Cancer has become a significant global public health issue， severely impacting public health and societal development. Despite advances in tumor treatment methods in recent years and a gradual decline in cancer mortality rates， drug-related adverse reactions and drug resistance remain substantial challenges. Traditional Chinese medicine （TCM） has demonstrated significant clinical efficacy in cancer treatment and small side effects， making it widely applied in the field of oncology. Xuefu Zhuyutang， derived from Yilin Gaicuo， is known for its abilities to invigorate blood circulation， dispel blood stasis， promote Qi flow， and alleviate pain. It was specifically formulated by the esteemed WANG Qingren of the Qing dynasty for the "blood stasis syndrome in the blood mansion" and is commonly used to treat Qi stagnation and blood stasis syndrome. Clinical studies have shown that Xuefu Zhuyutang， when combined with conventional Western medications， produces significant effects in the treatment of malignant tumors such as liver cancer， lung cancer， and cervical cancer. It substantially reduces the incidence of adverse reactions following Western treatments， including radiation esophagitis， radiation encephalopathy， radiation-induced oral mucositis， and edema. Additionally， it alleviates cancer-related pain and fever， blood hypercoagulability， and associated complications such as depression and anxiety， and also mitigates chemotherapy-induced side effects like hand-foot syndrome. Basic research has demonstrated its potential anti-tumor mechanisms， including the inhibition of Wnt/β-catenin signaling pathway activation， suppression of mitogen-activated protein kinase （MAPK） pathway activation， and anti-tumor angiogenesis. Pharmacological studies have revealed that its active components inhibit tumor cell proliferation and migration， induce tumor cell apoptosis， suppress tumor angiogenesis， enhance the cytotoxicity of natural killer cells against tumors， improve the tumor microenvironment， and regulate immune function. This paper reviewed the latest research progress on Xuefu Zhuyutang in the treatment of malignant tumors from four aspects： theoretical exploration， clinical studies， mechanisms of action， and pharmacological basis， aiming to provide insights and methods for the clinical diagnosis and treatment of malignant tumors.

Cancer has become a significant global public health issue， severely impacting public health and societal development. Despite advances in tumor treatment methods in recent years and a gradual decline in cancer mortality rates， drug-related adverse reactions and drug resistance remain substantial challenges. Traditional Chinese medicine （TCM） has demonstrated significant clinical efficacy in cancer treatment and small side effects， making it widely applied in the field of oncology. Xuefu Zhuyutang， derived from Yilin Gaicuo， is known for its abilities to invigorate blood circulation， dispel blood stasis， promote Qi flow， and alleviate pain. It was specifically formulated by the esteemed WANG Qingren of the Qing dynasty for the "blood stasis syndrome in the blood mansion" and is commonly used to treat Qi stagnation and blood stasis syndrome. Clinical studies have shown that Xuefu Zhuyutang， when combined with conventional Western medications， produces significant effects in the treatment of malignant tumors such as liver cancer， lung cancer， and cervical cancer. It substantially reduces the incidence of adverse reactions following Western treatments， including radiation esophagitis， radiation encephalopathy， radiation-induced oral mucositis， and edema. Additionally， it alleviates cancer-related pain and fever， blood hypercoagulability， and associated complications such as depression and anxiety， and also mitigates chemotherapy-induced side effects like hand-foot syndrome. Basic research has demonstrated its potential anti-tumor mechanisms， including the inhibition of Wnt/β-catenin signaling pathway activation， suppression of mitogen-activated protein kinase （MAPK） pathway activation， and anti-tumor angiogenesis. Pharmacological studies have revealed that its active components inhibit tumor cell proliferation and migration， induce tumor cell apoptosis， suppress tumor angiogenesis， enhance the cytotoxicity of natural killer cells against tumors， improve the tumor microenvironment， and regulate immune function. This paper reviewed the latest research progress on Xuefu Zhuyutang in the treatment of malignant tumors from four aspects： theoretical exploration， clinical studies， mechanisms of action， and pharmacological basis， aiming to provide insights and methods for the clinical diagnosis and treatment of malignant tumors.

ObjectiveTo investigate the correlation between sleep patterns and myopia progression among younger school-age children at a primary school in Changning District of Shanghai, based on the data from the Shanghai Students’ Common Diseases and Health Influencing Factors Monitoring System and a sleep-specific survey, so as to provide data support for myopia prevention and control in this age group. MethodsOne primary school was selected from the common diseases and health influencing factors monitoring system for students in Changning District, Shanghai. A total of 230 first-grade students were included in the study. Myopia and refractive parameters were examined, and sleep patterns were investigated. General demographic characteristics and myopia-related behavior data of the students were also collected. Sleep patterns were evaluated in terms of sleep duration, sleep efficiency, and sleep quality, with the latter assessed using the Chinese version of the Children’s Sleep Habits Questionnaire (CSHQ). Multiple linear regression and binary logistic regression models were used to analyze the association between sleep patterns and myopia progression among these students. ResultsThe results of the regression analyses revealed that the total CSHQ score of the students at baseline survey was (48.85±7.15) points. Their sleep efficiency was (94.49±8.48)%, sleep duration was (9.58±0.93) hours, and the proportion of those with insufficient sleep (<10 hours) was 78.26%. At baseline survey, students’ higher daytime sleepiness scores were associated with lower spherical equivalent (SE) ( β=-0.18, 95%CI: -0.31 to -0.04) and an increased risk of axial length (AL) / corneal radius (CR) ratio >3 (OR=1.52, 95%CI: 1.00 to 2.29), whereas longer sleep duration and higher sleep efficiency were associated with higher SE (β=0.18, 95%CI: 0.05 to 0.32; β=0.17, 95%CI: 0.04 to 0.31, respectively), shorter (AL) (β=-0.15, 95%CI: -0.27 to -0.03; β=-0.13, 95%CI: -0.25 to 0, respectively) and a reduced risk of AL /CR>3 (OR=0.70, 95%CI: 0.51 to 0.96; OR=0.73, 95%CI: 0.53 to 0.99, respectively). At baseline survey, children’s higher propensity for sleep problems (OR=1.70, 95%CI: 1.04 to 2.78), sleep resistance (OR=2.26, 95%CI: 1.36 to 3.75), and sleep anxiety scores (OR=2.15, 95%CI: 1.33 to 3.48) were all associated with an increased risk of AL/CR >3 at follow-up (all P<0.05). Furthermore, higher sleep anxiety scores predicted prolonged AL at follow-up (β=0.03, 95%CI: 0 to 0.05). According to the mixed-effects model, higher daytime sleepiness scores and prolonged sleep duration were independently linked to reduced right-eye SE (β=-0.05, 95%CI: -0.10 to 0, P<0.05) and shorter right-eye AL (β=-0.05, 95%CI: -0.10 to 0, P<0.05). ConclusionIn this school in Shanghai, there are problems of insufficient and poor-quality sleep among young children. Sleep problems such as sleep resistance, delayed sleep onset, sleep anxiety, and daytime sleepiness among children may accelerate the risk of myopia progression, while longer sleep duration and higher sleep efficiency may serve as protective factors against the occurrence and development of myopia.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Drug development encompasses multiple processes,wherein protein subcellular localization is essential.It promotes target identification,treatment development,and the design of drug delivery systems.In this research,a deep learning framework called LocPro is presented for predicting protein subcellular localization.Specifically,LocPro is unique in(a)combining protein representations from the pre-trained large language model(LLM)ESM2 and the expert-driven tool PROFEAT,(b)implementing a hybrid deep neural network architecture that integrates convolutional neural network(CNN),fully connected(FC)layer,and bidirectional long short-term memory(BiLSTM)blocks,and(c)developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels.Additionally,a dataset was curated and divided using a homology-based strategy for training and validation.Compar-ative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction.The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization.All in all,LocPro serves as a valuable complement to existing protein localization prediction tools.The web server is freely accessible at https://idrblab.org/LocPro/.

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 summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective:To analyze the impact of achieving behavioral and metabolic factor control targets on cardiovascular disease (CVD) risk in hypertensive patients.Methods:This retrospective study utilized data from the National Enssential Public Health Service program in Kunshan City, Jiangsu Province. Hypertensive patients who participated in the program in 2018 were enrolled and divided into six groups accoding to the number (0-1, 2, 3, 4, 5, or 6) of controlled behavioral and metabolic factors (blood glucose, blood pressure, low-density lipoprotein cholesterol, obesity, smoking, and physical activity). Baseline data were collected from the 2018 health examinations and stratified intervention management records to analyze the distribution of characteristics across groups. Patients were followed up, with incident CVD during follow-up as the primary outcome. Competing-risk Cox proportional hazards regression model was employed to assess the impact of achieving behavioral and metabolic control targets on CVD risk. Differences in cumulative incidence of CVD between groups were compared using Gray′s test for equality of cumulative incidence functions. The population attributable fractions (PAF) for each behavioral and metabolic factors were calculated using the "averisk" package in R software.Results:A total of 87 338 hypertensive patients were included, aged (62.88±9.14) years, with 42 419 males (48.57%). During a follow-up of 75.0 (60.0, 77.0) months, 10 200 incident cases of CVD and 3 187 non-CVD deaths were recorded. The cumulative incidence of CVD was 13.69% (95% CI 13.35-14.03), with no statistically significant difference between males and females (13.99% vs. 13.41%, Pgray=0.246). Cox regression analysis revealed that after adjusting for confounders, the risk of CVD in hypertensive patients showed a decreasing trend with an increasing number of controlled behavioral and metabolic factors ( P for trend<0.001). Specifically, achieving all six control targets was associated with a 48% reduction in CVD risk ( HR=0.52, 95% CI 0.44-0.62, P<0.001) compared to achieving only 0-1 control targets. Moreover, the combined PAF of all six factors for CVD incidence was 23.98% (95% CI 19.99%-27.97%). Physical inactivity had the highest PAF (8.70% (95% CI 5.19%-12.21%)), followed by uncontrolled blood glucose (7.30% (95% CI 6.36%-8.25%)) and elevated low-density lipoprotein cholesterol (5.54% (95% CI 3.58%-7.50%)). Conclusion:Compared to achieving only 0-1 control targets, attaining all six behavioral and metabolic control targets was associated with a 48% reduction in CVD risk among hypertensive patients. Furthermore, controlling all six factors could prevent 23.98% of CVD cases in the hypertensive population. Therefore, multifactorial coordinated interventions should be prioritized as a core strategy in the National Essential Public Health Services Program to effectively achieve the goal of primary CVD prevention at the population level.

Objective To explore the safety and accuracy of the disposable pulmonary nodule localization needle under CT-guided in the application for solitary pulmonary nodule(SPN).Methods A retrospective selection was conducted on 150 patients with SPN.All patients underwent thoracoscopic surgery after the lesions were localized by the disposable pulmonary nodule localization needle under CT-guided.According to the localization accuracy,they were divided into the better localization group(n=91)and the poorer localization group(n=59).Multivariate logistic regression analysis was performed to identify risk factors for poorer localization accuracy.Latent class analysis of the model was applied to compare the differences in the distribution characteristics and patterns of the influencing factors.Results Compared with the better localization group,the poorer localization group had an increase in both adverse postoperative pathological conditions and complications(P＜0.05).Age,course of disease,body mass index(BMI),smoking history,drinking history,diameter of the lesion,vertical distance from the nodule to the pleura,and thickness of the chest wall were the risk factors for poorer localization accuracy(P＜0.05).In both the high-risk group and the low-risk group with poorer localization accuracy,there were two mutually independent latent class analysis models.Compared with the low-risk group with poorer localization accuracy,the high-risk group exhibited a higher proportion of"more distribution of risk factors"(P＜0.05).Conclusion The quality of localization accuracy directly affects the probabilities of postoperative pathological conditions and complications.