AIM:To automatically identify and quantitatively assess myopia-related fundus structural changes by combining non-mydriatic color fundus photography with an artificial intelligence(AI)-powered quantitative fundus analysis system and to further analyze the correlations between these fundus parameters and spherical equivalent(SE), axial length(AL), and age, providing the objective basis for monitoring myopia progression and supporting the formulation of personalized myopia prevention and control strategies. METHODS:A cross-sectional study was conducted enrolling myopic patients aged 18-50 y who underwent myopia screening from March 2023 to December 2023. Patients were stratified into three groups based on SE: the -3.00 D

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

INTRODUCTION: Lecanemab has shown promise in treating early Alzheimer's disease (AD), but its safety and efficacy in Chinese populations remain unexplored. This study aimed to evaluate the safety and 6-month clinical outcomes of lecanemab in Chinese patients with mild cognitive impairment (MCI) or mild AD. METHODS: In this single-arm, real-world study, participants with MCI due to AD or mild AD received biweekly intravenous lecanemab (10 mg/kg). The study was conducted at Hainan Branch, Ruijin Hospital Shanghai Jiao Tong University School of Medicine. Patient enrollment and baseline assessments commenced in November 2023. Safety assessments included monitoring for amyloid-related imaging abnormalities (ARIA) and other adverse events. Clinical and biomarker changes from baseline to 6 months were evaluated using cognitive scales (mini-mental state examination [MMSE], montreal cognitive assessment [MoCA], clinical dementia rating-sum of boxes [CDR-SB]), plasma biomarker analysis, and advanced neuroimaging. RESULTS: A total of 64 patients were enrolled in this ongoing real-world study. Safety analysis revealed predominantly mild adverse events, with infusion-related reactions (20.3%, 13/64) being the most common. Of these, 69.2% (9/13) occurred during the initial infusion and 84.6% (11/13) did not recur. ARIA-H (microhemorrhages/superficial siderosis) and ARIA-E (edema/effusion) were observed in 9.4% (6/64) and 3.1% (2/64) of participants, respectively, with only two symptomatic cases (one ARIA-E presenting with headache and one ARIA-H with visual disturbances). After 6 months of treatment, cognitive scores remained stable compared to baseline (MMSE: 22.33 ± 5.58 vs . 21.27 ± 4.30, P = 0.733; MoCA: 16.38 ± 6.67 vs . 15.90 ± 4.78, P = 0.785; CDR-SB: 2.30 ± 1.65 vs . 3.16 ± 1.72, P = 0.357), while significantly increasing plasma amyloid-β 42 (Aβ42) (+21.42%) and Aβ40 (+23.53%) levels compared to baseline. CONCLUSIONS: Lecanemab demonstrated a favorable safety profile in Chinese patients with early AD. Cognitive stability and biomarker changes over 6 months suggest potential efficacy, though high dropout rates and absence of a control group warrant cautious interpretation. These findings provide preliminary real-world evidence for lecanemab's use in China, supporting further investigation in larger controlled studies. REGISTRATION ClinicalTrials.gov , NCT07034222.
Humans ; Alzheimer Disease/drug therapy* ; Male ; Female ; Aged ; Middle Aged ; Cognitive Dysfunction/drug therapy* ; Aged, 80 and over ; Amyloid beta-Peptides/metabolism* ; Biomarkers ; East Asian People

Objective:To evaluate the effectiveness of amplification intervention with hearing aids for restoring binaural auditory function in patients with unilateral moderate to severe sensorineural hearing loss. Methods:This study selected 30 patients with normal hearing in one ear and moderate to severe sensorineural hearing loss in the other ear. They were fitted with hearing aids for the worse ear and underwent more than half a year and one year of adaptation training. The Chinese translation of the Twelve-item version of SSQ（C-SSQ12）, angle identification test, speech recognition score（SRS） at different signal-to-noise ratios（SNR=5 and SNR=10） and audiometric thresholds were used to compare the results before and after hearing aid use to evaluate the effectiveness of the unilateral hearing loss intervention. Results:The results of the audiometric thresholds, C-SSQ12 scores, angle identification test, and SRS at SNR=5 and SNR=10 in the worse ear of the unilateral hearing loss patients after hearing aid use were all statistically significant compared to before hearing aid use（P<0.01）. Conclusion:Amplification intervention with hearing aids has significant effects on restoring binaural auditory function in patients with unilateral moderate to severe sensorineural hearing loss.
Humans ; Hearing Aids ; Hearing Loss, Unilateral/therapy* ; Middle Aged ; Hearing Loss, Sensorineural/rehabilitation* ; Adult ; Female ; Male ; Auditory Threshold ; Young Adult ; Aged

Given the increasing concern regarding antibacterial resistance, the antimicrobial properties of naphthoquinones have recently attracted significant attention. While 1,4-naphthoquinone and its derivatives have been extensively studied, the antibacterial properties of 5,8-dihydroxy-1,4-naphthoquinone derivatives remain relatively unexplored. This study presents a comprehensive in vitro and in vivo analysis of the antibacterial activity of 35 naturally sourced and chemically synthesized derivatives of 5,8-dihydroxy-1,4-naphthoquinone. Kirby-Bauer antibiotic testing identified three compounds with activity against methicillin-resistant Staphylococcus aureus (MRSA), with one compound (PNP-02) demonstrating activity comparable to vancomycin in minimum inhibitory concentration, minimum bactericidal concentration (MBC), and time-kill assays. Microscopic and biochemical analyses revealed that PNP-02 adversely affects the cell wall and cell membrane of MRSA. Mechanistic investigations, including proteomic sequencing analyses, Western blotting, and RT-qPCR assays, indicated that PNP-02 compromises cell membrane integrity by inhibiting arginine biosynthesis and pyrimidine metabolism pathways, thereby increasing membrane permeability and inducing bacterial death. In an in vivo mouse model of skin wound healing, PNP-02 exhibited antibacterial efficacy similar to vancomycin. The compound demonstrated low toxicity to cultured human cells and in hemolysis assays and remained stable during serum incubation. These findings suggest that PNP-02 possesses promising bioactivity against MRSA and represents a potential novel antibacterial agent.
Methicillin-Resistant Staphylococcus aureus/genetics* ; Anti-Bacterial Agents/chemistry* ; Naphthoquinones/administration & dosage* ; Animals ; Microbial Sensitivity Tests ; Mice ; Humans ; Staphylococcal Infections/microbiology* ; Molecular Structure

Objective:To analyze the key β-amyloid protein (Aβ) deposition in brain regions affecting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD).Methods:Based on the positron emission tomography data of Aβ in the Alzheimer's disease neuroimaging initiative database, the penalized generalized estimating equation (PGEE) and the mixed effects regression forest algorithm (MERF) were used to conduct dimensionality reduction analysis on 164 brain regions with Aβ deposition. Additionally, a multivariate longitudinal data joint model was used to screen the key Aβ deposition brain regions that influence the progression from MCI to AD.Results:Five key brain regions were commonly screened out by the PGEE and MERF models, they were the right prefrontal orbital cortex, the left superior temporal sulcus shore cortex, the right medial orbitofrontal cortex, the left putamen, and the right transverse temporal cortex, respectively. The results of the multivariate longitudinal data joint model based on these 5 Aβ deposition brain regions showed that, except the left superior temporal sulcus shore cortex, the longitudinal change trajectories of the other 4 Aβ deposition brain regions all affected the progression from MCI to AD ( P<0.05). Conclusion:The Aβ deposition in the right prefrontal orbital cortex, right medial orbitofrontal cortex, left putamen and right transverse temporal cortex affect the progression from MCI to AD.

OBJECTIVES: This study aims to explore the current status and risk factors of oral health-related quality of life OHRQoL in patients with mental disorders and provide evidence for effective intervention measures. METHODS: A total of 397 patients diagnosed with mental illness were selected by convenience sampling, and investigation was carried out using general data questionnaire, health literacy in dentistry-14 (HeLD-14), oral health impact profile-14 (OHIP-14), and oral health status checklist. RESULTS: The total score of OHIP-14 in patients with mental disorders was 8(2, 14). The score of HeLD-14 was negatively correlated with the score of OHIP-14 (r=-0.142, P<0.01). The results of multiple linear regression showed that six variables including annual family income, schizophrenia, sweets, frequency of visits to the dentist, dental caries, and missing teeth affected OHRQoL of patients with mental disorders (P<0.05). CONCLUSIONS The poor OHRQoL of psychiatric patients is associated with many factors. Medical personnel should pay attention to their oral health problems and develop targeted oral care programs throughout the course of disease to improve oral health and related quality of life of patients.
Humans ; Quality of Life ; Oral Health ; Mental Disorders ; Risk Factors ; Surveys and Questionnaires ; Male ; Female ; Dental Caries ; Adult ; Middle Aged ; Schizophrenia

Objective To establish an effective model for distinguishing glandular prodromal lesions(PGL)mixed with ground-glass nodules(mGGN)from minimally invasive adenocarcinoma(MIA)on CT based on artificial intelligence.Methods A retrospective analysis was conducted on the clinical and CT image data of 180 patients with lung adenocarcinoma confirmed by surgical pathology and with CT manifestations of mGGN in the First Affiliated Hospital of Wenzhou Medical University from January 2017 to June 2023,inclu-ding 66 patients with PGL and 114 patients with MIA.Patients were divided into the training set(n=144)and the test set(n=36)in an 8∶2 ratio using a completely random method.The quantitative parameters and radiomics features of the lesions in CT images were automatically extracted using artificial intelligence soft-ware(United Imaging Research Platform uRP).By incorporating the most obvious correlation features of omics through dimensionality reduction,five machine learning classifiers were established,including logistic regression(LR),support vector machine(SVM),Random forest(RF),Gaussian process(GP),and Decision Tree(DT).The classifier with the training set highest area under the curve(AUC)was selected as the best radiomics model,and output the result as radiomics score(Rad-score).The clinical information,CT morpho-logical characteristics and quantitative data of the two groups were included in the multivariate logistic regres-sion analysis to screen the independent influencing factors for effectively differentiating PGL and MIA,and a clinical model was established.Finally,a comprehensive prediction model was constructed based on Rad-score and clinical risk factors.The diagnostic performance of the three models was evaluated by using the AUC,sen-sitivity,specificity and accuracy of receiver operating characteristic(ROC)curve.Results Eleven radiomics features for distinguishing PGL from MIA were obtained through LASSO dimensionality reduction.Among the five machine learning classifiers,GP has the best diagnostic performance,with AUC of 0.865 in the train-ing set and 0.762 in the test set,respectively.Univariate and multivariate logistic regression analyses were used for clinical feature screening.The clinical model was constructed by using the average CT value,average long and short diameter,and solid partial long diameter of mGGN,and the AUCs of the training set and the test set were 0.870 and 0.794,respectively.The comprehensive prediction model demonstrated superior diag-nostic performance,with AUC,sensitivity,specificity,and accuracy in the training set being 0.948,81.1%,91.2%and 87.5%respectively,while 0.883,76.9%,91.3%and 86.1%respectively in the test set.Conclu-sion The comprehensive prediction model established based on the quantitative and omics feature analysis of pulmonary nodules by artificial intelligence can well distinguish mGGN mixed with PGL from MIA on CT,and can be used to guide clinical treatment decisions.

Objective:To identify genetic etiology of ischemic stroke(IS)based on pleiotropy of obe-sity related genes.Methods:A discordant sib-pair study was designed based on the Fangshan family co-hort in Beijing.Body mass index(BMI)polygenic risk score(PRS)was first constructed under different P values.Using the polygenic transmission disequilibrium test(pTDT),we then compared the actual BMI genetic risk of siblings with IS to their expected risk,to analyze whether higher BMI was over-trans-mitted to siblings with IS.The single nucleotide polymorphism(SNP)that comprised the PRS over-trans-mitted with IS and that corresponded to the highest heritability of IS were identified as a pleiotropy SNPs set between BMI and IS.This set was then utilized as a candidate set to identify and verify risk SNPs as-so-ciated IS by transmission disequilibrium test.Finally,we identified independent genomic risk loci and mapped to genes,we then explored the biological function of the identified risk loci and genes by func-tional annotation and pathway enrichment.Results:A total of 541 participants were enrolled,with an average age of(58.4±8.1)years,including 326 discordant sib pairs of ischemic stroke.Compared with non-IS participants,IS participants with males,education level below junior high school,hypertension and hyperlipidemia accounted for a higher proportion(P＜0.05).For all the BMI PRS,we found that the actual genetic risk of BMI in siblings with IS was higher than their expectation,suggesting that genetic risk associated with high BMI was over-transmitted with IS.Compared with other SNP sets,the set(P＜5 × 10-4)corresponded to the best analytical statistics of pTDT and the highest heritability of IS and was identified as the pleiotropy SNP set between BMI and IS.Within this set,there were 45 SNPs having linkage and association with IS,which were located in 43 independent genomic risk loci and mapped to 40 genes.These genes were significantly enriched in the lipid metabolism pathway.The rs2232852 cor-rected by multiple tests was mapped to CYB5R1 and ADIPOR1,which were related to lipid metabolism and the ferroptosis pathway.Conclusion:Pleiotropy between BMI-related genes and IS was observed.Forty-five SNPs were found with linkage and association with IS in the pleiotropy gene set and mapped to 40 genes,which were functionally enriched in lipid metabolic pathways.The rs2232852 corrected by multiple tests during association analysis validation was mapped to CYB5R1 and ADIPOR1,which were related to lipid metabolism and the ferroptosis pathway,suggesting that lipid metabolism and ferroptosis played an important role in the development of IS.