Abstract The prevention and control of myopia in Chinese children and adolescents has become a major public health issue. While maintaining increased outdoor activity as a cornerstone intervention, there is an urgent need to explore new complementary approaches that can be effectively implemented in both indoor and outdoor settings. In recent years, environmental spatial frequency has gained increasing attention as one of the key environmental factors influencing the development and progression of myopia. Both animal studies and human research have confirmed that indoor environments lacking mid to high spatial frequency components, often characterized as "visually impoverished", can promote axial elongation and myopia through mechanisms such as disruption of retinal neural signaling, impaired accommodative function, and altered expression of related molecules. Based on the scientific consensus, it is recommended that "enriching of environmental spatial frequency" should be integrated into the myopia prevention and control framework. Following the principles of schoolled organization, family cooperation, community involvement, and student participation, specific measures are put forward in three areas：optimizing school visual settings, improving home spatial environments, and promoting healthy visual behavior. The aim is to create "visually friendly" indoor environments as an important supplement to outdoor activity, thereby providing a novel perspective and strategy for comprehensively advancing myopia prevention and control among children and adolescents.

In order to explore the possible role and molecular mechanism of the combined action of leech and bear bile in liver and gallbladder diseases, this study first used network pharmacology methods to screen the components and targets of leech and bear bile, as well as the related target genes of liver and gallbladder diseases. The selected key genes were subjected to interaction network and GO/KEGG enrichment analysis. Then, using sodium oleate induced HepG2 cell lipid deposition model and DL-ethionine induced mouse fatty liver model, the activity of leech and bear bile alone and in combination in reducing liver fat was evaluated in vitro and in vivo, and the expression of key pathway related proteins suggested by network pharmacology was detected by Western blot. The results of network pharmacology analysis showed that the active ingredients of leech and bear bile have 295 intersecting targets with liver and gallbladder related diseases, involving more than 200 signaling pathways, including the PI3K/Akt signaling pathway and phospholipase D signaling pathway closely related to glucose and lipid metabolism. The results of in vitro validation experiments showed that both leech and bear bile, alone and in combination, can significantly inhibit the lipid deposition induced by sodium oleate in human liver cells, reduce the triacylglycerol level in cell culture supernatant, and inhibit the lipid content in liver cells. The observation results of Nile red staining confocal microscopy showed that the combination of leech and bear bile had better activity in reducing lipid deposition in liver cells compared to using them alone. In a mouse fatty liver model, the combination of leech and bear bile can better reduce elevated organ indices, blood lipids, and liver lipid levels, as well as lower the levels of serum liver injury biomarkers. The animals used in this experiment and related disposal meet the requirements of animal welfare. Before the experiment, it was reviewed and approved by IACUC, Institute of Materia Medica, Chinese Academy of Medical Sciences. The Western blot experiment results showed that the combination of leech and bear bile can significantly upregulate the expression levels of p-PI3K and p-Akt proteins, and increase the p-PI3K/PI3K and p-Akt/Akt ratios, which is consistent with the predicted results of network pharmacology. The combination of leech and bear bile has great potential for treating fatty liver disease, and activating the PI3K/Akt pathway may be one of the important mechanisms for reducing lipid deposition in liver cells.

ObjectiveTo investigate the feasibility and safety of endoscopic retrograde cholangiopancreatography （ERCP） combined with oral cholangiopancreatography in the treatment of major duodenal papilla gallbladder polyps. MethodsA retrospective analysis was performed for the clinical data of eight patients with choledocholithiasis and gallbladder polyps who underwent ERCP and combined with oral cholangiopancreatography for major duodenal papilla cholecystectomy in Center of Digestive Endoscopy， Jilin People’s Hospital， from May 2022 to June 2024， and related data were collected， including the success rate of surgery， the technical success rate of gallbladder polyp removal， the superselective method of cystic duct， the time of operation， the time of gallbladder polyp removal， and surgical complications. ResultsBoth the success rate of surgery and the technical success rate of gallbladder polyp removal reached 100%， and of all eight patients， three patients used guide wire to enter the gallbladder under direct view， while five patients received oral cholangiopancreatography to directly enter the gallbladder. The time of operation was 51.88±12.34 minutes， and the time of gallbladder polyp removal was 23.13±10.94 minutes. The diameter of gallbladder polyp was 2‍ ‍—‍ ‍8 mm， and pathological examination showed inflammatory polyps in three patients， adenomatous polyps in one patient， and cholesterol polyps in four patients. There were no complications during or after surgery. The patients were followed up for 2‍ ‍—‍ ‍27 months after surgery， and no recurrence of gallbladder polyp was observed. ConclusionOral cholangiopancreatography is technically safe and feasible in endoscopic major duodenal papilla cholecystectomy.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

ObjectiveTo investigate the alleviating effect of calcium cyanamide （CaCN₂） soil fumigation on replanting problems of Rehmannia glutinosa. MethodsNewly soil （NP） was used as the control group， while three treatment groups were established： replanted soil （RP）， newly soil treated with CaCN₂ （120 g·m²， tillage depth 25 cm） （NPCC）， and replanted soil treated with CaCN₂ （RPCC）. R. glutinosa was cultivated in all groups. At harvest， the tuber agronomic traits （number of enlarged roots， maximum root diameter， fresh weight， dry weight） were measured. The content of catalpol and rehmannioside D was quantified by ultra-high-performance liquid chromatography （UPLC） to evaluate medicinal quality. Rhizosphere soil available nutrients and enzyme activities were analyzed by assay kits. The community structure and composition of fungi and bacteria in rhizosphere soil were assessed via internal transcribed spacer 2 （ITS2） sequencing and 16S rDNA sequencing， respectively. ResultsCompared with NP， the RP group showed obviously reduced in tuber agronomic traits and quality indicators （P0.05）. However， the RPCC group showed significant improvement in agronomic traits and a notable increase in rehmannioside D content compared to RP （P0.05）. The contents of available phosphorus and potassium in RPCC and NP groups were obviously lower than those in RP （P0.05）. The polyphenol oxidase soil （S-PPO） activity in RP was obviously lower than in NP （P0.05）， while sucrose soil （S-SC）， acid phosphatase soil （S-ACP）， and S-PPO activities in RPCC were obviously higher than in RP （P0.05）. Microbial richness and diversity in RP were obviously higher than in NP （P0.05）， whereas no significant differences were observed between the RPCC and NP. The relative abundances of fungal genera Nectria， Myrothecium， Tomentella， and bacterial genus Skermanella were obviousl lower in RPCC and NP than in RP （P0.05）. Correlation analysis that S-ACP activity was positively correlated with the content of rehmannioside D （P0.05）. Fungal genera Engyodontium and Alternaria， and bacterial genera Pir4 lineage， Pirellula， Methyloversatilis， Brevundimonas， Ralstonia， and Acidibacter were obviously positively correlated with tuber dry weight （P0.05）. Conversely， fungal genera Pseudaleuria， Nectria， Haematonectria， Ceratobasidium， and bacterial genera Streptomyces， Skermanella， RB41， Gemmatimonas， and Bacillus were obviously negatively correlated with dry weight （P0.05）. The fungal genus Alternaria and bacterial genera Brevundimonas， Ralstonia， Acidibacter， and Dongia showed positive correlations with medicinal quality of R.glutinosa tuber， while fungal genera Pseudaleuria， Nectria， Stachybotrys， Fusarium， Gibberella， Ceratobasidium， and bacterial genera Sphingomonas， Skermanella， RB41， Gemmatimonas， and Bacillus were obviously negatively correlated （P0.05）. ConclusionCaCN₂ soil fumigation can significantly improve enzyme activities in replanted Rehmannia rhizosphere soil， enhance the utilization of available nutrients， reshape microbial community structure of replanted R.glutinosa at the family and genus level， and notably improve tuber agronomic traits and medicinal quality. This study provides a novel approach to alleviating replanting problems and offers insights for the integrated development of standardized cultivation techniques， including soil disinfection， nutrient-targeted regulation， and microbial inoculant application.

BACKGROUND: While emotional distress, encompassing anxiety and depression, has been associated with negative clinical outcomes, its impact across various clinical departments and general hospitals has been less explored. Previous studies with limited sample sizes have examined the effectiveness of specific treatments (e.g., antidepressants) rather than a systemic management strategy for outcome improvement in non-psychiatric inpatients. To enhance the understanding of the importance of addressing mental health care needs among non-psychiatric patients in general hospitals, this study retrospectively investigated the impacts of emotional distress and the effects of early detection and management of depression and anxiety on hospital length of stay (LOS) and rate of long LOS (LLOS, i.e., LOS >30 days) in a large sample of non-psychiatric inpatients. METHODS: This retrospective cohort study included 487,871 inpatients from 20 non-psychiatric departments of a general hospital. They were divided, according to whether they underwent a novel strategy to manage emotional distress which deployed the Huaxi Emotional Distress Index (HEI) for brief screening with grading psychological services (BS-GPS), into BS-GPS ( n = 178,883) and non-BS-GPS ( n = 308,988) cohorts. The LOS and rate of LLOS between the BS-GPS and non-BS-GPS cohorts and between subcohorts with and without clinically significant anxiety and/or depression (CSAD, i.e., HEI score ≥11 on admission to the hospital) in the BS-GPS cohort were compared using univariable analyses, multilevel analyses, and/or propensity score-matched analyses, respectively. RESULTS: The detection rate of CSAD in the BS-GPS cohort varied from 2.64% (95% confidence interval [CI]: 2.49%-2.81%) to 20.50% (95% CI: 19.43%-21.62%) across the 20 departments, with a average rate of 5.36%. Significant differences were observed in both the LOS and LLOS rates between the subcohorts with CSAD (12.7 days, 535/9590) and without CSAD (9.5 days, 3800/169,293) and between the BS-GPS (9.6 days, 4335/178,883) and non-BS-GPS (10.8 days, 11,483/308,988) cohorts. These differences remained significant after controlling for confounders using propensity score-matched comparisons. A multilevel analysis indicated that BS-GPS was negatively associated with both LOS and LLOS after controlling for sociodemographics and the departments of patient discharge and remained negatively associated with LLOS after controlling additionally for the year of patient discharge. CONCLUSION Emotional distress significantly prolonged the LOS and increased the LLOS of non-psychiatric inpatients across most departments and general hospitals. These impacts were moderated by the implementation of BS-GPS. Thus, BS-GPS has the potential as an effective, resource-saving strategy for enhancing mental health care and optimizing medical resources in general hospitals.
Humans ; Retrospective Studies ; Male ; Length of Stay/statistics & numerical data* ; Female ; Middle Aged ; Adult ; Psychological Distress ; Inpatients/psychology* ; Aged ; Anxiety/diagnosis* ; Depression/diagnosis*

Heart failure (HF) is a common end-stage clinical manifestation of cardiovascular diseases, imposing substantial health-related burdens worldwide. With its high mortality rates and poor long-term prognosis, there is a pressing need for novel therapies. SIRT1, a nicotinamide adenine dinucleotide (NAD⁺)-dependent deacetylase, has anti-cardiovascular aging properties and other cardioprotective effects, attracting much research attention in recent years. In addition, SIRT1 plays an important role in HF pathophysiology. This review summarized the roles of SIRT1 and its activators in HF, the changes of SIRT1 gene expression in cardiac tissues from animal models and HF patients, and the current status of clinical trials investigating SIRT1 activators as potential therapies for HF. This will provide new ideas for further exploration of pathological mechanisms and the development of clinical prevention strategies for HF.
Heart Failure/metabolism* ; Sirtuin 1/genetics* ; Humans ; Animals