Exercise, as a non-pharmacological intervention, holds a pivotal role in metabolic regulation, neuroplasticity, and immune homeostasis maintenance. However, human exercise studies are constrained by ethical limitations in tissue sampling, especially for key organs such as muscles and the brain. Meanwhile, rodent models like mice exhibit physiological differences in exercise patterns and metabolic rates from human. Despite these challenges, approximately 70% of human and mouse genes are conserved, providing a molecular basis for cross-species comparisons. This paper leverages the GEPREP database, which integrates human and mouse exercise transcriptomic data from multiple platforms, to conduct a comprehensive cross-species analysis of exercise-induced gene expression patterns. We employ a stringent data standardization process, including the conversion of orthologous genes and the filtering of low-expressing genes, to ensure the accuracy and reliability of the analysis. A mixed-effects model is utilized to assess differential gene expression across multiple cohorts, identifying genes that are significantly upregulated or downregulated in response to exercise. The analysis reveals a complex pattern of gene expression, with a significant number of genes showing conserved responses between humans and mice, particularly in acute aerobic exercise, where genes such as ATF3, PPARGC1A, and ANKRD1 are commonly upregulated. These genes are implicated in muscle stress response, metabolic regulation, and muscle adaptation, highlighting the shared molecular pathways activated by exercise across species. However, the study also uncovers substantial species-specific differences in gene expression, especially in chronic aerobic exercise, where the number of divergently regulated genes increases. These differences suggest that while some fundamental biological processes are conserved, the specific regulatory mechanisms and gene expression patterns can vary significantly between humans and mice. Functional enrichment analysis further reveals that conserved genes are involved in muscle development, inflammation regulation, and energy metabolism, while species-specific genes are associated with ion transport, extracellular matrix (ECM) organization, and muscle contraction, indicating the multifaceted impact of exercise on skeletal muscle function. The findings emphasize the importance of considering species-specific differences when interpreting results from animal models and translating them to human health applications. The study highlights the need for a more nuanced understanding of the molecular underpinnings of exercise-induced adaptations and underscores the value of cross-species comparative analyses in uncovering the evolutionary and functional basis of these responses. Future research should focus on integrating multi-omics data and expanding the analysis to include other tissues to provide a more comprehensive view of the systemic effects of exercise. Additionally, the development of species-specific gene editing models and the validation of key genes in exercise physiology will further enhance our understanding of the evolutionary logic behind exercise interventions. This study not only provides valuable insights into the molecular mechanisms of exercise-induced adaptations but also underscores the necessity of validating findings from animal models in human cohorts to ensure the reliability and applicability of translational research in exercise science. By addressing these aspects, the study aims to bridge the gap between basic research and clinical applications, ultimately contributing to the development of personalized exercise prescriptions and interventions that can effectively promote health and prevent diseases.

ObjectiveThe scale of microalgae farming industry is huge. During farming, it is easy for microalgae to be affected by miscellaneous bacteria and other contaminants. Because of that, periodic test is necessary to ensure the growth of microalgae. Present microscopy imaging and spectral analysis methods have higher requirements for experiment personnel, equipment and sites, for which it is unable to achieve real-time portable detection. For the purpose of real-time portable microalgae detection, a real-time microalgae detection system of low detection requirement and fast detection speed is needed. MethodsThis study has developed a microalgae detection system based on deep learning. A microscopy imaging device based on bright field was constructed. With imaged captured from the device, a neural network based on YOLOv3 was trained and deployed on microcomputer, thus realizing real-time portable microalgae detection. This study has also improved the feature extraction network by introducing cross-region residual connection and attention mechanism and replacing optimizer with Adam optimizer using multistage and multimethod strategy. ResultsWith cross-region residual connection, the mAP value reached 0.92. Compared with manual result, the detection error was 2.47%. ConclusionThe system could achieve real-time portable microalgae detection and provide relatively accurate detection result, so it can be applied to periodic test in microalgae farming.

Objective:To explore the application value of different nutritional screening tools in the evaluation of preoperative malnutrition assessment of Crohn's patients. Methods:Using the convenient sampling method, a retrospective analysis was conducted on CD patients who underwent elective surgery at the general surgery department of General Hospital of Eastern Theater Command from January 2021 to March 2022. The preoperative nutritional status of the patients was understood. Taking the consensus on malnutrition assessment diagnosis standards (GLIM) as the gold standard. The correlation, difference and diagnostic efficacy of 3 nutritional risk screening tools were compared. Results:A total of 212 patients were included. Using GLIM as the diagnostic standard, 131 patients (61.79％) had malnutrition. The incidence of malnutrition risk was 66.03％, 85.38％ and 55.66％ using NRS 2002 score, NS IBD score and PNI score, respectively. The sensitivities of the above three scores in the preoperative nutritional screening of IBD patients were 81.46％, 85.48％, 79.63％, respectively; the specificity were 62.36％, 54.71％, 57.12％, respectively; and the areas under the curve were 0.749, 0.763, 0.831, respectively. In the evaluation of diagnostic efficacy, NS IBD score had the highest sensitivity, and NRS 2002 had the best specificity. Conclusion:For patients with Crohn's disease undergoing elective surgery, the three nutritional risk screening tools can provide a basis for malnutrition risk screening. The items of PNI score are objective, concise, and convenient. As for the evaluation of diagnostic efficacy, the NS IBD score has the highest sensitivity and the NRS 2002 has the best specificity.

Sarcopenia is a syndrome associated with decreased muscle mass,decreased muscle strength,and reduced physical performance. Due to multiple factors such as tumor metabolism,systemic inflammatory response,disease progression,and reduced physical activity associated with treatment itself,the risk of sarcopenia in patients with lung cancer is higher than that of the general population. Sarcopenia is closely related to the clinical outcomes,including increased risk for mortality,and significantly impacts patients' long-term quality of life and mental health. This study systematic reviewed the risk factors for sarcopenia in patients with lung cancer,its negative effects on clinical outcomes,long-term quality of life and mental health,and the interventions for sarcopenia. Given the significant impact of sarcopenia on patients with lung cancer,it is urgent to explore a multidisciplinary intervention model to improve their survival and quality of life.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective To compare the early predictive value of different scoring systems for the severity,organ failure and complications of acute pancreatitis(AP)in elderly patients under the newly revised Atlanta criteria.Methods Patients with acute pancreatitis treated was collected.After admission,complete the computed tomography severity index(CTSI),the bedside index of severity in acute pancreatitis(BISAP),the pancreatis 3(PANC-3)and the harmlessness acute pancreatitis score(HAPS).The area under receiver operating characteristic(ROC)curve(AUC),sensitivity,specificity and Yordan's index of four scores for predicting SAP,local pancreatic complications and multiple organ failure were compared.Results The areas under the ROC curve predicted by the CTSI,BISAP,PANC-3 and HAPS scoring systems for SAP were 0.76,0.91,0.48 and 0.55;sensitivities of 75.87％,89.61％,61.18％and 78.38％;specificity of 80.29％,74.72％,67.48％and 69.69％;Yordan's index of 0.56,0.64,0.29 and 0.48,respectively.The AUC of CTSI,BISAP,PANC-3 and HAPS scoring systems for predicting local pancreatic complications were 0.94,0.82,0.59 and 0.64;sensitivity of 74.59％,68.23％,71.11％and 69.28％;specificity of 93.88％,83.01％,78.59％and 76.46％;Yordan's index were 0.68,0.51,0.50 and 0.46,respectively.The AUC of CTSI,BISAP,PANC-3 and HAPS scoring systems for predicting multiple organ failure were 0.60,0.84,0.64 and 0.80,sensitivities were 54.18％,74.82％,58.59％and 65.67％,specificity were 76.11％,77.20％,72.68％and 89.36％,Jordan's indices were 0.30,0.52,0.31 and 0.55,respectively.Conclusion BISAP score is higher than CTSI,HAPS and PANC-3 scoring system in predicting the accuracy of sap and the risk of multiple organ failure.

The post-translational modification of proteins is a key mechanism that imparts physiological functions to proteins,among which reversible phosphorylation modifications play a pivotal role in many biological processes.Aberrant changes in phosphorylation are often closely associated with various major disease processes.In recent years,with the aid of proteomic technologies and methods,high-throughput,high-precision qualitative and quantitative approaches for phosphorylated proteins have rapidly advanced.This article reviews the research progress of phosphorylated protein quantification and chemical proteomics analysis methods based on the"bottom-up"strategy,including phosphopeptide enrichment methods,mass spectrometry fragmentation methods,quantification analysis methods and phosphorylation site stoichiometry,and discusses the development trend of quantification and stoichiometric analysis methods for phosphorylated proteins.

Objective:To establish a prediction method of diopter based on sequence of ocular biological parameters.Methods:A stratified random cluster sampling method was used to extract the dataset. The dataset consisted of data collected from January 2022 to January 2023 by the Eye & ENT Hospital, Fudan University, from children aged 5 to 13 years in 2 key schools and 2 general schools of Yangpu District, Shanghai. Children’s ocular biological parameters, including sex, age, diopter, axial length, corneal curvature, and anterior chamber depth were collected. The slope of the optimally fitted straight line was calculated using the least squares method. The least square-back propagation (BP) neural network model was established by combining baseline data and the pre-processed rate of the change of ocular biological parameters. The dataset was divided into the training set and the validation set according to the ratio of 8:2 for five-fold cross-validation. The model performance was evaluated by using the mean absolute error (MAE), mean squared error (MSE), root mean square error (RMSE), correlation coefficient R, and coefficient of determination R2. Results:The optimal performances of R2, R, RMSE, MAE, and MSE of the least square-BP neural network model were 0.96, 0.981 9, 0.214 2, 0.139 9 D, 0.045 9, respectively. The regression equation between the predicted value and the true value of the diopter was y=0.97 x+ 0.014 8, R2=0.97, with good correlation. In the internal verification, MAE values of the diopter at three, six, nine, and twelve months of follow-up were 0.110 1, 0.136 0, 0.153 7, and 0.184 8 D, respectively, which achieved clinically acceptable performance (less than 0.25 D). In the external validation, the errors were less than 0.25 D at all ages. Conclusions:A prediction method of diopter based on sequence of ocular biological parameters was successfully developed.

Ferroptosis is a new type of programmed cell death different from apoptosis and necrosis.Its mechanism involves iron overload,lipid peroxidation,and reactive oxygen species(ROS)generation caused by disordered iron metabolism.Ferroptosis is associated with primary osteoporosis as well as the secondary osteoporosis such as steroid-induced osteoporosis,diabetic osteoporosis and postmenopausal osteoporosis.The Chinese medicines for the prevention and treatment of osteoporosis through the mechanism of ferroptosis mainly involve Chinese herbal compounds such as herbal pair of Eucommiae Cortex-Dipsaci Radix,Jintiange Capsules,and Bugu Shengsui Prescription,the single Chinese herbal medicine of Achyranthis Bidentatae Radix,and the active ingredients of herbal medicines such as icariin,gastrodin,quercetin,and artesunate.The prevention and treatment of osteoporosis by Chinese medicine monomer and Chinese herbal compound can inhibit ferroptosis through multiple targets and multiple pathways.At present,Chinese medicine has advantages in the prevention and treatment of postmenopausal osteoporosis.The prevention and treatment of osteoporosis by regulating the mechanism of ferroptosis can provide a direction for the future research on the prevention and treatment of osteoporosis by Chinese medicine.

Exertional heat stroke(EHS)is the most serious and life-threatening acute heat-related illness.It can develop from heat-related illnesses,and the prehospital management is a crucial in the diagnosis and treatment of EHS.The prognosis of EHS patients is largely determined by the rapid recognition,effective cooling,and standardized transportation during the prehospital period.Extensive research has demonstrated that medical security personnel still have fatal misconceptions in the prehospital recognition and management of EHS,mainly due to the lack of recognition and inappropriate treatment.This review summarizes the top 10 misconceptions in prehospital recognition and management of EHS,based on domestic and international research findings and combined with practical scenarios.It also provides an accurate prehospital management plan according to the China Expert Consensus on Diagnosis and Treatment of Heatstroke,aiming to reduce or avoid irreversible damage to EHS patients caused by these misunderstandings and to decrease the incidence,disability rate,and mortality rate of EHS.