The prevalence rate of metabolic associated fatty liver disease （MAFLD） is steadily increasing worldwide， and MAFLD is now considered a significant risk factor for a wide range of metabolic comorbidities. However， current clinical management strategies often address MAFLD from a single-disease perspective， lacking a comprehensive understanding of the central role and systemic impact of MAFLD in the prevention and control of metabolic comorbidities. This article reviews the current evidence supporting MASLD as both a trigger and a key node in systemic metabolic dysfunction and elaborates on how hepatic insulin resistance， lipotoxic injury， inflammatory responses， and dysregulation of hepatokines mediate organ-specific metabolic disorders including cardiovascular disease， chronic kidney disease， and diabetes. With reference to the latest national and international guidelines， this article proposes an integrated multidisciplinary management strategy， including liver-glucose joint intervention and a cross-organ “cardio-renal-hepatic” strategy， and it also advocates for a paradigm shift from conventional liver-focused management toward liver-centered systemic metabolic control， in order to effectively delay the progression of MAFLD and its related multisystem complications.

Objective To identify the independent predictors of programmed death-1 (PD-1) inhibitor-related endocrine adverse events and construct a clinically usable risk prediction model. Methods A total of 302 patients with solid tumors treated with PD-1 inhibitors were retrospectively enrolled. According to the presence or absence of endocrine immune-related adverse events (irAEs), the patients were divided into case group and control group. The clinical and laboratory indexes were compared between the two groups. Multivariable logistic regression was used to confirm independent predictors of endocrine irAEs. The nomogram was constructed, while the receiver operating characteristic (ROC) curve was used to test the prediction performance of the model. Results The overall incidence of endocrine irAEs was 21.9% (66/302), and the incidence of hypothyroidism was 19.5% (59/302). The age, PD-1 inhibitors, free thyroxine, thyroid peroxidase antibody (TPOAb), thyroglobulin, amylase, lymphocyte subset CD3 expression were statistically different between the two groups (P＜0.05). Multivariable logistic regression showed that higher expression of lymphocyte subset CD3 was a protective factor to prevent endocrine irAEs occurrence (P＝0.004), while age＜60 years, higher TPOAb and use of pembrolizumab were independent risk factors of endocrine irAEs (P＜0.05). The nomogram model thus constructed, and when the threshold probability of the model exceeded 0.1, its net benefit was higher. ROC curve showed that the AUC of the model to predict endocrine irAEs was 0.760. The prediction result of the model was highly consistent with the actual result. Conclusions The age, type of PD-1 inhibitor, baseline TPOAb level, and baseline CD3 expression can independently predict endocrine irAEs occurrence or not. The nomogram model based on this model has good predictive efficiency, which can provide reference for early identification of high-risk patients and immunotherapy management.

BACKGROUND: The optimal antidepressant dosages remain controversial. This study aimed to analyze the efficacy of antidepressants and characterize their dose-response relationships in the treatments of major depressive disorders (MDD). METHODS: We searched multiple databases, including the Embase, Cochrane Central Register of Controlled Trials, PubMed, and Web of Science, for the studies that were conducted between January 8, 2016, and April 30, 2023. The studies are double-blinded, randomized controlled trials (RCTs) involving the adults (≥18 years) with MDD. The primary outcomes were efficacy of antidepressant and the dose-response relationships. A frequentist network meta-analysis was conducted, treating participants with various dosages of the same antidepressant as a single therapy. We also implemented the model-based meta-analysis (MBMA) using a Bayesian method to explore the dose-response relationships. RESULTS: The network meta-analysis comprised 135,180 participants from 602 studies. All the antidepressants were more effective than the placebo; toludesvenlafaxine had the highest odds ratio (OR) of 4.52 (95% confidence interval [CI]: 2.65-7.72), and reboxetine had the lowest OR of 1.34 (95%CI: 1.14-1.57). Moreover, amitriptyline, clomipramine, and reboxetine showed a linear increase in effect size from low to high doses. The effect size of toludesvenlafaxine increased significantly up to 80 mg/day and subsequently maintained the maximal dose up to 160 mg/day while the predictive curves of nefazodone were fairly flat in different dosages. CONCLUSIONS: Although most antidepressants were more efficacious than placebo in treating MDD, no consistent dose-response relationship between any antidepressants was observed. For most antidepressants, the maximum efficacy was achieved at lower or middle prescribed doses, rather than at the upper limit. REGISTRATION No. CRD42023427480; https://www.crd.york.ac.uk/prospero/display_record.php?
Humans ; Antidepressive Agents/therapeutic use* ; Depressive Disorder, Major/drug therapy* ; Dose-Response Relationship, Drug ; Randomized Controlled Trials as Topic

OBJECTIVES: To explore the underlying pharmacological mechanisms and its potential effects of Chinese medicine herbal formula Sini Powder (SNP) on hepatocellular carcinoma (HCC). METHODS: The active components of SNP and their in vivo distribution were identified using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Construction of component-target-disease networks, protein-protein interaction network, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and molecular docking were employed to analyze the active components and anti-HCC mechanisms of SNP. Cell viability assay and wound healing assay were utilized to confirm the effect of SNP-containing serum (2.5%, 5.0%, 10%, 20%, and 40%), isoprenaline or propranolol (both 10, 100, and 1,000 µ mol/L) on proliferation and migration of HepG 2 or Huh7 cells. Meanwhile, the effect of isoprenaline or propranolol on the β 2 adrenergic receptor (ADRB2) mRNA expression on HepG2 cells were measured by real-time quantitative reverse transcription (RT-qPCR). Mice with subcutaneous tumors were either subjected to chronic restraint stress (CRS) followed by SNP administration (364 mg/mL) or directly treated with SNP (364 mg/mL). These two parallel experiments were performed to validate the effects of SNP on stress responses. Stress-related proteins and hormones were quantified using RT-qPCR, enzyme-linked immunosorbent assay, and immunohistochemistry. Metagenomic sequencing was performed to confirm the influence of SNP on the gut microbiota in the tumor-bearing CRS mice. RESULTS: The distribution of the 12 active components of SNP was confirmed in various tissues and feces. Network pharmacology analysis confirmed the anti-HCC effects of the 5 active components. The potential anti-HCC mechanisms of SNP may involve the epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC) and signal transducer and activator of transcription 3 (STAT3) pathways. SNP-containing serum inhibited the proliferation of HepG2 and Huh7 cells at concentrations of 2.5% and 5.0%, respectively, after 24 h of treatment. Furthermore, SNP suppressed tumor progression in tumor-bearing mice exposed to CRS. SNP treatment also downregulated the expressions of stress-related proteins and pro-inflammatory cytokines, primarily by modulating the gut microbiota. Specifically, the abundance of Alistipes and Prevotella, which belong to the phylum Bacteroidetes, increased in the SNP-treated group, whereas Lachnospira, in the phylum Firmicutes, decreased. CONCLUSION SNP can combat HCC by alleviating stress responses through the regulation of gut microbiota.
Animals ; Gastrointestinal Microbiome/drug effects* ; Liver Neoplasms/microbiology* ; Carcinoma, Hepatocellular/microbiology* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Powders ; Cell Proliferation/drug effects* ; Mice ; Molecular Docking Simulation ; Cell Line, Tumor ; Hep G2 Cells ; Receptors, Adrenergic, beta-2/genetics* ; Stress, Physiological/drug effects* ; Cell Movement/drug effects* ; Male ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Proto-Oncogene Mas

Colorectal tumorigenesis generally progresses from adenoma to adenocarcinoma, accompanied by dynamic changes in the tumor microenvironment (TME). A randomized controlled trial has confirmed the efficacy and safety of Shen-Bai-Jie-Du decoction (SBJDD) in preventing colorectal tumorigenesis. However, the mechanism remains unclear. In this study, we employed single-cell RNA sequencing (scRNA-seq) to investigate the dynamic evolution of the TME and validated cell infiltration with multiplex immunohistochemistry and flow cytometry. Bulk RNA sequencing was utilized to assess the underlying mechanisms. Our results constructed the mutually verifiable single-cell transcriptomic atlases in Apc ^Min/+ mice and clinical patients. There was a marked accumulation of CCL22⁺ dendritic cells (DCs) and an enhanced immunosuppressive action, which SBJDD and berberine reversed. Combined treatment with cholesterol and lipopolysaccharide induced characteristic gene expression of CCL22⁺ DCs, which may represent "exhausted DCs". Intraperitoneal injection of these DCs after SBJDD treatment eliminated its therapeutic effects. TMEM131 derived CCL22⁺ DCs generation by TNF signaling pathway and may be a potential target of berberine in retarding colorectal tumorigenesis. These findings emphasize the role of exhausted DCs and the regulatory mechanisms of SBJDD and berberine in colorectal cancer (CRC), suggesting that the multi-component properties of SBJDD may help restore TME homeostasis and offer novel cancer therapy.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objective:To learn about physicians’ concepts and commonly employed method in hyaluronic acid injection and provide reference data for the standardization of pain management.Methods:This study was a cross-sectional study. Convenient sampling method was used to distribute questionnaires to cosmetic injectors and patients experienced with hyaluronic acid injections to collect data on their views of pain associated with hyaluronic acid injections. The physician portion was collected offline from June 15 to July 20, 2022, and the patient portion was collected from November 14, 2022, to December 6, 2022, via the Questionnaire Star platform. The physician questionnaire consisted of 17 questions, question types included single choice, multiple choice and essay questions. The patient questionnaire consisted of 6 questions, question types included single choice and multiple choice. Relevant data were analyzed using SPSS 22.0 software for descriptive statistics, and data were presented in the form of cases and percentages (%).Results:Sixty-two physician questionnaires and 123 patient questionnaires were collected. 42 (67.74%) physicians observed from their daily practice that more than 50% of their patients were very concerned about pain during injection; 101 (82.11%) patients scored ≥5 out of 10 for concern about impending pain prior to hyaluronic acid filler injection. At the time of treatment, 48 (77.42%) physicians advised patients to choose a lidocaine-containing hyaluronic acid filler for reasons including a significant reduction in injection pain (53 cases, 85.48%) and patient comfort with the treatment experience (59 cases, 95.16%). 60 (48.78%) patients were willing to choose an anesthesia-containing product at the time of injection, but the price of the anesthesia-containing product influenced the patient’ s choice (55 cases 44.72%) .Conclusions:Pain from cosmetic injectable treatments is an important issue to both physicians and patients. Lidocaine-containing hyaluronic acid is recognized by physicians and patients for its analgesic effect and high safety profile. There is no perfect solution for pain in cosmetic injection treatment, and multidisciplinary collaboration may be needed to solve the problem.

Objective:To learn about physicians’ concepts and commonly employed method in hyaluronic acid injection and provide reference data for the standardization of pain management.Methods:This study was a cross-sectional study. Convenient sampling method was used to distribute questionnaires to cosmetic injectors from plastic surgery department of public hospitals or medical beauty institutions and patients experienced with hyaluronic acid injections to collect data on their views of pain associated with hyaluronic acid injections. The physician portion was collected offline from June 15 to July 20, 2022, and the patient portion was collected from November 14 to December 6, 2022, via the Questionnaire Star platform. The physician questionnaire consisted of 17 questions, question types included single choice, multiple choice and essay questions. The patient questionnaire consisted of 6 questions, question types included single choice and multiple choice. Relevant data were analyzed using SPSS 22.0 software for descriptive statistics, and data were presented in the form of cases(%).Results:Sixty-two physician questionnaires and 123 patient questionnaires were collected. 42 (67.74%) physicians observed from their daily practice that more than 50% of their patients were very concerned about pain during injection; 101 (82.11%) patients scored ≥5 out of 10 for concern about impending pain prior to hyaluronic acid filler injection. At the time of treatment, 48 (77.42%) physicians advised patients to choose a lidocaine-containing hyaluronic acid filler for reasons including a significant reduction in injection pain (53 cases, 85.48%) and patient comfort with the treatment experience (59 cases, 95.16%). 60 (48.78%) patients were willing to choose an anesthesia-containing product at the time of injection, but the price of the anesthesia-containing product influenced the patient’s choice (55 cases, 44.72%).Conclusion:Pain from cosmetic injectable treatments is an important issue to both physicians and patients. Lidocaine-containing hyaluronic acid is recognized by physicians and patients for its analgesic effect and high safety profile. There is no perfect solution for pain in cosmetic injection treatment, and multidisciplinary collaboration may be needed to solve the problem.

Objective:To investigate the short-term outcome of transoral robotic thyroidectomy.Methods:This is a retrospective case series study. The clinicopathologic characteristics and postoperative results of 107 patients who underwent transoral robotic thyroidectomies in the Department of Thyroid and Breast Surgery of the 960 th Hospital of People′s Liberation Army from May 2020 to August 2023 were retrospectively analyzed. There were 12 males and 95 females, with an age of (31.8±9.4) years (range: 11 to 55 years), including 20 benign tumors and 87 thyroid papillary carcinoma. Postoperative follow-up was carried out through returning visit and telephone, mainly to observe the recovery of postoperative complications, cosmetic effects and recurrence results. Results:All transoral robotic thyroidectomy was successfully completed without conversion to open surgery. The tumor size of thyroid papillary carcinoma patients was (5.6±2.7) mm (range: 2 to 15 mm). Furthermore, central cervical lymph node metastasis was found in 45 cases. The number of central cervical lymph nodes retrieved and metastasized ( M(IQR)) were 11 (8) (range: 3 to 26) and 1 (3) (range: 0 to 13), respectively. There was no recurrent laryngeal nerve injury and permanent hypoparathyroidism. The transient hypoparathyroidism after surgery was 8 cases. Other complications occurred as follows: postoperative infection ( n=1), left submandibular perforation ( n=1), skin scald ( n=1), and perioral numbness ( n=1), oral tear ( n=2). The postoperative stay was 6 (2) days (range: 3 to 11 days). No local lymph node recurrence or metastasis occurred after a follow-up of (22.6±10.0) months (range: 1.0 to 37.4 months). All patients were satisfied with the postoperative cosmetic results, the aesthetic effect score was 9.3 (0.2) (range: 8.4 to 9.6) one month after surgery. Conclusion:For highly screened patients with early thyroid cancer, experienced surgeons can perform a transoral robotic thyroidectomy that has excellent cosmetic results.