[Objective] To explore the predictive value of HALP score for prognosis in patients with multiple myeloma (MM). [Methods] A retrospective analysis was conducted on laboratory indicators and related clinical data of newly diagnosed multiple myeloma (NDMM) patients, treated at the Affiliated Hospital of North Sichuan Medical College from January 2016 to October 2023, prior to their first treatment. The HALP score was calculated, and the optimal cutoff value for HALP was determined using X-tile software. Survival analysis was performed using Kaplan-Meier curves for high HALP and low HALP groups. Univariate and multivariate analyses were conducted using the Cox regression model, and a forest plot was generated using Graphpad Prism to illustrate factors that may impact patient prognosis. The predictive ability of HALP score combined with β2-microglobulin and ECOG score for prognosis in MM patients was evaluated using receiver operating characteristic curve (ROC) analysis. [Results] A total of 203 MM patients were included, with the optimal cutoff value for HALP score being 29.15 (P<0.05). Among them, 101 patients were in the low HALP score group, and 102 patients were in the high HALP score group. The results of univariate and multivariate analysis using the Cox regression model showed that a HALP score <29.15 was an independent risk factor for progression-free survival (PFS) and overall survival (OS) (P<0.05). ROC curve analysis indicated that the combination of HALP score with β2-microglobulin and ECOG score had a higher predictive value for prognosis in MM patients compared to using HALP score alone. [Conclusion] The HALP score is closely related to the prognosis of patients with NDMM. A low HALP score indicates a poorer prognosis, while the combination of HALP score with β2-microglobulin and ECOG score provides a higher predictive value when assessed together.

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.

OBJECTIVE: Gastric cancer (GC) is one of the most common malignancies seen in clinic and requires novel treatment options. Morin is a natural flavonoid extracted from the flower stalk of a highly valuable medicinal plant Prunella vulgaris L., which exhibits an anti-cancer effect in multiple types of tumors. However, the therapeutic effect and underlying mechanism of morin in treating GC remains elusive. The study aims to explore the therapeutic effect and underlying molecular mechanisms of morin in GC. METHODS: For in vitro experiments, the proliferation inhibition of morin was measured by cell counting kit-8 assay and colony formation assay in human GC cell line MKN45, human gastric adenocarcinoma cell line AGS, and human gastric epithelial cell line GES-1; for apoptosis analysis, microscopic photography, Western blotting, ubiquitination analysis, quantitative polymerase chain reaction analysis, flow cytometry, and RNA interference technology were employed. For in vivo studies, immunohistochemistry, biomedical analysis, and Western blotting were used to assess the efficacy and safety of morin in a xenograft mouse model of GC. RESULTS: Morin significantly inhibited the proliferation of GC cells MKN45 and AGS in a dose- and time-dependent manner, but did not inhibit human gastric epithelial cells GES-1. Only the caspase inhibitor Z-VAD-FMK was able to significantly reverse the inhibition of proliferation by morin in both GC cells, suggesting that apoptosis was the main type of cell death during the treatment. Morin induced intrinsic apoptosis in a dose-dependent manner in GC cells, which mainly relied on B cell leukemia/lymphoma 2 (BCL-2) associated agonist of cell death (BAD) but not phorbol-12-myristate-13-acetate-induced protein 1. The upregulation of BAD by morin was due to blocking the ubiquitination degradation of BAD, rather than the transcription regulation and the phosphorylation of BAD. Furthermore, the combination of morin and BCL-2 inhibitor navitoclax (also known as ABT-737) produced a synergistic inhibitory effect in GC cells through amplifying apoptotic signals. In addition, morin treatment significantly suppressed the growth of GC in vivo by upregulating BAD and the subsequent activation of its downstream apoptosis pathway. CONCLUSION Morin suppressed GC by inducing apoptosis, which was mainly due to blocking the ubiquitination-based degradation of the pro-apoptotic protein BAD. The combination of morin and the BCL-2 inhibitor ABT-737 synergistically amplified apoptotic signals in GC cells, which may overcome the drug resistance of the BCL-2 inhibitor. These findings indicated that morin was a potent and promising agent for GC treatment. Please cite this article as: Wang Y, Sun XY, Ma FQ, Ren MM, Zhao RH, Qin MM, Zhu XH, Xu Y, Cao ND, Chen YY, Dong TG, Pan YF, Zhao AG. Morin inhibits ubiquitination degradation of BCL-2 associated agonist of cell death and synergizes with BCL-2 inhibitor in gastric cancer cells. J Integr Med. 2025; 23(3): 320-332.
Humans ; Flavonoids/therapeutic use* ; Stomach Neoplasms/pathology* ; Animals ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; Cell Line, Tumor ; Apoptosis/drug effects* ; Cell Proliferation/drug effects* ; Ubiquitination/drug effects* ; Mice ; Drug Synergism ; Mice, Inbred BALB C ; Mice, Nude ; Xenograft Model Antitumor Assays ; Flavones

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

McCune-Albright syndrome(MAS) is a postzygotic somatic mutation disorder caused by activating mutations in the GNAS gene, which encodes the α subunit of the stimulatory G protein. Its clinical features typically include polyostotic fibrous dysplasia, cafe-au-lait skin pigmentation, and endocrine hyperactivity, such as Cushing′s syndrome, hyperthyroidism, and growth hormone excess. Here, we report two rare cases of MAS complicated with adrenocorticotropic hormone(ACTH)-independent Cushing syndrome, and provide a review and analysis of previously reported MAS cases associated with Cushing′s syndrome.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

OBJECTIVE To study the characteristics,micro-traits and microscopic characteristics of Peucedani radix and seven kinds of its common varieties and summarize the key identification characteristics so as to provide a reference for the effective identifica-tion of Peucedani radix and its common varieties.METHODS The key identification features and high-definition images of Peucedani radix and its common varieties were obtained by using the identification methods of traits,microtraits and microscopy,combined with the techniques of depth-of-field extended imaging and image stitching,and some of the features were digitally extracted and statistical-ly analyzed by SPSS26.0 software.RESULTS The high-definition color image data of Peucedani radix and its common varieties were obtained.Its specific identification features were:root head length and annular sparseness,skin pore shape and area,root texture,and fracture surface oil spot density,etc.under the property identification;the diameter and number of oil chambers,the number of cathe-ters,the presence or absence of bast fibers and wood fibers,etc.under the microscopic identification.The results of statistical analysis showed that there were significant differences in skin pore area,oil chamber diameter and density,and conduit density among different varieties of Peucedani radix(P<0.01).CONCLUSION Micro-traits and microidentification methods can be comprehensively ap-plied to distinguish Peucedani radix and its common varieties.In particular,the microscopic features of polarized light holographic col-or images in cross section have significant distinguishing significance,and some of the features are digitally extracted and statistically analyzed,which makes up for the shortcomings of subjective factors in the traditional empirical identification research,and provides a reference for the circulation,testing,clinical medication,and standard drafting of Peucedani radix.

Cancer incidence in China has been rising steadily,with a particularly heavy burden from several high-prevalence malignancies.Medical examination for cancer plays a critical role in the early detection of cancer,precancerous lesions,and precursor conditions,thereby facilitating timely diagnosis and intervention.Such examination also addresses the growing demand for person-alized cancer screening services among diverse population groups.The development of evidence-based,context-specific cancer screening guidelines is essential to enhance the standardization,quality,and equity of preventive screening practices across the country,ultimately improving out-comes in early cancer detection and treatment.Guided by the Department of Medical Emergency Response of the National Health Commission,the Guidelines for Medical Examination for Cancer in Health Examination Agency(2025 Edition)were developed under the leadership of the National Cancer Center.A multidisciplinary panel of experts formulated the guidelines in accordance with the principles and methodology of the World Health Organization Handbook for Guideline Deve-lopment.The guidelines provide evidence-based recommendations on key clinical domains:target cancers and populations,overall screening workflow,screening protocols,diagnostic technolo-gies,result interpretation,follow-up procedures,and quality control.The primary objective is to standardize cancer screening practices in health examination agency and strengthen China's ca-pacity for prevention and control of high-burden cancers.

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.