Objective: To investigate the preventive and reparative mechanisms of platelet-rich plasma-biodegradable quick setting spray (PRP-BQSS) on solar dermatitis, thereby providing a safe and effective novel therapeutic approach for clinical application. Methods: PRP-BQSS was prepared. A ultraviolet B (UVB)-induced solar dermatitismodel was established in SPF-grade male SD rats. The rats were divided into the prevention experiment (treated with PRP-BQSS, L' Oréal SPF 50+sunscreen, Nature's Hall SPF 50+sunscreen, or saline) and the treatment experiment (treated with PRP-BQSS, Jingwanhong ointment, Green ointment, or saline). The effects were evaluated by measuring epidermal thickness (HE staining) and quantifying the integrated optical density (IOD) of inflammatory cells (CD11b staining). One-way ANOVA and Tukey's HSD test were performed using GraphPad Prism 9.4.0. Results: The PRP-BQSS exhibited significant efficacy in both prevention and repair. In the prevention experiment, the PRP-BQSS prevention group (Group A) showed only mild pale red erythema on the dorsal skin of rats, without significant swelling or desquamation. Histological analysis revealed that epidermal thickness in Group A (36.55±6.58 μm) was comparable to Groups B (L' Oréal, 34.84±6.59 μm) and C (Natural Hall, 34.59±8.20 μm)(P>0.05), but significantly lower than that in Group D (control group, 47.82±11.69 μm). Skin sections from Group A demonstrated intact epidermal structure with clear stratification and no significant inflammatory cell infiltration. The CD11b-positive cell count (24.30±7.43) was significantly lower than that in Group D (33.65±8.47, P<0.05). In the treatment experiment, HE staining of Group A (PRP-BQSS treatment group) showed intact epidermal structure with orderly arrangement of the basal layer, spinous layer, and granular layer, thin and uniform stratum corneum, and regular collagen fiber arrangement. The epidermal thickness of Group A (37.10±6.41 μm) showed no significant difference from Groups B (Jingwanhong ointment group, 38.66±9.07 μm) or C (Green ointment group, 35.72±4.98 μm)(P>0.05), but was significantly lower than that in Group D (control group, 48.35±8.99 μm)(P<0.05). The integral optical density value of CD11b-positive cells in Group A (32.82±11.01) was significantly lower than that in Group D (47.25±13.52, P>0.05). Moreover, the degree of inflammatory infiltration in Group A was relatively lower compared to Group B (37.14±9.20) and Group C (34.32±16.87), suggesting a superior repair capacity. However, the intergroup differences were not statistically significant (P>0.05). Conclusion: PRP-BQSS hydrogel dressing possesses dual preventive and reparative functions. It exerts its effects by reducing CD11b-positive cell infiltration (inflammation suppression) and promoting the orderly arrangement of the basal layer-epidermal layer-granular layer (epidermal reconstruction). This material holds promise as a novel and effective therapeutic approach for the prevention and treatment of solar dermatitis, particularly suitable for high-risk populations such as children, individuals with sensitive skin, and those engaged in outdoor activities.

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 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 assess the effectiveness of kinetic parameters of 18F-prostate specific membrane antigen (PSMA)-1007 PET/MR in distinguishing tumor recurrence (TR) from radiation necrosis (RN) in glioma patients. Methods:From January 2023 to June 2023, imaging data of 10 patients (6 males, 4 females; media age of 39.5 years) with gliomas who were suspected of recurrence and were referred for 18F-PSMA-1007 PET/MR scans at Sun Yat-Sen University Cancer Center were retrospectively analyzed. Static parameters from 18F-PSMA-1007 PET scans, including SUV max, SUV mean, metabolic tumor volume (MTV), and total lesion′s PSMA (TLP), as well as dynamic parameters including K 1, k 2, k 3, k 4, net influx rate (K i), and volume of distribution ( Vt) were obtained by using compartmental and multigraphical models. Additionally, parameters from dynamic contrast-enhanced MRI (DCE-MRI) were collected. Mann-Whitney U test was used to compare parameter differences between TR and RN groups. Spearman rank correlation analysis was used to explore the correlation between K i and DCE-MRI parameters. Results:Finally, 8 cases were diagnosed as TR and 2 cases were diagnosed as RN. The kinetic compartmental model-based evaluation determined that irreversible 2-tissue model (2T3K) provided the best-fitting results. The differences in SUV mean (median: 2.48 vs 0.89; Z=-2.09, P=0.044), SUV max (median: 4.04 vs 1.40; Z=-2.09, P=0.044), and K i (median: 1.33×10 -2vs 3.87×10 -3;Z=-2.10, P=0.044) between TR and RN groups were statistically significant. Some parameters of DCE-MRI also showed differences between the two groups ( Z=-2.09, P=0.044 for all). The K i yielded moderate correlation with DCE-MRI parameter Ve ( rs=0.650, P=0.042), while correlations between K i and other DCE-MRI parameters were not significant ( rs values: from -0.207 to 0.632, all P>0.05). Conclusion:Dynamic and multi-parametric 18F-PSMA-1007 PET/MR system holds promise for accurately distinguishing TR from RN in treated glioma patients.

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

The regulation of rhizosphere bacterial community structure and metabolism by plants in municipal solid waste landfills is a key to enhancing the biodegradation of chlorobenzene (CB). In this study, we employed biodiversity and metabolomics methods to systematically analyze the mechanisms of different plant species in regulating the rhizosphere bacterial community structure and metabolic features and then improved the methane (CH₄) oxidation and CB degradation capacity. The results showed that the rhizosphere soil of Rumex acetosa exhibited the highest CH₄ oxidation and CB degradation capacity of 0.08 g/(kg·h) and 1.72×10^-6 g/(L·h), respectively, followed by the rhizosphere soil of Amaranthus spinosus L., with the rhizosphere soil of Broussonetia papyrifera showing the weakest activity. Rumex acetosa promoted the colonization of Methylocaldum in the rhizosphere, and the small-molecule organic amine, such as triethylamine and N-methyl-aniline, secreted from the roots of this plant enhanced the tricarboxylic acid cycle and nicotinamide metabolism, thereby increasing microbial activity and improving CH₄ and CB degradation efficiency. Conversely, cinnamic acid and its derivatives secreted by Broussonetia papyrifera acted as autotoxins, inhibiting microbial activity and exacerbating the negative effects of salt stress on key microbes such as methanotrophs. This study probed into the mechanisms of typical plants growing in landfill cover soil in regulating bacterial ecological functions, offering theoretical support and practical guidance for the plant-microbe joint control of landfill gas pollution.
Biodegradation, Environmental ; Rhizosphere ; Soil Microbiology ; Waste Disposal Facilities ; Chlorobenzenes/metabolism* ; Bacteria/metabolism* ; Soil Pollutants/metabolism* ; Methane/metabolism* ; Plant Roots/microbiology* ; Amaranthus/microbiology* ; Soil

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.

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/.