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.

OBJECTIVE: To study the results, re-donation situation and characteristics of single-reagent reactive blood donors who were put into the reentry strategy in Wuhan area, explore the rationality and effectiveness of the current reentry strategy, and provide data support for the improvement of the reentry process of blood donors. METHODS: From January 2020 to December 2023, blood donors who conform the reentry criteria and voluntarily applied for returning to Wuhan Blood Center were tested and the results were analyzed. According to the reentry strategy, serological testing and nucleic acid testing were carried out in parallel, serological testing was performed by ELISA with reagents from two different manufacturers, and the primary reactive samples were tested by double-well retest, and HBV/HCV/HIV nucleic acid detection was performed by RT-PCR with an individual donor test mode. Supplementary HBcAb testing was applied for HBV single reagent reactivity by chemiluminescence method. Supplementary TP-WB testing was applied for returning blood donors with repeated TP single reagent reactivity. If returning blood donors with HIV single reagent reactivity were repeated single reagent reactivity, the samples were sent to local CDC for confirmatory test. RESULTS: 7 098 blood donors were qualified for reentry, 716 donors voluntarily applied for reentry, 436 donors successfully reentry, 251 donors entered the next round, 29 donors could not reentry. The reentry rates for the past four years were 66.67%（42/63）, 54.73%（81/148）, 60.71%（136/224） and 62.99%（177/281）, respectively. Up to December 31, 2023, 275 donors donated blood again, and the donation rates for past four years were 76.19%（32/42）, 72.84%（59/81）, 61.76%（84/136） and 56.50%（100/177）, respectively. After donating blood, 31 donors were disqualified again by blood screening and subjected to permanent deferral. The results of returning to the team had statistical differences in reentry items, educational level, age, and marriage（P < 0.05）. CONCLUSION The current reentry strategy adopted by the blood donation and supply institution can effectively retain part of blood donors, reduce the negative emotions of blood donors and increase blood resources.
Humans ; Blood Donors ; China ; Hepatitis B ; Enzyme-Linked Immunosorbent Assay ; Hepatitis C ; Male

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

Objective To investigate the genetic association between nonalcoholic fatty liver disease(NAFLD)and type 2 diabetes mellitus(T2DM)using bidirectional two-sample Mendelian randomization(MR),as well as the causal relationship between NAFLD and T2DM across different body mass index(BMI)categories.Methods The data were derived from genome-wide association studies conducted in European populations,with a sample size of 32 941 cases for NAFLD,312 646 cases for T2DM,and 681 275 cases for BMI.The univariate and multivariate MR methods were used to assess the bidirectional causal relationship between NAFLD and T2DM in the general population and across different BMI subtypes.The methods of inverse-variance weighting,MR-Egger regression,constrained maximum likelihood and model averaging,and weighted median were used to conduct the MR analysis,and MR-Pleiotropy Residual Sum and Outlier,radial MR,the MR-Egger intercept method,and the Cochrane Q test were used for sensitivity analysis.Results The univariate MR analysis revealed a bidirectional causal relationship between NAFLD and T2DM in the general population(forward analysis:odds ratio[OR]=9.75,95%confidence interval[CI]:2.57-37.00,P＜0.001;reverse analysis:OR=1.01,95%CI:1.00-1.01,P＜0.01).After adjustment for BMI,the multivariate MR analysis showed that the causal relationship between NAFLD and T2DM remained significant in the general population(OR=33.12,95%CI:7.57-144.95,P＜0.000 1).The subgroup analysis showed a causal relationship between NAFLD and T2DM across all BMI subtypes(lean subgroup:OR=12.19,95%CI:3.35-44.40,P＜0.001;overweight subgroup:OR=4.30,95%CI:1.69-10.92,P＜0.01;obese subgroup:OR=1.67,95%CI:1.14-2.44,P＜0.01).Conclusion This study reveals the causal relationship between NAFLD and T2DM in the general population of NAFLD and across different BMI subtypes from a genetic perspective.

Objective:To explore the feasibility and safety of remote programming technology based on 5G cloud technology support platform in postoperative follow-up of cardiovascular implantable electronic devices(CIED).Methods:This study was a multicenter cross-sectional study. CIED patients from 12 hospitals lacking full-time follow-up specialists in Sichuan Province were enrolled from June 2021 to October 2021. All patients′ devices received remote inspecting and programming by the follow-up specialist of the remote follow-up center of the Third People′s Hospital of Chengdu through 5G cloud technology support platform. The baseline data, device alarm events, device reprogramming events, adverse reactions and satisfaction questionnaire survey results were collected.Results:A total of 195 CIED implantation patients were included, with an age of (72.5±11.3) years, including 103 males (52.6%). All patients completed remote inspecting and programming successfully, with a duration of (5.8±4.0) min. Ninety-one patients′ CIED were reprogrammed, with a total of 104 parameter adjustments. No abnormal communication or adverse events occurred. The satisfaction questionnaire showed that 97.9%(191/195) of the patients trusted or relatively trusted remote follow-up and 86.7%(169/195) of the patients were willing to choose remote follow-up mode for device management.Conclusion:The remote programming based on 5G cloud technology support platform may be feasible and safe for postoperative follow-up of CIED patients.

Public health and social measures (PHSMs) are one of the most important measures in the prevention and control of COVID-19 and have also been effective in suppressing the spread of influenza viruses, but their effectiveness has not been fully investigated. This study aimed to review the progress of research on the impact of PHSMs on influenza during the COVID-19 pandemic based on the latest evidence of the effectiveness of various PHSMs in controlling transmission of influenza viruses, to provide scientific evidence for optimizing influenza prevention and control strategies.

Public health and social measures (PHSMs) are one of the most important measures in the prevention and control of COVID-19 and have also been effective in suppressing the spread of influenza viruses, but their effectiveness has not been fully investigated. This study aimed to review the progress of research on the impact of PHSMs on influenza during the COVID-19 pandemic based on the latest evidence of the effectiveness of various PHSMs in controlling transmission of influenza viruses, to provide scientific evidence for optimizing influenza prevention and control strategies.

Objective To describe the current state of research and future research hotspots through a metrological analysis of the literature in the field of forensic anthropological remains identification re-search.Methods The data retrieved and extracted from the Web of Science Core Collection (WoSCC),the core database of the Web of Science information service platform (hereinafter referred to as "WoS"),was used to analyze the trends and topic changes in research on forensic identification of human re-mains from 1991 to 2022.Network visualisation of publication trends,countries (regions),institutions,authors and topics related to the identification of remains in forensic anthropology was analysed using python 3.9.2 and Gephi 0.10.Results A total of 873 papers written in English in the field of forensic anthropological remains identification research were obtained.The journal with the largest number of publications was Forensic Science International (164 articles).The country (region) with the largest number of published papers was China (90 articles).Katholieke Univ Leuven (Netherlands,21 articles) was the institution with the largest number of publications.Topic analysis revealed that the focus of forensic anthropological remains identification research was sex estimation and age estimation,and the most commonly studied remains were teeth.Conclusion The volume of publications in the field of forensic anthropological remains identification research has a distinct phasing.However,the scope of both international and domestic collaborations remains limited.Traditionally,human remains identifica-tion has primarily relied on key areas such as the pelvis,skull,and teeth.Looking ahead,future re-search will likely focus on the more accurate and efficient identification of multiple skeletal remains through the use of machine learning and deep learning techniques.