Objective:To assess prenatal Bisphenol A(BPA)exposure levels and explore their preliminary associations with maternal and fetal characteristics in a population from Northeastern Yunnan.Methods:A cross-sectional analys...Objective:To assess prenatal Bisphenol A(BPA)exposure levels and explore their preliminary associations with maternal and fetal characteristics in a population from Northeastern Yunnan.Methods:A cross-sectional analysis was performed using data and urine samples from 70 pregnant women in their third trimester recruited at Qujing Central Hospital.Urinary BPA was measured by HPLC-MS/MS.Participants were stratified into high and low BPA exposure groups based on the median concentration.Results:BPA was detected in all samples(100%)with a median concentration of 2.41μg/L(IQR:0.68-4.96).The high BPA exposure group(≥2.41μg/L)had a significantly higher proportion of gestational diabetes mellitus(GDM)(42.9%vs.17.1%,p=0.021)and a lower median fetal birth weight(3250 g vs.3450 g,p=0.048)compared to the low exposure group.Conclusion:This pilot study reveals ubiquitous BPA exposure in pregnant women from Northeastern Yunnan.The observed preliminary associations with GDM and reduced fetal birth weight warrant further investigation in larger,longitudinal studies.展开更多
Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentrat...Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentration,and forming defects are prone to occur during their extrusion.This study focuses on an Al-Zn-Mg-Cu ultra-high-strength aluminum alloy profile with a double-U,multi-cavity thin-walled structure.Firstly,hot compression experiments were conducted at temperatures of 350○C,400○C,and 450○C,with strain rates of 0.01 and 1.0 s^(−1),to investigate the plastic deformation behavior of the material.Subsequently,a 3D coupled thermo-mechanical extrusion simulation model was established using Deform-3D to systematically analyze the influence of die structure and process parameters on metal flow velocity,effective stress/strain,and temperature distribution.The simulation revealed significant velocity differences,stress concentration,and uneven temperature distribution.Key parameters,including mesh density,extrusion ratio,die fillet,and bearing length,were optimized through full-factorial experiments.This optimization,combined with a stepped flow-guiding die design,effectively improved the metal flow pattern during extrusion.Trial production based on both the initial and optimized parameters were carried out.A comparative analysis demonstrates that the optimized scheme results in a final profile whose cross-section matches the target design closely,with complete filling of complex features and no obvious forming defects.This research provides a valuable reference for the extrusion process optimization and die design of complex-section profiles made from ultra-high-strength aluminum alloys.展开更多
Objective This study aimed to determine the temporal trends in sleep duration among Chinese adults.Methods In this series of repeated nationally representative cross-sectional surveys(China Chronic Disease and Risk Fa...Objective This study aimed to determine the temporal trends in sleep duration among Chinese adults.Methods In this series of repeated nationally representative cross-sectional surveys(China Chronic Disease and Risk Factors Surveillance)conducted between 2010 and 2018,a total of 645,420 adult participants(97,741 in 2010;175,749 in 2013;187,777 in 2015;and 184,153 in 2018)were included in the trend analysis.Linear and logistic regression models were utilized to assess trends in sleep duration.Results In 2018,the estimated overall mean sleep duration among the Chinese adult population was7.58(SD,1.45)hours per day,with no significant trend from 2010.A significant increase in short sleep duration(≤6 hours)was observed in the total population,from 15.3%(95%CI:14.1%–16.5%)in 2010 to18.5%(95%CI:17.7%–19.3%)in 2018(P<0.001).Similarly,the trend in long sleep duration(>9 hours)was also significant,increasing in weighted prevalence from 7.2%(95%CI:6.3%–8.1%)in 2010 to 9.0%(95%CI:8.2%–9.9%)in 2018(P<0.001).Conclusion The prevalence of both short and long sleep durations significantly increased among Chinese adults from 2010 to 2018,highlighting the urgency of health initiatives to promote optimal sleep duration in China.展开更多
With the expansion of peanut planting area year by year,film mulching cultivation has become increasingly important in peanut production due to its unique advantages in enhancing both yield per unit area and overall e...With the expansion of peanut planting area year by year,film mulching cultivation has become increasingly important in peanut production due to its unique advantages in enhancing both yield per unit area and overall economic benefits.Based on the varietal characteristics of‘Zhouhua 5’and addressing practical issues in peanut production,this paper summarized key techniques for high-yield and high-efficiency film mulching cultivation of this variety.These techniques cover all critical stages,including land preparation and fertilization,seed preparation,sowing methods,field management,and timely harvesting,providing technical guidance for varietal promotion and peanut production.展开更多
Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating th...Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.展开更多
Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance ...Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.展开更多
We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In...We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In two complementary experiments,the use of photographs to estimate cross-sectional areas was first validated,then the use of a caliper and diameter tape was computer-simulated.The results indicated that the photographic method offers high precision,with mean relative errors below 0.1%,minimal deviation,and no significant bias,and the traditional methods led to substantial and systematic errors,with deviations from circularity and convexity significantly increasing the errors in area estimation.展开更多
Heat exchangers play a crucial role in thermal energy systems,with their performance directly impacting efficiency,cost,and environmental impact.Apowerful technique for performance improvement can be given by passive ...Heat exchangers play a crucial role in thermal energy systems,with their performance directly impacting efficiency,cost,and environmental impact.Apowerful technique for performance improvement can be given by passive enhancement strategies,which are characterized by their dependability and minimal external power requirements.This comprehensive review critically assesses recent advancements in such passive methods to evaluate their heat transfer mechanisms,performance characteristics,and practical implementation challenges.Our methodology involves a systematic and comprehensive analysis of various heat transfer enhancement techniques,including surface modifications,extended surfaces,swirl flow devices,and tube inserts.This approach synthesizes and integrates findings from a broad spectrum of experimental investigations and numerical simulations to establish a cohesive understanding of their performance characteristics and underlyingmechanisms.Based on the findings,passive heat transfer techniques result in significant improvements in thermal performance;for instance,corrugated and roughened surfaces increase the heat transfer coefficient by 50%–200%,and advanced insert geometries,such as modified twisted tapes,can increase it by more than 300%,typically accompanied by significant pressure-drop penalties.However,an important finding is the general trade-off between enhanced heat transfer and higher frictional loss,which requires optimization depending on the applications.Finally,this review also provides recommendations that will document the gaps of various passive techniques in heat exchangers to future address.展开更多
With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comp...With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.展开更多
Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao)...Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.展开更多
Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience...Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.展开更多
THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of...THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of the Yuan(1206-1368),Ming(1368-1644),and Qing(1616-1911)dynasties,and is still highly regarded to this day.展开更多
In-situ stress is a key parameter for underground mine design and rock stability analysis.The borehole overcoring technique is widely used for in-situ stress measurement,but the rheological recovery deformation of roc...In-situ stress is a key parameter for underground mine design and rock stability analysis.The borehole overcoring technique is widely used for in-situ stress measurement,but the rheological recovery deformation of rocks after stress relief introduces errors.To improve accuracy,this study proposes an in-situ stress solution theory that incorporates time-dependent stress relief effects.Triaxial stepwise loadingunloading rheological tests on granite and siltstone established quantitative relationships between instantaneous elastic recovery and viscoelastic recovery under different stress levels,confirming their impact on measurement accuracy.By integrating a dual-class elastic deformation recovery model,an improved in-situ stress solution theory was derived.Additionally,accounting for the nonlinear characteristics of rock masses,a determination method for time-dependent nonlinear mechanical parameters was proposed.Based on the CSIRO hollow inclusion strain cell,time-dependent strain correction equations and long-term confining pressure calibration equations were formulated.Finally,the proposed theory was successfully applied at one iron mine(736 m depth)in Xinjiang,China,and one coal mine(510 m depth)in Ningxia,China.Compared to classical theory,the calculated mean stress values showed accuracy improvements of 6.0%and 9.4%,respectively,validating the applicability and reliability of the proposed theory.展开更多
Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of suc...Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.展开更多
Objective The relationship between non-high-density lipoprotein(NHDL)cholesterol to high-density lipoprotein cholesterol(HDL-C)ratio(NHHR)and stoke remains unknown.This study aimed to evaluate the association between ...Objective The relationship between non-high-density lipoprotein(NHDL)cholesterol to high-density lipoprotein cholesterol(HDL-C)ratio(NHHR)and stoke remains unknown.This study aimed to evaluate the association between the adult NHHR and stroke occurrence in the United States of America(USA).Methods To clarify the relationship between the NHHR and stroke risk,this study used a multivariable logistic regression model and a restricted cubic spline(RCS)model to investigate the association between the NHHR and stroke,and data from the National Health and Nutrition Examination Survey(NHANES)from 2005 to 2018.Subgroup and sensitivity analyses were conducted to test the robustness of the results.Results This study included 29,928 adult participants,of which 1,165 participants had a history of stroke.Logistic regression analysis of variables demonstrated a positive association between NHHR and stroke(OR 1.24,95%CI:1.03-1.50,P=0.026).Compared with the lowest reference group of NHHR,participants in the second,third,and fourth quartile had a significantly increased risk of stroke after full adjustments(OR:1.35,95%CI:1.08-1.69)(OR:1.83,95%CI:1.42-2.36)(OR:2.04,95%CI:1.50-2.79).In the total population,a nonlinear dose-response relationship was observed between the NHHR and stroke risk(P non-linearity=0.002).This association remained significant in several subgroup analyses.Further investigation of the NHHR may enhance our understanding of stroke prevention and treatment.Conclusion Our findings suggest a positive correlation between the NHHR and an increased prevalence of stroke,potentially serving as a novel predictive factor for stroke.Timely intervention and management of the NHHR may effectively mitigate stroke occurrence.Prospective studies are required to validate this association and further explore the underlying biological mechanisms.展开更多
Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.T...Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.展开更多
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
Objectives:This study aimed to classify young breast cancer patients into distinct ambivalence over emotional expression and to explore the factors influencingthe level of ambivalence over emotional expression.Methods...Objectives:This study aimed to classify young breast cancer patients into distinct ambivalence over emotional expression and to explore the factors influencingthe level of ambivalence over emotional expression.Methods:A total of 217 young breast cancer patients were enrolled from a tertiary Grade A oncology hospital in Tianjin,China,using the convenience sampling method.All participants completed the general questionnaire,Ambivalence over Emotion Expression Questionnaire(AEQ),and Family Adapt-Ability and Cohesion Evaluation Scales-Chinese Version(FACES-CV).We employed exploratory latent profileanalysis for ambivalence over emotional expression profilingand logistic regression analysis to identify the influentialfactors Results:The results of the latent profileanalysis supported the models of four latent profiles,which were definedas“low conflict-lowexpression reflection”(19.2%),“high conflict-high inhibition expression”(43.9%),“moderate conflict-highregret expression”(18.1%),and“moderate conflict-desire understand”(18.8%).Logistic regression revealed that family cohesion,marital status,residence,per capita monthly income,and cancer stage were the influencingfactors of ambivalence over emotional expression in young breast cancer patients(P<0.05)Conclusions:Levels of ambivalence over emotional expression ameast cancer patients with breast cancer were highly heterogeneous.Medical staff should provide psychological counseling and health education tailored to the unique characteristics of emotional expression ambivalence in different patient groups to promote healthy emotional expression among patients.展开更多
OBJECTIVE:To investigate the difference in gut microbiota between population with damp-heat constitution(DHC)and balanced constitution(BC).METHODS:A multi-centered cross-sectional casecontrol study was conducted,which...OBJECTIVE:To investigate the difference in gut microbiota between population with damp-heat constitution(DHC)and balanced constitution(BC).METHODS:A multi-centered cross-sectional casecontrol study was conducted,which included 249 participants with damp-heat constitution or balanced constitution.Baseline information of participants was collected,and stool samples were collected for gut microbiota analysis.Principal coordinate analysis,linear discriminant analysis effect size analysis,receiver operating characteristic,random forest model,and phylogenetic investigation of communities by reconstruction of unobserved states methods were used to reveal the relationship between gut microbiota and the damp-heat constitution.RESULTS:Compared to those in the BC group,the richness and diversity of the microbiota,specifically those of several short-chain fatty acid producing genera such as Barnesiella,Coprobacter,and Butyricimonas,were significantly decreased in the DHC group.Regarding biological functions,flavonoid biosynthesis,propanoate metabolism,and nucleotide sugar metabolism were suppressed,while arachidonic acid metabolism and glutathione metabolism were enriched in the DHC group.Finally,a classifier based on the microbiota was constructed to discriminate between the DHC and BC populations.CONCLUSION:The gut microbiota of the DHC population exhibits significantly reduced diversity and is closely related to inflammation,metabolic disorders,and liver steatosis,which is consistent with clinical observations,thus serving as a potential diagnostic tool for traditional Chinese medicine constitution discrimination.展开更多
Objective:Postpartum nutrition plays a critical role in maternal recovery and long-term health.However,the nutritional status of working mothers in the postpartum period remains understudied.This study aimed to assess...Objective:Postpartum nutrition plays a critical role in maternal recovery and long-term health.However,the nutritional status of working mothers in the postpartum period remains understudied.This study aimed to assess the dietary quality of postpartum women in urban Beijing,identify occupational-related factors influencing their diet,and explore potential interventions to improve maternal nutrition during the postpartum period.Methods:In this cross-sectional analysis,554 women one year after delivery were recruited from ten community health centers.Sociodemographic,occupational and postpartum care variables were collected via questionnaire.Dietary intake over the preceding year was assessed using a food frequency questionnaire.The modified dietary balance index for postpartum women were used for dietary quality assessment.Results:The study revealed severe dietary imbalances among postpartum women,characterized by excessive consumption of cereals,eggs,and meats,while their intake of vegetables,fruits,and dairy products was inadequate.According to dietary balance index for postpartum women,66.25%of mothers showed varying degrees of excessive intake.45.31%of mothers experienced varying levels of insufficient intake,with only 19.86%of participants having a relatively balanced diet.Occupational differences were observed,with women in the commercial employment group showing higher levels of excessive food intake.The analysis of influencing factors showed that family monthly income,maternity leave,and postpartum care significantly affected the dietary quality.Conclusions:Postpartum women in Beijing experience widespread dietary imbalances,with both excesses and deficiencies.Occupational context and related factors significantly shape diet quality.These findings highlight the need for targeted nutritional interventions tailored to the specific challenges of different occupational groups.展开更多
文摘Objective:To assess prenatal Bisphenol A(BPA)exposure levels and explore their preliminary associations with maternal and fetal characteristics in a population from Northeastern Yunnan.Methods:A cross-sectional analysis was performed using data and urine samples from 70 pregnant women in their third trimester recruited at Qujing Central Hospital.Urinary BPA was measured by HPLC-MS/MS.Participants were stratified into high and low BPA exposure groups based on the median concentration.Results:BPA was detected in all samples(100%)with a median concentration of 2.41μg/L(IQR:0.68-4.96).The high BPA exposure group(≥2.41μg/L)had a significantly higher proportion of gestational diabetes mellitus(GDM)(42.9%vs.17.1%,p=0.021)and a lower median fetal birth weight(3250 g vs.3450 g,p=0.048)compared to the low exposure group.Conclusion:This pilot study reveals ubiquitous BPA exposure in pregnant women from Northeastern Yunnan.The observed preliminary associations with GDM and reduced fetal birth weight warrant further investigation in larger,longitudinal studies.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFB3710805).
文摘Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentration,and forming defects are prone to occur during their extrusion.This study focuses on an Al-Zn-Mg-Cu ultra-high-strength aluminum alloy profile with a double-U,multi-cavity thin-walled structure.Firstly,hot compression experiments were conducted at temperatures of 350○C,400○C,and 450○C,with strain rates of 0.01 and 1.0 s^(−1),to investigate the plastic deformation behavior of the material.Subsequently,a 3D coupled thermo-mechanical extrusion simulation model was established using Deform-3D to systematically analyze the influence of die structure and process parameters on metal flow velocity,effective stress/strain,and temperature distribution.The simulation revealed significant velocity differences,stress concentration,and uneven temperature distribution.Key parameters,including mesh density,extrusion ratio,die fillet,and bearing length,were optimized through full-factorial experiments.This optimization,combined with a stepped flow-guiding die design,effectively improved the metal flow pattern during extrusion.Trial production based on both the initial and optimized parameters were carried out.A comparative analysis demonstrates that the optimized scheme results in a final profile whose cross-section matches the target design closely,with complete filling of complex features and no obvious forming defects.This research provides a valuable reference for the extrusion process optimization and die design of complex-section profiles made from ultra-high-strength aluminum alloys.
基金supported by the National Natural Science Foundation of China(82341245,82371491)the Chinese Central Government(Key Project of Public Health Program)the National Key Research and Development Program of China(2018YFC1311706,2018YFC1311702)。
文摘Objective This study aimed to determine the temporal trends in sleep duration among Chinese adults.Methods In this series of repeated nationally representative cross-sectional surveys(China Chronic Disease and Risk Factors Surveillance)conducted between 2010 and 2018,a total of 645,420 adult participants(97,741 in 2010;175,749 in 2013;187,777 in 2015;and 184,153 in 2018)were included in the trend analysis.Linear and logistic regression models were utilized to assess trends in sleep duration.Results In 2018,the estimated overall mean sleep duration among the Chinese adult population was7.58(SD,1.45)hours per day,with no significant trend from 2010.A significant increase in short sleep duration(≤6 hours)was observed in the total population,from 15.3%(95%CI:14.1%–16.5%)in 2010 to18.5%(95%CI:17.7%–19.3%)in 2018(P<0.001).Similarly,the trend in long sleep duration(>9 hours)was also significant,increasing in weighted prevalence from 7.2%(95%CI:6.3%–8.1%)in 2010 to 9.0%(95%CI:8.2%–9.9%)in 2018(P<0.001).Conclusion The prevalence of both short and long sleep durations significantly increased among Chinese adults from 2010 to 2018,highlighting the urgency of health initiatives to promote optimal sleep duration in China.
基金Supported by Zhoukou Key Science and Technology Research Project(20200816).
文摘With the expansion of peanut planting area year by year,film mulching cultivation has become increasingly important in peanut production due to its unique advantages in enhancing both yield per unit area and overall economic benefits.Based on the varietal characteristics of‘Zhouhua 5’and addressing practical issues in peanut production,this paper summarized key techniques for high-yield and high-efficiency film mulching cultivation of this variety.These techniques cover all critical stages,including land preparation and fertilization,seed preparation,sowing methods,field management,and timely harvesting,providing technical guidance for varietal promotion and peanut production.
基金supported by Healthy China initiative of Traditional Chinese Medicine(No.889042).
文摘Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.
文摘Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.
文摘We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In two complementary experiments,the use of photographs to estimate cross-sectional areas was first validated,then the use of a caliper and diameter tape was computer-simulated.The results indicated that the photographic method offers high precision,with mean relative errors below 0.1%,minimal deviation,and no significant bias,and the traditional methods led to substantial and systematic errors,with deviations from circularity and convexity significantly increasing the errors in area estimation.
文摘Heat exchangers play a crucial role in thermal energy systems,with their performance directly impacting efficiency,cost,and environmental impact.Apowerful technique for performance improvement can be given by passive enhancement strategies,which are characterized by their dependability and minimal external power requirements.This comprehensive review critically assesses recent advancements in such passive methods to evaluate their heat transfer mechanisms,performance characteristics,and practical implementation challenges.Our methodology involves a systematic and comprehensive analysis of various heat transfer enhancement techniques,including surface modifications,extended surfaces,swirl flow devices,and tube inserts.This approach synthesizes and integrates findings from a broad spectrum of experimental investigations and numerical simulations to establish a cohesive understanding of their performance characteristics and underlyingmechanisms.Based on the findings,passive heat transfer techniques result in significant improvements in thermal performance;for instance,corrugated and roughened surfaces increase the heat transfer coefficient by 50%–200%,and advanced insert geometries,such as modified twisted tapes,can increase it by more than 300%,typically accompanied by significant pressure-drop penalties.However,an important finding is the general trade-off between enhanced heat transfer and higher frictional loss,which requires optimization depending on the applications.Finally,this review also provides recommendations that will document the gaps of various passive techniques in heat exchangers to future address.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2023-00235509Development of security monitoring technology based network behavior against encrypted cyber threats in ICT convergence environment).
文摘With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.
文摘Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.
基金supported by the National Natural Science Foundation of China,No.31760290,82160688the Key Development Areas Project of Ganzhou Science and Technology,No.2022B-SF9554(all to XL)。
文摘Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.
文摘THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of the Yuan(1206-1368),Ming(1368-1644),and Qing(1616-1911)dynasties,and is still highly regarded to this day.
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2024ZD1700201)the National Natural Science Foundation of China(Nos.U2034206,51974014 and 51574014)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2024A1515011631)the National Key Research and Development Project of China(No.2022YFC3004601)。
文摘In-situ stress is a key parameter for underground mine design and rock stability analysis.The borehole overcoring technique is widely used for in-situ stress measurement,but the rheological recovery deformation of rocks after stress relief introduces errors.To improve accuracy,this study proposes an in-situ stress solution theory that incorporates time-dependent stress relief effects.Triaxial stepwise loadingunloading rheological tests on granite and siltstone established quantitative relationships between instantaneous elastic recovery and viscoelastic recovery under different stress levels,confirming their impact on measurement accuracy.By integrating a dual-class elastic deformation recovery model,an improved in-situ stress solution theory was derived.Additionally,accounting for the nonlinear characteristics of rock masses,a determination method for time-dependent nonlinear mechanical parameters was proposed.Based on the CSIRO hollow inclusion strain cell,time-dependent strain correction equations and long-term confining pressure calibration equations were formulated.Finally,the proposed theory was successfully applied at one iron mine(736 m depth)in Xinjiang,China,and one coal mine(510 m depth)in Ningxia,China.Compared to classical theory,the calculated mean stress values showed accuracy improvements of 6.0%and 9.4%,respectively,validating the applicability and reliability of the proposed theory.
文摘Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.
文摘Objective The relationship between non-high-density lipoprotein(NHDL)cholesterol to high-density lipoprotein cholesterol(HDL-C)ratio(NHHR)and stoke remains unknown.This study aimed to evaluate the association between the adult NHHR and stroke occurrence in the United States of America(USA).Methods To clarify the relationship between the NHHR and stroke risk,this study used a multivariable logistic regression model and a restricted cubic spline(RCS)model to investigate the association between the NHHR and stroke,and data from the National Health and Nutrition Examination Survey(NHANES)from 2005 to 2018.Subgroup and sensitivity analyses were conducted to test the robustness of the results.Results This study included 29,928 adult participants,of which 1,165 participants had a history of stroke.Logistic regression analysis of variables demonstrated a positive association between NHHR and stroke(OR 1.24,95%CI:1.03-1.50,P=0.026).Compared with the lowest reference group of NHHR,participants in the second,third,and fourth quartile had a significantly increased risk of stroke after full adjustments(OR:1.35,95%CI:1.08-1.69)(OR:1.83,95%CI:1.42-2.36)(OR:2.04,95%CI:1.50-2.79).In the total population,a nonlinear dose-response relationship was observed between the NHHR and stroke risk(P non-linearity=0.002).This association remained significant in several subgroup analyses.Further investigation of the NHHR may enhance our understanding of stroke prevention and treatment.Conclusion Our findings suggest a positive correlation between the NHHR and an increased prevalence of stroke,potentially serving as a novel predictive factor for stroke.Timely intervention and management of the NHHR may effectively mitigate stroke occurrence.Prospective studies are required to validate this association and further explore the underlying biological mechanisms.
基金funded by the project of Guangdong Provincial Basic and Applied Basic Research Fund Committee(2022A1515240073)the Pearl River Talent Recruitment Program(2019CX01G338),Guangdong Province.
文摘Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金funded by Tianjin Key Medical Discipline(Specialty)Construction Project,China(Grant No.TJYXZDXK-011A)Tianjin Medical University Cancer Institute&Hospital Nursing Special Fund Project(H2304)。
文摘Objectives:This study aimed to classify young breast cancer patients into distinct ambivalence over emotional expression and to explore the factors influencingthe level of ambivalence over emotional expression.Methods:A total of 217 young breast cancer patients were enrolled from a tertiary Grade A oncology hospital in Tianjin,China,using the convenience sampling method.All participants completed the general questionnaire,Ambivalence over Emotion Expression Questionnaire(AEQ),and Family Adapt-Ability and Cohesion Evaluation Scales-Chinese Version(FACES-CV).We employed exploratory latent profileanalysis for ambivalence over emotional expression profilingand logistic regression analysis to identify the influentialfactors Results:The results of the latent profileanalysis supported the models of four latent profiles,which were definedas“low conflict-lowexpression reflection”(19.2%),“high conflict-high inhibition expression”(43.9%),“moderate conflict-highregret expression”(18.1%),and“moderate conflict-desire understand”(18.8%).Logistic regression revealed that family cohesion,marital status,residence,per capita monthly income,and cancer stage were the influencingfactors of ambivalence over emotional expression in young breast cancer patients(P<0.05)Conclusions:Levels of ambivalence over emotional expression ameast cancer patients with breast cancer were highly heterogeneous.Medical staff should provide psychological counseling and health education tailored to the unique characteristics of emotional expression ambivalence in different patient groups to promote healthy emotional expression among patients.
基金National Nonprofit Institute Research Grant for the Institute of Basic Theory for Chinese Medicine,China Academy of Chinese Medical Sciences:Mechanism of Regulating Phlegm-Dampness Constitution to Prevent Metabolic Diseases based on Gut Microbiota-host DNA Methylation(No.YZ-202151)。
文摘OBJECTIVE:To investigate the difference in gut microbiota between population with damp-heat constitution(DHC)and balanced constitution(BC).METHODS:A multi-centered cross-sectional casecontrol study was conducted,which included 249 participants with damp-heat constitution or balanced constitution.Baseline information of participants was collected,and stool samples were collected for gut microbiota analysis.Principal coordinate analysis,linear discriminant analysis effect size analysis,receiver operating characteristic,random forest model,and phylogenetic investigation of communities by reconstruction of unobserved states methods were used to reveal the relationship between gut microbiota and the damp-heat constitution.RESULTS:Compared to those in the BC group,the richness and diversity of the microbiota,specifically those of several short-chain fatty acid producing genera such as Barnesiella,Coprobacter,and Butyricimonas,were significantly decreased in the DHC group.Regarding biological functions,flavonoid biosynthesis,propanoate metabolism,and nucleotide sugar metabolism were suppressed,while arachidonic acid metabolism and glutathione metabolism were enriched in the DHC group.Finally,a classifier based on the microbiota was constructed to discriminate between the DHC and BC populations.CONCLUSION:The gut microbiota of the DHC population exhibits significantly reduced diversity and is closely related to inflammation,metabolic disorders,and liver steatosis,which is consistent with clinical observations,thus serving as a potential diagnostic tool for traditional Chinese medicine constitution discrimination.
基金supported by an Innovation Fund for Medical Sciences of the Chinese Academy of Medical Sciences (Grant No.2019-I2M-2-007).
文摘Objective:Postpartum nutrition plays a critical role in maternal recovery and long-term health.However,the nutritional status of working mothers in the postpartum period remains understudied.This study aimed to assess the dietary quality of postpartum women in urban Beijing,identify occupational-related factors influencing their diet,and explore potential interventions to improve maternal nutrition during the postpartum period.Methods:In this cross-sectional analysis,554 women one year after delivery were recruited from ten community health centers.Sociodemographic,occupational and postpartum care variables were collected via questionnaire.Dietary intake over the preceding year was assessed using a food frequency questionnaire.The modified dietary balance index for postpartum women were used for dietary quality assessment.Results:The study revealed severe dietary imbalances among postpartum women,characterized by excessive consumption of cereals,eggs,and meats,while their intake of vegetables,fruits,and dairy products was inadequate.According to dietary balance index for postpartum women,66.25%of mothers showed varying degrees of excessive intake.45.31%of mothers experienced varying levels of insufficient intake,with only 19.86%of participants having a relatively balanced diet.Occupational differences were observed,with women in the commercial employment group showing higher levels of excessive food intake.The analysis of influencing factors showed that family monthly income,maternity leave,and postpartum care significantly affected the dietary quality.Conclusions:Postpartum women in Beijing experience widespread dietary imbalances,with both excesses and deficiencies.Occupational context and related factors significantly shape diet quality.These findings highlight the need for targeted nutritional interventions tailored to the specific challenges of different occupational groups.
