Temporomandibular joint osteoarthritis is a common chronic degenerative disease,in which joint pain is the most signif-icant symptom,but its pathogenesis is still unclear.Significant subchondral bone lesions can occur in the early stage of osteoarthritis progression,and more and more experimental evidence shows that subchondral bone lesions play an important role in the pain caused by osteoarthritis.Osteoclasts,osteocytes,osteoblasts,endothelial cells,new generating nerves and blood vessels in the sub-chondral bone matrix microenvironment interact with each other and participate in the process of osteoarthritis pain.Therefore,regu-lating the subchondral bone matrix microenvironment is expected to become a new strategy to control joint pain.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Network pharmacology and molecular docking were employed to predict the mechanism of Zhizhu Decoction in regulating macrophage polarization to reduce adipose tissue inflammation in obese children, and animal experiments were then carried out to validate the prediction results. The active ingredients and targets of Zhizhu Decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). The inflammation related targets in the adipose tissue of obese children were searched against GeneCards, OMIM, and DisGeNET, and a drug-disease-target network was established. STRING was used to construct a protein-protein interaction(PPI) network and screen for core targets. R language was used to carry out Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses. AutoDock was used for the molecular docking between core targets and active ingredients. 24 SPF grade 6-week C57B/6J male mice were adaptively fed for 1 week, and 8 mice were randomly selected as the blank group. The remaining 16 mice were fed with high-fat diet for 8 weeks to onstruct a high-fat diet induced mouse obesity model. After successful modeling, the 16 mice were randomly divided into model group and Zhizhu Decoction group, with 8 mice in each group. Zhizhu Decoction group was intervened by gavage for 14 days, once a day. Blank group and model group were given an equal amount of sterile double distilled water(ddH_2O) by gavage daily. After the last gavage, serum and inguinal adipose tissue were collected from mice for testing. The morphology of inguinal adipose tissue was observed by hematoxylin-eosin(HE) staining, the levels of inflammatory factors interleukin-6(IL-6) and tumor necrosis factor-α(TNF-α)were detected by enzyme-linked immunosorbent assay(ELISA), and the protein expression of macrophage marker molecule nitric oxide synthase(iNOS) and epidermal growth factor like hormone receptor 1(F4/80) was detected by immunofluorescence staining. Network pharmacology predicted luteolin, naringenin, and nobiletin as the main active ingredients in Zhizhu Decoction and 15 core targets. KEGG pathway enrichment analysis revealed involvement in the key signaling pathway of nuclear factor κB(NF-κB). Molecular docking showed that the active ingredients of Zhizhu Decoction bound well to the core targets. Animal experiment showed that compared with the model group, Zhizhu Decoction reduced the distribution of inflammatory cytokines in the inguinal adipose tissue of mice, lowered the levels of TNF-α and IL-6 in the serum(P<0.05, P<0.01), and down-regulated the expression of iNOS and F4/80(P<0.05). The results showed that the active ingredients in Zhizhu Decoction, such as luteolin, naringenin, and nobiletin, inhibit the aggregation of macrophages in adipose tissue, downregulate their classic activated macrophage(M1) polarization, reduce the expression of inflammatory factors IL-6 and TNF-α, and thus improve adipose tissue inflammation in obese mice.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation ; Adipose Tissue/immunology* ; Mice ; Male ; Humans ; Network Pharmacology ; Macrophages/immunology* ; Mice, Inbred C57BL ; Child ; Protein Interaction Maps/drug effects* ; Obesity/genetics* ; Inflammation/drug therapy*

OBJECTIVE: To investigate the clinical effect of minimally invasive technique in the treatment of moderate and severe gluteal muscle contracture. METHODS: A retrospective study was conducted on 85 patients (170 sides) with bilateral gluteal muscle contracture admitted from January 2016 to December 2019. All patients were treated with minimally invasive release of tendon knife. There were 32 males and 53 females, ranging in age from 15 to 37 years old, with an average age of (22.3±6.3) years old. Operation time, intraoperative blood loss, incision length, first postoperative ambulation time, complication rate, recurrence rate, and Harris hip score (HHS) were analyzed and evaluated. RESULTS: The average follow-up time was (16.2±4.6) months, ranging from 12 to 30 months. The operation time ranged from 7 to 15 min, with an average of (10.2±3.1) min. Intraoperative blood loss ranged from 2 to 20 ml, with an average of (8.4±2.2) ml. The incision length ranged from 0.6 to 2.0 cm, with an average of (0.8±0.3) cm. The time to postoperative ambulation ranged from 12 to 28 h, with an average of (20.0±3.2) h. All patients achieved primary wound healing without sciatic nerve injury or recurrence. HHS hip function scores ranged from 90 to 98, with an average score of (96.2±1.4). Complications included intraoperative tendon blade tip fracture in two cases (removed under fluoroscopic guidance) and subcutaneous hematoma in three cases-two resolved with compression and one with open evacuation.. Twenty-nine patients exhibited transient swaying gait postoperatively, of which 24 patients returned to normal after 4 weeks and 5 patients returned to normal after 6 weeks. CONCLUSION Minimally invasive tendon blade release is a safe and effective technique for treating gluteal muscle contracture, offering minimal trauma, rapid recovery, and excellent cosmetic and functional outcomes. However, it exhibits a low risk of blade tip fracture and sciatic nerve injury, warranting experienced surgical handling.
Humans ; Male ; Female ; Adult ; Minimally Invasive Surgical Procedures/methods* ; Adolescent ; Retrospective Studies ; Buttocks/surgery* ; Young Adult ; Contracture/surgery* ; Tendons/surgery* ; Muscle, Skeletal/surgery*

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To evaluate the safety and efficacy of combined inflatable mediastinoscopy with laparoscopy guided by the concept of “reduced field and port” during esophagectomy for esophageal cancer.Methods:This is a retrospective cohort study. The clinical data of 497 patients with esophageal squamous cell carcinoma who underwent minimally invasive esophagectomy at the Center of Minimally Invasive Thoracic Surgery, the Second Affiliated Hospital of Naval Medical University, between January 2017 and December 2024 were retrospectively analyzed. There were 416 male and 81 female patients, with an age of (68.3±8.0) years (range: 44 to 89 years). Patients were divided into the traditional video-assisted thoracoscopic surgery group (Group A, n=354) and the combined inflatable mediastinoscopy with laparoscopic surgery group(Group B, n=143) based on the surgical approach. Furthermore, Group B was subdivided into the multiport laparoscopic group (Group B1, n=81) and the single-incision laparoscopic surgery plus one port group (Group B2, n=62). Perioperative indicators and postoperative survival differences were compared between the groups. Inter-group comparisons were performed using the independent sample t-test, χ2 test, or Fisher′s exact probability test. Survival curves were plotted using the Kaplan-Meier method, and the Log-rank test was used to analyze the survival differences between groups. Results:Compared with Group A, Group B demonstrated a significantly shorter operative time ((181.8±11.4) minutes vs. (196.7±8.1)minutes, t=16.09, P<0.01), a lower incidence of postoperative pulmonary complications (8.4% (12/143) vs. 17.8% (63/354), χ2=6.27, P=0.012), lower perioperative mortality (0 vs. 3.1%(11/354), P=0.039), and a shorter postoperative hospital stay ((16.2±2.2)days vs. (18.9±4.1)days, t=8.56, P<0.01). There was no significant difference in the anastomotic leak rate, number of lymph nodes dissected, or intraoperative blood loss between the two groups (all P>0.05). Overall survival time and recurrence-free survival time showed no significant difference between the two groups (all P>0.05). Subgroup analysis revealed no significant differences in perioperative indicators or postoperative complication rates between Group B1 and Group B2. Conclusions:Compared with traditional thoracoscopic combined with laparoscopic surgery, inflatable mediastinoscopy offered advantages in terms of lower postoperative pulmonary complication rates, shorter operative time, reduced postoperative hospital stay, and lower perioperative mortality. The “reduced field and port” concept could further minimize surgical trauma during the transmediastinal approach for esophagectomy while ensuring surgical safety and efficacy.

Temporomandibular joint osteoarthritis is a common chronic degenerative disease,in which joint pain is the most signif-icant symptom,but its pathogenesis is still unclear.Significant subchondral bone lesions can occur in the early stage of osteoarthritis progression,and more and more experimental evidence shows that subchondral bone lesions play an important role in the pain caused by osteoarthritis.Osteoclasts,osteocytes,osteoblasts,endothelial cells,new generating nerves and blood vessels in the sub-chondral bone matrix microenvironment interact with each other and participate in the process of osteoarthritis pain.Therefore,regu-lating the subchondral bone matrix microenvironment is expected to become a new strategy to control joint pain.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.