Objective To investigate the post-discharge exercise behavior and factors influencing moderate to vigorous intensity physical activity (MVPA) in patients undergoing lung surgery. Methods A total of 2874 patients from the large prospective, observational perioperative lung symptom study cohort (CN-PRO-Lung 3) in the Department of Thoracic Surgery at Sichuan Cancer Hospital between April 7, 2021, and January 31, 2024, were selected as the survey subjects. A survey was conducted using the Investigation of Exercise Behavior after Lung Surgery questionnaire and the International Physical Activity Questionnaire-Short Form (IPAQ-SF) among patients who underwent lung surgery. Binary logistic regression was used to analyze the factors influencing patients’ engagement in MVPA. Results A total of 702 patients were surveyed, including 252 males and 450 females, with an average age of (52.4±10.2) years. Patients with lung cancer accounted for 85.9%. Only 36.0% of the patients had regular exercise habits, while 42.3% did not engage in any physical activity. The three main barriers for postoperative exercise were physical discomfort (pain, coughing, shortness of breath, etc, 54.7%), lack of professional guidance (41.7%), and concerns about the surgical wound (28.9%). The proportions of patients engaging in vigorous, moderate, and low-intensity physical activity were 5.7%, 28.2%, and 66.1%, respectively. Multivariate analysis showed that patients with a personal annual income ≥50000 yuan (OR=1.52, 95%CI 1.01-2.29, P=0.044), high school education or above (OR=1.92, 95%CI 1.33-2.76, P<0.001), and lobectomy (OR=1.44, 95%CI 1.02-2.03, P=0.037) engaged in more MVPA. Conclusion Patients undergoing lung surgery have inadequate physical activity after discharge, particularly lacking in MVPA. Patients with higher income, higher educational levels, and lobectomy are more frequently engaged in MVPA. Measures such as symptom control, providing exercise guidance, and enhancing education on wound care may potentially improve the inadequate physical activity in lung surgery patients after discharge.

Objective: The efficacy of antidepressants is influenced by a combination of genetic, individual, and environmental factors. This study aimed to investigate the association between the miR-182 rs76481776 polymorphism and the response to antidepressant treatment in major depressive disorder (MDD) patients, and its underlying molecular mechanisms. Methods: This study enrolled 180 MDD patients and 180 healthy controls. The rs76481776 genotype was determined using TaqMan-based qPCR. The severity of depression and treatment response were assessed using the Hamilton Depression Rating Scale (HAMD). The expression of miR-182 and BDNF was measured using RT-qPCR. The regulatory relationship between miR-182 and BDNF was confirmed through a luciferase reporter gene assay. The correlation between miR-182 and BDNF expression was evaluated using the Pearson correlation coefficient. Results: The T allele of rs76481776 was a significant risk factor for MDD (OR = 2.182, 95% CI: 1.424−3.345, p ＜ 0.001) and was significantly associated with higher baseline scores on the HAMD. Moreover, individuals carrying the T allele (CT/TT genotype) exhibited a significantly poorer response to antidepressant treatment and a lower remission rate within 12 months compared to those with the CC genotype (p ＜ 0.05). Mechanistically, miR-182 was highly expressed in patients with MDD (p ＜ 0.05), and its expression was even higher in T allele carriers (p ＜ 0.05). miR-182 could directly target and suppress BDNF, leading to decreased BDNF expression in MDD patients, and its expression was significantly and inversely correlated with BDNF expression. Conclusion The T allele of rs76481776 diminished the therapeutic efficacy of antidepressants by up-regulating miR-182 expression and subsequently suppressing BDNF expression.

Objective To explore the association between serum uric acid levels and the cumulative incidence risk of atrial fibrillation, and to evaluate the predictive value of different uric acid levels for the onset of atrial fibrillation. Methods A retrospective selection of 451 879 participants from the large-scale prospective epidemiological cohort UK Biobank, aged 40-69 years, all completed a median follow-up of 13.6 years. Participants were divided into groups based on the interquartile range of serum uric acid levels (Q1–Q4) related to gender and whether they were diagnosed with hyperuricemia. Cox proportional hazards model, sensitivity analysis, and other methods were used to compare baseline data and atrial fibrillation incidence during follow-up among each group of participants. Results Individuals with higher baseline uric acid levels tended to be older, more obese, and had lower education levels and a history of cancer, along with significantly higher levels of triglyceride, low-density lipoprotein cholesterol, and C-reactive protein, but lower high-density lipoprotein cholesterol levels (P<0.001); the highest uric acid group showed the highest diabetes prevalence (6.49%). Participants with higher serum uric acid levels (log-rank P<0.05) or diagnosed with hyperuricemia had significantly higher incidence of atrial fibrillation (P<0.001). After adjusting for potential confounders, compared to Q1 uric acid level group, the Q4 level was associated with a 20% increased risk of atrial fibrillation (HR=1.20, 95%CI 1.16–1.25). Each 74.7 μmol/L increase in uric acid level was associated with a 9% increased incidence risk of atrial fibrillation (HR=1.09, 95%CI 1.08–1.11). Individuals with hyperuricemia had a 20% increased incidence risk of atrial fibrillation (HR=1.20, 95%CI 1.17–1.24). A nonlinear association was observed between uric acid levels and the incidence risk of atrial fibrillation (P for nonlinearity <0.01). Subgroup analysis indicated significant heterogeneity of the risk effect across subgroups, with a higher risk associated with hyperuricemia in females. Conclusions Elevated blood uric acid levels may increase the cumulative risk of atrial fibrillation, and this pathogenic effect is significantly correlated with age, race, cancer history, body mass index, and sex.

Objective: To investigate the urban and rural differences in adverse outcomes of pulmonary tuberculosis (PTB) in patients with pulmonary tuberculosis-diabetes mellitus comorbidity (PTB-DM), so as to provide insights into improving the prevention and treatment measures for PTB-DM. Methods: Patients with PTB-DM who were admitted and discharged from 14 designated tuberculosis hospitals in Hangzhou City from 2018 to 2022 were selected. Basic information, and history of diagnosis and treatment were collected through hospital information systems. The adverse outcomes of PTB were defined as endpoints, and the proportions of adverse outcomes of PTB in urban and rural patients with PTB-DM were analyzed. Factors affecting the adverse outcomes of PTB were identified using a multivariable Cox proportional hazards regression model. Results: A total of 823 patients with PTB-DM were enrolled, including 354 (43.01%) urban and 469 (56.99%) rural patients. There were 112 (13.61%) patients with adverse outcomes of PTB. The proportions of adverse outcomes of PTB in urban and rural patients were 14.41% and 13.01%, respectively, with no statistically significant difference (P>0.05). Multivariable Cox proportional hazards regression analysis identified first diagnosed in county-level hospitals or above (HR=2.107, 95%CI: 1.181-3.758) and drug resistance (HR=3.303, 95%CI: 1.653-6.600) as the risk factors for adverse outcomes of PTB in urban patients with PTB-DM, while the treatment/observed management throughout the process (HR=0.470, 95%CI: 0.274-0.803) and fixed-dose combinations throughout the process (HR=0.331, 95%CI: 0.151-0.729) as the protective factors for adverse outcomes in rural patients with PTB-DM. Conclusions There are differences in influencing factors for adverse outcomes of PTB in urban and rural patients with PTB-DM. The adverse outcomes of PTB are associated with first diagnosed hospitals and drug resistance in urban patients, and are associated with the treatment/observed management and fixed-dose combinations throughout the process in rural patients.

Objective To investigate the effect of field angle on the results of in vivo dose validation of electronic portal imaging device(EPID)in patients.Methods Design the mold test and analyze the influence of different mold thicknesses and different frame angles on the 2D γ pass rate.Twenty-three patients who un-derwent radiotherapy in the Department of Radiotherapy of Jinhua Municipal Central Hospital from January to June 2023 were selected as the research object.In vivo dose verification was carried out during treatment to obtain 2D γ pass rate using same-day sector beam CT(FBCT)of planned CT and executive image guided(IG-RT)as reference images,and the influence of field angle on pass rate was analyzed.Results When the frame angle was unchanged,the area of the shooting field was larger than 17 cm×17 cm,and the 2D γ passing rate decreased with the increase of the thickness.The frame angle had no effect on the 2D γ pass rate when the mold thickness was constant.In clinical treatment data,the passage rate of 2D γ near 0°/180° was higher than that near 90°/270°(P＜0.05),and the passage rate near 90°/270° in the FBCT group was higher than that in the IGRT group(P＜0.05).The median passing rate of 3 mm 2D γ was 97.97％in 3％of the 23 patients.The non-IGRT group was 96.81％,the IGRT group was 97.89％,the FBCT group was 98.94％.There was a statistically significant difference in 2D γ passing rate between the non-IGRT group and the IGRT group(Z=-5.083,P＜0.05),and there was a statistically significant difference in 2D γ passing rate between the IGRT group and the FBCT group(Z=-10.657,P＜0.05).Conclusion Clinically,the difference of pass rate in vi-vo dose verification at different rack angles is mainly due to the difference of images within and between ses-sions.Using same-day FBCT as the reference image for in-vivo dose verification can improve the accuracy of pass rate and eliminate the influence of image difference between sessions.

Objective To establish an ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry(UPLC-QTOF-MS)method for identifying the active ingredients of Zhizi Houpu decoction,and to predict its material basis and mechanism of anti-insomnia effects using network pharmacology.Methods The chemical components of Zhizi Houpu decoction were identified according to UHPLC-QTOF-MS ion fragmentation rule combined with compound library and literature review.Components with oral bioavailability(OB)≥30％and drug-like properties(DL)≥0.18 were selected to construct the Zhizi Houpu decoction-active ingredients-target network.The STRING database and the Database for Annotation,Visualization,and Integrated Discovery(DAVID)were used to screen key target proteins.Subsequently,enrichment analysis was performed for biological processes,molecular functions,cellular components,and signaling pathways.Results A total of 107 chemical components were identified,including 35 compounds related to insomnia and 11 anti-insomnia targets such as AKT serine/threonine kinase 1,tumor protein 53,and prostaglandin-endoperoxide synthase 2.Gene Ontology functional enrichment analysis indicated that Zhizi Houpo decoction may exert its effects through cellular components such as the presynaptic membrane,dendrite,and plasma membrane,by participating in biological processes like chemical synaptic transmission,G protein signaling pathway,and neuron apoptosis,and by regulating molecular functions such as G protein-coupled serotonin receptor activity.Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that its anti-insomnia effects were mainly concentrated in pathways such as neuroactive ligand-receptor interaction,calcium signaling pathway,serotonergic synapse,and cyclic adenosine monophosphate signaling pathway.Conclusion The anti-insomnia effect of Zhizi Houpo decoction is the result of a synergistic action involving multiple components,multiple targets,and multiple pathways.Its material basis and mechanism of action are primarily related to regulating biological processes such as neurotransmitter metabolism,synaptic function,neuronal apoptosis,and inflammatory response.

Objective To investigate the impact of sleep modes on the risk for diseases of the body systems.Methods Based on a subset of UK Biobank dataset comprising 87 617 participants,3 sleep dimensions including 6 sleep indicators were obtained through a wrist-worn accelerometer,that is sleep duration and onset,sleep rhythm(relative amplitude and stability),and sleep quality(sleep efficiency and number of awakenings).Latent profile analysis(LPA)was applied to identify and classify distinct sleep modes.Then their longitudinal medical records were the association between different sleep modes and the risk for 467 diseases.Results LPA identified 5 subgroups of unique sleep modes in the participants.Among the 5 subgroups,the subgroup 4 had relatively optimal levels in above sleep indicators.Compared to the subgroup 4,the other 4 subgroups exhibited variations in different sleep dimensions,with at least one indicator demonstrating an unfavorable trend.These subgroups also revealed differences in racial composition,shift work and social deprivation index.Moreover,there were notable differences in the risk of various system diseases among the subgroups(P<0.05).When compared to the subgroup 4,the other 4 subgroups exhibited an elevated risk for certain diseases(comprising a total of 126 diseases),with the diseases of the circulatory system,digestive system and musculoskeletal system most common.Among the 5 subgroups,the subgroup 2(shorter sleep duration and later sleep onset)and the subgroup 5(rhythm disorder)had the highest counts of associated risks,amounting to 85 and 91 types,respectively,but there was certain difference in their systematic composition.Conclusion There are different sleep modes within the participants,and the modes are potentially associated with an increased risk for diseases of body systems.Comprehensive interventions targeting overall sleep modes rather than single sleep indicator may yield obvious health benefits.

Objective To evaluate the resuscitation efficacy of novel lyophilized platelets(LP,thrombin-stimulated platelets)combined with lactated Ringer's(LR)solution in rabbits with hemorrhagic shock and seawater immersion.Methods Fifty rabbits were randomly assigned to 5 groups(Groups A,B,C,D and E,n=10).After all rabbits were anesthetized with 3%pentobarbital sodium at a dose of 1 mL/kg,soft tissue injury was inflicted in the left lower limb.The blood loss from the soft tissue injury was quantified after gauze hemostasis.The right lower limb was subjected to femoral artery catheterization,followed by blood withdrawal equivalent to 26%of the total blood volume of the rabbit.The rabbits were then vertically immersed in 3%artificial seawater,with the water level reaching above the xiphoid process,and were retrieved in 15 min later.Resuscitation strategies were applied to the rabbits from different group:Group A(no resuscitation),Group B(resuscitation with LR solution),Group C(resuscitation with LR solution and fresh platelets),Group D(resuscitation with LR solution and LP),and Group E(resuscitation with LR solution and novel LP).Coagulation function test,routine blood test,blood gas analysis,and thromboelastography were conducted at baseline and at 1,2 and 4 h after injury.Results The LP and rabbit model of hemorrhagic shock and seawater immersion were successfully prepared.At 1 h after injury,the mean arterial pressure(MAP)of Groups C,D and E(infused with platelet preparations)was significantly higher than that of Group A(without resuscitation,P<0.05);the lactate(Lac)content of Group C was obviously lower than that of Groups A and B(P<0.05);the base excess(BE)and blood urea nitrogen(BUN)levels of Groups C,D and E were notably lower than those of Groups A and B(P<0.05);and the prothrombin time(PT)of Group A was significantly longer than that of before injury(P<0.05).At 2 h after injury,the MAP of Groups C and D was significantly higher than that of Groups A and B,and that of Group E was notably higher than that of Group A(P<0.05);the Lac content of Groups C and E was obviously lower than that of Groups A and B,while that of Group D was also lower than that of Group A(P<0.05);the BE and BUN levels of Groups C,D and E were remarkably lower than those of Groups A and B(P<0.05);the maximum amplitude(MA)value of Group C was higher than that of Group A,while the value of Groups A and D at this time was significantly lower than the corresponding value before injury(P<0.05);and the activated partial clotting time(APTT)of Groups A and D was statistically longer than the corresponding baseline time(P<0.05).At 4 h after injury,the MAP of Groups C,D,and E was higher than that of Groups A and B,and that of Group B was higher than that of Group A(P<0.05);the Lac and BUN levels of Groups C,D,and E were lower than those of Groups A and B(P<0.05);the BE level of Groups C and D were lower than those of Groups A and B(P<0.05);the MA value of Groups B,C,and E were higher than those of Group A(P<0.05),while the MA value and APTT value of Groups A and D were significantly lower than their corresponding baseline values(P<0.05).Conclusion For rabbits with hemorrhagic shock and seawater immersion,the novel LP combined with LR solution can significantly increase the MAP level,reduce Lac content,and sustainably maintain blood clot firmness and coagulation function.

The efficient,precise,and rapid detection of trace copper ions(Cu2+)is of paramount importance in the realms of food safety,environmental monitoring,and medical health.By ingeniously utilizing the chemical properties of benzotriazole compounds in copper protection,and introducing an electrochemical reduction strategy,a silver nanoparticle composite structure supported by a nickel foam substrate was developed as an active platform for surface-enhanced Raman scattering(SERS)detection.This platform employed benzotriazole-5-carboxylic acid(BTAC)as a specific SERS probe molecule to achieve sensitive analysis of metal ion concentrations.The detection mechanism revealed a highly selective coordination between the Cu2+and the nitrogen atom in the triazole ring of BTAC,triggering subtle structural changes in the triazole ring.This was manifested by a significant and quantifiable shift in the characteristic peak of the SERS spectrum(particularly at 1001 cm-1),with a maximum shift of up to 30 cm-1.This phenomenon not only addressed the issue of reproducibility in quantitative analysis caused by the non-uniformity of SERS substrate materials but also significantly broadened the application boundaries of SERS technology for trace metal ion detection.It enabled ultra-sensitive detection of Cu2+concentrations ranging from 1×10-6 to 1×10-11 mol/L,with a detection limit as low as 1×10-11 mol/L,significantly enhancing detection sensitivity and accuracy.This work provided a novel and efficient strategy for rapid detection of trace Cu2+and enriched the application potential of SERS technology in food safety,environmental monitoring and biomedical analysis.

Diabetes is one of the top ten fatal diseases globally,and effective diabetes management can significantly reduce the incidence and progression of diabetes-related complications.Traditional blood glucose monitoring relies on fingertip blood sampling to measure glucose concentration,which requires multiple finger pricks per day.However,the long intervals between tests often result in missed hyperglycemic or hypoglycemic events.Therefore,there is an urgent need for non-invasive,continuous,and accurate glucose monitoring technologies to improve patient compliance and provide timely alerts for abnormal glucose levels.Sensors based on electrochemical detection methods,which indirectly estimate glucose levels by analyzing interstitial fluid,sweat,or other bodily fluids,have emerged as a promising direction due to their high sensitivity and low cost.This review focused on recent advancements in non-invasive,continuous glucose monitoring sensors developed using various electrochemical detection methods,with an in-depth analysis of chronoamperometry,impedance spectroscopy,and voltammetry in sensor applications.Finally,the challenges faced by current detection methods in non-invasive continuous glucose monitoring was summarized,and the future directions,including the integration of enzyme-free sensors with deep learning algorithms to enhance accuracy and reliability were proposed.