“Runner’s high” refers to a momentary sense of pleasure that suddenly appears during running or other exercise activities, characterized by anti-anxiety, pain relief, and other symptoms. The neurobiological mechanism of “runner’s high” is unclear. This review summarizes human and animal models for studying “runner’s high”, analyzes the neurotransmitters and neural circuits involved in runner’s high, and elucidates the evidence and shortcomings of researches related to “runner’s high”. This review also provides prospects for future research. Research has found that exercise lasting more than 30 min and with an intensity exceeding 70% of the maximum heart rate can reach a “runner’s high”. Human experiments on “runner’s high” mostly use treadmill exercise intervention, and evaluate it through questionnaire surveys, measurement of plasma AEA, miRNA and other indicators. Animal experiments often use voluntary wheel running intervention, and evaluate it through behavioral experiments such as conditional place preference, light dark box experiments (anxiety), hot plate experiments (pain sensitivity), and measurement of plasma AEA and other indicators. Dopamine, endogenous opioid peptides, endogenous cannabinoids, brain-derived neurotrophic factor, and other substances increase after exercise, which may be related to the “runner’s high”. However, attention should be paid to the functional differences of these substances in the central and peripheral regions, as well as in different brain regions. Moreover, current studies have not identified the targets of the neurotransmitters or neural factors mentioned above, and further in-depth researches are needed. The mesolimbic dopamine system, prefrontal cortex-nucleus accumbens projection, ventral hippocampus-nucleus accumbens projection, red nucleus-ventral tegmental area projection, cerebellar-ventral tegmental area projection, and brain-gut axis may be involved in the regulation of runner’s high, but there is a lack of direct evidence to prove their involvement. There are still many issues that need to be addressed in the research on the neurobiological mechanisms of “runner’s high”. (1) Most studies on “runner’s high” involve one-time exercise, and the characteristics of changes in “runner’s high” during long-term exercise still need to be explored. (2) The using of scales to evaluate subjects lead to the lacking of objective indicators. However, some potential biomarkers (such as endocannabinoids) have inconsistent characteristics of changes after one-time and long-term exercise. (3) The neurotransmitters involved in the formation of the “runner’s high” all increase in the peripheral and/or central nervous system after exercise. Attention should be paid to whether peripheral substances can enter the blood-brain barrier and the binding effects of neurotransmitters to different receptors are completely different in different brain regions. (4) Most of the current evidence show that some brain regions are activated after exercise. Is there a functional circuit mediating “runner’s high” between these brain regions? (5) Although training at a specific exercise intensity can lead to “runner’s high”, most runners have not experienced “runner’s high”. Can more scientific training methods or technological means be used to make it easier for people to experience the “runner’s high” and thus be more willing to engage in exercise? (6) The “runner’s high” and “addiction” behaviors are extremely similar, and there are evidences that exercise can reverse addictive behaviors. However, why is there still a considerable number of people in the sports population and even athletes who smoke or use addictive drugs instead of pursuing the “pleasure” brought by exercise? Solving the problems above is of great significance for enhancing the desire of exercise, improving the clinical application of neurological and psychiatric diseases through exercise, and enhancing the overall physical fitness of the population.

Over the past three decades， China has made significant progress in the prevention and control of viral hepatitis， and the incidence rates of new-onset pediatric hepatitis B virus infections and acute viral hepatitis in the population have reduced to a relatively low level； however， there is still a heavy disease burden of chronic viral hepatitis in China， which severely affects the health status of the population. This study systematically summarizes the achievements of viral hepatitis prevention and control in China， analyzes existing problems and challenges， and proposes comprehensive prevention and control strategies and measures to eliminate viral hepatitis as a public health threat based on the national conditions of China， in order to provide a reference for related departments in China on how to achieve the action targets for eliminating viral hepatitis as a public health threat by 2030.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.

Objective: To explore the relationship between depressive symptoms, negative life events and resilience among primary and secondary school teachers, so as to provide a reference for mental health promotion in school teachers. Methods: During November to December 2022, a questionnaire survey was conducted using convenient cluster sampling method to select 11 332 in service teachers from 38 schools in 8 provinces (cities) including Beijing, Guangdong, Anhui, Hubei, Sichuan, Xinjiang, Liaoning, and Heilongjiang. The Patient Health Questionnaire-9 items, a self developed 21-item Adverse Life Events questionnaire, and a 10-item Conner-Davidson Resilience Scale were used to assess depressive symptoms, experiences of negative life events, and resilience levels of the teachers, respectively. The relationship between depressive symptoms, negative life events and psychological resilience were analyzed by multiple linear regression and stratified regression. Results: The detection rate of depressive symptoms among primary and secondary school teachers was 14.0%. Negative life events of primary and secondary school teachers were positively correlated with depressive symptoms ( r =0.35), while psychological resilience was negatively correlated with depressive symptoms ( r =-0.45) ( P <0.05). After adjusting for possible covariates including gender and marital status, negative life events were positively correlated with depressive symptoms ( β=0.22, P <0.01). Resilience played a moderating role in the association of negative life events with depressive symptoms among primary and secondary school teachers ( B=-0.15, P <0.01). Conclusions Negative life events experiences are associated with higher level of depressive symptoms among school teachers. However, resilience might mitigate the negative effects of negative life events on depressive symptoms, playing a protective role in teachers mental health.

Animals ; Macaca mulatta ; Optic Disk ; Glaucoma ; Craniocerebral Trauma ; Intraocular Pressure ; Low Tension Glaucoma

Objective To explore the relationship and internal path between activities of daily living(ADL),sleep quality and mental health of community elderly people in Shanghai.Methods A questionnaire survey was conducted among community residents aged 60 years and older seeing doctors in community health care center of five streets in Shanghai during Sept to Dec,2021 using convenience sampling.Activities of Daily Living(ADL),Pittsburgh Sleep Quality Index(PSQI)and 10-item Kessler Psychological Distress Scale(K10)were adopted in the survey.Single factor analysis,correlation analysis and multiple linear regression were used to analyze the data.The effect relationship between the variables was tested using Bootstrap's mediated effects test.Results A total of 1 864 participants were included in the study.The average score was 15.53±4.47 for ADL,5.60±3.71 for PSQI and 15.50±6.28 for K10.The rate of ADL impairment,poor sleep quality,poor and very poor mental health of the elderly were 23.6%,27.3%,11.9%and 4.9%,respectively.ADL and sleep quality were all positively correlated with mental health(r=0.321,P＜0.001;r=0.466,P＜0.001);ADL was positively correlated with sleep quality(r=0.294,P＜0.001).Multiple linear results of factors influencing mental health showed that ADL(β= 0.457,95%CI:0.341-0.573),sleep quality(β =0.667,95%CI:0.598-0.737)and mental health were positively correlated(P＜0.001).Sleep quality partially mediated the relationship between ADL and mental health(95%CI:0.078-0.124)with an effect size of 33.0%.Conclusion Sleep quality is a mediator between ADL and mental health among community elderly people.Improving ADL and sleep quality may improve mental health in the population.

Objective To investigate the relationship between insomnia,gastrointestinal symptoms,and glycosylated hemoglobin(HbA1c)levels in individuals diagnosed with type 2 diabetes mellitus(T2DM),as well as the related influencing factors.Methods A total of 910 T2DM patients treated in our multicenter from January 2022 to December 2022 were enrolled in this study.General information(gender,age,smoking and drinking history,exercise,course of disease,treatment and complications),HbA1c,Athens Insomnia Scale(AIS)scores and Gastrointestinal Symptoms Rating Scale(GSRS)scores of patients were collected.The differences of sleep and gastrointestinal symptoms between groups were analyzed,and the correlation between the differences and HbA1c was analyzed.Furthermore,the risk factors for non-standard HbA1c were analyzed.Results The AIS score and GSRS score in the HbA1c control group were less than those in the non-standard group(P＜0.01).Insomnia was reported by 37.0％of T2DM patients,and the HbA1c level in the insomnia group was significantly higher than that in the non-insomnia group(10.00％±2.38％vs.8.26％±1.73％,P＜0.01).Gastrointestinal symptoms were present in 57.5％of T2DM patients,and the HbA1c levels in the group with gastrointestinal symptoms were significantly higher than those in the group without gastrointestinal symptoms(9.26％±2.23％vs.8.43％±1.98％,P＜0.01).Furthermore,26.3％of T2DM patients experienced both insomnia and gastrointestinal symptoms.Remarkably,the HbA1c levels in the group with both insomnia and gastrointestinal symptoms were significantly higher than those in the group without either condition(10.18％±2.44％vs.8.45％±1.86％,P＜0.01).Correlation analysis demonstrated a significant association between sleep quality,gastrointestinal function,and HbA1c levels(P＜0.01).The logistic regression analysis result revealed that age,GSRS score,AIS score,and the presence of insomnia combined with gastrointestinal symptoms were independent risk factors for predicting HbA1c≥6.5％(P＜0.01).Having both insomnia and gastrointestinal symptoms concurrently was the strongest risk factor for substandard HbA1c control,and the risk of blood sugar control may increase about 5 times when both appear together.Conclusion Insomnia and gastrointestinal symptoms are common comorbidities in T2DM patients,showing a cross-interfering relationship,and they appear together with poor blood sugar control,interact causally,and amplify each other.

Objective To study the mechanism of polyene phosphatidylcholine in improving metabolic disorders and fatty liver induced by high fat diet.Methods Thirty-two C57BL/6 mice were randomly divided into blank group,control group,model group and experimental group.The blank group was fed with low-fat diet and intraperitoneal injection of 10％glucose 200 μL twice a week.Control group was fed with low-fat diet twice a week and intraperitoneally injected 10％glucose solution 200 μL containing polyene phosphatidylcholine(PPC)20 μg.Model group was fed with high-fat diet and intraperitoneal injection of 10％glucose 200 μL twice a week.Experimental group was fed with high-fat diet twice a week and intraperitoneally injected 10％glucose solution 200 μL containing PPC 20 μg.The body weight of the mice was measured,blood glucose test strips and insulin resistance was analyzed.The levels of triglyceride(TG),high density lipoprotein(HDL),low density lipoprotein(LDL),glutamic oxalic aminotransferase(GOT)and glutamic pyruvic aminotransferase(GPT)in serum and liver were analyzed by biochemical method.The levels of tumor necrosis factor-α(TNF-α),interleukin-6 and IL-8 were detected by enzyme-linked immunosorbent assay(ELISA).Results The serum TG levels of blank group,control group,model group and experimental group were(0.15±0.01),(0.11±0.01),(0.21±0.01)and(0.12±0.01)mmol·L-1;LDL levels were(0.41±0.01),(0.25±0.01),(0.71±0.02)and(0.49±0.01)mmol·L-1;GOT levels were(30.30±0.89),(31.39±1.18),(43.04±2.82)and(25.64±0.72)mmol·L-1;GPT levels were(9.15±0.45),(7.39±1.88),(12.87±1.81)and(7.96±1.64)mmol·L-1;fasting blood glucose levels were(4.97±0.08),(6.08±0.18),(8.12±0.20)and(7.29±0.02)mmol·L-1;fasting insulin levels were(6.52±1.11),(5.45±0.28),(54.83±4.32)and(30.55±2.73)mU·L-1;the levels of TNF-α in liver tissues were(3.98±0.63),(3.95±0.98),(20.55±4.71)and(15.28±1.73)pg·g-1;IL-6 levels were(18.93±8.56),(17.64±3.29),(59.40±4.63)and(37.54±7.33)pg·g-1;IL-8 levels were(67.16±12.37),(59.44±3.58),(198.40±9.27)and(132.10±7.04)pg·g-1.The difference of above indicatory between experimental group and model group was statistically significant(all P＜0.05).Conclusion Polyene phosphatidylcholine may inhibit the expression of TNF-α,IL-6 and IL-8 inflammatory factors by mediating the inhibition of inflammation on liver tissue and then improve metabolic disorders.

Inflammasome is a kind of intracellular polyprotein complex,which is an important component of the complex system of local inflammatory microenvironment after human tissue damage.When the inflammasome is activated,it induces the activation of cysteine aspartate proteinase 1(caspase-1),mediates the maturation and secretion of proinflammatory cytokines,such as interleukin(IL)-1 β and IL-18,and induces cell death,which plays an important role in regulating the host immune response to pathogen infection and tissue repair of cell damage.Nod-like receptor protein 3(NLRP3)inflammatory body,which is composed of NLRP3,pro-cysteine aspartic acid specific protease-1(pro-caspase-1)and apoptosis-related spot-like protein(ASC),is the most deeply and widely studied type of inflammatory body,which plays an important role in the regulation of inflammation.When NLRP3 inflammatory bodies are activated,inflammatory mediators are produced and released,which participate in the occurrence and development of a variety of inflammatory diseases.Some studies have shown that traditional Chinese medicine can improve the pathological state of a variety of diseases by inhibiting NLRP3 inflammatory bodies,and play a role in the prevention and treatment of a variety of inflammatory diseases,including cardiovascular diseases,joint inflammation,diabetes and so on.This paper systematically combs the mechanism of NLRP3 inflammatory bodies,and summarizes the latest research reports on the effects of traditional Chinese medicine compound prescription,traditional Chinese medicine monomers and traditional Chinese medicine extracts on NLRP3 inflammatory bodies in the treatment of inflammatory diseases,in order to provide new ideas for the further study of the pathogenesis and drug treatment of many inflammatory diseases.