Abstract The prevention and control of myopia in Chinese children and adolescents has become a major public health issue. While maintaining increased outdoor activity as a cornerstone intervention, there is an urgent need to explore new complementary approaches that can be effectively implemented in both indoor and outdoor settings. In recent years, environmental spatial frequency has gained increasing attention as one of the key environmental factors influencing the development and progression of myopia. Both animal studies and human research have confirmed that indoor environments lacking mid to high spatial frequency components, often characterized as "visually impoverished", can promote axial elongation and myopia through mechanisms such as disruption of retinal neural signaling, impaired accommodative function, and altered expression of related molecules. Based on the scientific consensus, it is recommended that "enriching of environmental spatial frequency" should be integrated into the myopia prevention and control framework. Following the principles of schoolled organization, family cooperation, community involvement, and student participation, specific measures are put forward in three areas：optimizing school visual settings, improving home spatial environments, and promoting healthy visual behavior. The aim is to create "visually friendly" indoor environments as an important supplement to outdoor activity, thereby providing a novel perspective and strategy for comprehensively advancing myopia prevention and control among children and adolescents.

Objective: To report the antibody identification, blood management during pregnancy and the monitoring process of fetal hemolytic disease of fetus and newborn (HDFN) in a pregnant woman with a history of blood transfusion and pregnancy who developed anti-Jr . Methods: Saline tube technique and anti-human globulin technique were used for maternal blood typing, unexpected antibody screening and identification, as well as for determining antibody titer and IgG subclasses. PCR-SSP was employed for genotyping of 18 blood group systems. Next-generation sequencing (NGS) was utilized for gene sequencing of 38 blood group systems. Sanger sequencing was applied to verify rare blood group mutations detected by NGS and to investigate the corresponding rare blood group genes in family members. Blood preparation was achieved through anemia management in prenatal clinics and autologous blood collection during pregnancy. The newborn underwent the three primary tests for HDFN and plasma IgG subclass testing. Results: The pregnant woman's blood type was B, RhD positive, with a positive unexpected antibody screen, and the antibody identification pattern was consistent with a high-frequency antigen antibody. Gene sequencing revealed a homozygous ABCG2 c.376C>T mutation in the woman, resulting in the Jr(a-) phenotype, and anti-Jr antibody was present in her plasma. No compatible Jr(a-) blood was found among family members. The maternal anti-Jr IgG titer remained stable at 256 during pregnancy, with no detectable IgG1 or IgG3 subclasses against the Jr antigen. A total of 800 mL of autologous blood was collected in two stages during pregnancy. The newborn was B, RhD positive, Jr(a+), with a positive unexpected antibody screen (anti-Jr ). IgG subclass typing detected no IgG1 or IgG3. The direct antiglobulin test was positive, while the acid elution test was negative. Conclusion: The combination of serology and blood group genetic analysis provides a diagnostic basis for identifying antibodies to high-frequency antigens. Managing perinatal anemia and implementing staged autologous blood storage can secure blood supply for the perioperative period. IgG antibody subclass typing offers a reference for clinical assessment and prevention of HDFN.

In order to investigate the chemical constituents of glycosides in Aconitum tanguticum (Maxim.) Stapf, column chromatographic techniques such as silica gel, ODS, Sephadex LH-20, and semi-preparative high performance liquid chromatography were used to afford eight glycosides from the n-butanol fraction of the 85% ethanol extract of Aconitum tanguticum. Based on the physicochemical properties and spectral data, these compounds were identified as N-4-O-(β-D-glucopyranosyl)-phenethylbenzamide (1), N-(2'-β-D-glucopyranosyl-5'-methoxysalicyl)-4-hydroxy-3-methoxyanthranilic acid methyl ester (2), N-(2'-β-D-glucopyranosyl-5'-hydroxysalicyl)-4-hydroxy-3-methoxyanthranilic acid methyl ester (3), salidroside (4), benzyl primeveroside (5), phenethanol-β-D-xylose-(1''→6')-β-D-glucopyranoside (6), 4-dihydroxyphenethoxy-8-O-β-D-[6-O-(4-O-β-D-glucopyranosyl)-feruloyl]-glucopyranoside (7), phenethanol-α-L-arabinopyranosyl-(1''→6')-β-D-glucopyranoside (8). Among them, compounds 1 and 2 were new compounds, and compounds 5,6,8 were isolated from Aconitum tanguticum for the first time.

Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

Chemical constituents of n-butanol fraction of ethanol extract from the leaves of Cyclocarya paliurus (Batalin) Iljinskaja were studied. Ten compounds were purified by silica gel, MCI, ODS, Sephadex LH-20 column chromatography and semi-preparative high-performance liquid chromatography. Based on the physicochemical properties and spectroscopic data, these compounds were identified as (4S)-4,8-dihydroxy-α-tetralone-5-[6′-(3′′,5′′-dimethoxy-(E)-p-coumaroyl)]-β-D-glucopyranoside (1), (4S)-4,8-dihydroxy-α-tetralone-5-[6′-(E)-feruloyl]-β-D-glucopyranoside (2), (1S,3R,4S,5R)-4,5-di-O-caffeoyl quinic acid methyl ester (3), (1R,3R,4S,5R)-3,4-di-O-caffeoyl quinic acid methyl ester (4), (3R,5R)-3,4,5-tri-O-caffeoylquinic acid methyl ester (5), (1R,3R,4S,5R)-3-O-caffeoyl-5-O-p-coumaroyl quinic acid methyl ester (6), (1R,3R,4S,5R)-3-O-p-coumaroy-4-O-caffeoyl quinic acid methyl ester (7), (1R,3R,4S,5R)-3-O-caffeoyl-4-O-p-coumaroy quinic acid methyl ester (8), (3R,5R)-3,5-di-O-caffeoyl quinic acid methyl ester (9) and (1S,3R,4R,5R)-4-O-caffeoyl-5-O-feruloyl quinic acid methyl ester (10). Among them, compound 1 was a new compound, and compounds 3–10 were isolated from the genus Cyclocarya for the first time.

Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective To explore the predictive value of serum levels of CXC chemokine ligand 4(CXCL4),CXC receptor 3 chemokine(CXCR3)for postoperative cerebral vasospasm(CVS)in patients with ruptured intracranial aneurysms.Methods The clinical data of 106 patients with intracranial aneurysms rupture who under went craniotomy and clipping surgery at the Central Hospital of Enshi Tujia and Miao Autonomous Prefecture from October 2020 to December 2022 were collected.The incidence of CVS was observed.Serum CXCL4 and CXCR3 levels were compared at 1,3,7 days after surgery between patients without CVS and patients with CVS.Spearman correlation coefficient was used to analyze the relationship between serum CXCL4,CXCR3 levels and CVS degree.ROC curve was used to analyze the value of serum CXCL4 and CXCR3 levels in predicting postoperative CVS.Results Among 106 patients with ruptured intracranial aneurysms,a total of 38 cases(35.85%)developed CVS after surgery,and 68 cases(64.15%)did not develop CVS.There was no statistically obvious difference in preoperative serum levels of CXCL4 and CXCR3 between the CVS group and the non CVS group(t=0.104,0.141,all P>0.05).The serum levels of CXCL4 and CXCR3 in the non CVS group were lower than those before surgery 1,3,and 7 day after surgery,and the differences were statistically significant(q=14.867,17.525,24.384;16.274,20.251,34.237,all P<0.05).Compated with preoperative levels,the levels of serum CXCL4 and CXCR3 in the CVS group decreased on postoperative 1 and 7 days,and the differences were statistically significant(q=9.486,4.858;10.760,9.104,all P<0.05).Compared with the mild CVS group,the serum levels of CXCL4 and CXCR3 in the moderate and severe CVS groups were obviously increased(q=2.982,5.992;2.961,3.465),and the serum levels of CXCL4 and CXCR3 in the severe CVS group were higher than those in the moderate CVS group(q=3.564,4.036),and the differences were statistically significant(all P<0.05),respectively.Spearman results showed that serum levels of CXCL4 and CXCR3 were positively correlated with the severity of CVS(r=0.491,0.483,all P<0.05).The ROC curve results showed that the AUC of CXCL4 and CXCR3 combined in predicting postoperative CVS in patients with intracranial ruptured aneurysms was higher than that of CXCL4,CXCR3 alone,and the differences were statistically significant(Z=2.937,2.750,all P<0.05).Conclusion The serum levels of CXCL4 and CXCR3 in ruptured intracranial aneurysms patients with postoperative CVS are obviously elevated,and the combined detection of the two can effectively predict the occurrence of CVS.

Objective To explore the role of sevoflurane(SEV)in sepsis-induced acute lung injury(ALI)and observe its impact on the Wnt/β-catenin signaling pathway.Methods Forty C57 mice were randomly divided into 4 groups(n=10 each):Sham,CLP,SEV,and SEV+XAV(β-catenin inhibitor).A sepsis model was established via cecal ligation and puncture.Lung injury was evaluated using HE staining,lung wet/dry weight ratio,and TUNEL staining.Levels of inflammatory factors(TNF-α,IL-1β,IL-6)were detected by ELISA.Oxidative stress indices(SOD,MDA,ROS)were measured by colorimetry and flow cytometry.Hindlimb blood perfusion and oxygenation were assessed with laser speckle flowmetry.Expressions of key Wnt pathway molecules and down-stream target genes(c-Myc,Cyclin D1)were detected by RT-qPCR and Western blot.Co-localization of β-catenin and SP-C(a marker of type Ⅱ alveolar epithelial cells)in lung tissues was determined by immunofluorescence staining.Results Compared with the Sham group,the CLP group exhibited significant increases in sepsis severity,lung pathological damage including alveolar structure destruction,inflammatory infiltration,and apoptosis,elevation in pro-inflammatory cytokine levels,and significant decrease in SOD and increase in MDA and ROS.Additionally,lower limb blood flow and oxygenation levels were significantly reduced,while the expression of β-catenin and its downstream target genes,as well as the co-localization signal and fluorescence intensity of β-catenin with SP-C,were significantly downregulated(all P<0.05).Compared with the CLP group,the SEV group showed significant improvements in all these indicators.However,compared with the SEV group,the SEV+XAV group demon-strated a reversed protective effect,with all indicators approaching the levels observed in the CLP group(all P<0.05).Conclusion Sevoflurane alleviates sepsis-induced ALI by activating Wnt/β-catenin signaling pathway,exerting anti-inflammatory and antioxidant effects,and enhancing the expression and localization of β-catenin in type Ⅱ alveolar epithelial cells.

Objective:To develop and validate the Pain nursing Competency Evaluation Questionnaire for Nursing Students to provide an effective tool for measuring the pain management competency of nursing students in China.Methods:The questionnaire was constructed through literature review, semi-structured interviews, focus group discussions, Delphi expert consultation, and a pre-survey. From September 2023 to January 2024, a convenience sampling method was used to select 250 nursing students from Hangzhou Normal University and Lishui University in Zhejiang Province for the survey. Reliability and validity of the developed questionnaire were tested. A random sample of 30 nursing students was selected for retesting after two weeks.Results:A total of 10 female experts were consulted through correspondence. The Pain Care Competency Evaluation Questionnaire for nursing students consists of 36 items. Through exploratory factor analysis, five common factors were extracted: pain health education, comprehensive pain assessment, pain screening and assessment, analgesic interventions, and analgesic side effects nursing, which together explained 61.695% of the variance. The content validity of the questionnaire was 0.96, and the item-level content validity index ranged from 0.900 to 1.000. The overall Cronbach′s α coefficient was 0.924, and the Cronbach′s α coefficients for the five dimensions ranged from 0.856 to 0.915. The test-retest reliability was 0.831. Conclusions:The Pain Care Competency Evaluation Questionnaire for nursing students developed in this study has good reliability and validity. It can be used as a tool to assess nursing students′ competency in pain care and provides a reference for the design and optimization of pain care courses and clinical practice programs for nursing students in undergraduate institutions.