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.

By systematically combing ancient and modern literature， this paper examined Tribuli Fructus and Astragali Complanati Semen（ACS） used in the famous classical formulas from the aspects of name， origin， production area， harvesting and processing， clinical efficacy， so as to provide a basis for the development of famous classical formulas containing such medicinal materials. The results showed that the names of Tribuli Fructus in the past dynasties were mostly derived from its morphology， and there were nicknames such as Baijili， Cijili and Dujili. The name of ACS in the past dynasties were mostly originated from its production areas， and there were nicknames such as Baijili， Shayuan Jili and Tongjili. Because both of them had the name of Baijili， confusion began to appear in the Song dynasty. In ancient and modern times， the main origin of Tribuli Fructus were Tribulus terrestris， and ancient literature recorded the genuine producing areas of Tribuli Fructus was Dali in Shaanxi and Tianshui in Gansu， but today it is mainly cultivated in Anhui and Shandong. The fruit is the medicinal part， harvested in autumn throughout history. There is no description of the quality of Tribuli Fructus in ancient times， and the plump， firm texture， grayish-white color is the best in modern times. Traditional processing methods for Tribuli Fructus included stir-frying and wine processing， while modern commonly used is purified， fried and salt-processed. The ancient records of Tribuli Fructus were spicy， bitter， and warm in nature， with modern research adding that it is slightly toxic. The main effects of ancient and modern times include treating wind disorders， improving vision， promoting muscle growth， and treating vitiligo. The mainstream base of ACS used throughout history is Astragalus complanatus. Ancient texts indicated ACS primarily originated from Shaanxi province. Today， the finest varieties come from Tongguan and Dali in Shaanxi. The medicinal part is the seed， traditionally harvested in autumn. Modern harvesting occurs in late autumn or early winter， followed by sun-drying. Ancient texts valued seeds with a fragrant aroma as superior， while modern standards prioritize plump， uniform and free of impurities. Traditional processing methods for ACS included frying until blackened and wine-frying， while modern practice commonly employs purification methods. In terms of medicinal properties， the ancient and modern records are sweet and warm in nature. Due to originally classified under Tribuli Fructus， its effects were thus regarded as equivalent to those of Tribuli Fructus， serving as the medicine for treating wind disorders， additional functions included tonifying the kidneys and treating vitiligo. The present record of its efficacy is to tonify the kidney and promote Yang， solidify sperm and reduce urine， nourish the liver and brighten the eye， etc. Based on the textual research results， it is suggested that when developing the famous classical formulas of Tribuli Fructus medicinal materials， we should pay attention to the specific reference object of Baijili， T. terrestris and A. complanatus should be identified and selected， and the processing method should be in accordance with the requirements of the formulas.

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/.

Objective:To deeply explore the thematic needs and characteristics of learners regarding course elements based on the review texts of nursing massive open online courses (MOOC), providing a reference for achieving effective alignment between digital nursing education content and learner needs.Methods:Data were collected from the review texts of 112 nursing courses on the Chinese University MOOC platform using a web crawler script written with Python′s Requests library. The collection period spanned from the course launch dates to December 31, 2023. Sentiment analysis and high-frequency words analysis were conducted using Chinese text Nature language processing library, and core themes of learners′ positive and negative reviews were extracted using the latent dirichlet allocation.Results:A corpus of 18 184 nursing MOOC review texts was constructed, with positive sentiment reviews accounting for 89.30% (16 238/18 184) and negative sentiment reviews making up 10.70% (1 946/18 184). Word frequency analysis revealed that most nursing MOOC serve as carriers for blended online and offline teaching models, with students being the primary target audience, though social participants were also involved. The reviews effectively mirrored real-world clinical nursing scenarios. The need of learners was categorized into three major themes: content design and assessment, course resources and teaching strategies, and software applications and platform functionality.Conclusions:This study, leveraging text mining technology, thoroughly investigated the three thematic characteristics of nursing MOOC needs of online learners and proposed targeted optimization recommendations. Future research could incorporate other online teaching platforms and comprehensively construct a sentiment lexicon for nursing online course reviews using big data modeling and machine learning algorithms. These would enable a holistic analysis of the digital nursing education landscape, allowing for precise improvements to address existing shortcomings.

Objective:To deeply explore the thematic needs and characteristics of learners regarding course elements based on the review texts of nursing massive open online courses (MOOC), providing a reference for achieving effective alignment between digital nursing education content and learner needs.Methods:Data were collected from the review texts of 112 nursing courses on the Chinese University MOOC platform using a web crawler script written with Python′s Requests library. The collection period spanned from the course launch dates to December 31, 2023. Sentiment analysis and high-frequency words analysis were conducted using Chinese text Nature language processing library, and core themes of learners′ positive and negative reviews were extracted using the latent dirichlet allocation.Results:A corpus of 18 184 nursing MOOC review texts was constructed, with positive sentiment reviews accounting for 89.30% (16 238/18 184) and negative sentiment reviews making up 10.70% (1 946/18 184). Word frequency analysis revealed that most nursing MOOC serve as carriers for blended online and offline teaching models, with students being the primary target audience, though social participants were also involved. The reviews effectively mirrored real-world clinical nursing scenarios. The need of learners was categorized into three major themes: content design and assessment, course resources and teaching strategies, and software applications and platform functionality.Conclusions:This study, leveraging text mining technology, thoroughly investigated the three thematic characteristics of nursing MOOC needs of online learners and proposed targeted optimization recommendations. Future research could incorporate other online teaching platforms and comprehensively construct a sentiment lexicon for nursing online course reviews using big data modeling and machine learning algorithms. These would enable a holistic analysis of the digital nursing education landscape, allowing for precise improvements to address existing shortcomings.

Objective To investigate the expression of the histone deacetylase SIRT7 in glioma cells and its impact on epithelial-mesenchymal transformation(EMT),as well as its effects on proliferative,migratory and invasive capabilities of glioma cells.Methods Bioinformatics analysis was conducted on data from glioma patients in the Cancer Genome Atlas(TCGA)and the Chinese glioma Genome Atlas(CGGA)databases to explore the expression of SIRT7 gene in gliomas and its correlation with tumor grading,molecular characteristics and patient clinical prognosis.Glioma cells were randomly divided into control,SIRT7 knockdown,SIRT7 overexpression,drug treatment(10 μmol/L hydrochlorothiazide)and drug(10 μmol/L hydrochlorothiazide)+SIRT7 overexpression groups.The CCK-8 assay,cell scratch assay and Transwell assay were used to observe the effects of upregulating and downregulating SIRT7 expression on glioma cell proliferation,migration and invasion.RT-qPCR and Western blotting were employed to detect the effects of SIRT7 on the expression of neural cadherin(N-cadherin),Vimentin,E-cadherin,transforming growth factor-β(TGF-β),Ki-67,and Smad3 protein in glioma cells.Nude mouse tumor-bearing experiments were conducted to observe the effect of SIRT7 knockdown on glioma growth.Results Higher expression levels of SIRT7 gene were associated with poorer clinical prognosis(P＜0.0001).SIRT7 expression levels were significantly correlated with tumor grading and 1p19q coding status(P＜0.01).Compared with normal HA cells,glioma cells showed significantly increased SIRT7 expression levels(P＜0.01).CCK-8 assay results indicated that,compared with control group,the proliferation activity of glioma cells in SIRT7 knockout group was significantly decreased(P＜0.01),while SIRT7 overexpression group showed significantly increased proliferation activity(P＜0.01).EdU assay results showed that,compared with control group,the proportion of glioma cells in the proliferative stage was significantly decreased in SIRT7 knockdown group(P＜0.01),and significantly increased in SIRT7 overexpression group(P＜0.01).Western blotting results revealed that,compared with control group,the protein expression levels of TGF-β,Smad3,N-cadherin and Vimentin were significantly decreased in SIRT7 knockdown group(P＜0.01),while the expression level of E-cadherin protein was significantly increased(P＜0.05).SIRT7 overexpression group showed significantly increased protein expression levels of TGF-β,Smad3,N-cadherin and Vimentin(P＜0.05),and a significantly decrease in E-cadherin protein expression level(P＜0.05).Scratch assay results indicated that,compared with control group,the migration ability of cells in SIRT7 knockdown group and drug group was significantly decreased(P＜0.01),and SIRT7 overexpression group showed significantly increased cell migration ability(P＜0.05).Compared with drug group,drug+SIRT7 overexpression group exhibited significantly increased cell migration ability(P＜0.01).Transwell assay results showed that,compared with control group,the migration and invasion abilities of cells in SIRT7 knockdown group and drug group were significantly decreased(P＜0.01),and SIRT7 overexpression group exhibited significantly increased migration and invasion abilities(P＜0.01).Compared with drug group,drug+SIRT7 overexpression group showed significantly increased migration and invasion abilities(P＜0.01).Nude mouse tumor-bearing assay results indicated that the volume and weight of glioma in SIRT7 knockdown group were significantly reduced compared with control group(P＜0.01).Conclusions Glioma patients with high SIRT7 expression have poorer clinical prognosis.SIRT7 can regulate the TGF-β/Smad3 pathway to mediate EMT,promoting the proliferation and migration of glioma cells.SIRT7 knockdown can inhibit the growth of transplanted gliomas in nude mice.

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/.

OBJECTIVE To establish the precise management model for the centralized preparation of cytotoxic drugs in pharmacy intravenous admixture services(PIVAS),and evaluate the effects of its application.METHODS Pharmacists in PIVAS established the precise management model by soliciting clinical opinions and consulting literature on the centralized preparation of cytotoxic drugs and continuously refining every step of the preparation of cytotoxic drugs,based on data feedback from the information closed-loop management system and the limit of stability time of finished solutions.The indicators such as the preparation time,delivery time,the storage time of finished infusion solutions after preparation,and the completion rate of infusion within the stability time limit were analyzed before the implementation(January to December 2023)and after the implementation(January to December 2024)of this model,to evaluate its application effectiveness.RESULTS The overall framework for the precise management model included upgrading the functions of the prescription review system,improving the prescription review database,providing specialized training for PIVAS pharmacists,managing dynamic batch decision for drug preparation,managing special drugs,managing finished infusion distribution,and establishing a continuous improvement mechanism.Compared with before implementation,the average preparation time of the second and third batches of cytotoxic drugs with more concentrated morning preparation tasks in this model was significantly shorter than before implementation(P＜0.05);the delivery time of finished infusion after implementation[(11.49±2.92)min]was significantly shorter than the delivery time before implementation[(22.11±5.03)min](P＜0.001);the storage time of some drugs with shorter stable time limit and carboplatin in combination regimens(paclitaxel or docetaxel+carboplatin)was significantly shortened compared to before implementation(P＜0.05),and the completion rate of infusion within the stability time limit was significantly improved compared to before implementation(P＜0.05).CONCLUSIONS Our hospital has successfully established a precise management model for the centralized preparation of cytotoxic drugs in PIVAS.This mode can significantly shorten the preparation time of each batch of PIVAS in the morning,make batch decisions more reasonable and improve the infusion completion rate within the stable time limit of the finished product.