Oxidative stress is a pivotal factor in the onset and progression of diabetic kidney disease （DKD）， and it plays an essential role in the prevention and treatment of DKD. The "Gaozhuo" pathogenesis posits that DKD is characterized by the invasion of Gaozhuo and damage to the kidney collaterals， with the underlying cause being the insufficiency of spleen Qi and the internal formation of Gaozhuo， which provides valuable guidance on oxidative stress. The insufficiency of spleen Qi and the internal formation of Gaozhuo represent a dynamic， evolving process. Gaozhuo invades the kidney collaterals， impairs kidney Qi， and progressively leads to the congealing and stagnation of Gaozhuo and blood， ultimately resulting in the failure of both the spleen and kidneys. The damage caused by Gaozhuo to the kidney collaterals and kidney Qi is analogous to the organ and functional damage of the kidneys induced by excessive reactive oxygen species and oxidative stress. Damage to the kidney collaterals means organic injuries to the glomeruli， renal tubules， and renal interstitium， and the depletion of kidney Qi refers to damage to glomerular filtration and renal tubular reabsorption. The congealing and stagnation of Gaozhuo and blood in the kidney collaterals is similar to oxidative stress-induced thickening of the glomerular basement membrane and fibrosis. The interaction between spleen and kidney Qi deficiency and the congealing and stagnation of Gaozhuo and blood creates a vicious cycle that exacerbates the condition， ultimately evolving into the failure of both the spleen and kidneys. The failure of the spleen and kidneys is analogous to renal failure， and its extreme manifestation is end-stage renal disease and uremia. The treatment of oxidative stress in DKD with traditional Chinese medicine （TCM） is based on the principles of strengthening the spleen and tonifying the kidneys， and dispelling turbidity and removing blood stasis. According to the syndrome type， it is recommended to use methods such as strengthening the spleen and tonifying Qi while dispelling dampness and removing turbidity， strengthening the spleen and tonifying the kidneys while dispelling dampness and removing turbidity， strengthening the spleen and tonifying the kidneys while dispelling turbidity and removing blood stasis， or consolidating the spleen and kidneys while clearing away turbidity and blood stasis.

Objective: To investigate the effects of Zuogui Jiangtang Yishen Formula (左归降糖益肾方, ZGJTYSF) in regulating the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3)/caspase-1/gasdermin D (GSDMD) signaling axis on pyroptosis in rats with diabetic kidney disease (DKD). Methods: Fifty male specific pathogen-free (SPF) grade Goto-Kakizaki (GK) rats (12 weeks old) were fed a high-fat diet for one month to establish an early DKD model. Model establishment was confirmed when fasting blood glucose (FBG) ≥ 11.1 mmol/L and urinary albumin-to-creatinine ratio (uACR) ≥ 30 mg/g. The successfully modeled early DKD rats were randomly divided by random number table into five groups (n = 10 per group): model group; dapagliflozin group (1.0 mg/kg, by gavage, served as positive control); and low-, medium-, and high-dose of ZGJTYSF groups (4.9, 9.9, and 19.9 g/kg, respectively, by gavage). Age-matched male SPF Wistar rats (n = 10) served as control group. Rats in control and model groups were gavaged with equivalent volumes of distilled water. Treatment lasted 12 weeks. Changes in uACR, FBG, and renal function were observed in all groups. Hematoxylin-eosin (HE), periodic acid-Schiff (PAS), and Masson staining were used to observe renal histopathological changes. Immunohistochemistry was performed to detect the localization and expression of caspase-1, GSDMD, and NLRP3 in rat renal tissues. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL) was utilized to detect pyroptosis in renal tissues. Quantitative real-time polymerase chain reaction (qPCR) and Western blot were applied to detect mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, interleukin (IL)-1β, and IL-18. Results: Compared with model group, all doses of ZGJTYSF showed reductions in FBG, with medium- and high-dose of ZGJTYSF groups demonstrating significant decreases at week 8 and 12 (P < 0.05). For uACR, all doses of ZGJTYSF groups exhibited a decreasing trend, with high-dose of ZGJTYSF group being significantly lower than low- and medium-dose of ZGJTYSF groups at week 12 (P < 0.05) and showing no significant difference from dapagliflozin group (P > 0.05). No significant differences in renal function parameters (serum creatinine, blood urea nitrogen, and uric acid) were observed among groups (P > 0.05). Histopathological examination revealed milder glomerular and tubular lesions in both ZGJTYSF groups and dapagliflozin group, with renal pathological changes in high-dose of ZGJTYSF group resembling those in dapagliflozin group. Immunohistochemistry demonstrated significantly reduced expression of caspase-1, GSDMD, and NLRP3 in renal tissues of dapagliflozin group and high-dose of ZGJTYSF group compared with model group (P < 0.05 or P < 0.01), while the differences in low- and medium-dose of ZGJTYSF groups were not statistically significant (P > 0.05). TUNEL assay showed significantly fewer TUNEL-positive cells in renal tissues of dapagliflozin and high-dose of ZGJTYSF groups (P < 0.01), indicating a marked reduction in pyroptotic cells. Molecular analysis revealed that compared with model group, both dapagliflozin and high-dose of ZGJTYSF groups showed significantly downregulated mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, IL-1β, and IL-18 in renal tissues (P < 0.01), while low- and medium-dose of ZGJTYSF groups showed downward trends without statistical significance (P > 0.05). Conclusion ZGJTYSF may inhibit renal pyroptosis by regulating the NLRP3/caspase-1/GSDMD signaling axis, thereby preventing and treating early renal injury in DKD and delaying the onset and progression of DKD.

Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.

The circadian clock plays a critical role in regulating various physiological processes, including gene expression, metabolic regulation, immune response, and the sleep-wake cycle in living organisms. Post-translational modifications (PTMs) are crucial regulatory mechanisms to maintain the precise oscillation of the circadian clock. By modulating the stability, activity, cell localization and protein-protein interactions of core clock proteins, PTMs enable these proteins to respond dynamically to environmental and intracellular changes, thereby sustaining the periodic oscillations of the circadian clock. Different types of PTMs exert their effects through distincting molecular mechanisms, collectively ensuring the proper function of the circadian system. This review systematically summarized several major types of PTMs, including phosphorylation, acetylation, ubiquitination, SUMOylation and oxidative modification, and overviewed their roles in regulating the core clock proteins and the associated pathways, with the goals of providing a theoretical foundation for the deeper understanding of clock mechanisms and the treatment of diseases associated with circadian disruption.
Protein Processing, Post-Translational/physiology* ; Circadian Rhythm/physiology* ; Humans ; Animals ; CLOCK Proteins/physiology* ; Circadian Clocks/physiology* ; Phosphorylation ; Acetylation ; Ubiquitination ; Sumoylation

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

OBJECTIVE To explore the application value of a diagnostic model based on machine learning and SHAP in the diagnosis of severe pneumonia caused by adenovirus infection in children.METHODS A total of 562 children with adenovirus infection who were admitted to Wuhan Third Hospital from Mar.2023 to Apr.2024 were selected and divided into a non-pneumonia group(n=236)and a pneumonia group(n=326).The pneumonia group was further divided into a training set(n=245)and a validation set(n=81)at a ratio of 3∶1.The training set was further categorized into a severe group(n=90)and a non-severe group(n=155)based on the severity of pneumonia.M ultivariate logistic regression analysis was used to identify the risk factors for severe pneumonia in children with adenovirus infection,and collinearity diagnosis was performed.Receiver operating characteristic(ROC)curves were used to validate the predictive performance of the model in both the training and validation sets,and the optimal model was selected.The optimal predictive model was interpreted using SHAP.RESULTS Compared with the non-pneumonia group,the pneumonia group had a high proportion of children aged＜2 years,with cough,wheezing,pulmonary consolidation,pleural effusion,mixed infections and allergic history,as well as long hospital stays and fever duration(P＜0.05).After univariate analysis and collinearity diagnosis to exclude confounding factors,the length of hospital stay(OR=1.112),fever duration(OR=1.964),wheezing(OR=2.430),pulmonary consolidation(OR=2.546),mixed infections(OR=2.617)and LDH level(OR=1.613)were identified as risk factors for severe pneumonia in children with adenovirus infection(P＜0.05).Among the eight machine learning models constructed based on these risk factors,the gradient boosting machine(GBM)model demonstrated the best performance in predicting severe pneumonia in children with adenovirus in-fection,with area under the curve(AUC)of 0.796 and 0.785 in the training and validation sets,respectively.SHAP analysis revealed that the top four contributing characteristics were LDH level,wheezing,fever duration and pulmonary consolidation.CONCLUSIONS The GBM model exhibits optimal performance in predicting the risk of severe pneumonia in children with adenovirus infection.Among the predictive characteristics,LDH level,wheezing,fever duration and pulmonary consolidation are significant,providing valuable reference for clinical di-agnosis and treatment.

OBJECTIVE: To investigate the effectiveness of tibial transverse transport (TTT) in treating Wagner grade 3-4 type 2 diabetic foot ulcers and analyze dynamic changes in immunoglobulin levels. METHODS: The clinical data of 68 patients with Wagner grade 3-4 type 2 diabetic foot ulcers treated with TTT between May 2022 and September 2023 was retrospectively analyzed. The cohort included 49 males and 19 females, aged 44-91 years (mean, 67.3 years), with 40 Wagner grade 3 and 28 grade 4 ulcers. The duration of type 2 diabetes ranged from 5 to 23 years, with an average of 10 years. The number of wound healing cases, healing time, amputation cases, death cases, and complications were observed and recorded. Serum samples were collected at 6 key time points [1 day before TTT and 3 days, 7 days (the first day of upward transverse transfer), 14 days (the first day of downward transverse transfer), 21 days (the first day after the end of transfer), 36 days (the first day after the removal of the transfer device)], and the serum immunoglobulin levels were detected by flow cytometry including immunoglobulin G (IgG), IgA, IgM, IgE, complement C3 (C3), C4, immunoglobulin light chain κ (KAP), immunoglobulin light chain λ (LAM). RESULTS: All the 68 patients were followed up 6 months. Postoperative pin tract infection occurred in 3 cases and incision infection in 2 cases. Amputation occurred in 5 patients (7.4%) at 59-103 days after operation, and 8 patients (11.8%) died at 49-77 days after operation; the wounds of the remaining 55 patients (80.9%) healed in 48-135 days, with an average of 80 days. There was no recurrence of ulcer, peri-osteotomy fracture, or local skin necrosis during follow-up. The serum immunoglobulin levels of 55 patients with wound healing showed that the levels of IgG and IgM decreased significantly on the 3rd and 7th day after operation compared with those before operation ( P<0.05), and gradually returned to the levels before operation after 14 days, and reached the peak on the 36th day. IgA levels continued to decrease with time, and there were significant differences at all time points when compared with those before operation ( P<0.05). The level of IgE significantly decreased at 21 days after operation compared with that before operation ( P<0.05), while it was higher at other time points than that before operation, but the difference was not significant ( P>0.05). The level of C3 showed a clear treatment-related increase, which was significantly higher on the 7th, 14th, and 21st days after operation than that before operation ( P<0.05), and the peak appeared on the 14th day. The change trend of C4 level was basically synchronous with that of C3, but the amplitude was smaller, and the difference was significant at 7 and 14 days after operation compared with that before operation ( P<0.05). There was no significant difference in KAP/LAM between different time points before and after operation ( P>0.05). CONCLUSION TTT can accelerate wound healing, effectively treat diabetic foot ulcer, and reduce amputation rate, and has definite effectiveness. The potential mechanisms of TTT in the treatment of diabetic foot ulcers include the dynamic regulation of IgG, IgA, IgM, and IgE levels to balance the process of inflammation and repair, and the periodic increase of C3 and C4 levels may promote tissue cleaning, angiogenesis, and anti-infection defense.
Humans ; Male ; Female ; Middle Aged ; Aged ; Diabetic Foot/immunology* ; Wound Healing ; Adult ; Retrospective Studies ; Aged, 80 and over ; Treatment Outcome ; Tibia/transplantation* ; Diabetes Mellitus, Type 2/complications* ; Amputation, Surgical ; Immunoglobulins/blood* ; Immunoglobulin G/blood*

Objective To develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

PURPOSE: To investigate the incidence and influencing factors of bone loss in patients with spinal cord injury (SCI). METHODS: A retrospective case-control study was conducted. Patients with SCI in our hospital from January 2019 to March 2023 were collected. According to the correlation between bone mineral density (BMD) at different sites, the patients were divided into the lumbar spine group and the hip joint group. According to the BMD value, the patients were divided into the normal bone mass group (t > -1.0 standard deviation) and the osteopenia group (t ≤ -1.0 standard deviation). The influencing factors accumulated as follows: gender, age, height, weight, cause of injury, injury segment, injury degree, time after injury, start time of rehabilitation, motor score, sensory score, spasticity, serum value of alkaline phosphatase, calcium, and phosphorus. The trend chart was drawn and the influencing factors were analyzed. SPSS 26.0 was used for statistical analysis. Correlation analysis was used to test the correlation between the BMD values of the lumbar spine and bilateral hips. Binary logistic regression analysis was used to explore the influencing factors of osteoporosis after SCI. p < 0.05 was considered statistically significant. RESULTS: The incidence of bone loss in patients with SCI was 66.3%. There was a low concordance between bone loss in the lumbar spine and the hip, and the hip was particularly susceptible to bone loss after SCI, with an upward trend in incidence (36% - 82%). In this study, patients with SCI were divided into the lumbar spine group (n = 100) and the hip group (n = 185) according to the BMD values of different sites. Then, the lumbar spine group was divided into the normal bone mass group (n = 53) and the osteopenia group (n = 47); the hip joint group was divided into the normal bone mass group (n = 83) and the osteopenia group (n = 102). Of these, lumbar bone loss after SCI is correlated with gender and weight (p = 0.032 and < 0.001, respectively), and hip bone loss is correlated with gender, height, weight, and time since injury (p < 0.001, p = 0.015, 0.009, and 0.012, respectively). CONCLUSIONS The incidence of bone loss after SCI was high, especially in the hip. The incidence and influencing factors of bone loss in the lumbar spine and hip were different. Patients with SCI who are male, low height, lightweight, and long time after injury were more likely to have bone loss.
Humans ; Spinal Cord Injuries/complications* ; Male ; Female ; Retrospective Studies ; Incidence ; Adult ; Bone Density ; Middle Aged ; Case-Control Studies ; Osteoporosis/etiology* ; Lumbar Vertebrae ; Bone Diseases, Metabolic/etiology* ; Aged ; Risk Factors