OBJECTIVE: To explore the current research status and hotspots in the field of biomechanics of diabetic foot by bibliometric analysis methods. METHODS: Literatures related to biomechanics of diabetic foot published in the Web of Scienc Core Collection (WoSCC) from 1981 to 2024 were searched. CiteSpace software and R language bibliometrics plugin were used to conduct a visual analysis of annual publication volume of the literature, including publication volume of each country and region, the publication situation of authors and institutions, the citation situation of individual literature, and the co-occurrence network of keywords. RESULTS: Totally 996 literatures were included, and the number of published papers increased steadily. The United States (261 papers) and China (89 papers) were the top two countries in terms of the number of published papers. The mediating centrality of the United States was 0.94, and that of China was 0.01. Scholars such as Cavanagh and institutions like the Cleveland Clinic were at the core of research in this field. High-frequency keywords include plantar pressure (plantar pressure), diabetic foot (diabetic foot), ulceration (ulcer), etc. The research focuses on plantar pressure, ulcer formation and prevention, etc. CONCLUSION Biomechanical research on diabetic foot mainly focuses on the pressure distribution on the sole of the foot, callus formation, mechanical analysis of soft tissues on the sole of the foot, and the study of plantar decompression caused by Achilles tendon elongation. The research trend has gradually shifted from focusing on joint range of motion to gait and the design of braces and assistive devices, and has begun to pay attention to muscle strength, gait imbalance and proprioception abnormalities.
Humans ; Diabetic Foot/physiopathology* ; Biomechanical Phenomena ; Bibliometrics

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

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

ObjectiveTo investigate the value of noninvasive imaging detection （FibroScan）， two serological models of gamma-glutamyl transpeptidase-to-platelet ratio （GPR） score and S index， and two inflammatory factors of interleukin-6 （IL-6） and tumor necrosis factor-α （TNF-α） in predicting liver fibrosis in patients with HBeAg-positive chronic hepatitis B （CHB）， as well as the consistency of liver biopsy in pathological staging， and to provide early warning for early intervention of CHB. MethodsA retrospective analysis was performed for 131 HBeAg-positive CHB patients who underwent liver biopsy in The Third People’s Hospital of Kunming from January 2019 to December 2023. The results of liver biopsy were collected from all patients， and related examinations were performed before liver biopsy， including total bilirubin， alanine aminotransferase， platelet count， gamma-glutamyl transpeptidase， albumin， IL-6， TNF-α， liver stiffness measurement （LSM）， and abdominal ultrasound. An analysis of variance was used for comparison of normally distributed continuous data between groups， and the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between groups； the chi-square test was used for comparison of categorical data between groups. A Kappa analysis was used to investigate the consistency between LSM noninvasive histological staging and pathological staging based on liver biopsy， and the Spearman analysis was used to investigate the correlation between each variable and FibroScan in the diagnosis of liver fibrosis stage. The Logistic regression analysis was used to construct joint predictive factors. The receiver operating characteristic （ROC） curve was used to evaluate the value of each indicator alone and the joint predictive model in the diagnosis of liver fibrosis， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsIn the consistency check， inflammation degree based on liver biopsy had a Kappa value of 0.807 （P<0.001）， and liver fibrosis degree based on liver biopsy had a Kappa value of 0.827 （P<0.001）， suggesting that FibroScan noninvasive histological staging and liver biopsy showed good consistency in assessing inflammation degree and liver fibrosis stage. Age was positively correlated with LSM， GPR score， S index， IL-6， and TNF-α （all P<0.05）， and GPR score， S index， IL-6， and TNF-α were positively correlated with LSM （all P<0.05）. GPR score， S index， IL-6， and TNF-α were all independent risk factors for diagnosing significant liver fibrosis （≥S2） and progressive liver fibrosis （≥S3） （all P<0.05）. As for each indicator alone， GPR score had the highest value in the diagnosis of significant liver fibrosis （≥S2）， followed by S index， IL-6， and TNF-α， while S index had the highest value in the diagnosis of progressive liver fibrosis （≥S3）， followed by GPR score， TNF-α， and IL-6. The joint model had a higher predictive value than each indicator alone （all P<0.05）. ConclusionThere is a good consistency between FibroScan noninvasive histological staging and pathological staging based on liver biopsy. GPR score， S index， IL-6， and TNF-α are independent risk factors for evaluating different degree of liver fibrosis in CHB， and the combined prediction model established by them can better diagnose liver fibrosis.

AIM To study the chemical constituents from Citri reticulatae Pericarpium Viride and their anti-triple negative breast cancer activities in vitro.METHODS The ethanolic extract of Citri reticulatae Pericarpium Viride was isolated and purified by silica gel,polyamide,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The anti-triple negative breast cancer activities were screened by SRB assay,and their effects on the proliferation of triple negative breast cancer cell lines HCC1806,HCC1937 and MDA-MB-231 in vitro were evaluated.RESULTS Twenty compounds were isolated and identified as nobiletin(1),tangeritin(2),5,4'-dihydroxy-7,8-dimethoxy flavonoid(3),naringenin(4),artemetin(5),5-demethynobiletin(6),3,5,6,7,8,3',4'-pentamethoxy flavonoid(7),5,4'-dihydroxy-3,6,7,8,3'-pentamethoxyflavone(8),xanthomicrol(9),p-hydroxycinnamic acid(10),5,4'-dihydroxy-6,7,8,3'-tetramethoxyflavone(11),pectolinarigenin(12),4'-dihydroxy-5,6,7-tetramethoxyflavone(13),hispidulin(14),4',5,6,7-tetramethoxy-flavone(15),1-methyl-4-(prop-1-en-2-yl)cyclohexane-1,2-diol(16),umbelliferone(17),5-hydroxymethyl furfural(18),hydroquinone(19),1H-indole-3-carbaldehyde(20).Compound 8 showed a significant inhibitory effect with the IC50 value of(5.36±0.24)μmol/L on HCC1806 cells.CONCLUSION Compound 20 is isolated from genus Citrus for the first time,8,12-13,16-17 are isolated from this plant for the first time.Compound 8 show inhibitory effects on the proliferation of HCC1806,HCC1937 and MDA-MB-231 cells in vitro and have the strongest activities.Compounds 3-4,11-12,15,17 and 19 show strong inhibitory effect on HCC1806 cells.Compounds 15,19 also inhibit the proliferation of HCC1937 cells in vitro.

Objective:To formulate the Guidelines for the Construction of Community Health Service Centers in Pudong New Area, Shanghai. Methods:This was a qualitative study. This study was divided into 2 stages. The first stage of the study was conducted from June to August 2023 and involved the heads of the General Affairs Departments of the 47 community health service centers in Pudong New Area. These individuals completed online questionnaires to compile a database on the current status of matching supply and demand resources in community health service centers in Pudong New Area. The second stage of the study run from September 2023 to August 2024. Firstly, the functional modules of China′s community health service centers would be clarified through a literature review. The construction scale and design requirements of similar institutions at home and abroad would be benchmarked, as well as practical experience. The results of Phase 1 research would then be combined to form the " Community Health Service Center Infrastructure Configuration Requirements and Design Suggestions (Draft)". Then, relevant experts were brought together to discuss the draft and form the " Community Health Service Center Infrastructure Configuration Requirements and Design Recommendations (Revised Version)". The experts involved in the discussion specialized in the study of infrastructure resource allocation for medical institutions. Finally, the medical and healthcare system managers, community health service center users, and relevant commissions and bureaus of Pudong New Area were consulted to further revise and finalize the Guidelines for the Construction of Community Health Service Centers in Pudong New Area, Shanghai. Results:The total floor area of community health service centers in Pudong New Area was 57% (31/55), the number of beds per 1 000 people was 14% (8/55), and the total number of beds was 10% (6/60). These figures showed that urgent upgrades and construction in accordance with the new standards were required. The final " Guidelines for the Construction of Community Health Service Centers" of Shanghai Pudong New Area comprised 15 chapters, covering topics from the macro construction scale, site selection and general plan to architectural design, structural design, water supply and sewage treatment, ventilation and air conditioning, electrical systems, informatics, medical gas supply, indoor design, signage, marking and fire protection, etc. The guidelines have been revised to incorporate the functional design of the 5 basic rooms, with a particular focus on the creating humanistic spaces and promoting digitalization. Particular attention was paid to creating humanistic spaces and improving ageing with digital applications. Conclusions:The Guidelines for the Construction of Community Health Service Centers in Pudong New Area of Shanghai have been successfully formulated. These guidelines can be used to guide the subsequent high-quality and standardized development of community health service centers.

Gastric cancer with peritoneal metastasis (GCPM) is a common and lethal manifestation of advanced gastric cancer, with a median survival of only 5-11 months. This consensus was developed by 30 experts from Asia (China, Japan, Korea, and Singapore) using the Delphi method and the GRADE evidence grading system. A total of 29 statements were formulated, covering the diagnosis and assessment of GCPM, indications for laparoscopic exploration and NIPS (normothermic intraperitoneal and systemic treatment), treatment regimens, prevention and management of complications, criteria for conversion surgery, and postoperative intraperitoneal therapy. The consensus aims to standardize clinical practice and improve the prognosis of patients with GCPM.

In China,lung cancer ranks first in the incidence and death of malignant tumors.Early diagnosis and timely treatment can significantly improve the survival rate of lung cancer.However,75％of patients are already in the advanced stage at the time of initial diagnosis,missing the best treatment opportunity.Lung nodules are the manifestations of early lung cancer.How to accurately distinguish benign and malignant pul-monary nodules and avoid missing diagnosis of malignant lung nodules and over-treatment of benign lung nod-ules are important clinical problems.Liquid biopsy has the advantages of non-invasiveness,high reproducibili-ty,operability,easy dynamic monitoring and overcoming tumor heterogeneity,which can realize early detection and diagnosis of malignant tumors.Besides,it is the most potential precision tumor detection technology,which is expected to become a breakthrough in the diagnosis of benign and malignant lung nodules.This arti-cle reviews the research and application of liquid biopsy in the diagnosis of lung nodules in recent years,in or-der to provide ideas for clinical application and future research.

Advancements in artificial intelligence(AI)and emerging technologies are rapidly expanding the exploration of chemical space,facilitating innovative drug discovery.However,the transformation of novel compounds into safe and effective drugs remains a lengthy,high-risk,and costly process.Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development.Despite this need,no comprehensive tool currently supports systematic evaluation and efficient screening.Here,we present druglikeFilter,a deep learning-based framework designed to assess drug-likeness across four critical dimensions:1)physicochemical rule evaluated by systematic determination,2)toxicity alert investigated from multiple perspectives,3)binding affinity measured by dual-path analysis,and 4)compound synthesizability assessed by retro-route prediction.By enabling automated,multidimensional filtering of compound libraries,druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates,which can be freely accessed at https://idrblab.org/drugfilter/.