Objective To investigate the microbial contamination and its influencing factors of indoor air in public places in Xi'an City, to assess the health risk of employees, and to provide a scientific basis for improving the indoor environment of public places. Methods Total bacterial count and total fungal count in indoor air were monitored in hotels/inns, shopping malls/supermarkets, gyms, and waiting rooms in Xi'an from 2023 to 2024. The health risk assessment of employees was evaluated according to the Chinese Population Exposure Parameters Manual (Adult Volume). Results Overall, the standard-exceeding rate of total bacterial count in Xi'an was 3.85%, and the median values of total bacterial count and total fungal count were 350 CFU/m3 and 300 CFU/m3, respectively. The results of the generalized linear model showed that high indoor temperature and PM10 levels were associated with increased indoor bacterial concentrations (β>0, P<0.05), while high daily passenger flow, and high indoor relative humidity and PM₁₀ levels were associated with increased indoor fungal concentrations (β>0, P<0.05). The multivariate logistic regression showed that high levels of indoor bacterial and fungal concentrations were risk factors for respiratory discomfort among employees. The hazard quotient (HQ) values for all types of public places were less than 1, indicating that the health risk of microbial aerosol exposures for employees was relatively low. Conclusion The indoor microbial pollution in public places in Xi'an is relatively mild, but countermeasures still need to be taken to reduce indoor air microbial contamination.

Objective: The cross sectional study aimed to identify predominant co-occurrence patterns among six common mental health issues in college students, so as to provide empirical basis for designing targeted interventions. Methods: From October 2024, a total of 9 837 students from 4 universities in Xiangtan City, Hunan Province, participated in the current study by multistage random cluster sampling method. Participants completed self report measures, including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7 item Scale (GAD-7), Young s Internet Addiction Diagnostic Questionnaire, the Adolescent Insomnia Symptom Self rating Scale, the Ottawa Self injury Inventory, and the Brief Community Assessment of Psychic Experiences Questionnaire. Demographic and co-occurrence characteristics were first compared using Chi square or trend Chi-square tests, followed by application of the Apriori algorithm to mine association rules for primary co-occurrence patterns. Results: The detection rate of co-occuring the common mental health issues was 46.44%. The detection rate was significantly higher in female than in male students (50.42%, 43.61%; χ 2=44.46) and in students from rural versus urban areas (47.22%, 44.60%; χ 2=5.67) (both P <0.05). Significant differences were observed among freshmen, sophomores, juniors, and seniors (46.63%, 48.35%, 45.05% , 43.66%, respectively; χ 2=9.22, P <0.05), although no statistically significant trend was detected ( χ 2 trend =3.75, P = 0.05 ). Association rule mining identified “anxiety + depression” “anxiety + psychotic experiences + depression” and “anxiety + sleep disorder + depression” as the combinations with the highest support. In addition, “anxiety+depression+Internet addiction+psychotic experiences =>sleep disorder (>= refered to the occurrence of the latter item under the condition that the former item occurs)” and “anxiety + depression+Internet addiction=>sleep disorder” were combinations with relatively high confidence. Conclusions Co-occurrence of these mental health issues among college students is high and exhibits diverse patterns. Strategies to address this burden should prioritize integrated interventions that target these specific combinations of factors.

OBJECTIVE To investigate the effects and mechanism of the Yishen paidu formula on renal fibrosis in rats with chronic renal failure （CRF） through the reactive oxygen species （ROS）/thioredoxin-interacting protein （TXNIP）/NOD-like receptor thermal protein domain associated protein 3 （NLRP3） pathway. METHODS Rats were randomly divided into control group， model group， Yishen paidu formula low-dose （Yishen paidu formula-L） group， Yishen paidu formula high-dose （Yishen paidu formula- H） group， Yishen paidu formula-H+pcDNA-NC group， and Yishen paidu formula-H+ pcDNA-TXNIP group， with 10 rats in each group. Except for control group， all other rats were fed a diet containing 0.5% adenine to establish a CRF model； the rats were then administered corresponding drugs or normal saline intragastrically or via tail vein， once daily， for 8 consecutive weeks. After the last administration， the levels of serum creatinine （Scr）， blood urea nitrogen （BUN）， ROS， superoxide dismutase （SOD）， malondialdehyde （MDA）， tumor necrosis factor-α （TNF-α）， interleukin （IL）-6， and IL-1β were measured in each group. Pathological changes in renal tissue were observed， and the protein expression levels of Collagen Ⅲ， α-smooth muscle actin （α-SMA）， transforming growth factor-β1 （TGF-β1）， TXNIP and NLRP3 in renal tissue were detected. RESULTS Compared with model group， the renal histopathological damage and fibrosis of rats in Yishen paidu formula-L group and Yishen paidu formula-H group were significantly alleviated. The levels of Scr， BUN， ROS， MDA， TNF- α， IL-6 and IL-1β， and the protein expressions of Collagen Ⅲ， α-SMA， TGF-β1， TXNIP and NLRP3 were significantly decreased， while SOD levels were significantly increased （P＜0.05）. Moreover， the changes were more pronounced in the Yishen paidu formula-H group （P＜0.05）. Compared with Yishen paidu formula-H+pcDNA-NC group， above indexes of rats in Yishen paidu formula-H+pcDNA-TXNIP group were reversed significantly （P＜0.05）. CONCLUSIONS Yishen paidu formula can inhibit renal fibrosis in CRF rats by suppressing the ROS/TXNIP/NLRP3 pathway.

ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

The integration of large language model （LLM） and traditional Chinese medicine （TCM） promotes the informatization of TCM，and also provides a new direction for the inheritance and innovation of TCM in the new era. Based on the research background of LLM，the development process of LLM based on the Transformer architecture is summarized，and the research progress of LLM in TCM is reviewed. The main process of constructing TCM LLMs and the key techniques used by researchers during model development are summarized. Based on the related literature， the main application scenarios of TCM LLMs and the research explorations conducted by TCM researchers using LLMs are outlined. Meanwhile，the current challenges faced in the development of TCM LLMs are analyzed. Further improvements are urgently needed in the construction of high-quality data，the evaluation methodology of TCM LLMs，the interpretability of the model， multimodal fusion of TCM LLMs， and the development of TCM prescription recommendation models. Looking forward to the future development of LLM in TCM，it is expected to provide a reference for the deeper integration of LLMs and TCM，and facilitate the modernization of TCM.

Objective To explore the predictive value of fat attenuation index(FAI)and fibrous plaque index(FPI)for the prognosis of patients with acute coronary syndrome(ACS).Methods A retrospective cohort study was conducted on 334 ACS patients undergoing percutaneous coronary intervention(PCI)in the First Affiliated Hospital of Army Military Medical University and Yongchuan Hospital of Chongqing Medical University from March 2021 to July 2023.All patients received coronary computed tomography angiography(CCTA)to measure FAI and FPI.According to the occurrence of major adverse cardiovascular events(MACE)with 1 year of follow-up,they were divided into MACE group(n=108)and non-MACE group(n=226).The baseline data,CCTA data and results of laboratory tests were collected and compared between the 2 groups.Multivariate logistic regression analysis was used to analyze the relationship of FAI and FPI with the prognosis of ACS patients,and ROC curve was drawn to evaluate its predictive efficiency.Results Among the 334 ACS patients,108(32.34%)experienced MACE.When compared with the non-MACE group,the MACE group exhibited significantly larger proportions of diabetes(72.22%vs 31.86%)and left main coronary artery disease(18.52%vs 7.08%),but lower success rate of operation(79.63%vs 93.81%,P<0.05).Radiologic results showed that the proportion of severe stenosis(20.37%vs 10.62%),FAI(-80.12±6.41 HU vs-72.34±7.09 HU)and FPI(0.58±0.41 vs 0.26±0.12)were obviously increased in the MACE group than the non-MACE group(P<0.05).Laboratory tests indicated that there were statistical differences between the 2 groups in high-density lipoprotein-cholesterol(HDL-C,1.20±0.15 vs 1.09±0.16 mmol/L),miR-126(0.91±0.12 vs 0.96±0.15)and SST2(38.45±5.67 vs 34.30±4.89 ng/mL,P<0.05).Multivariate Logistic regression analysis revealed that FAI(OR=1.200,95%CI:1.136～1.268),FPI(OR=63.157,95%CI:14.126～282.374),moderate stenosis(OR=1.332,95%CI:1.024～1.859),severe stenosis(OR=1.480,95%CI:1.074～2.039),miR-126(OR=0.007,95%CI:0.001～0.077),and sST2(OR=1.192,95%CI:1.113～1.277)were independent predictors of MACE(P<0.05).ROC curve analysis displayed that stenosis degree(AUC=0.622,95%CI:0.561～0.683,P=0.001),FAI(AUC=0.790,95%CI:0.741～0.839,P=0.001)and FPI(AUC=0.700,95%CI:0.638～0.761,P=0.001),miR-126(AUC=0.646,95%CI:0.584～0.707,P=0.001),sST2(AUC=0.700,95%CI:0.638～0.761,P=0.001)had certain predictive values for ACS prognosis.Conclusion Coronary FAI and FPI can be used as independent prognostic indicators of ACS patients,and their numerical changes are closely related to plaque stability and inflammatory state.

Objective To explore the underlying mechanisms by which time-restricted feeding(TRF)attenuates dextran sodium sulfate(DSS)-induced colitis in mice via modulation of regenerating islet-derived protein 3 gamma(Reg3γ)expression and gut microbiota.Methods Six-week-old C57BL/6 mice were stratified by body weight and randomized into ad libitum feeding(AL)and TRF groups(n=7).The AL mice were given unrestricted food access,whereas the TRF mice were allowed feeding only during 00:00 and 08:00 daily,for totally 4 weeks.Mouse colitis model was induced at the fourth week by adding 2.5%dextran sodium sulfate(DSS)in drinking water for 6 d.Disease severity and the effects of TRF were assessed with disease activity index(DAI)scoring,colon length measurement,HE staining and histopathological scoring,and mRNA expression levels of regenerating islet-derived 3 gamma(Reg3g)and inflammatory cytokines in colonic tissues.Another 14 mice were randomized into AL plus antibiotic cocktail(AL+ABX)and TRF plus antibiotic cocktail(TRF+ABX)groups,with 7 animals in each group.ABX was administered to deplete gut microbiota and evaluate the microbiota dependence of TRF in attenuating colitis.Fecal samples from AL and TRF mice were analyzed by 16S ribosomal RNA sequencing(16S rRNA-seq),and serum lipopolysaccharide(LPS)level was measured.The colonic epithelial cells were collected for RNA-seq.Results After modeling,the AL mice exhibited typical colitis symptoms,such as weight loss,diarrhea,and hematochezia.TRF intervention significantly attenuated these above symptoms,with lower DAI scores from day 4 post-modeling(P<0.001),reduced colon shortening(P<0.01),preserved tissue architecture,and decreased inflammation.RT-qPCR analysis showed that TRF down-regulated colonic mRNA expression levels of Reg3g and pro-inflammatory cytokines(IL-1 β,IL-6,TNF-α)(P<0.05)while up-regulated that of anti-inflammatory factor IL-10(P<0.000 1)when compared with the corresponding levels in AL mice.ABX treatment led no significant differences between the AL+ABX and TRF+ABX groups in term of DAI score,colon length,or histopathology.Obviously down-regulated Reg3g was observed in the TRF+ABX group than the AL+ABX group(P<0.05),whereas L-1β,IL-6,TNF-α and IL-10 showed no notable changes.16S rRNA-seq revealed that TRF markedly reshaped gut microbiota composition,with increased Gram-positive bacterial abundance,reduced Gram-negative bacteria,with concomitant lower serum LPS level(P<0.001).RNA-seq also indicated significant suppression of NF-κB and other inflammation-related signaling pathways in the TRF group.Conclusion TRF attenuates DSS-induced colitis in mice by downr-egulating Reg3γ expression,reshaping gut microbiota,and reducing serum LPS level,and thereby suppressing NF-κB-mediated inflammatory signaling pathways.

The blue fluorescent carbon dots(TMCDs)and cyan fluorescent carbon dots(TMCDs-H2O)were synthesized fromm-phenylenediamine and tricarballylic acid through air-assisted melting polymerization and one-step hydrothermal method,respectively.Air purging could effectively inhibit the side reactions and reduce the derivative structures in the carbon dots product.The structure and morphology of these two materials were systematically characterized using liquid nuclear magnetic resonance spectroscopy(NMR),mass spectrometry(MS),and transmission electron microscopy.Compared to TMCDs-H2O((3.12±0.63)nm),TMCDs showed a smaller average particle size(approximately(1.85±0.02)nm).The NMR and MS analysis revealed that although the main structure of both types of carbon dots was similar,TMCDs exhibited a simpler structure with higher degree of polymerization.These results suggested that supramolecular interactions might introduce numerous small molecule derivatives into TMCDs-H2O particles,resulting in lower polymerization degree,multiple substructures,and larger particle size characteristics for this material.When employed as chemical sensors for metal ion detection,in the linear range of 1×10-5-5×10-4 mol/L,the detection limits of Fe3+by TMCDs and TMCDs-H2O were 3.3×10-6 mol/L and 3.8×10-6 mol/L,respectively.The experimental results demonstrated that the recoveries of CDs and inductively coupled plasma optical emission spectrometer(ICP-OES)were similarity,whereas TMCDs displayed a considerable relative standard deviation.This study demonstrated that endogenously derived structures in CDs could enhance the performance of metal ion sensing.

Current ambient mass spectrometry ionization often requires external auxiliary equipment such as high-voltage power supply,gas cylinder,and syringe pump.Moreover,the process of sample preparation is cumbersome,and the experimental operations are complex,which makes it difficult to adapt to real-time on-site detection.In this work,a novel method was proposed,in which direct sampling of raw samples,online extraction of interest analytes,and ionization of target molecules were integrated into a single unit.With the developed method,the in-situ extraction and nano-electrospray ionization for both liquid and solid raw samples were achieved.Also,a handheld ion source and its pose adjustment device were developed,and the position and angle parameters were subsequently optimized.The performance of the ionization device was tested using standard solutions of caffeine and reserpine.The limits of detection(LODs)were 0.08 μg/L and 0.14 μg/L,with relative standard deviations(RSDs)≤3.7% and≤5.6%,respectively,indicating that the device possessed high sensitivity and stability.Using this device,three different concentrations of reserpine standard solutions were continuously tested for five days.The intra-day RSDs were consistently≤4.7% and the inter-day RSDs were all≤10.3%,showing the good working stability of the device.Without any pretreatment,a rapid qualitative detection of medicinal components including astragaloside II and cycloastragenol in five traditional Chinese medicines was carried out,with RSDs≤8.0% and≤7.1%,respectively.Additionally,rapid qualitative detection of gallic acid,a medicinal component,in white peony roots,and hypaphorine as well as quercetin in cowherb seeds were carried out,with RSDs≤7.0%,≤6.4% and≤6.1%,respectively.These results demonstrated that the ionization technology and device exhibited good stability during qualitative detection of raw samples.