enabling timely maintenance actions.The proposed approach demonstrates strong applicability for enhancing the reliability and operational safety of distribution transformers in simulated environments,offering a promising foundation for future real-time and field-level implementations.
基金supported via funding from Prince Sattam bin Abdulaziz University project number(PSAU/2025/03/32440).
文摘Parkinson’s disease remains a major clinical issue in terms of early detection,especially during its prodromal stage when symptoms are not evident or not distinct.To address this problem,we proposed a new deep learning 2-based approach for detecting Parkinson’s disease before any of the overt symptoms develop during their prodromal stage.We used 5 publicly accessible datasets,including UCI Parkinson’s Voice,Spiral Drawings,PaHaW,NewHandPD,and PPMI,and implemented a dual stream CNN–BiLSTM architecture with Fisher-weighted feature merging and SHAP-based explanation.The findings reveal that the model’s performance was superior and achieved 98.2%,a F1-score of 0.981,and AUC of 0.991 on the UCI Voice dataset.The model’s performance on the remaining datasets was also comparable,with up to a 2–7 percent betterment in accuracy compared to existing strong models such as CNN–RNN–MLP,ILN–GNet,and CASENet.Across the evidence,the findings back the diagnostic promise of micro-tremor assessment and demonstrate that combining temporal and spatial features with a scatter-based segment for a multi-modal approach can be an effective and scalable platform for an“early,”interpretable PD screening system.
基金supported by the National Natural Science Foundation of China,Nos.82304990(to NY),81973748(to JC),82174278(to JC)the National Key R&D Program of China,No.2023YFE0209500(to JC)+4 种基金China Postdoctoral Science Foundation,No.2023M732380(to NY)Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine,No.202102010014(to JC)Huang Zhendong Research Fund for Traditional Chinese Medicine of Jinan University,No.201911(to JC)National Innovation and Entrepreneurship Training Program for Undergraduates in China,No.202310559128(to NY and QM)Innovation and Entrepreneurship Training Program for Undergraduates at Jinan University,Nos.CX24380,CX24381(both to NY and QM)。
文摘Early life stress correlates with a higher prevalence of neurological disorders,including autism,attention-deficit/hyperactivity disorder,schizophrenia,depression,and Parkinson's disease.These conditions,primarily involving abnormal development and damage of the dopaminergic system,pose significant public health challenges.Microglia,as the primary immune cells in the brain,are crucial in regulating neuronal circuit development and survival.From the embryonic stage to adulthood,microglia exhibit stage-specific gene expression profiles,transcriptome characteristics,and functional phenotypes,enhancing the susceptibility to early life stress.However,the role of microglia in mediating dopaminergic system disorders under early life stress conditions remains poorly understood.This review presents an up-to-date overview of preclinical studies elucidating the impact of early life stress on microglia,leading to dopaminergic system disorders,along with the underlying mechanisms and therapeutic potential for neurodegenerative and neurodevelopmental conditions.Impaired microglial activity damages dopaminergic neurons by diminishing neurotrophic support(e.g.,insulin-like growth factor-1)and hinders dopaminergic axon growth through defective phagocytosis and synaptic pruning.Furthermore,blunted microglial immunoreactivity suppresses striatal dopaminergic circuit development and reduces neuronal transmission.Furthermore,inflammation and oxidative stress induced by activated microglia can directly damage dopaminergic neurons,inhibiting dopamine synthesis,reuptake,and receptor activity.Enhanced microglial phagocytosis inhibits dopamine axon extension.These long-lasting effects of microglial perturbations may be driven by early life stress–induced epigenetic reprogramming of microglia.Indirectly,early life stress may influence microglial function through various pathways,such as astrocytic activation,the hypothalamic–pituitary–adrenal axis,the gut–brain axis,and maternal immune signaling.Finally,various therapeutic strategies and molecular mechanisms for targeting microglia to restore the dopaminergic system were summarized and discussed.These strategies include classical antidepressants and antipsychotics,antibiotics and anti-inflammatory agents,and herbal-derived medicine.Further investigations combining pharmacological interventions and genetic strategies are essential to elucidate the causal role of microglial phenotypic and functional perturbations in the dopaminergic system disrupted by early life stress.
基金supported by grants from the National Natural Science Foundation of China(G.F.Wang,grant number 82204071)(P.Y.Su,grant numbers 81874268 and 82473655)the Research Funds of the Center for Big Data and Population Health of IHM(P.Y.Su,No.JKS2023016)Anhui Provincial Health Commission Scientific Research Project(Y.Zhou,No.AHWJ2023A30027)。
文摘Vitamin D deficiency(VDD)represents a significant nutritional concern among children and adolescents.The estimated prevalence of VDD in China is 46.8%in this population^([1]).VDD during childhood and adolescence has been associated with the onset of various conditions,including acute respiratory infections,asthma,atopic dermatitis,and food allergies^([2]).Multiple factors,including age,sun exposure,adiposity,and genetics,influence vitamin D levels^([2,3]).Increasing attention has been directed toward understanding the environmental determinants that may influence vitamin D status.Given the potential of metallic pollutants to disrupt endocrine function and their ubiquity in the environment,investigating the effects of metal exposure on human vitamin D status,particularly in vulnerable populations,is imperative.
基金the King Salman center for Disability Research for funding this work through Research Group No.KSRG-2024-050.
文摘Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.
基金supported by the Ministry of Science and Technology of China,No.2020AAA0109605(to XL)Meizhou Major Scientific and Technological Innovation PlatformsProjects of Guangdong Provincial Science & Technology Plan Projects,No.2019A0102005(to HW).
文摘Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.
