[摘 要] 目的：明确线粒体DNA（mtDNA）部分缺失对结肠上皮细胞NCM460的影响。方法：通过溴化乙锭（EB）诱导建立mtDNA部分缺失细胞模型（mtDNA-reduced）及恢复模型（reverted），采用CCK-8、活性氧（ROS）及线粒体膜电位检测评估线粒体功能，通过葡萄糖、乳酸及糖酵解关键酶活性检测评估代谢表型，通过Transwell实验及WB法检测细胞侵袭及上皮-间质转化（EMT），通过polyHEMA包被培养检测失巢凋亡抵抗能力；检测PI3K/Akt/mTOR信号通路及程序性死亡配体1（PD-L1）表达，并通过PI3K抑制剂LY294002验证。结果：GEPIA数据库分析显示mtDNA编码基因在结直肠癌中低表达（P < 0.05）；组织芯片显示COX1蛋白在正常结肠组织高表达，在癌组织中低表达（P < 0.05）。mtDNA-reduced NCM460细胞线粒体功能受损（生长速率下降、ROS生成减少、线粒体膜电位降低，P < 0.05），呈现Warburg效应（葡萄糖摄取增加、乳酸分泌增多、糖酵解关键酶活性增强，P < 0.05），侵袭能力增强（P < 0.05）且发生EMT，并抵抗失巢凋亡（P < 0.05）。该细胞PI3K/Akt/mTOR通路激活且PD-L1表达上调；经LY294002处理后，葡萄糖含量有降低趋势（P > 0.05）、细胞活性下降（P < 0.05），PD-L1表达下调（P < 0.05）。结论：结肠上皮细胞NCM460中mtDNA部分缺失可诱导其恶性转化及免疫逃逸。

AIM:To evaluate the clinical efficacy of three types of spectacle lenses with different peripheral microstructure designs in controlling myopia progression among children.METHODS: Retrospective case analysis was conducted. Children diagnosed with myopia aged 6 to 12 y who were received initial spectacle fitting and completed 1-year follow-up at the Optometry Clinic of Suining Central Hospital between January 2023 and August 2024 were enrolled. Only right eye data of all subjects were included for analysis. Based on the type of spectacle lenses independently selected by the children and their parents/guardians, they were divided into four groups: diffusion optics technology(DOT), cylindrical annular refractive element(CARE), highly aspherical lenslets(HAL), and single-vision lenses(SVL). Changes in axial length(AL)and spherical equivalent(SE)from baseline were observed after 1-year lens wear in four groups. Variations between three peripheral microstructure-designed spectacles and single-vision spectacles were compared. The effects of different lens designs on spherical power, astigmatism, corneal curvature, corneal astigmatism, anterior chamber depth, lens thickness, and vitreous cavity depth were analyzed.RESULTS:In this retrospective study, a total of 118 eyes from 118 myopic children were included. There were 28 eyes in 28 children in DOT group [16 males and 12 females, age 10(9, 12)y]. CARE group contained 26 eyes in 26 children, [12 males and 14 females, age 11(9, 12)y]. HAL group had 26 eyes in 26 children [16 males and 10 females, age 10(9, 11)y]. SVL group included 38 eyes in 38 children [20 males and 18 females, age 11(9, 12)y]. There were no significant differences in age, gender, baseline AL, or SE among the four groups(all P>0.05). After 1-year wearing, no increase and slight regression were observed in AL and SE in the DOT group, with no significant differences compared with baseline(all P>0.05). AL and SE increased to varying degrees in the CARE, HAL and SVL groups(all P<0.01). Significant inter-group differences were found in the changes of AL and SE(F=22.820, 30.949, both P<0.001). The mean changes in AL and SE for the DOT group(-0.034±0.180 mm, 0.040±0.243 D)were significantly smaller than those in the CARE group(0.225±0.174 mm, -0.375±0.308 D)and the HAL group(0.147±0.130 mm, -0.255±0.256 D). The changes of AL and SE in the three groups were significantly lower than those in the SVL group(0.355±0.240 mm, -0.891±0.592 D)(all P<0.05).CONCLUSION: In children, short-term wear of spectacles with peripheral microstructural design demonstrates better myopia control efficacy compared to single-vision spectacles. DOT lenses show superior short-term efficacy compared with CARE and HAL lenses.

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

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.

Epidural spinal cord stimulation (eSCS) represents an emerging neuromodulation technology that ameliorates motor dysfunction in patients with spinal cord injury, Parkinson's disease, and stroke by activating sensory afferent fibers, enhancing spinal cord neural network integration, optimizing brain-spinal cord information transmission, and inducing neural plasticity. This article reviews the mechanism, electrode implantation, and stimulation parameter of eSCS, and application of eSCS in spinal cord injury, Parkinson's disease, and stroke, aiming to provide valuable insight for its clinical implementation.

OBJECTIVE To explore the effect of oral cleaning with traditional Chinese medicine preparations on de-colonization of oropharyngeal bacteria and hospital-acquired pneumonia(HAP)in elderly patients undergoing non-inva-sive mechanical ventilation.METHODS A total of 520 elderly patients who were treated with non-invasive mechani-cal ventilation in Enze Hospital of Enze Medical Center(Group)from Jan.2022 to Dec.2024 were recruited as the research subjects and were randomly divided into the normal saline group and the traditional Chinese medicine(TCM)preparation group,with 260 cases in each group.The two groups were respectively treated with normal saline and TCM preparations for oral cleaning,twice a day in the morning and evening.The dental plaque index score,isolation rate of oropharyngeal pathogens,incidence of HAP and isolation rates of pathogens causing HAP were observed and compared between the two groups.RESULTS There were no significant differences in the dental plaque index score and the isolation rate of oropharyngeal pathogens between the two groups of patients before the first cleaning.However,the dental plaque index score and the isolation rate of oropharyngeal pathogens were low-er in the TCM preparation group than in the normal saline group after the first cleaning and the continuous clean-ing for 5 days(P＜0.05).The incidence of HAP of the TCM preparation group(3.63％)was lower than that of the normal saline group(8.91％)(x2=5.872,P=0.015).The isolation rate of gram-negative bacteria from lower respiratory tract secretions of the patients with HAP was lower in the TCM preparation group than in the normal saline group(P＜0.05);there were no significant differences in the isolation rates of gram-positive bacteria and fungi between the two groups.CONCLUSION As compared with the normal saline for routine oral cleaning of the elderly patients undergoing non-invasive mechanical ventilation,the TCM preparations may facilitate the decoloni-zation of oropharyngeal bacteria and remarkably reduce the incidence of HAP,which may provide a new idea for decolonization of oropharyngeal bacteria and reduction of incidence of HAP.

Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

Increasing evidence showed that histone deacetylase 6(HDAC6)dysfunction is directly associated with the onset and progression of various diseases,especially cancers,making the development of HDAC6-targeted anti-tumor agents a research hotspot.In this study,artificial intelligence(AI)technology and molecular simulation strategies were fully integrated to construct an efficient and precise drug screening pipeline,which combined Voting strategy based on compound-protein interaction(CPI)prediction models,cascade molecular docking,and molecular dynamic(MD)simulations.The biological potential of the screened compounds was further evaluated through enzymatic and cellular activity assays.Among the identified compounds,Cmpd.18 exhibited more potent HDAC6 enzyme inhibitory activity(IC50=5.41 nM)than that of tubastatin A(TubA)(IC50=15.11 nM),along with a favorable subtype selectivity profile(selectivity index ≈ 117.23 for HDAC1),which was further verified by the Western blot analysis.Additionally,Cmpd.18 induced G2/M phase arrest and promoted apoptosis in HCT-116 cells,exerting desirable antiproliferative activity(IC50=2.59 μM).Furthermore,based on long-term MD simulation trajectory,the key residues facilitating Cmpd.18's binding were identified by decomposition free energy analysis,thereby elucidating its binding mechanism.Moreover,the representative conformation analysis also indicated that Cmpd.18 could stably bind to the active pocket in an effective conformation,thus demonstrating the potential for in-depth research of the 2-(2-phenoxyethyl)pyridazin-3(2H)-one scaffold.

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/.

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