The philosophy of “treating disease before its onset” is a fundamental concept of traditional Chinese medicine (TCM), permeating its diagnostic and therapeutic framework, and is central to clinical practice. However, current TCM diagnostic and treatment models for the “pre-disease to disease” window period face several limitations, including the lack of comprehensive clinical parameters, difficulties in characterizing and integrating heterogeneous multimodal data, and insufficient dynamic precision in interventions and efficacy evaluations. To address these issues, guided by Professor Candong Li’s theory of TCM stateology, this study focuses on integrating objective multimodal data. It proposes a new model for personalized TCM diagnosis and treatment targeting the “pre-disease to disease” window period. This approach first proposes the idea of restructuring the conceptual framework of “symptom” and integrating multi-source heterogeneous data at macroscopic, mesoscopic, and microscopic levels to form a three-dimensional assessment indicator system. By integrating graph neural networks, convolutional neural networks, attention mechanisms, and knowledge graph-guided weight allocation, this approach enables collaborative representation, alignment, and fusion of multi-source data. Subsequently, it plans to construct a multimodal fusion model at both feature and decision levels, in order to establish mappings between indicators and TCM state elements, and to screen key indicators characterizing pathological evolution during the window period. Furthermore, it proposes a technical path for enhancing model interpretability using methods such as SHapley Additive exPlanations (SHAP) and Ablation-CAM++. Finally, with state assessment as the core, it proposes the concept of constructing a dynamic evaluation method for individualized diagnosis and treatment based on time-series data analysis using algorithms such as long short-term memory (LSTM) networks and gated recurrent units (GRUs). Moreover, a causal inference framework and semi-supervised learning strategies are introduced to enable quantitative evaluation of individual intervention effects and to provide interpretable therapeutic feedback, forming a complete technical path from data representation and fusion, weight adjustment, and interpretability analysis, to dynamic diagnosis feedback. This study aims to address deficiencies in the current TCM diagnosis and treatment model during the “pre-disease to disease” window period and to provide an operational framework for the clinical practice of TCM’s “treating disease before its onset”.

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.

OBJECTIVES: To analyze bone mass distribution and the factors affecting bone mass in a general Chinese Han cohort undergoing physical examinations at our center. METHODS: We retrospectively collected the data of bone mineral density (BMD) measurements from 30 599 healthy Han Chinese adults (age≥20 years) who underwent dual-energy X-ray absorptiometry scans at our hospital from July, 2013 to July, 2023. Basic parameters including height, body weight, and gender were recorded, and descriptive statistics and correlation analyses were performed using R software. RESULTS: In this cohort, the male individuals had a mean peak BMD of 1.00±0.12 g/cm² in the lumbar vertebrae, 0.94±0.14 g/cm² in the femoral neck, and 0.99±0.13 g/cm² in the total hip, significantly higher than the values in the female individuals [0.99±0.12 g/cm² in the lumbar vertebrae (P=0.022), 0.79±0.11 g/cm² in the femoral neck (P<0.001), and 0.88±0.11 g/cm² in the total hip (P<0.001)]. In the overall cohort, the BMD values of the lumbar spine and femur decreased with age after reaching their peak levels. There was a positive correlation between BMD value and body mass index (BMI) in both male and female individuals. The 2013-2014 period recorded the lowest BMD values in the lumbar, hip, and femoral neck, which tended to increase steadily in the following years (2015-2023). CONCLUSIONS Our data suggest that the BMD values vary among different populations, and future multi-center studies using more accurate BMD detection technology are warranted to capture the variation patterns of BMD with demographic characteristics of specific populations.
Humans ; Bone Density ; Absorptiometry, Photon ; Male ; Female ; Retrospective Studies ; Osteoporosis/diagnostic imaging* ; Adult ; Middle Aged ; Lumbar Vertebrae/diagnostic imaging* ; China/epidemiology* ; Femur Neck/diagnostic imaging* ; Aged ; Beijing/epidemiology* ; Young Adult

The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

OBJECTIVE: To compare the efficacy and safety of intravenous colistin sulfate combined with nebulized inhalation versus intravenous monotherapy for pulmonary infections caused by carbapenem-resistant organism (CRO). METHODS: A multicenter retrospective cohort study was conducted. Clinical data were collected from patients admitted to the intensive care unit (ICU) of 10 tertiary class-A hospitals in Henan Province between July 2021 and May 2023, who received colistin sulfate for CRO pulmonary infections. Data included baseline characteristics, inflammatory markers [white blood cell count (WBC), neutrophil count (NEU), procalcitonin (PCT), C-reactive protein (CRP)], renal function indicators [serum creatinine (SCr), blood urea nitrogen (BUN)], life support measures, anti-infection regimens, clinical efficacy, microbiological clearance rate, and prognostic outcomes. Patients were divided into two groups: intravenous group (colistin sulfate monotherapy via intravenous infusion) and combination group ((intravenous infusion combined with nebulized inhalation of colistin sulfate). Changes in parameters before and after treatment were analyzed. RESULTS: A total of 137 patients with CRO pulmonary infections were enrolled, including 89 in the intravenous group and 48 in the combination group. Baseline characteristics, life support measures, daily colistin dose, and combination regimens (most commonly colistin sulfate plus carbapenems in both groups) showed no significant differences between two groups. The combination group exhibited higher clinical efficacy [77.1% (37/48) vs. 59.6% (52/89)] and microbiological clearance rate [60.4% (29/48) vs. 39.3% (35/89)], both P < 0.05. Pre-treatment inflammatory and renal parameters showed no significant differences between two groups. Post-treatment, the combination group showed significantly lower WBC and CRP [WBC (×10⁹/L): 8.2±0.5 vs. 10.9±0.6, CRP (mg/L): 14.0 (5.7, 26.6) vs. 52.1 (24.4, 109.6), both P < 0.05], whereas NEU, PCT, SCr, and BUN levels showed no significant between two groups. ICU length of stay was shorter in the combination group [days: 16 (10, 25) vs. 21 (14, 29), P < 0.05], although mechanical ventilation duration and total hospitalization showed no significant differences between two groups. CONCLUSIONS Intravenous colistin sulfate combined with nebulized inhalation improved clinical efficacy and microbiological clearance in CRO pulmonary infections with an acceptable safety profile.
Humans ; Colistin/therapeutic use* ; Retrospective Studies ; Administration, Inhalation ; Anti-Bacterial Agents/therapeutic use* ; Carbapenems/pharmacology* ; Male ; Female ; Middle Aged ; Gram-Negative Bacteria/drug effects* ; Aged ; Treatment Outcome ; Respiratory Tract Infections/drug therapy*

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective:To investigate the inpact of thyroid cancer-derived cancer-associated fibroblasts(CAF) autophagy on papillary thyroid cancer(PTC).Methods:CAF and normal fibroblasts were isolated from cancerous and adjacent normal thyroid tissues from four PTC patients. Expressions of fibroblast activation protein(FAP) and α-smooth muscle actin in cells were assessed. Conditioned medium of CAF and normal fibroblasts were prepared and used to culture PTC cells. The effects of CAF and normal fibroblasts on survival, proliferation, migration, invasion and iodine uptake of PTC cells were evaluated through cell proliferation assay, cell scratch assay, cell invasion assay, and cell iodine uptake assay. The autophagy level of CAF was also evaluated. Autophagy inhibition and activation were used to regulate the autophagy of CAF, and then their effects on PTC cell proliferation, migration and invasion were further evaluated. The in vivo effect of CAF autophagy on PTC xenograft tumor growth was evaluated.Results:CAF exhibited higher FAP expression and basal autophagy levels. PTC cells co-cultured with CAF-conditioned media showed enhanced proliferation, migration, invasion, and reduced iodine uptake. Autophagy inhibition reduced these effects, while autophagy activation further promoted them. In vivo, inhibiting CAF autophagy suppressed tumor growth.Conclusions:CAF promotes PTC cell malignancy through autophagy activation, enhancing proliferation, migration, and invasion while reducing iodine uptake.

Objective:To investigate the level of urinary serine protease(Corin) in early diabetic kidney disease(DKD) and its correlation with clinical stage.Methods:One hundred and seventy-three patients with type 2 diabetes mellitus(DM) from two tertiary A hospitals in Henan, diagnosed between April 2023 and December 2023 were selected as the research group, and 120 healthy subjects were selected as the control group. Basic clinical information and laboratory data were collected, and urinary Corin level was detected. DM patients were classified into G1-G5 stages based on estimated glomerular filtration rate(eGFR), and those in the early DKD stages(G1-G3) were further divided into A1-A3 subgroups based on urinary albumin/creatinine ratio(ACR). Spearman correlation analysis was performed to assess relationships between urinary Corin and other indicators, linear regression analysis identified factors influencing urinary Corin in early DKD patients, logistic regression analysis evaluated the risk factors for early DKD, and receiver operating characteristic(ROC) curve analysis determined the diagnostic value of urinary Corin in early DKD. Results:Urinary Corin levels were significantly higher in early DKD patients compared to healthy controls, with levels increasing as ACR rose( P<0.05). Urinary Corin was positively associated with serum creatinine( r=0.570), urea( r=0.458), cystatin C( r=0.693), ACR( r=0.616), urinary transferrin( r=0.448), urinary α1 microglobulin( r=0.507), urinary n-acetyl-β-D-glucosaminase( r=0.388) and A subgroup( r=0.692) while was negatively correlated with eGFR( r=-0.647), albumin( r=-0.312)(all P<0.05). eGFR was the only independent factor affecting urinary Corin. After adjusting for confounding factors in logistic regression analysis, urinary Corin was still an independent influencing factor for early DKD. ROC curve analysis indicated that urinary Corin had a diagnostic AUC of 0.842(95% CI 0.791-0.892, P<0.001), with a cut-off value of 2 226.04 pg/mL, sensitivity of 0.712, and specificity of 0.858 for early DKD diagnosis. Conclusions:Urinary Corin was elevated in early DKD patients and correlated with clinical stage. Urinary Corin is an independent factor of early DKD, and a reliable predictor of early DKD diagnosis.

Objective:To explore the feasibility and and clinical efficacy of lingual mucosa replacement ureteral stenosis repair and plasty for the treatment of long segment ureteral polyps.Methods:Clinical data of 3 patients (4 sides) with long-segment ureteral polyps admitted to the Second Hospital of Lanzhou University from October 2017 to October 2019 were retrospectively analyzed. Two cases were male and one case was female. The ages were22, 16, and 45 years old. Preoperative urologic ultrasound, CT urography and ureteroscopy were performed. The lesions were located on the left side in 3 cases and on the right side in 1 case; the stenosis was located in the middle and upper ureter; the length of the ureteral stenosis was 6, 7, 6, and 6 cm, respectively; and the preoperative blood creatinine was 72, 85, and 70 μmol/L, respectively. Three cases underwent ureteral stenosis repair and plasty with tongue mucosal substitution. During the operation, the ureter was fully exposed and longitudinally incised, polyps were removed, and 7.0-10.0 cm long and 1.5-2.0 cm wide lingual mucosa was harvested according to the length of the stenosis, and then the lingual mucosa was transplanted to the muscular layer and the inner surface of the sheath in the stenosed ureter, fixed with 6-0 thread until the muscular layer was rolled into shape and wrapped with a large omentum. All of them left one double-J tube in the ureter on the affected side. Perioperative results and complications were recorded. The patients' blood creatinine and anterior and posterior renal pelvic diameters were compared before and after treatment.Results:In our study, all three 4-sided surgeries were successfully completed without any serious intraoperative or postoperative complications (Clavien-Dindo score ≥ grade Ⅲ). Mean surgical. Time was (240.0±49.0) min, intraoperative bleeding was 50 ml, postoperative drain retention time was (6.3±2.5) d, and median postoperative hospitalization time was 6.5(3, 9)d. The double J-tube was removed at 3 months postoperatively, and renal function and imaging tests were reviewed. Because the postoperative follow-up results of patient 1 were missing, the mean value of blood creatinine in the other 2 patients was 73.0 μmol/L at 3 months postoperatively, which was significantly improved compared with the preoperative value of 58.2 μmol/L, and the difference was statistically significant ( P < 0.05). And the average value of anterior and posterior renal pelvic separation diameters of the other 2 patients after surgery was <5 mm, which was significantly improved compared with the preoperative value of 17.9 mm, but the difference was not statistically significant ( P>0.05).There was no restenosis in all 2 patients after surgery, and the intravenous urography showed that the ureter was patent after the surgery, and the degree of urinary obstruction did not aggravate. The group was followed up for 3 to 8 months (mean 4.7 months), and no recent complications have occurred so far. Conclusions:Lingual mucosa replacement ureteral stenosis repair and plasty for the treatment of ureteral polyps in the long segment has a high success rate and precise efficacy, and its operation is feasible.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.