Objective To explore the clinical efficacy of robot-assisted coronary artery bypass grafting through a small incision in the left intercostal space in the treatment of multivessel coronary disease. Methods A retrospective analysis was conducted on the clinical data of patients who underwent coronary artery bypass grafting through a small incision in the left intercostal space at Central China Fuwai Hospital of Zhengzhou University from January 1, 2023 to October 15, 2024. Patients were divided into a robotic group and a minimally invasive group based on whether the surgery was assisted by the Da Vinci robot. Results A total of 81 patients were included, with 57 in the minimally invasive group, including 41 males and 16 females, with a median age of 65.0 (57.5, 69.5) years; and 24 in the robotic group, including 17 males and 7 females, with a median age of 61.0 (56.0, 69.0) years. There was no statistically significant difference in baseline data between the two groups (P>0.05). The robotic group had less intraoperative bleeding [300 (200, 438) mL vs. 500 (375, 600) mL, P=0.006], shorter postoperative mechanical ventilation time [15.0 (13.3, 23.5) h vs. 22.0 (15.5, 39.5) h, P=0.037], and lower incidence of postoperative pain [8 (33.3%) vs. 33 (57.9%), P=0.043]. The hospitalization cost in the robotic group was higher than that in the minimally invasive group [130491 (123298, 135691) yuan vs. 123892 (115543, 133449) yuan, P=0.023]. There was no statistical difference in postoperative laboratory indicators between the two groups (P>0.05). There was also no statistical difference in the duration of surgery, postoperative 24 h drainage volume, ICU stay time, postoperative hospital stay or incidences of perioperative compications including pleural effusion, transfusion, new-onset atrial fibrillation, acute kidney injury, non-union of incision, major cardiovascular and cerebrovascular adverse events, and reoperation between the two groups (P>0.05). Conclusion Compared with the minimally invasive group, the robotic group shows satisfactory efficacy and can effectively reduce postoperative pain and intraoperative bleeding, and shorten postoperative mechanical ventilation time.

To review the clinical characteristics, short-term outcomes, and risk factors of patients with infective endocarditis(IE) who underwent surgical treatment at a single center, and to summarize treatment experience.

Integrated metabolomic and lipidomic profiling,utilizing liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS),has emerged as a pivotal strategy for biomarker discovery.However,the inherent polarity disparity between metabolites and lipids complicates simultaneous analysis.To address this,a dual-stationary phase polarity-extended liquid chromatography(PELC)system was developed,which surpassed conventional one-dimensional LC(1D-LC)by enabling comprehensive coverage of both polar and non-polar compounds within a single injection.This system enhanced chromatographic resolution,peak capacity,and throughput while minimizing analytical variability.Extracellular vesicles(EVs),lipid bilayer-enclosed nanoparticles ubiquitously present in biofluids,had gained prominence as reservoirs of cancer biomarkers due to their cargo stability and pathophysiological relevance.Herein,the application of PELC-HRMS for concurrent metabolome-lipidome profiling in EVs was pioneered.A total of 193 metabolites were identified using this technique coupled with MS-DIAL software and Human Metabolome Database.Subsequently,this technique was employed to explore potential biomarkers for prostate cancer(PCa).Multivariate analysis identified 17 differentially abundant metabolites in PCa,implicating dysregulated pathways including purine metabolism,starch and sucrose metabolism,galactose metabolism,cysteine and methionine metabolism,and biosynthesis of unsaturated fatty acids.Notably,creatine(AUC=0.92)and DG 42:5(AUC=0.80)demonstrated robust diagnostic efficacy,attributable to their broad polarity ranges and EV-specific enrichment.This study established PELC as a high-fidelity platform for multi-omics integration in complex biospecimens,advancing mechanistic insights into metabolic rewiring and disease pathophysiology.

Objective:To develop a deep learning-based segmentation model for anterior segment ultrasound biomicroscopy (UBM) images to automatically segment the anterior segment tissues of patients with primary angle-closure glaucoma (PACG).Methods:A single-center retrospective case series was conducted.A small-scale dataset comprised 468 UBM images of the anterior chamber angle closure from 156 patients with PACG who underwent the UBM examination at Tianjin Medical University Eye Hospital between July 12, 2022, and February 20, 2023.The UBM images were randomly split into a training dataset of 228 images and a testing dataset of 152 images using a random seed method in a ratio of 6∶4.The models were trained using the PSPNet model with MobileNet V2 and ResNet50 as backbones, the DeepLab v3+ model with MobileNet V2 and Xception as backbones, and the SegFormer model with MiT-B0 and MiT-B2 as backbones.The testing dataset was used for result prediction and to achieve segmentation of four regions: the cornea and sclera, iris, ciliary body, and anterior lens surface.To evaluate the performance of the models in segmenting the anterior segment structures, multiple metrics were assessed, including the mean intersection over union (mIoU), Dice coefficient, precision, recall, false negative rate, and specificity.A comparative analysis of the test results across the different models was subsequently performed.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Tianjin Medical University Eye Hospital (No.2023KY-05).Results:The two models with the best segmentation performance were PSPNet and DeepLab v3+ .The PSPNet model with ResNet50 as the backbone achieved the mIoU of 85.11%, Dice coefficient of 91.38%, precision of 91.83%, recall of 90.94%, false negative rate of 9.06%, and specificity of 98.89%.The DeepLab v3+ model with MobileNet V2 as the backbone achieved an mIoU of 85.84%, Dice coefficient of 92.01%, precision of 92.67%, recall of 91.36%, false negative rate of 8.64%, and specificity of 98.90%.Among the five key metrics, mIoU, Dice coefficient, recall, false negative rate, and specificity, DeepLab v3+ exhibited the best segmentation performance.In addition, the DeepLab v3+ model with Xception as the backbone had the highest precision among all models, reaching 92.77%.Conclusions:The deep learning-based DeepLab v3+ model achieves precise segmentation of anterior segment tissue structures in PACG anterior segment UBM image segmentation, providing auxiliary support for clinical diagnosis.

Objective:To explore associated factors of post-discharge depressive symptom severity in patients with bipolar disorder.Methods:A longitudinal follow-up was conducted to investigate the demographic,behavioral,and clinical characteristics,and social function among discharged patients with bipolar disorder who met the DSM-5 diagnostic criteria.Clinical characteristics were assessed with the Hamilton Depression Scale(HAMD)and Brief Psychiatric Rating Scale(BPRS).Single factor and multivariate regression were carried out to explore the associat-ed factors of depressive symptom severity in patients with bipolar disorder.Results:A total of 298 discharged pa-tients with bipolar disorder were face-to-face interviewed to complete the follow-up survey.At follow-up time,psy-chotic symptoms(standardized(β)=0.18),housework((β)=0.23),social interaction((β)=0.17)and BPRS total score((β)=0.46)were positively associated with HAMD total score.Productive labor and work((β)=-0.27)and person-al life management((β)=-0.15)were negatively associated with HAMD total scores.Conclusion:Post-discharge depressive symptom severity in bipolar disorder patients is influenced by multiple factors.Effective management of psychotic symptoms,combined with enhanced community-based social rehabilitation and functional recovery,may help reduce the persistence or worsening of depressive symptoms and improve prognosis.

Anxiety is a major emotional disorder manifested in the individual's expectation of future threats.The incidence rate of anxiety is about 7.3％,with the highest lifetime prevalence rate among mental health conditions.The mechanism of anxiety overlaps with depression,and anxiety is a typical symptom of various mental diseases or emotional disorders in traditional Chinese medicine.The high rates of comorbidity and disability pose serious threats to people's health.Animal models are important tools for studying anxiety and are of great use for deciphering the pathogenesis of anxiety and for developing drugs.The traditional paradigm of stress-induced anxiety,however,is relatively limited.Based on traditional theory combined with clinical and animal experimental data,we propose a new hypothesis of"insufficiency of ZhiYi'causing anxiety,defined as"an anxiety state induced by the inability of an individual to meet their own needs,limited or lacking after multiple attempts,rendered hindered and powerless by an inability to meet their desires".This hypothesis is more in line with the typical manifestations of despair,lack of pleasure,and social withdrawal in clinical patients,and is supported by traditional theory and experimental data showing"hunger but unable to eat,food but unable to obtain,and gain but not full".Based on this,the established modeling paradigm is easy to apply,with good repeatability and low cost,and can be used to establish anxiety models in rats and mice,to provide a theoretical and model basis for the development and pharmacological evaluation of anti-anxiety drugs.

OBJECTIVE: To investigate the biological behavior, differentiation ability, and differential gene expression of lymph node mesenchymal stem cells (MSCs) in patients with diffuse large B-cell lymphoma (DLBCL) and reactive lymphoid hyperplasia (RLH), providing a theoretical basis for clinical chemotherapy resistance. METHODS: Lymph node MSCs from patients with DLBCL and RLH were separated, passaged and cultured. The cell morphology and growth status were observed. Flow cytometry was performed to detect the immune phenotype of MSCs. The in vitro directed differentiation ability of the two types of MSCs was observed. High-throughput sequencing was used to analyze the differential gene expression and enrichment of two groups of MSCs. RESULTS: The lymph node MSCs of patients with DLBCL and RLH had similar cell morphology and growth characteristics, and both groups of MSCs expressed CD90, CD105, and CD73 on the cell surface. Compared with lymph node MSCs derived from patients with RLH, lymph node MSCs derived from DLBCL patients showed stronger osteogenic and adipogenic differentiation abilities. High-throughput sequencing results displayed that lymph node MSCs derived from DLBCL patients significantly upregulated some genes such as TOP2A, LFNG, GRIA3, SEC14L2, SPON2, AURKA, LRRC15, FOXD1, HOXC9, CDC20 and remarkably downregulated some genes such as TBC1D8, LDLR, PCDHAC2, POLH, PKP2, ANKRD37, DMKN, HSD11B1, ARHGAP20, PTGS1,etc. CONCLUSION Lymph node MSCs in DLBCL patients exhibit unique biological behavior and gene expression profiles, which may be closely related to clinical chemotherapy resistance.
Humans ; Mesenchymal Stem Cells/cytology* ; Lymphoma, Large B-Cell, Diffuse/pathology* ; Cell Differentiation ; Lymph Nodes/pathology* ; Pseudolymphoma/pathology*

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Sigma-1 receptor (σ ₁R) has become a focus point of drug discovery for central nervous system (CNS) diseases. A series of novel 1-phenylethan-1-one O-(2-aminoethyl) oxime derivatives were synthesized. In vitro biological evaluation led to the identification of 1a, 14a, 15d and 16d as the most high-affinity (K _i < 4 nmol/L) and selective σ ₁R agonists. Among these, 15d, the most metabolically stable derivative exhibited high selectivity for σ ₁R in relation to σ ₂R and 52 other human targets. In addition to low CYP450 inhibition and induction, 15d also exhibited high brain permeability and excellent oral bioavailability. Importantly, 15d demonstrated effective antipsychotic potency, particularly for alleviating negative symptoms and improving cognitive impairment in experimental animal models, both of which are major challenges for schizophrenia treatment. Moreover, 15d produced no significant extrapyramidal symptoms, exhibiting superior pharmacological profiles in relation to current antipsychotic drugs. Mechanistically, 15d inhibited GSK3β and enhanced prefrontal BDNF expression and excitatory synaptic transmission in pyramidal neurons. Collectively, these in vivo proof-of-concept findings provide substantial experimental evidence to demonstrate that modulating σ ₁R represents a potential new therapeutic approach for schizophrenia. The novel chemical entity along with its favorable drug-like and pharmacological profile of 15d renders it a promising candidate for treating schizophrenia.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins