Objective:To establish a prognostic prediction model for hepatocellular carcinoma (HCC) using bioinformatics approaches to guide personalized therapy.Methods:Based on bioinformatics, the differential analysis was carried out on the GSE19665 data set of The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and Gene Expression Omnibus (GEO), and the same differentially expressed genes were obtained by means of Wayne diagram. Functional enrichment analyses using Gene Ontology, Kyoto Encyclopedia of Genes and Genome, and Gene Set Enrichment Analysis were conducted on co-expressed genes. Based on clinicopathological and transcriptomic profiles, TCGA-LIHC patients were stratified into training ( n=246) and internal validation ( n=116) cohorts, with external validation using Japanese liver cancer data ( n=231) from the International Cancer Genome Consortium. A LASSO-Cox regression-derived risk scoring model was established and visualized as a nomogram. The clinical utility of the risk score was evaluated through multiple analytical approaches.A nomogram incorporating the risk score was developed, and its predictive performance was validated using the concordance index (C-index) and calibration curves. The measurement data of normal distribution were expressed as mean±standard deviation( ± s), and the t-test was used for comparison between groups. The measurement data with non-normal distribution were expressed as M( Q1, Q3), and the Wilcoxon test was used for comparison between groups. The Kruskal-Wallis test was applied to evaluate the significance of the differences among multiple groups. The prognostic value of the risk score was estimated using Kaplan-Meier analysis and ROC curve. Multivariate Cox regression clarified the independent prognostic value of the risk score. Results:Differential analysis identified 457 commonly expressed differentially expressed genes (DEGs). Enrichment analysis revealed that these common DEGs were significantly enriched in pathways related to the cell cycle of tumor cells.The LASSO-Cox regression model selected eight candidate genes ( CENPA, NDC80, ANXA10, NEIL3, G6 PD, MCM10, SOCS2, MMP1). The predictive risk score generated using these eight genes demonstrated a strong association with the overall survival of HCC patients.The nomogram combining the predictive risk score with clinicopathological features exhibited high predictive performance in both the training and validation cohorts. Furthermore, the prognostic value of this risk score was successfully validated in the external validation cohort. Conclusion:This study successfully developed a new predictive model that accurately predicts the 1-year, 3-year and 5-year survival rates of patients with liver cancer. This can serve as a potential tool to help guide patients in personalized treatment.

Background and Aims:Chronic skin ulcers are a significant disease affecting patients'daily lives and psychological well-being.Abnormalities in the cells and extracellular matrix within the tissue may disrupt the balance of the microenvironment,hindering the normal skin repair process and leading to delayed healing of the ulcer.There is currently a lack of research on the mechanisms underlying the development of chronic ulcers and their diagnostic biomarkers.Single-cell sequencing,a newly developed high-throughput sequencing method in recent years,uses gene sequencing at the single-cell resolution to precisely reveal disease mechanisms and has been applied in various diseases.This study used single-cell transcriptome sequencing(scRNA-Seq)to investigate the cellular heterogeneity in chronic skin ulcer tissue to elucidate the potential molecular mechanisms behind delayed healing and provide new insights for clinical treatment.Methods:The scRNA-Seq technology was used to compare the differences in cell subpopulations and gene expression between chronic ulcer tissue and normal skin tissue.Single cells were sorted using a microfluidic platform,and cDNA libraries were constructed for subsequent differential gene analysis and functional enrichment analysis.Results:scRNA-Seq analysis revealed significant immune-metabolic remodeling features in chronic ulcer tissue:the number of B cells,monocytes,and macrophages in ulcer tissue increased by 2.1 to 3.5 times compared to the normal tissue control.This was accompanied by widespread activation of collagen synthesis genes(COL1A1/COL3A1)and synergistic suppression of immune regulators(e.g.,granzyme family GZMA/GZMB/H).Cross-cell subpopulation functional network analysis showed that hypoxia response mediated by the HIF-1 signaling pathway and PI3K/Akt pathway abnormalities formed a positive feedback loop,exacerbating the imbalance in the secretion of inflammatory factors(CXCL3/8,TGFBI)and compensatory upregulation of mitochondrial oxidative phosphorylation.Conclusion:Chronic skin ulcers exhibit significant differences in cellular heterogeneity and gene expression,suggesting that chronic ulcers are not simply tissue defects but a complex pathological process dominated by chronic inflammation and immune dysregulation.The coordinated dysregulation of multiple cell subpopulations in the ulcer microenvironment,along with persistent inflammatory responses and metabolic abnormalities,is interconnected through the HIF-1/TNF/MAPK pathway network.Downregulation of granzyme gene family members and abnormal histone modifications may contribute to immune clearance defects,providing a theoretical basis for developing novel therapies targeting epigenetic regulation or mitochondrial function.

Background and Aims:Chronic skin ulcers are a significant disease affecting patients'daily lives and psychological well-being.Abnormalities in the cells and extracellular matrix within the tissue may disrupt the balance of the microenvironment,hindering the normal skin repair process and leading to delayed healing of the ulcer.There is currently a lack of research on the mechanisms underlying the development of chronic ulcers and their diagnostic biomarkers.Single-cell sequencing,a newly developed high-throughput sequencing method in recent years,uses gene sequencing at the single-cell resolution to precisely reveal disease mechanisms and has been applied in various diseases.This study used single-cell transcriptome sequencing(scRNA-Seq)to investigate the cellular heterogeneity in chronic skin ulcer tissue to elucidate the potential molecular mechanisms behind delayed healing and provide new insights for clinical treatment.Methods:The scRNA-Seq technology was used to compare the differences in cell subpopulations and gene expression between chronic ulcer tissue and normal skin tissue.Single cells were sorted using a microfluidic platform,and cDNA libraries were constructed for subsequent differential gene analysis and functional enrichment analysis.Results:scRNA-Seq analysis revealed significant immune-metabolic remodeling features in chronic ulcer tissue:the number of B cells,monocytes,and macrophages in ulcer tissue increased by 2.1 to 3.5 times compared to the normal tissue control.This was accompanied by widespread activation of collagen synthesis genes(COL1A1/COL3A1)and synergistic suppression of immune regulators(e.g.,granzyme family GZMA/GZMB/H).Cross-cell subpopulation functional network analysis showed that hypoxia response mediated by the HIF-1 signaling pathway and PI3K/Akt pathway abnormalities formed a positive feedback loop,exacerbating the imbalance in the secretion of inflammatory factors(CXCL3/8,TGFBI)and compensatory upregulation of mitochondrial oxidative phosphorylation.Conclusion:Chronic skin ulcers exhibit significant differences in cellular heterogeneity and gene expression,suggesting that chronic ulcers are not simply tissue defects but a complex pathological process dominated by chronic inflammation and immune dysregulation.The coordinated dysregulation of multiple cell subpopulations in the ulcer microenvironment,along with persistent inflammatory responses and metabolic abnormalities,is interconnected through the HIF-1/TNF/MAPK pathway network.Downregulation of granzyme gene family members and abnormal histone modifications may contribute to immune clearance defects,providing a theoretical basis for developing novel therapies targeting epigenetic regulation or mitochondrial function.

To promote the construction of a wound repair and regeneration system with Chinese characteristics, it is necessary to follow the principle of combining traditional Chinese and Western medicine, and integrate theory, clinical practice, and teaching. Traditional Chinese medicine emphasizes a holistic concept and the principle of dialectical treatment, while Western medicine focuses on etiological analysis and local treatment. The combination of Chinese and Western medicine can complement each other's advantages and improve treatment effectiveness. The key technological innovations in repairing and regenerating systems cover areas such as drug therapy, physical therapy, and the application of biomaterials. This article discusses the development potential and challenges of combining traditional Chinese and Western medicine in the field of wound repair and regeneration, providing new ideas and methods for the development of wound repair and regeneration. It is expected to bring better medical services and treatment effects to patients undergoing repair and regeneration.

Objective:To study the predictive role of tumor burden score (TBS) for tumor recurrence after radical resection in patients with hepatocellular carcinoma (HCC).Methods:Clinical data of 202 patients with HCC undergoing radical surgery at the 900th Hospital of Joint Logistics Support Force of the Chinese People's Liberation Army, between January 2015 and December 2017 were retrospectively analyzed, including 128 males and 74 females, aged (53.66±11.93) years old. The receiver operating characteristic (ROC) curve was used to assess the accuracy of TBS in predicting postoperative tumor recurrence. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors influencing postoperative tumor recurrence. A nomogram was established and validated using calibration curves and the C-index. Kaplan-Meier survival analysis was utilized to compare survival differences between the two patient groups.Results:The area under the ROC curve for TBS in predicting postoperative tumor recurrence in HCC patients was 0.779 (95% CI: 0.717-0.842), with an optimal cutoff value of 6.2. Univariate analysis revealed that factors such as hepatitis B virus DNA level >500 IU/ml, larger maximum tumor dia-meter, and TBS>6.2 were significant risk factors for postoperative tumor recurrence (all P<0.05). Multivariate analysis further indicated that TBS>6.2 ( OR=3.60, 95% CI: 1.081-12.012, P=0.037) and maximum tumor diameter ( OR=1.240, 95% CI: 1.034-1.487, P=0.020) were independent risk factors for postoperative recurrence. Based on these risk factors, a nomogram model was established, achieving a C-index of 0.788. Kaplan-Meier survival analysis showed a better postoperative overall survival and recurrence-free survival of the low TBS group compared to those of the high TBS group (all P<0.05). Conclusion:TBS can serve as a predictive indicator for the recurrence after radical resection in patients with HCC. Both TBS and tumor size are independent risk factors for postoperative recurrence. The nomogram model can be used for predicting recurrence following radical resection in HCC patients.

The increasing prevalence of the aging population, and inadequate and uneven distribution of medical resources, have led to a growing demand for telemedicine services. Gait disturbance is a primary symptom of neurological disorders such as Parkinson's disease (PD). This study proposed a novel approach for the quantitative assessment and analysis of gait disturbance from two-dimensional (2D) videos captured using smartphones. The approach used a convolutional pose machine to extract human body joints and a gait phase segmentation algorithm based on node motion characteristics to identify the gait phase. Moreover, it extracted features of the upper and lower limbs. A height ratio-based spatial feature extraction method was proposed that effectively captures spatial information. The proposed method underwent validation via error analysis, correction compensation, and accuracy verification using the motion capture system. Specifically, the proposed method achieved an extracted step length error of less than 3 cm. The proposed method underwent clinical validation, recruiting 64 patients with Parkinson's disease and 46 healthy controls of the same age group. Various gait indicators were statistically analyzed using three classic classification methods, with the random forest method achieving a classification accuracy of 91%. This method provides an objective, convenient, and intelligent solution for telemedicine focused on movement disorders in neurological diseases.
Humans ; Aged ; Parkinson Disease/diagnosis* ; Aging ; Algorithms ; Gait ; Lower Extremity

Objective:To evaluate extrathecal vs. intrathecal approach of Glisson's pedicle in laparoscopic hepatectomy of hepatocellular carcinoma (HCC). Methods:Clinical data of 96 HCC patients receiving laparoscopic hepatectomy at the Department of Hepatobiliary Surgery, the 900 Hospital of the United Logistics Force from Jan 2019 to Jun 2022 were retrospectively analyzed. Thrity-six cases were treated with extrathecal approach of Glisson's pedicle and 60 cases were by intrathecal approach.All those 60 undergoing intrathecal approach cases were matched by 1∶1 propensity score matching, and the caliper value was 0.02. The duration of surgery, blocking-time of hepatoduodenal ligament, intraoperative blood loss, indexes of the liver function and the prothrombin time on the 1st day of the postoperative period, rate of the postoperative complications, postoperative hospital stay, postoperative survival and recurrence were compared between the two groups.Results:After propensity score matching, 32 cases in each group were identified. The operation time of the extrathecal group was shorter than that of the intrathecal group [(207.5±77.4) minutes vs. (248.6±74.7) minutes, P=0.03], the intraoperative bleeding volume was less than that of the intrathecal group [(150.0(100.0, 300.0) ml vs. 250.0(150.0, 587.5) ml, P=0.01], and the albumin level was higher on the 1st day after the surgery [(36.5±3.2) g/L vs. (34.3±3.2) g/L, P<0.01]. There was no statistically significant difference in postoperative liver function, coagulation, complications, hospitalization time, all over survival rate between the two groups (all P>0.05). Conclusion:Extrathecal approach for Glisson's pedicle is safe and feasible in laparoscopic hepatectomy for HCC, with simpler surgical procedure, less intraoperative trauma.

Intelligent medical image segmentation methods have been rapidly developed and applied, while a significant challenge is domain shift. That is, the segmentation performance degrades due to distribution differences between the source domain and the target domain. This paper proposed an unsupervised end-to-end domain adaptation medical image segmentation method based on the generative adversarial network (GAN). A network training and adjustment model was designed, including segmentation and discriminant networks. In the segmentation network, the residual module was used as the basic module to increase feature reusability and reduce model optimization difficulty. Further, it learned cross-domain features at the image feature level with the help of the discriminant network and a combination of segmentation loss with adversarial loss. The discriminant network took the convolutional neural network and used the labels from the source domain, to distinguish whether the segmentation result of the generated network is from the source domain or the target domain. The whole training process was unsupervised. The proposed method was tested with experiments on a public dataset of knee magnetic resonance (MR) images and the clinical dataset from our cooperative hospital. With our method, the mean Dice similarity coefficient (DSC) of segmentation results increased by 2.52% and 6.10% to the classical feature level and image level domain adaptive method. The proposed method effectively improves the domain adaptive ability of the segmentation method, significantly improves the segmentation accuracy of the tibia and femur, and can better solve the domain transfer problem in MR image segmentation.
Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Magnetic Resonance Imaging ; Knee ; Knee Joint

Wound repair is a fundamental task that the whole field of the Burn and Plastic surgery pays urgent attention to and longs for a breakthrough. In this column, wound repair balance laws theory is expounded and we are expecting people in the field gradually began to value the use of balance law. Guided by the law of balance principle, people are required to conduct scientific research, improve clinical technique and develop new materials. The theory is designed to improve the level of scientific research and clinical diagnosis, and will set up a new milestone in the field of wound repair.

Objective:To investigate the safety and efficacy of venetoclax with low-dose cytarabine (LDAC) in Chinese patients with acute myeloid leukemia (AML) who are unable to tolerate intensive induction chemotherapy.Methods:Adults ≥ 18 years with newly diagnosed AML who were ineligible for intensive chemotherapy were enrolled in this international, randomized, double-blind, placebo-controlled trial. Globally, patients ( n=211) were randomized 2∶1 to either venetoclax with LDAC or placebo with LDAC in 28-d cycles, with LDAC on days 1-10. The primary endpoint was OS; the secondary endpoints included response rates, event-free survival, and adverse events. Results:A total of 15 Chinese patients were enrolled (venetoclax arm, n=9; placebo arm, n=6) . The median age was 72 years (range, 61-86) . For the primary analysis, the venetoclax arm provided a 38% reduction in death risk compared with the placebo[hazard ratio ( HR) , 0.62 (95% CI 0.12-3.07) ]. An unplanned analysis with an additional 6 months of follow-up demonstrated a median OS of 9.0 months for venetoclax compared with 4.1 months for placebo. The complete remission (CR) rates with CR with incomplete blood count recovery (CRi) were 3/9 (33%) and 0/6 (0%) , respectively. The most common non-hematologic adverse effects (venetoclax vs placebo) were hypokalemia[5/9 (56%) vs 4/6 (67%) ], vomiting[4/9 (44%) vs 3/6 (50%) ], constipation[2/9 (22%) vs 4/6 (67%) ], and hypoalbuminemia[1/9 (11%) vs 4/6 (67%) ]. Conclusion:Venetoclax with LDAC demonstrated meaningful efficacy and a manageable safety profile in Chinese patients consistent with the observations from the global VIALE-C population, making it an important treatment option for patients with newly diagnosed AML who are otherwise ineligible for intensive chemotherapy.