Objective A scoping review of domestically and internationally published studies on finite element analysis(FEA)based on three-dimensional(3D)human body model in preventing pressure ulcer(PU)was conducted,aiming to provide new directions for improving the prevention strategies of pressure ulcer.Methods We conducted a systematic search in both Chinese and English medical databases,including PubMed,Embase,CINAHL,Web of Science,Cochrane Library,Sinomed,CNKI,Wanfang and VIP,and engineering database(Engineering Village Compen-dex).The search period was from the inception of each database to July 29,2024.The information was extracted,and the results were analyzed and standardized for reporting.Results A total of 30 studies were included.The general methods of FEA based on 3D human body model include establishing geometric model,meshing,defining material properties,loading and setting boundary conditions,and solving equations.According to the contents of studies,they could be categorized into 4 distinct application domains,including identification of risk groups(n=9),position management(n=9),preventive dressings(n=10)and supportive surfaces(n=7).Conclusion FEA based on 3D human body model provides a foundation to PU biomechanical mechanism research and a scientific basis to the supplement and optimization of clinical prevention.Future studies should integrate clinical problems with simulations and further optimize simulations techniques and protocols.

Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.

Small cell lung cancer (SCLC) is the thoracic malignant tumor and accounts for about 15% of lung malignancies and transfer often occurs by the time of diagnosis. Extensive stage-small cell lung cancer (ES-SCLC) accounts for about 2/3 of all SCLC. For many years, radiotherapy has occupied an important position in the treatment of SCLC, especially in the treatment of ES-SCLC, because SCLC is more sensitive to radiotherapy. However, in recent years, immune checkpoint inhibitor has shown more excellent antitumor activity in the treatment of ES-SCLC and become the mainstream argument for the treatment of ES-SCLC. However, will radiotherapy be buried by the times among the therapeutic approaches for ES-SCLC? In this article, we will review the clinical progress of radiotherapy, immunotherapy and combination therapy for ES-SCLC.
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Humans ; Small Cell Lung Carcinoma/therapy* ; Lung Neoplasms/therapy* ; Immunotherapy ; Neoplasm Staging ; Radiotherapy/methods* ; Combined Modality Therapy

Objective A scoping review of domestically and internationally published studies on finite element analysis(FEA)based on three-dimensional(3D)human body model in preventing pressure ulcer(PU)was conducted,aiming to provide new directions for improving the prevention strategies of pressure ulcer.Methods We conducted a systematic search in both Chinese and English medical databases,including PubMed,Embase,CINAHL,Web of Science,Cochrane Library,Sinomed,CNKI,Wanfang and VIP,and engineering database(Engineering Village Compen-dex).The search period was from the inception of each database to July 29,2024.The information was extracted,and the results were analyzed and standardized for reporting.Results A total of 30 studies were included.The general methods of FEA based on 3D human body model include establishing geometric model,meshing,defining material properties,loading and setting boundary conditions,and solving equations.According to the contents of studies,they could be categorized into 4 distinct application domains,including identification of risk groups(n=9),position management(n=9),preventive dressings(n=10)and supportive surfaces(n=7).Conclusion FEA based on 3D human body model provides a foundation to PU biomechanical mechanism research and a scientific basis to the supplement and optimization of clinical prevention.Future studies should integrate clinical problems with simulations and further optimize simulations techniques and protocols.

Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.

A chronic refractory wound is caused by continuous skin damage. At the same time， it may be formed due to repeated infection， vascular insufficiency， diabetes， tumors， chronic osteomyelitis， and other reasons， resulting in wound repair interruption and recovery delay. Chronic refractory wound seriously affects the quality of life of patients and consumes a lot of medical resources. Polysaccharides in traditional Chinese medicine （TCM） are the effective components of most TCM. Modern pharmacological studies have found that polysaccharides contained in TCM have anti-inflammatory， antioxidant， anti-radiation， hypoglycemic， antiviral， anti-tumor， hypolipidemic， and immunomodulatory effects. Through the summary and analysis of the literature， it was found that the mechanism of polysaccharides in TCM to promote chonic refractory wound repair was mainly realized from the following aspects： firstly， regulating inflammatory cytokines like interleukin-4 （IL-4）， interleukin-10 （IL-10）， interleukin-8 （IL-8）， and tumor necrosis factor-α （TNF-α） or regulating macrophage-related inflammatory proteins and chemotactic proteins like MIP-2， MCP-1， to shorten the inflammatory period. Secondly， activating growth factors like platelet-derived growth fator （PDGF）， basic fibroblast growth factor （bFGF）， TGF-α， and vascular endothelial growth factor （VEGF） to recruit endothelial cells and fibroblasts into tissue proliferation. Thirdly， activationg VEGF and its downstream receptor vascular endothelial growth factor receptor-1 （VEGFR-1） and vascular endothelial growth factor receptor-2 （VEGFR-2）-mediatated protein kinase C/extracellular regulated kinases （PKC/ERK） signaling pathway or promoting angiogenesie and improving wound blood flow through angiotensin （ANG）. Fourthly， promoting the ablility of collagen synthesis by enhancing the secretion of hydroxyproline and hyaluronic acid （HA） from fibroblasts （FB） and regulating relevant matrix metalloenzymes and their enzyme inhibitor to regulate the extracellular matrix. Fifthly， eliminating free radiccals to reduce the damage caused by oxidative stress to tissue. Sixthly， enhancing the phagocytic ability of macrophages， the activity of natural killer cells， and the proliferation of T cells to improve the defense ability of tissue. Polysaccharides in TCM can repair wounds in many ways at the same time. Its advantage lies in the multiple targets and multiple pathways. It is expected that the research will pay more attention to the mechanism of wound repair by polysaccharide components in TCM when improving the treatment of chronic refractory wounds.

Tuberculosis （TB） and human immunodeficiency virus infection / acquired immune deficiency syndrome （HIV/AIDS） are both serious global public health threats. Early detection of infected persons and/or patients through TB/HIV bi-directional screening is crucial for prevention and control strategy in China and globally. In recent years， with the promotion and application of new TB and HIV detection technologies worldwide， TB/HIV bi-directional screening technologies and strategies have made remarkable changes. This expert consensus introduces the significance and challenges of TB/HIV bi-directional screening， summarizes important progress of research and applications， and makes recommendations on screening measures and procedures to further strengthen TB/HIV bi-directional screening in China.

Diabetic foot ulcer is a serious and destructive complication of diabetes， with the rates of disability and mortality increasing year by year， which poses a serious threat to human physical and mental health. In the treatment of diabetic foot ulcer with traditional Chinese medicine （TCM）， the combination of syndrome differentiation and overall concept can not only alleviate TCM syndrome but also accelerate wound healing， reduce wound recurrence， delay the further deterioration of diabetic foot ulcer， and decrease the rates of disability and mortality. Modern studies have demonstrated that the difficult healing of diabetic foot ulcer is closely associated with the abnormal distribution of cytokines such as inflammatory cytokines， growth factors， and chemokines. With the deepening of modern medical research on TCM， the treatment of diabetic foot ulcer via regulation of cytokines by Chinese medicinal monomers and prescriptions has become a research focus. This paper summarizes the current research status at home and abroad and draws the following conclusions. ① Sesamol， geniposide， Danggui Buxuetang， and Zizhu ointment can regulate tumor necrosis factor-α （TNF-α）， interleukin （IL）-1， IL-6， IL-10 and other inflammatory cytokines to inhibit wound inflammation. ② Angelicae Dahuricae Radix， salvianolic acid B， Sixiao powder， Badu Shengji ointment （Zhuang medicine）， etc.， regulate vascular endothelial growth factor （VEGF）， platelet-derived growth factor （PDGF）， transforming growth factor （TGF）， epidermal growth factor （EGF） and other growth factors to promote collagen deposition and angiogenesis on wound surface. ③ Paeoniflorin， cryptanshinone， bee venom， and Huiyang Shengji decoction regulate CXC chemokine ligand （CXCL） 1， CXCL2， C-C chemokine ligand （CCL） 2， CCL3， stromal cell-derived factor-1α （SDF-1α）， monocyte chemoattract protein-1 （MCP-1） and other chemokines to reduce inflammatory response and promote neovascularization and wound granulation tissue formation. ④ In the treatment of diabetic foot ulcer， Chinese medicinal monomers and prescriptions have different and complicated mechanisms. The multi-target treatment manner determines that Chinese medicines can act on a variety of cytokines to participate in various stages of wound healing and thus play a therapeutic role. The conclusion above aims to provide ideas for the experimental research and clinical treatment of diabetic foot ulcer with TCM in the future.

【Objective】 To select and identify miRNA signatures to predict TMB level in gastric cancer based on The Cancer Genome Atlas (TCGA) database and machine learning methods. 【Methods】 MiRNA expression and somatic mutation profiles of gastric cancer (GC) were downloaded from TCGA database. R "limma" package was performed to select differentially expressed miRNAs between high-TMB and low-TMB groups. Two machine learning algorisms, random forest (RF), and Support Vector Machine-Recursive Feature Elimination were utilized to identify miRNAs with the highest discriminative ability. ROC was used to test the predictive ability of these signatures in multiple datasets. Besides, immune cells of different TMB levels were compared by the CIBERSORT method. 【Results】 A total of 56 differentially expressed miRNAs (DE-miRNAs) were filtered. Functional enrichment analysis showed that these DE miRNAs are mainly enriched in signaling pathways related to tumor occurrence and development as well as immunity-related biological processes. The RF and SVM-RFE algorithms jointly identified 10 diagnostic features of miRNAs, among which only hsa-miR-210-3p is considered the most relevant predictive biomarker for TMB classification. The AUC value of hsa-miR-210-3p in the training, testing, and total sets is 0.822, 0.721, and 0.793, respectively, and has been validated in other cancer types. Besides, CIBERSORT analysis suggests differences in immune cell infiltration between high- and low-TMB groups. Meanwhile, there is a significant positive correlation between the expression of immune checkpoint related genes and mismatch repair related genes and hsa-miR-210-3p. 【Conclusion】 This study successfully identified hsa-miR-210-3p as a predictive biomarker for TMB classification, which can effectively predict TMB values in gastric cancer and other cancer patients and may provide some guidance for immunotherapy.

Inflammatory myofibroblastic tumor is a rare tumor of mesenchymal origin. A case of intratracheal inflammatory myofibroblastic tumor in a male child was reported. The clinical characteristics, diagnosis, treatment and prognosis of the disease were reviewed based on the literature, and a differential diagnosis between inflammatory myofibroblastic tumor and hamartoma was performed to ultimately confirm the nature of the tumor in the child.
Humans ; Child ; Male ; Trachea/pathology* ; Granuloma, Plasma Cell/diagnosis* ; Prognosis ; Diagnosis, Differential ; Tomography, X-Ray Computed