Background: Visceral white adipose tissue (vWAT) inflammation is a critical pathology of obesity-caused heart damage and is closely associated with adipocyte endoplasmic reticulum (ER) dysfunction. Serine (or cysteine) peptidase inhibitor, clade A, member 3C (Serpina3c) has been identified as an adipokine with anti-vWAT inflammatory effects. However, it remains unclear whether Serpina3c deficiency promotion of vWAT inflammation involves adipocyte ER dysfunction and whether it further contributes to heart damage in obesity. Methods: Wild type and Serpina3c knockout (Serpina3c–/–) mice were fed a high-fat diet (HFD) for 12 weeks. An adeno-associated virus (AAV) was injected locally into epididymal white adipose tissue (eWAT) of Serpina3c–/– mice to induce eWAT-adipocyte- specific overexpression of Serpina3c (AAV-Serpina3c) or knockdown of hypoxia-inducible factor 1α (AAV-shHIF1α). In vitro experiments were performed in 3T3-L1 adipocytes. Results: Serpina3c–/– mice exhibited more severe eWAT, serum and heart inflammation after HFD feeding. Consistently, these adverse phenotypes were mitigated in AAV-Serpina3c and AAV-shHIF1α mice. Mechanistically, ER oxidoreductase 1α (Ero1α) and protein disulfide isomerase (PDI) family members PDIA3 and PDIA4 were found to be target genes of HIF1α. In the obese mice, Serpina3c deficiency caused adipocyte more hypertrophy, and activated HIF1α-Ero1α/PDI mediated ER overoxidation and ER stress in eWAT. Subsequently, this led to increased adipocyte apoptosis and chemokine production and decreased adiponectin expression, which promoted macrophage infiltration and M1 polarization in eWAT, thus exacerbating eWAT inflammation and ultimately facilitating serum and distal heart inflammation. Conclusion These findings indicate that Serpina3c is a significant regulator of adipocyte ER redox homeostasis, thus highlighting Serpina3c as a potential therapeutic target for obesity-related eWAT inflammation and heart damage.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Arson is classified as a violent crime,and often involves accelerants that significantly increase casualties and property damage.These accelerants,typically flammable liquids with low saturated vapor pressure,present volatile characteristic components in fire residues,making evidence preservation critical for accurate forensic analysis.In this study,the preservation performance of AMPAC(American KAPAC polyester sampling bags)and polyethylene(PE)evidence bags were evaluated under simulated field conditions(40 oC)through gas chromatography-mass spectrometry(GC-MS)technique,focusing on background interference,sealing integrity,and cross-contamination.The results demonstrated that AMPAC bags exhibited minimal background interference(C12?C14 alkanes detected after 3?7 days)and effective gasoline sealing,though slight losses of C2?C3 alkylbenzenes and trace cross-contamination were observed.In contrast,PE bags showed significant background hydrocarbons(C15?C19 alkanes)and pronounced gasoline component losses,including C2?C4 alkylbenzenes,naphthalenes,and indenes.Notably,severe cross-contamination of gasoline markers was detected in adjacent blank PE bags,with characteristic components such as C2?C4 alkylbenzenes,naphthalenes,methylnaphthalenes,dimethylnaphthalenes,indenes,indanes,methylindenes,and dimethylindenes identified,indicating substantial cross-contamination issues in PE evidence bags.Microstructural analysis revealed superior sealing in AMPAC bags attributed to their smooth,dense surface morphology compared to PE's rougher,porous structure.This study established a comprehensive evaluation framework for fire residue evidence containers,and found that PE bags were unsuitable for long-term gasoline evidence preservation due to compromised integrity.These findings provided critical references for forensic container selection in fire investigations.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

The chemical composition of Paeoniae Radix Alba(PRA) is complex, with primary secondary metabolites including monoterpenoids, tannins, triterpenoids, and flavonoids. In previous studies on the material basis of PRA, it was found that, in addition to the widely studied characteristic monoterpene glycosides, tannic acid components also play an important role in the efficacy of PRA. However, their pharmacological effects have not been thoroughly investigated. This paper reviews the tannic acid components in PRA, including pentagaloyl glucose(PGG), tetragaloyl glucose(TGG), trigaloyl glucose(TriGG), and gallic acid, along with their structures, properties, and characteristics to provide a detailed discussion of their pharmacological activities and related mechanisms, aiming to offer a theoretical basis for the material basis research and clinical application of PRA.
Paeonia/chemistry* ; Tannins/chemistry* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Animals ; Plant Extracts

This study aims to explore whether Albiziae Cortex-Tribuli Fructus can exert an anti-hepatic fibrosis effect by regulating the nuclear factor E2-related factor 2(Nrf2)/NOD-like receptor protein 3(NLRP3)/cysteine protease-1(caspase-1) pathway and analyze its potential mechanism. In the in vivo experiment, a mouse model of hepatic fibrosis was established by subcutaneous injection of carbon tetrachloride. The levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), collagen type Ⅳ(ColⅣ), laminin(LN), procollagen type Ⅲ(PCⅢ), and hyaluronic acid(HA) in the serum of mice were measured using a fully automated biochemical analyzer and ELISA. Hematoxylin and eosin(HE) and Masson staining were used to observe inflammation and collagen fiber deposition in the liver tissue. Western blot and RT-qPCR were employed to detect the protein and mRNA expression of collagen type Ⅰ(collagen Ⅰ), α-smooth muscle actin(α-SMA), Nrf2, NLRP3, gasdermin D(GSDMD), and caspase-1 in the hepatic tissue. In the in vitro experiment, human hepatic stellate cells(HSC-LX2) were pretreated with Nrf2 agonist or inhibitor, followed by the addition of blank serum, AngⅡ + blank serum, and AngⅡ + Albiziae Cortex-Tribuli Fructus-containing serum for intervention. Western blot was used to detect the protein expression of Nrf2, NLRP3, GSDMD, caspase-1, α-SMA, GSDMD-N, and apoptosis-associated speck-like protein(ASC) in cells. DCFH-DA fluorescence probe was used to detect the cellular ROS levels. The results from the in vivo experiment showed that, compared with the model group, Albiziae Cortex-Tribuli Fructus significantly reduced the serum levels of AST, ALT, ColⅣ, LN, PCⅢ, and HA, reduced the infiltration of inflammatory cells and collagen fiber deposition in the liver tissue, significantly upregulated the protein and mRNA expression of Nrf2 in the liver tissue, and significantly downregulated the protein and mRNA expression of collagen I, α-SMA, NLRP3, GSDMD, and caspase-1 in the liver tissue. The results from the in vitro experiment showed that Nrf2 activation decreased the protein expression of NLRP3, GSDMD, caspase-1, α-SMA, GSDMD-N, ASC, and ROS levels in HSC-LX2, while Nrf2 inhibition showed the opposite trend. Furthermore, Albiziae Cortex-Tribuli Fructus-containing serum directly decreased the expression of the above proteins and ROS levels. In conclusion, Albiziae Cortex-Tribuli Fructus can effectively improve hepatic fibrosis, and its mechanism of action may involve inhibiting pyroptosis through the regulation of the Nrf2/NLRP3/caspase-1 pathway.
Animals ; NF-E2-Related Factor 2/genetics* ; Liver Cirrhosis/genetics* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Caspase 1/genetics* ; Male ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Signal Transduction/drug effects* ; Humans ; Liver/metabolism* ; Mice, Inbred C57BL ; Plant Extracts ; Tribulus

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Alzheimer’s disease (AD), a progressive neurodegenerative disorder and the leading cause of dementia in the elderly, is characterized by severe cognitive decline, loss of daily living abilities, and neuropsychiatric symptoms. This condition imposes a substantial burden on patients, families, and society. Despite extensive research efforts, the complex pathogenesis of AD, particularly the early mechanisms underlying cognitive dysfunction, remains incompletely understood, posing significant challenges for timely diagnosis and effective therapeutic intervention. Among the various cellular components implicated in AD, GABAergic interneurons have emerged as critical players in the pathological cascade, playing a pivotal role in maintaining neural network integrity and function in key brain regions affected by the disease. GABAergic interneurons represent a heterogeneous population of inhibitory neurons essential for sustaining neural network homeostasis. They achieve this by precisely modulating rhythmic oscillatory activity (e.g., theta and gamma oscillations), which are crucial for cognitive processes such as learning and memory. These interneurons synthesize and release the inhibitory neurotransmitter GABA, exerting potent control over excitatory pyramidal neurons through intricate local circuits. Their primary mechanism involves synaptic inhibition, thereby modulating the excitability and synchrony of neural populations. Emerging evidence highlights the significant involvement of GABAergic interneuron dysfunction in AD pathogenesis. Contrary to earlier assumptions of their resistance to the disease, specific subtypes exhibit vulnerability or altered function early in the disease process. Critically, this impairment is not merely a consequence but appears to be a key driver of network hyperexcitability, a hallmark feature of AD models and potentially a core mechanism underlying cognitive deficits. For instance, parvalbumin-positive (PV⁺) interneurons display biphasic alterations in activity. Both suppressing early hyperactivity or enhancing late activity can rescue cognitive deficits, underscoring their causal role. Somatostatin-positive (SST⁺) neurons are highly sensitive to amyloid β-protein (Aβ) dysfunction. Their functional impairment drives AD progression via a dual pathway: compensatory hyperexcitability promotes Aβ generation, while released SST-14 forms toxic oligomers with Aβ, collectively accelerating neuronal loss and amyloid deposition, forming a vicious cycle. Vasoactive intestinal peptide-positive (VIP⁺) neurons, although potentially spared in number early in the disease, exhibit altered firing properties (e.g., broader spikes, lower frequency), contributing to network dysfunction (e.g., in CA1). Furthermore, VIP release induced by 40 Hz sensory stimulation (GENUS) enhances glymphatic clearance of Aβ, demonstrating a direct link between VIP neuron function and modulation of amyloid pathology. Given their central role in network stability and their demonstrable dysfunction in AD, GABAergic interneurons represent promising therapeutic targets. Current research primarily explores three approaches: increasing interneuron numbers (e.g., improving cortical PV⁺ interneuron counts and behavior in APP/PS1 mice with the antidepressant citalopram; transplanting stem cells differentiated into functional GABAergic neurons to enhance cognition), enhancing neuronal activity (e.g., using low-dose levetiracetam or targeted activation of specific molecules to boost PV⁺ interneuron excitability, restoring neural network γ‑oscillations and memory; non-invasive neuromodulation techniques like 40 Hz repetitive transcranial magnetic stimulation (rTMS), GENUS, and minimally invasive electroacupuncture to improve inhibitory regulation, promote memory, and reduce Aβ), and direct GABA system intervention (clinical and animal studies reveal reduced GABA levels in AD-affected brain regions; early GABA supplementation improves cognition in APP/PS1 mice, suggesting a therapeutic time window). Collectively, these findings establish GABAergic interneuron intervention as a foundational rationale and distinct pathway for AD therapy. In conclusion, GABAergic interneurons, particularly the PV⁺, SST⁺, and VIP⁺ subtypes, play critical and subtype-specific roles in the initiation and progression of AD pathology. Their dysfunction significantly contributes to network hyperexcitability, oscillatory deficits, and cognitive decline. Understanding the heterogeneity in their vulnerability and response mechanisms provides crucial insights into AD pathogenesis. Targeting these interneurons through pharmacological, neuromodulatory, or cellular approaches offers promising avenues for developing novel, potentially disease-modifying therapies.