Objective To introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.

Objective: To analyze the association between insufficient sleep and score of depressive symptoms among junior and senior high school students, so as to provide a scientific reference for targeted early intervention measures of adolescents depressive symptoms. Methods: From September to November 2023, a stratified cluster random sampling method was used to select 96 080 junior and senior high school students from 409 schools in 113 districts and counties in Shaanxi Province. A questionnaire survey was conducted using the 2023 Shaanxi Provincial Common Student Diseases and Health Influencing Factors Survey Form, and their height and weight were measured. Propensity score (PS) matched (1∶1) analysis was used to match participants with insufficient sleep to those sufficient sleep students. Through the gradual correction of the confounders, three multilevel linear models were established to analyze the association between insufficient sleep and depressive symptoms score, and subgroup analysis was conducted afterward. Results: A total of 70 135 (73.00%) students had insufficient sleep. After PS matching, 25 894 pairs were matched. Before PS matching, after adjusting for gender, educational stage, region, adolescent characteristics, boarding status, smoking, alcohol consumption, outdoor activities and body mass index grouping, linear regression analysis results showed that compared with students who got adequate sleep, students who lacked sleep had an increase of 1.39 scores ( B=1.39, 95%CI =1.28-1.51) in depressive symptoms; after PS matching, students with insufficient sleep got an increase of 1.32 scores ( B=1.32, 95%CI =1.17- 1.45 ) in depressive symptoms score compared with those who had adequate sleep (both P <0.05). Conclusions The insufficient sleep is associated with the increase of the depressive symptoms score of junior and senior high school students. It is recommended that junior and senior high school students should keep a good sleeping habit, so as to reduce the prevalence of depressive symptoms.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

Objective To investigate the epidemiological characteristics of malaria and provide a basis for developing improved prevention and control measures. Methods Data were obtained from the Chinese Disease Prevention and Control Information System. Malaria surveillance data for Nanning City from January 1,2023, to December 31,2024, were exported from the Infectious Disease Reporting Information Management Subsystem. The characteristics of the two groups of malaria cases were compared. Results A total of 103 imported malaria cases were reported in Nanning City in 2024, representing a 38.32% decrease compared with the same period of the previous year. No statistically significant difference were observed between cases reported in 2023 and 2024 in terms of average age, gender ratio, proportion of parasite species, and monthly reporting distribution;however, statistically significant differences were found in the proportion of reporting areas and current residence areas(χ2= 13.572 and 10.355, respectively; P = 0.001 and 0.035, respectively). The proportion of cases reported in Shanglin County and the proportion of cases residing in Shanglin County were both lower than those during the same period of the previous year. Conclusions The high aggregation of imported malaria cases in Nanning City has decreased. Medical institutions in areas other than Shanglin County should strengthen their vigilance against malaria.

Objective To understand the distribution, species composition, seasonal fluctuations, and presence of Dabie bandavirus in ticks in Tai'an City, providing a basis for assessing tick-borne disease risks and formulating prevention strategies. Methods Free-living ticks were monitored using the flagging method, whereas parasitic ticks were monitored through host surface examination. Reverse transcription-polymerase chain reaction (RT-qPCR) was used to detect the presence of Bandavirus dabieense in tick specimens. Results The density of free-living ticks in Tai'an City showed a continuous decreasing trend over the 3 years from 2021 to 2023, with an average tick density of 0.43 ticks/(flag·100 m). The dominant habitats were scenic areas and forests, and the seasonal fluctuations exhibited a bimodal pattern, peaking in March and August. The only free-living tick species captured was Haemaphysalis longicornis. Over the 3 years, the average tick index for parasitic ticks was 1.85, with sheep as the primary host. Seasonal fluctuations also followed a bimodal pattern, peaking in March and August. The primary parasitic tick species captured were H. longicornis and Rhipicephalus sanguineus. No Dabie bandavirus was detected in the tick specimens. Conclusions Tick density in Tai'an City remains relatively high, necessitating continued efforts to enhance tick surveillance and implement targeted prevention measures in rural environments to further reduce the health risks posed by tick-borne diseases.

ObjectiveMicrotube associated protein-2 （MAP-2）， alpha-tubulin （α-tubulin）， and synaptophysin （SYP） are important proteins in neuronal signal communication. This paper observed the effects of modified Zhigancao Tang on the expression of serum α-Synuclein （α-Syn） and its oligomers， MAP-2， α-tubulin， and SYP of patients with liver and kidney deficiency of Parkinson's disease （PD）， analyzed their correlation， and evaluated the therapeutic effect of modified Zhigancao Tang in patients with liver and kidney deficiency of PD based on α-Syn transmission pathway mediated by neuronal communication in vivo. MethodsA total of 60 patients with PD who met the inclusion criteria were randomly divided into a treatment group （30 cases） and a control group （30 cases）. Both groups were treated on the basis of PD medicine， and the treatment group was treated with modified Zhigancao Tang. Both groups were treated for 12 weeks. The changes in UPDRS score， TCM syndrome score， and expression of serum α-Syn and its oligomers， MAP-2， α-tubulin， and SYP were observed before and after 12 weeks of treatment in each group. The correlation between the above-mentioned serum biological indexes and the levels of serum α-Syn and its oligomers was analyzed. ResultsAfter treatment， the TCM syndrome score， UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ score of the treatment group were significantly decreased （P<0.05， P<0.01）. The UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ scores in the treatment group were significantly decreased compared with those in the control group after treatment （P<0.05）. After treatment， the total effective rate of the control group was 63.3% （19/30）， and that of the treatment group was 86.7% （26/30）. The clinical effect of the observation group was better than the control group （Z=-2.03， P<0.05）. The total effective rate of the observation group was better than that of the control group， and the difference was statistically significant （χ²=5.136， P<0.05）. After treatment， the oligomer level of serum α-Syn and MAP-2 level in the treatment group were significantly decreased （P<0.05， P<0.01）. The levels of serum α-Syn and its oligomers， as well as α-tubulin in the treatment group， were significantly decreased compared with those in the control group after treatment （P<0.05， P<0.01）. Serum α-Syn was correlated with serum MAP-2 and α-Syn oligomer in patients with PD （P<0.05， P<0.01） but not correlated with serum SYP . Serum α-Syn oligomers of patients with PD were correlated with serum MAP-2 and α-tubulin （P<0.05， P<0.01） but not correlated with serum SYP level. Serum SYP of patients with PD was correlated with serum MAP-2 （P<0.05）. ConclusionModified Zhigancao Tang has a therapeutic effect on patients with liver and kidney deficiency of PD by inhibiting the production of α-Syn oligomers and intervening α-Syn microtubule transport pathway in vivo.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.

Traditional development of small protein scaffolds has relied on display technologies and mutation-based engineering, which limit sequence and functional diversity, thereby constraining their therapeutic and application potential. Protein design tools have significantly advanced the creation of novel protein sequences, structures, and functions. However, further improvements in design strategies are still needed to more efficiently optimize the functional performance of protein-based drugs and enhance their druggability. Here, we extended an evolution-based design protocol to create a novel minibinder, BindHer, against the human epidermal growth factor receptor 2 (HER2). It not only exhibits super stability and binding selectivity but also demonstrates remarkable properties in tissue specificity. Radiolabeling experiments with ^99mTc, ⁶⁸Ga, and ¹⁸F revealed that BindHer efficiently targets tumors in HER2-positive breast cancer mouse models, with minimal nonspecific liver absorption, outperforming scaffolds designed through traditional engineering. These findings highlight a new rational approach to automated protein design, offering significant potential for large-scale applications in therapeutic mini-protein development.

Natural polyphenols are a group of components widely found in traditional Chinese medicines and have been demonstrated to delay or prevent the development of aging and age-related diseases in recent years. As far as we know, the studies of natural polyphenols in aging and aging-related diseases have never been extensively reviewed. In the present paper, we reviewed recent advances of natural polyphenols in aging and common age-related diseases and the current technological methods to improve the bioavailability of natural polyphenols. The results showed that natural polyphenols have the potential to prevent or treat aging and common age-related diseases through multiple mechanisms. Nanotechnology, structural modifications, and matrix processing could provide strong technical support for the development of natural polyphenols to prevent or treat aging and age-related diseases. In conclusion, natural polyphenols have important potential in the prevention and treatment of aging and age-related diseases.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.