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 association between serum IgG concentration and renal prognosis in patients with IgA nephropathy (IgAN).Methods:It was a multi-center retrospective cohort study, patients with biopsy proven primary IgAN who were recorded in the Chinese IgA Nephropathy Information Registration System between April 1996 and September 2018 were included. Exclusion criteria were: (1) age <18 years; (2) <8 glomeruli in biopsy specimens; (3) estimated glomerular filtration rate (eGFR) <15 ml·min -1·(1.73 m 2) -1 at biopsy; (4) missing baseline serum IgG values; (5) incomplete follow-up data; (6) follow-up duration <12 months. Enrolled patients were divided into 3 groups according to the baseline tertiles of serum IgG: ≤9.50 g/L (G1 group), 9.51-11.99 g/L (G2 group), and ≥12.00 g/L (G3 group). Clinical, and pathological parameters were compared across groups. The endpoint events were defined as doubled serum creatinine level from baseline, or end-stage renal disease (ESRD). Results:A total of 1 976 IgAN patients were included in this study, 631 were in G1 group, 664 in G2 group, and 681 in G3 group. The comparison of baseline clinical data showed that there were statistically significant differences among the three groups in terms of gender, age, microscopic hematuria, edema, body mass index, systolic blood pressure, diastolic blood pressure, hemoglobin, serum creatinine, eGFR, 24-hour urine protein quantity, blood uric acid, blood albumin, serum IgA, serum IgM, the proportion of using immunosuppressants, and the proportion of using glucocorticoids (all P<0.05). In terms of pathology, the higher the serum IgG concentration, the relatively less severe the overall renal pathological damage. The results of univariate Cox regression analysis showed that gender, systolic blood pressure, diastolic blood pressure, hemoglobin, serum creatinine, eGFR, 24-hour urine protein quantity, total protein, serum albumin, globulin, serum IgG, Oxford renal pathological classification, glomerular sclerosis ratio, and glomerular IgM deposition were all associated with the occurrence of renal endpoint events (all P<0.05). Based on clinical practice and previous studies, after adjusting for gender, age, systolic blood pressure, diastolic blood pressure, eGFR, 24-hour urine protein quantity, body mass index, Oxford renal pathological classification, glomerular sclerosis ratio, and the use of renin-angiotensin-aldosterone system inhibitors, glucocorticoids, and immunosuppressants, multivariate Cox regression analysis showed that as a continuous variable, the baseline serum IgG level ( HR=0.91, 95% CI 0.87-0.96) was independently associated with the risk of renal endpoint events in IgAN patients; as a categorical variable, with serum IgG ≤ 9.50 g/L as the reference, serum IgG 9.51-11.99 g/L and serum IgG ≥ 12.00 g/L were independent factors for the occurrence of renal endpoint events in IgAN patients ( HR=0.69, 95% CI 0.49-0.96, P=0.027; HR=0.50, 95% CI 0.34-0.74, P<0.001). During a median follow-up of 33(21, 53) months started from the date of renal biopsy and continued until December 31, 2019, the median follow-up duration was 33 (21, 53) months, and a total of 232 patients (11.74%) reached the composite endpoint. Kaplan-Meier survival analysis showed that the higher the serum IgG concentration in patients with IgAN, the higher their cumulative renal survival rate (Log-rank test, χ2=47.176, P<0.001). Conclusion:The higher level of serum IgG at diagnosis is associated with better clinicopathologic features and renal outcomes, and may portend better renal survival in IgAN patients.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

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 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.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

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

OBJECTIVE: To analyze the correlation between the expression levels of Tim-3, C-myc and the proportion of T lymphocyte subsets and prognosis in patients with acute lymphoblastic leukemia (ALL). METHODS: The research group selected 60 ALL patients admitted to our hospital from December 2019 to December 2021, while the control group selected 55 healthy volunteers who underwent physical examination in our hospital. The expression levels of Tim-3, C-myc mRNA and the proportion of T lymphocyte subsets in the two groups were detected. The mortality rate of ALL patients was calculated, and the correlation between the expression levels of Tim-3, C-myc, and the proportion of T lymphocyte subsets and pathological features and prognosis was analyzed. RESULTS: Compared with the control group, the levels of Tim-3, C-myc and CD8⁺ in the research group were increased, while the levels of CD3⁺ , CD4⁺ and CD4⁺ /CD8⁺ were decreased (all P < 0.001). The levels of Tim-3, C-myc mRNA, CD3⁺ , CD4⁺ , CD8⁺ , CD4⁺ /CD8⁺ were correlated with risk classification and extramedullary infiltration (all P < 0.05). The survival rate of patients with low expression of Tim-3, C-myc, and CD8⁺ was higher than that of patients with high expression, while the survival rate of patients with high expression of CD3⁺ , CD4⁺ , and CD4⁺ /CD8⁺ was higher than that of patients with low expression (all P < 0.05). Univariate analysis showed that the deceased patients had higher proportions of extramedullary infiltration and high-risk classification, as well as higher levels of Tim-3, C-myc, and CD8⁺ , while lower levels of CD3⁺ , CD4⁺ , and CD4⁺ /CD8⁺ compared with surviving patients (all P < 0.01). Multivariate logistic regression analysis showed that extramedullary invasion, risk classification, Tim-3, C-myc, CD3⁺ , CD4⁺ , CD8⁺ , CD4⁺ /CD8⁺ were the main factors affecting the prognosis of ALL patients (all P < 0.05). ROC curve analysis showed that the combination of Tim-3, C-myc, and T lymphocyte subsets had higher sensitivity and accuracy in predicting prognosis of ALL patients compared with the single diagnosis of Tim-3, C-myc, CD3⁺ , CD4⁺ , CD8⁺ , and CD4⁺ /CD8⁺ (P < 0.05). CONCLUSION ALL patients show higher levels of Tim-3, C-myc mRNA and CD8⁺ but lower levels of CD3⁺ , CD4⁺ and CD4⁺/CD8⁺. Moreover, the expression levels of Tim-3, C-myc, CD3⁺ , CD4⁺ , CD8⁺ and CD4⁺/CD8⁺ are correlated with extramedullary invasion, high-risk classification and prognosis.
Humans ; Hepatitis A Virus Cellular Receptor 2/metabolism* ; Prognosis ; Proto-Oncogene Proteins c-myc/metabolism* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/diagnosis* ; T-Lymphocyte Subsets ; Male ; Female ; Adult ; Middle Aged ; Adolescent ; RNA, Messenger

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.