ObjectiveTo investigate the effect of solute carrier family 7 member 5 (SLC7A5) inhibitor JPH203 on renal fibrosis induced by unilateral ureteral obstruction in mice. MethodsSixteen SPF male C57BL/6 mice were randomly divided into the control group and the experimental group, with 8 mice in each group. The mouse model of renal fibrosis was established by unilateral ureteral obstruction. From the third day after surgery, the mice in the control group were intraperitoneally injected with phosphate-buffered saline (PBS) for 11 consecutive days, and the injection dose was 200 μL/d. Mice in the experimental group received intraperitoneal injection of JPH203 (50 mg/kg) every day for 11 days. On day 14, the mice were euthanized, then the kidney tissues were obtained. Hematoxylin and eosin (HE) staining was used to assess renal tissue damage, Masson staining was used to evaluate collagen fiber deposition in the extracellular matrix, and immunohistochemistry was used to detect the levels of fibroblast activation markers α-smooth muscle actin (α-SMA) and collagen type Ⅰ (COL-Ⅰ) in kidney tissues. Western blotting was further performed to measure the expression levels of SLC7A5 and transforming growth factor-β1 (TGF-β1), as well as the phosphorylation levels of mammalian target of rapamycin complex 1 (mTORC1) signaling pathway-related molecules. Real-time quantitative PCR was used to verify changes in the mRNA levels of SLC7A5, α-SMA, and COL-Ⅰ in kidney tissues. ResultsCompared with the control group, the experimental group showed reduced destruction of renal tissue structure and a significantly lower pathological injury score (P<0.05). Additionally, collagen deposition in the extracellular matrix was decreased, and the percentage of collagen fiber area was significantly reduced (P<0.001) in the experimental group. The levels of fibroblast activation markers α-SMA and COL-Ⅰ were significantly lower in the experimental group (both P<0.001). The expression levels of SLC7A5 and TGF-β1 were also significantly decreased (P<0.001), and the phosphorylation levels of mTORC1 signaling pathway-related proteins 4E-BP1 and mTORC1 were significantly reduced (P<0.001). Real-time quantitative PCR confirmed that the mRNA levels of SLC7A5, α- SMA, and COL-Ⅰ in kidney tissues were significantly lower in the experimental group (P<0.001). ConclusionJPH203 may inhibit the progression of renal fibrosis in mice by suppressing SLC7A5 expression, regulating the mTORC1 signaling pathway, and altering fibroblast activation status.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

BACKGROUND: Pancreatic cancer is a lethal malignancy prone to gemcitabine resistance. The single-strand selective monofunctional uracil DNA glycosylase (SMUG1), which is responsible for initiating base excision repair, has been reported to predict the outcomes of different cancer types. However, the function of SMUG1 in pancreatic cancer is still unclear. METHODS: Gene and protein expression of SMUG1 as well as survival outcomes were assessed by bioinformatic analysis and verified in a cohort from Fudan University Shanghai Cancer Center. Subsequently, the effect of SMUG1 on proliferation, cell cycle, and migration abilities of SMUG1 cells were detected in vitro . DNA damage repair, apoptosis, and gemcitabine resistance were also tested. RNA sequencing was performed to determine the differentially expressed genes and signaling pathways, followed by quantitative real-time polymerase chain reaction and Western blotting verification. The cancer-promoting effect of forkhead box Q1 (FOXQ1) and SMUG1 on the ubiquitylation of myelocytomatosis oncogene (c-Myc) was also evaluated. Finally, a xenograft model was established to verify the results. RESULTS: SMUG1 was highly expressed in pancreatic tumor tissues and cells, which also predicted a poor prognosis. Downregulation of SMUG1 inhibited the proliferation, G1 to S transition, migration, and DNA damage repair ability against gemcitabine in pancreatic cancer cells. SMUG1 exerted its function by binding with FOXQ1 to activate the Protein Kinase B (AKT)/p21 and p27 pathway. Moreover, SMUG1 also stabilized the c-Myc protein via AKT signaling in pancreatic cancer cells. CONCLUSIONS SMUG1 promotes proliferation, migration, gemcitabine resistance, and c-Myc protein stability in pancreatic cancer via protein kinase B signaling through binding with FOXQ1. Furthermore, SMUG1 may be a new potential prognostic and gemcitabine resistance predictor in pancreatic ductal adenocarcinoma.
Humans ; Pancreatic Neoplasms/pathology* ; Forkhead Transcription Factors/genetics* ; Signal Transduction/genetics* ; Animals ; Cell Line, Tumor ; Proto-Oncogene Proteins c-akt/metabolism* ; Cell Proliferation/physiology* ; Mice ; Uracil-DNA Glycosidase/genetics* ; Female ; Male ; Gemcitabine ; Mice, Nude ; Apoptosis/physiology* ; Deoxycytidine/analogs & derivatives* ; Cell Movement/genetics*

Objective:To investigate the risk factors and their predictive efficacy for early postoperative infection in elderly patients with intertrochanteric femur fracture.Methods:A retrospective cohort study was conducted to analyze the clinical data of 286 elderly patients with intertrochanteric femur fracture admitted to Zhengzhou Orthopedic Hospital between August 2021 and August 2024, including 154 males and 132 females, aged 60-80 years [(72.5±5.8)years]. Fracture involved the left side in 148 patients and the right side in 138 patients. Internal fixation was performed on 214 patients and joint replacement on 72. Based on the occurrence of infection within two weeks postoperatively, the patients were divided into infection group ( n=25) and non-infection group ( n=261). Data were collected from the two groups, including basic information [gender, age, body mass index (BMI), cause of injury, fracture side], admission data (fasting blood glucose, diastolic blood pressure, systolic blood pressure), preoperative data [American Society of Anesthesiologists (ASA) classification, AO classification, serum C-reactive protein (CRP), serum albumin (Alb), serum CRP/Alb ratio, time from injury to surgery], and treatment-related information (surgical type, duration of surgery, intraoperative blood loss, quality of intraoperative reduction, postoperative antibiotic use). Univariate analysis and multivariate Logistic stepwise regression analysis were used to identify independent risk factors for early postoperative infection in elderly patients with intertrochanteric femur fracture. The receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of each factor. Results:Univariate analysis showed significant differences between the two groups in fasting blood glucose on admission, preoperative serum CRP, preoperative serum Alb, preoperative serum CRP/Alb ratio, and duration of surgery ( P<0.01). There were no significant differences between the two groups in the remaining variables ( P>0.05). Multivariate Logistic stepwise regression analysis indicated that fasting blood glucose on admission ( OR=2.65, 95% CI 1.32, 5.32, P<0.01), preoperative serum CRP ( OR=1.10, 95% CI 1.04, 1.18, P<0.01), preoperative serum Alb ( OR=0.79, 95% CI 0.70, 0.90, P<0.01), preoperative serum CRP/Alb ( OR=143.78, 95% CI 4.46, 46.77, P<0.01), and duration of surgery ( OR=1.07, 95% CI 1.02, 1.11, P<0.01) were significantly associated with early postoperative infection in elderly patients with intertrochanteric femur fracture. ROC curve analysis showed that the sensitivity and specificity of preoperative serum CRP/Alb in predicting early postoperative infection in elderly patients with intertrochanteric femur fracture were 88.00% and 88.10%, and that the AUC of preoperative serum CRP/Alb prediction was 0.92, significantly greater than the AUC predicted separately by fasting blood glucose at admission, preoperative serum CRP, preoperative serum Alb and duration of surgery (0.76, 0.75, 0.77, 0.76, respectively). The optimal cut-off value for the preoperative serum CRP/Alb ratio was 1.78. Conclusions:Fasting blood glucose on admission, preoperative serum CRP, Alb, CRP/Alb ratio, and duration of surgery are independent risk factors for early postoperative infection in elderly patients with intertrochanteric femur fracture. These factors all possess certain predictive value for early postoperative infection, but the preoperative serum CRP/Alb ratio demonstrates the best predictive efficacy.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To investigate the clinical value of 18F-NaF PET/CT coronary plague imaging in evaluating the long-term prognosis of patients with coronary artery disease (CAD). Methods:A retrospective cohort study was conducted among 54 patients (37 males and 17 females, aged (57.2±9.8) years) diagnosed with CAD from a multicenter study between September 2015 and October 2022. All patients underwent 18F-NaF PET/CT and coronary angiography (CAG) within 1 week, and the PET/CT imaging was performed at the First Hospital of Shanxi Medical University. Major adverse cardiovascular events (MACE) were followed up. ROC curves were established to obtain the optimal thresholds of SUV max and accumulated SUV max of all lesions of main coronary artery branches (S-SUV max) for predicting MACE. Cox proportional risk model and Kaplan-Meier method (log-rank test) were used to analyze the predictive value of PET parameters for MACE. Differences in metabolic parameters between 2 groups were compared by Mann-Whitney U test. Results:The median follow-up time of the 54 patients was 6.0(1.8, 6.6) years, and 13(24.1%) patients developed MACE, including 7 deaths, 5 myocardial infarction and 1 severe arrhythmia. S-SUV max in MACE group was significantly higher than that in the non-MACE group (2.64(2.08, 4.49) vs 1.83(0.95, 2.90); Z=-2.04, P=0.041). ROC curve showed that the optimal threshold of S-SUV max for MACE prediction was 2.05 (AUC=0.690). Multivariate Cox analysis showed that S-SUV max was a strong predictor of MACE (hazard ratio ( HR)=2.434(95% CI: 1.547-3.828), P<0.001). ROC curve showed that the optimal threshold of SUV max to predict MACE was 0.55 (AUC=0.659), and univariate Cox analysis showed that SUV max was a factor to predict MACE ( HR=10.192 (95% CI: 2.667-38.953), P=0.001). In 25 patients with incomplete revascularization (ICR), Kaplan-Meier analysis showed that the incidence of MACE in patients with positive 18F-NaF uptake (single medium stenosis (40%-70%) with SUV max≥0.55) was significantly higher than that in patients with negative 18F-NaF uptake (5/14 vs 0/11; χ2=6.07, P=0.014). Conclusions:18F-NaF PET/CT can be used as an independent predictor of MACE in patients with CAD and can quantitatively assess the long-term progression of moderate coronary artery stenosis. In the future, it is expected to be a new non-invasive way to guide the revascularization treatment decision of multi-vessel CAD.

Objective To explore the relationship between dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and clinical pathological features of invasive breast cancer and lymphovascular invasion(LVI).Methods Imaging and clinical pathological data were retrospectively collected from 508 patients with invasive breast cancer who underwent breast DCE-MRI at the First Medical Center of Chinese PLA General Hospital from January 2019 to August 2021.Patients were divided into the LVI-positive(LVI+)group(n=79)and LVI-negative(LVI-)group(n=429)based on postoperative pathological results.Univariate and multivariate logistic regression analyses were used to identify risk factors for LVI.Results Compared with LVI-group,LVI+group had a higher proportion of patients aged<45 years(44.3%vs.27.0%,P=0.002),non-mass-like enhancement(NME)(31.7%vs.17.7%,P=0.004),Ki-67 expression rate(40.0%vs.30.0%,P<0.001),high Ki-67 expression(94.9%vs.78.1%,P=0.001),Luminal B subtype(76.0%vs.60.1%,P=0.008),and positive axillary lymph nodes rate(72.2%vs.31.5%,P<0.001),while the proportion of Luminal A subtype was lower(2.5%vs.21.5%,P<0.001).Univariate and multivariate logistic regression analyses showed that age≥45 years(OR=0.468,95%CI 0.280-0.783,P=0.004)was an independent protective factor for LVI,while NME(OR=1.987,95%CI 1.126-3.444,P=0.016)was an independent risk factor.Compared with Luminal A subtype,patients with Luminal B subtype(OR=10.482,95%CI 3.164-64.923,P=0.001),HER-2 overexpression subtype(OR=11.571,95%CI 2.755-79.341,P=0.003)and triple-negative subtypes(OR=8.433,95%CI 1.985-57.908,P=0.009)had a higher risk of LVI.Conclusions Age≥45 years is an independent protective factor for LVI,while NME is an independent risk factor.Among molecular subtypes,patients with Luminal B,HER-2 overexpression and triple-negative subtypes have a higher risk of LVI compared with the Luminal A subtype.