ObjectiveTo explore the mechanism by which Tangbikang granules improve diabetic peripheral neuropathy based on ferroptosis mediated by the adenosine monophosphate-activated protein kinase/nuclear factor erythroid 2-related factor 2 （AMPK/Nrf2） signaling pathway. MethodsA diabetes model was established using spontaneous male Zucker diabetic fatty （ZDF） rats. After successful modeling， the rats were divided into a normal group， a model group， high-， medium-， and low-dose Tangbikang granules groups， and a metformin hydrochloride group. The high-， medium-， and low-dose Tangbikang granules groups were administered by gavage at doses of 2.5， 1.25， 0.625 g·kg^-1， respectively. The metformin hydrochloride group received 0.135 g·kg^-1 by gavage， while the remaining groups received an equal volume of deionized water. Administration continued for 12 weeks. Blood glucose levels were measured after administration， and at 4， 8， 12 weeks. Following the 12-week intervention， the thermal pain threshold and the sciatic nerve conduction velocity （SNCV） were measured. The levels of malondialdehyde （MDA）， superoxide dismutase （SOD）， and adenosine triphosphate （ATP） in the sciatic nerve were measured using enzyme-linked immunosorbent assay （ELISA）. Morphological changes in the sciatic nerve were observed using hematoxylin and eosin （HE） staining， and the ultrastructural changes were examined using transmission electron microscopy. The levels of glutathione peroxidase 4 （GPx4） were detected using immunofluorescence （IF） assay. The protein expression levels of p-AMPK， Nrf2， GPx4， and acyl-CoA synthetase long-chain family member 4 （ACSL4） were detected using Western blot. ResultsCompared with the normal group， the model group had significantly higher blood glucose levels after administration and at weeks 4， 8 and 12 （P<0.01）. The thermal pain threshold was significantly prolonged （P<0.01）， and the SNCV was significantly slowed down （P<0.01）. The SOD and ATP levels significantly decreased （P<0.01）， while the MDA levels significantly increased （P<0.01）. Pathologically， the sciatic nerve fibers in the model group showed a dispersed structure， disordered and sparse arrangement， axonal atrophy， irregular myelin sheath halo， increased and swollen Schwann cell nuclei， obvious endoneurial fibrosis， and collagen hyperplasia. Immunofluorescence assay revealed fragmented red fluorescence and significantly reduced expression of GPx4 （P<0.01）. Western blot analysis showed significantly decreased protein expression levels of p-AMPK， Nrf2， and GPx4 （P<0.01）， and significantly increased expression of ACSL4 （P<0.01） in the model group. Compared with the model group， fasting blood glucose level decreased significantly in the high-dose Tangbikang granules group at weeks 4 and 12 （P<0.05）. The thermal pain threshold was significantly shortened in the high- and medium-dose Tangbikang granules groups （P<0.01）. The SNCV was significantly accelerated in the high- and medium-dose Tangbikang granules groups （P<0.01）. The SOD levels were significantly elevated in the high-dose Tangbikang granules group （P<0.01）. The MDA levels significantly decreased in all Tangbikang granules groups （P<0.01）. Both the metformin hydrochloride group and the high-dose Tangbikang granules group exhibited relatively orderly and densely arranged sciatic nerve fibers with more regular myelin sheath halos. The GPx4 expression significantly increased in both the metformin hydrochloride group and all Tangbikang granules groups （P<0.01）. The protein expression levels of p-AMPK， Nrf2， and GPx4 were significantly increased （P<0.01）， while ACSL4 protein expression significantly decreased （P<0.01）. ConclusionTangbikang granules may improve peripheral neuropathy by suppressing ferroptosis through the regulation of the AMPK/Nrf2 signaling pathway.

BACKGROUND: The primary limitation to kidney transplantation is organ shortage. Recent progress in gene editing and immunosuppressive regimens has made xenotransplantation with porcine organs a possibility. However, evidence in pig-to-human xenotransplantation remains scarce, and antibody-mediated rejection (AMR) is a major obstacle to clinical applications of xenotransplantation. METHODS: We conducted a kidney xenotransplantation in a brain-dead human recipient using a porcine kidney with five gene edits (5GE) on March 25, 2024 at Xijing Hospital, China. Clinical-grade immunosuppressive regimens were employed, and the observation period lasted 22 days. We collected and analyzed the xenograft function, ultrasound findings, sequential protocol biopsies, and immune surveillance of the recipient during the observation. RESULTS: The combination of 5GE in the porcine kidney and clinical-grade immunosuppressive regimens prevented hyperacute rejection. The xenograft kidney underwent delayed graft function in the first week, but urine output increased later and the single xenograft kidney maintained electrolyte and pH homeostasis from postoperative day (POD) 12 to 19. We observed AMR at 24 h post-transplantation, due to the presence of pre-existing anti-porcine antibodies and cytotoxicity before transplantation; this AMR persisted throughout the observation period. Plasma exchange and intravenous immunoglobulin treatment mitigated the AMR. We observed activation of latent porcine cytomegalovirus toward the end of the study, which might have contributed to coagulation disorder in the recipient. CONCLUSIONS 5GE and clinical-grade immunosuppressive regimens were sufficient to prevent hyperacute rejection during pig-to-human kidney xenotransplantation. Pre-existing anti-porcine antibodies predisposed the xenograft to AMR. Plasma exchange and intravenous immunoglobulin were safe and effective in the treatment of AMR after kidney xenotransplantation.
Transplantation, Heterologous/methods* ; Kidney Transplantation/methods* ; Heterografts/pathology* ; Immunoglobulins, Intravenous/administration & dosage* ; Graft Survival/immunology* ; Humans ; Animals ; Sus scrofa ; Graft Rejection/prevention & control* ; Kidney/pathology* ; Gene Editing ; Species Specificity ; Immunosuppression Therapy/methods* ; Plasma Exchange ; Brain Death ; Biopsy ; Male ; Aged

Metabolic diseases characterized by an imbalance in energy homeostasis represent a significant global health challenge. Individuals with metabolic diseases often suffer from complications related to disorders in lipid metabolism, such as obesity and non-alcoholic fatty liver disease (NAFLD). Understanding core genes involved in lipid metabolism can advance strategies for the prevention and treatment of these conditions. Stearoyl-CoA desaturase 1 (SCD1) is a key enzyme in lipid metabolism that converts saturated fatty acids into monounsaturated fatty acids. SCD1 plays a crucial regulatory role in numerous physiological and pathological processes, including energy homeostasis, glycolipid metabolism, autophagy, and inflammation. Abnormal transcription and epigenetic activation of Scd1 contribute to abnormal lipid accumulation by regulating multiple signaling axes, thereby promoting the development of obesity, NAFLD, diabetes, and cancer. This review comprehensively summarizes the key role of SCD1 as a metabolic hub gene in various (patho)physiological contexts. Further it explores potential translational avenues, focusing on the development of novel SCD1 inhibitors across interdisciplinary fields, aiming to provide new insights and approaches for targeting SCD1 in the prevention and treatment of metabolic diseases.
Stearoyl-CoA Desaturase/metabolism* ; Humans ; Metabolic Diseases/physiopathology* ; Lipid Metabolism/physiology* ; Animals ; Obesity/enzymology* ; Non-alcoholic Fatty Liver Disease

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

OBJECTIVES: To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels. METHODS: The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT). RESULTS: The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049). CONCLUSIONS The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans ; Adult ; Male ; Attention/physiology* ; Female ; Middle Aged ; Reproducibility of Results ; Young Adult ; Psychometrics

A retrospective analysis was conducted on the clinical course of two children with PICALM-MLLT10-positive acute leukemia treated at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, between July 2021 and July 2023. The patients were diagnosed with acute T-lymphoblastic leukemia with central nervous system involvement and high-risk acute myeloid leukemia, respectively. Both achieved bone marrow complete remission after conventional chemotherapy combined with venetoclax. Following conversion to molecular negativity, they underwent sequential allogeneic hematopoietic stem cell transplantation. At the latest follow-up, both patients were alive and in good clinical condition. These observations suggest that proceeding to hematopoietic stem cell transplantation after venetoclax-based chemotherapy may improve the long-term survival of children with PICALM-MLLT10-positive leukemia.
Humans ; Hematopoietic Stem Cell Transplantation ; Male ; Female ; Child, Preschool ; Transplantation, Homologous ; Child ; Leukemia, Myeloid, Acute/genetics* ; Oncogene Proteins, Fusion/genetics*

OBJECTIVE: To investigate the relationship between serum levels of fibroblast growth factor-23 (FGF-23), heparanase (HPSE) and early renal impairment (RI) in patients with multiple myeloma (MM). METHODS: A retrospective analysis was conducted on the clinical data of 125 MM patients who were initially diagnosed in the Department of Hematology of the First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology from June 2020 to June 2023. The patients were divided into RI group (>176.80 μmol/L) and non-RI group (≤176.80 μmol/L) based on their serum creatinine levels when diagnosed. The baseline data and laboratory indexes of the two groups were compared. The relationship between serum FGF-23, HPSE and early RI in MM patients was analyzed. RESULTS: Among 125 newly diagnosed MM patients, 33 cases developed early RI, accounting for 26.40%. The proportion of light chain type, blood urea nitrogen (BUN), blood uric acid, lactate dehydrogenase, FGF-23, and HPSE levels in RI group were higher than those in non-RI group (all P <0.05). There was no statistical significant difference in other data between the two groups (P >0.05). Multivariate logistic regression analysis showed that BUN, FGF-23 and HPSE were associated with early RI in MM patients (all P <0.05). The serum FGF-23 level was divided into Q1-Q4 groups by quartile, and the serum HPSE level was divided into q1-q4 groups. The correlation analysis showed that with the increase of serum FGF-23 and HPSE levels, the incidence of early RI increased (r =0.668, 0.592). Furthermore, logistic regression analysis showed that after controlling for confounding factors, elevated levels of serum FGF-23 and HPSE were still influencing factors for early RI in MM patients (OR>1, P <0.05). According to Pearson's linear correlation test, there was a positive correlation between serum FGF-23 level and HPSE level (r =0.373). CONCLUSION There is a certain correlation between serum levels of FGF-23, HPSE and early RI in MM patients, and the incidence of early RI is higher in patients with abnormally high levels of both.
Humans ; Multiple Myeloma/complications* ; Fibroblast Growth Factor-23 ; Retrospective Studies ; Fibroblast Growth Factors/blood* ; Glucuronidase/blood* ; Male ; Female ; Middle Aged ; Renal Insufficiency/blood* ; Aged

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.