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 To investigate the effects of baicalin （BC） on insulin resistance in rats with gestational diabetes mellitus （GDM） and its underlying mechanism based on the adenosine monophosphate-activated protein kinase （AMPK）/suppressor of variegation 3-9 homolog 1 （SUV39H1）/histone H3 lysine 9 trimethylation （H3K9me3） axis. METHODS A GDM rat model was established by a combination of a high-fat diet and streptozotocin injection. The successfully modeled rats were divided into the GDM group， BC low-dose group， BC high-dose group， and high-dose of BC+AMPK inhibitor （Compound C） group， with 10 rats in each group. Another 10 pregnant rats fed a normal diet served as the control group. Rats in each group were given corresponding drugs/normal saline intragastrically and/or intraperitoneally， once daily for 2 consecutive weeks. After the last administration， the levels of fasting blood glucose （FBG）， pancreatic function indexes [fasting insulin （FINS）， homeostasis model assessment of insulin resistance （HOMA-IR）， insulin sensitivity index （ISI）]， blood lipid indexes （total cholesterol， triglyceride， low-density lipoprotein cholesterol）， liver function indexes （alanine transferase， aspartate transferase， alkaline phosphatase）， inflammatory indicators （C-reactive protein， interleukin-1β， interleukin-6）， metabolic regulatory protein [complement-C1q/tumor necrosis factor-related protein 3 （CTRP3）]， insulin sensitivity related factors [glucose transporter 4 （GLUT4）， adiponectin]， and oxidative stress indicators [superoxide dismutase （SOD）， catalase （CAT）， malondialdehyde （MDA）] were measured. Pathological changes in liver tissue were observed， and the expressions of proteins related to the AMPK/SUV39H1/H3K9me3 axis in liver tissue were detected. RESULTS Compared with the GDM group， rats in the BC low- and high-dose groups showed varying degrees of improvement in pathological changes such as disordered cell arrangement， vacuolar degeneration， lipid deposition， and inflammatory cell infiltration in liver tissue. Their FBG and FINS levels， HOMA-IR， the levels of blood lipid indexes， liver function indexes， inflammatory indicators and MDA， and the expressions of SUV39H1 and H3K9me3 were significantly decreased or down-regulated， while metabolic regulatory protein， insulin sensitivity-related factors and AMPK protein phosphorylation levels were significantly increased （ P ＜0.05）. The improvement was more significant in the BC high-dose group （ P ＜0.05）. Compound C could significantly reverse the ameliorative effects of high-dose BC on the above quantitative indicators （ P ＜0.05）. CONCLUSIONS BC can significantly reduce oxidative stress and inflammatory responses， increase serum levels of CTRP3， GLUT4 and adiponectin， thereby improving insulin resistance in GDM rats. These effects may be related to the activation of AMPK and inhibition of SUV39H1-mediated H3K9me3 modification.

Dry eye disease(DED)is a common ocular surface disorder worldwide, primarily characterized by a loss of homeostasis of the tear film, and frequently associated with meibomian gland dysfunction(MGD), decreased tear film stability, ocular discomfort, and visual impairment. In recent years, factors such as the widespread use of digital devices,the aging population, and environmental changes have contributed to a significant increase in its global prevalence, making it a major public health concern. Red light therapy(RLT), also known as low-level laser therapy(LLLT)or photobiomodulation(PBM), is a non-invasive treatment that utilizes low-energy red or near-infrared light to irradiate tissues. It exerts photobiomodulatory effects to promote cellular repair and functional recovery. This therapy has demonstrated considerable potential in treating various ocular conditions. Its broader clinical application could improve therapeutic outcomes, alleviate patient discomfort and financial burden, and reduce the consumption of healthcare resources, thereby yielding significant socio-economic benefits. This paper systematically reviews the multifaceted mechanisms and application prospects of RLT in managing DED, including its anti-inflammatory effects, improvement of meibomian gland function, promotion of conjunctival goblet cell repair, and alleviation of visual fatigue, aiming to provide a theoretical foundation and practical reference for its clinical adoption.

ObjectiveBola-like short peptides exhibit novel self-assembly properties due to the formation of peptide dimers via hydrogen bonding interactions between their C-terminals. In this configuration, hydrophilic amino acids are distributed at both terminals, making these peptides behave similarly to Bola peptides. The electrostatic repulsive interactions arising from the hydrophilic amino acids at each terminal can be neutralized, thereby greatly promoting the lateral association of β-sheets. Consequently, assemblies with significantly larger widths are typically the dominant nanostructures for Bola-like peptides. To investigate the effect of hydrophilic amino acids on the self-assembly behavior of Bola-like peptides, the peptides Ac-RI₃-CONH₂ and Ac-HI₃-CONH₂ were designed and synthesized using the Bola-like peptide Ac-KI₃-CONH₂ as a template. Their self-assembly behavior was systematically examined. MethodsAtomic force microscopy (AFM) and transmission electron microscopy (TEM) were employed to characterize the morphology and size of the assemblies. The secondary structures of the assemblies were analyzed using circular dichroism (CD) and Fourier transform infrared (FTIR) spectroscopy. Small-angle neutron scattering (SANS) was used to obtain detailed structural information at a short-length scale. Based on these experimental results, the effects of hydrophilic amino acids on the self-assembly behavior of Bola-like short peptides were systematically analyzed, and the underlying formation mechanism was explored. ResultsThe aggregation process primarily involved three steps. First, peptide dimers were formed through hydrogen bonding interactions between their C-terminals. Within these dimers, the hydrophilic amino acids K, R, and H were positioned at both terminals, enabling the peptides to self-assemble in a manner similar to Bola peptides. Next, β-sheets were formed via hydrogen bonding interactions along the peptide backbone. Finally, self-assemblies were generated through the lateral association of β-sheets. The results demonstrated that both Ac-KI₃-CONH₂ and Ac-RI₃-CONH₂ could self-assemble into double-layer nanotubes with diameters of approximately 200 nm. These nanotubes were formed by the edge fusion of helical ribbons, which initially emerged from twisted ribbons. Notably, the primary assemblies of these peptides exhibited opposite chirality: nanofibers formed by Ac-KI₃-CONH₂ displayed left-handed chirality, whereas those formed by Ac-RI₃-CONH₂ exhibited right-handed chirality. This reversal in torsional direction was primarily attributed to the different abilities of K and R to form hydrogen bonds with water. In contrast, Ac-HI₃-CONH₂ formed narrower twisted ribbons with a significantly reduced width of approximately 30 nm, which was attributed to the strong steric hindrance caused by the imidazole rings. The multilayer height of these ribbons was mainly due to the unique structure of the imidazole rings, which can function as both hydrogen bond donors and acceptors, thereby promoting aggregate growth in the vertical direction. ConclusionThe final morphology of the self-assemblies resulted from a delicate balance of various non-covalent interactions. By altering the types of hydrophilic amino acid residues in Bola-like short peptides, the relative strength of non-covalent interactions that drive assembly formation can be effectively regulated, allowing precise control over the morphology and chirality of the assemblies. This study provides a simple and effective approach for constructing diverse self-assemblies and lays a theoretical foundation for the development of functional biomaterials.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To investigate the acceptance and satisfaction of tuberculosis prevention and control personnel in Beijing with the patient management system, and to provide a basis for further improving the patient management model. Methods A survey was conducted on the current usage, satisfaction, willingness to use and system improvement opinions of the patient management system among medical staff involved in the supervision and medication management of pulmonary tuberculosis patients in Beijing. Results A total of 360 medical staff participated in the survey. ^“Patient management^” was the function with the largest number of users, accounting for 96.94%. The proportion of users of each module who believed that the module's design met actual work needs was over 90%. About 94.44% of respondents believed that patient management systems facilitated the transfer and sharing of information between institutions. And 90.83% of respondents thought that the patient management system was easy to operate, and 89.17% of respondents believed that patient management systems reduced workload. About 97.50% of respondents were satisfied with the overall use of the patient management system. The results of the influencing factor analysis showed that those with 3 or less modules designed to meet actual work were less satisfied than those with more than 3 modules, and the difference was statistically significant (P=0.001). Respondents put forward suggestions for improvement on the optimization of operational details such as system response speed, interface design, system login and query statistics. Conclusion Medical staff involved in the follow-up management of pulmonary tuberculosis patients are highly satisfied with their work using the patient management system. During the promotion and use, it is still necessary to continuously optimize the system functions according to work needs so that the system can truly facilitate work.

Objective: To explore the association of physical activity and sugar sweetened beverage consumption with psychological sub health among middle school students in Bao an District, Shenzhen, so as to provide a reference for adolescent mental health promotion. Methods: A questionnaire survey was conducted in November 2024 by a stratified cluster random sampling method to select 6 926 junior and senior middle school students from 5 middle schools in Shenzhen. The questionnaire from Youth Risk Behavior Surveillance System was used to assess the consumption of sugar sweetened beverages, and physical activity Rating Scale was used to assess the level of physical activity, and Brief Instrument on Psychological Health of Youths was used to evaluate the psychological sub health status. The Chi -square test was used to analyze the differences in the detection rates of psychological sub health among different groups of middle school students, and a multivariate Logistic regression model was established to analyze the effects of physical activity and sugar sweetened beverage consumption and their combined effects on the psychological sub health of middle school students. Results: The detection rate of psychological sub health among middle school students in Bao an District, Shenzhen was 18.93%. Multivariate Logistic regression analysis showed that, after controlling for confounding factors such as gender, school stage, family residence, family economic status, parental literacy, academic stress and number of friends, lack of physical activity or excessive sugar sweetened beverage consumption were associated with increased risks of psychological sub health among middle school students ( OR =1.36, 1.45); and the highest risk of psychological sub health was found in middle school students who were lack of physical activity and excessive sugar sweetened beverage consumption ( OR =2.59) ( P <0.01). Further analysis by school stages showed that junior high school students with sufficient physical activity and excessive intake of sugary drinks ( ROR =2.10), lack of physical activity and excessive intake of sugary drinks ( ROR =2.31) were at higher risks of psychological sub health than senior high school students( P <0.05). Conclusions Insufficient physical activity and excessive sugar sweetened beverage consumption are closely associated with an increased risk of psychological sub health among middle school students. Effective interventions should be targeted to reduce the risk of psychological sub health problems among middle school students.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

Objective To explore predictive factors of severe community-acquired pneumonia (CAP) complicated with respiratory failure (RF) and to develop and internally validate a clinical prediction model. Methods A retrospective study was conducted on 350 patients with severe CAP admitted to Tianyou Hospital Affiliated to Wuhan University of Science and Technology from September 2022 to December 2024. Patients were randomly divided into a training set (n＝245) and a validation set (n＝105) in a 7∶3 ratio, and further categorized into RF and non-RF groups. LASSO regression was applied to optimize variable selection. Multivariate logistic analysis was used to construct the prediction model, followed by internal validation. Results Univariate regression analysis identified male, hypertension, diabetes, coronary heart disease, age, CURB-65 score, white blood cell count, neutrophil count, C-reactive protein (CRP), serum amyloid A, procalcitonin, and hospital stay as risk factors for RF in severe CAP, while albumin level was a protective factor. LASSO regression selected CURB-65 score, albumin level, and CRP for inclusion in the final model. The area under the receiver operating characteristic curve was 0.903 in the training set and 0.919 in the validation set. Calibration curve analysis demonstrated excellent agreement between predicted and observed probabilities in both sets, and Hosmer-Lemeshow goodness-of-fit tests indicated no significant deviations. Threshold probabilities ranged from 0.01 to 0.99 in both training and validation sets. Conclusions CURB-65 score, albumin level, and CRP are independent predictors of RF in severe CAP. The clinical prediction model based on these factors exhibits strong discrimination, calibration, goodness-of-fit, and clinical utility.