Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Cancer stands as a significant global public health challenge, and cancer screening serves as a pivotal strategy for reducing its mortality. Presently, only a limited number of cancer types have appropriate screening methods available. Traditional single-cancer screening approaches are fraught with limitations, including invasiveness, low accuracy, and poor patient compliance. Multi-cancer early detection (MCED) leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA, cell-free RNA, proteins, and metabolites in blood and other bodily fluids. This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage, showcasing immense potential for improving existing cancer screening strategies. This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED, biomarker selection and detection technologies, the criteria for cancer type selection, research design and clinical utility evaluation, as well as implementation pathways. The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED, thereby facilitating the continuous optimization of cancer screening strategies.

Objective To systematically analyze the risk prediction instruments for central line associated bloodstream infection in ICU patients,with a view to provide references for clinical practice.Methods The PubMed,Embase,Web of Science,Cochrane Library,CIN AHL,CNKI,WanFang,VIP and CBM Database were searched from inception to May 2024.There were 2 researchers who independently screened the literature,extracted the information,and assessed the risk of bias and applicability of the included literature.Results 11 studies were involved in the final review,involving 9 risk prediction models and 2 risk assessment tables,9 of which validated the predictive efficacy or reliability and validity of the instruments.Conclusion The risk prediction instruments for central line associated bloodstream infection in ICU patients had good predictive efficacy and applicability,but the overall risk of bias was high.It is recommended that further examination,verification the existing instruments should be conducted,or to build a prediction instrument with low risk of bias and high applicability.

Cancer stands as a significant global public health challenge,and cancer screening serves as a pivotal strategy for reducing its mortality.Presently,only a limited number of cancer types have appropriate screening methods available.Traditional single-cancer screen-ing approaches are fraught with limitations,including invasiveness,low accuracy,and poor patient compliance.Multi-cancer early detection(MCED)leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA,cell-free RNA,proteins,and metabolites in blood and other bodily fluids.This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage,showcasing immense potential for improving existing can-cer screening strategies.This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED,biomarker selection and detection technologies,the criteria for cancer type selection,research design and clinical utility evaluation,as well as implementation path-ways.The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED,thereby facilitating the continuous optimization of cancer screening strategies.

Objective:To investigate the impact of peripheral blood prolymphocyte percentage on the prognosis of patients with chronic lymphocytic leukemia (CLL) .Methods:This study included 300 patients diagnosed with CLL at the Department of Hematology of Jiangsu Provincial People’s Hospital from October 2011 to December 2020. The association between prolymphocyte percentage and other parameters was analyzed, and the optimal cutoff prolymphocyte percentage was determined by X-tile analysis. Further survival analysis and prognostic model construction were used to validate the predictive value of prolymphocyte percentage.Results:Of the 300 eligible patients with CLL who were enrolled, 50 received Bruton tyrosine kinase inhibitors (BTKi) as first-line treatment. The group with higher prolymphocyte percentage comprised more patients in the advanced stages ( P=0.010) and had higher β 2-microglobulin ( P<0.001), unmutated immunoglobulin heavy-chain variable region gene ( P<0.001), and TP53 aberration ( P=0.004). The optimal cutoff percentage of prolymphocytes was 1%. Patients with a prolymphocyte percentage >1% had significantly shorter treatment-free survival (TFS) ( P<0.001) and overall survival time ( P=0.007) than patients with a prolymphocyte percentage ≤1%. On multivariate analysis, prolymphocyte percentage >1% tended to have an independent prognostic value for TFS [ HR=1.405 (95% CI 0.971~2.032), P=0.071]. Compared with the nomogram of CLL international prognostic index (CLL-IPI) alone, the nomogram of CLL-IPI combined with prolymphocyte percentage showed better discrimination (area under the curve: 0.778 vs. 0.637; P=0.006). In addition, patients with a prolymphocyte percentage >1% were more likely to progress after BTKi treatment ( P=0.038) . Conclusion:Peripheral blood prolymphocyte percentage was associated with various clinical and biological parameters and prognosis among patients with treatment-naive CLL.

Allergic rhinitis (AR), a globally prevalent immune-mediated inflammatory condition, is still an incurable disease. In the present study, we have validated the impact of the Kelch-like ECH associated protein 1 (Keap1)-related oxidative stress and inflammatory response in clinical AR patient peripheral blood and nasal swab samples, emphasizing the biological relevance of Keap1 and AR. Targeting Keap1 -nuclear factor erythroid 2-related factor 2 (Nrf2) related anti-oxidative stress may be effective for AR intervention. Drawing inspiration from the Keap1 homodimerization and the E3 ligase characteristics, we herein present a design of novel bivalent molecules for chemical knockdown of Keap1. For the first time, we characterized ternary complexes of Keap1 dimer and one molecule of bivalent compounds. The best bivalent molecule 8 encompasses robust capacity to degrade Keap1 as a homoPROTAC^KEAP1. It efficaciously suppresses inflammatory cytokines in extensively different cells, including human nasal epithelial cells. Moreover, in an AR mouse model, we confirmed that the chemical degradation induced by homoPROTAC^KEAP1 led to therapeutic benefits in managing AR symptoms, oxidative stress and inflammation. In summary, our findings underscore the efficacy of targeting the Keap1 system through the homoPROTAC-ing technology as an innovative and promising treatment strategy for the incurable allergic disorders.

Objective To investigate the population composition,seasonal dynamics,and infestation levels of cockroaches in Lanzhou,China,and to provide information for the scientific development of cockroach control strategies.Methods Monitoring was conducted at three locations using the sticky trap method.Habitats included farm product markets,catering establishments,hotels,hospitals,and residential areas.Results From 2016 to 2023,the average cockroach density was 0.77 insects per board,with an average infestation rate of 10.84%.Blattella germanica was the dominant species.Seasonal density of cockroaches showed an approximately unimodal distribution,peaking in September.The highest average density and infestation rates were observed in farm product markets.Conclusions Cockroach density and infestation levels in Lanzhou remained relatively low.A comprehensive prevention and control strategy focusing on environmental management in key areas should be implemented according to the seasonal fluctuations.

Objective To investigate the effect of remimazolam(Rem)on retinal ischemia-reper-fusion injury(RIRI)in rats and its regulatory mechanism on the high-mobility group box 1(HMGB1)/receptor for advanced glycation end products(RAGE)/nuclear factor-κB(NF-κB)signaling pathway.Methods Rats were randomly divided into Sham group,Model group,Rem-L group(low-dose Rem),Rem-M group(medium-dose Rem),Rem-H group(high-dose Rem),and high-dose Rem plus HMGB1 activator dexamethasone(DEX)group(Rem-H+DEX group),with 15 rats in each group.Except for the Sham group,RIRI model was established in the other groups by increasing in-traocular pressure.Hematoxylin and eosin(HE)staining was used to observe the changes in retinal tissue structure in each group.The TUNEL method was used to detect retinal tissue apoptosis.En-zyme-linked immunosorbent assay(ELISA)was performed to detect the expression levels of interleu-kin-1β(IL-1β),tumor necrosis factor-α(TNF-α),and interleukin-6(IL-6)in the serum of rats in each group.Kits were used to detect the levels of oxidative stress indicators,including superoxide dis-mutase(SOD),glutathione peroxidase(GSH-PX),and malondialdehyde(MDA).Western blot was used to detect the expression levels of hypoxia-related factors[hypoxia-inducible factor-1α(HIF-1α),vascular endothelial growth factor(VEGF)]and HMGB1/RAGE/NF-κB signaling pathway-related proteins in retinal tissue.Results Compared with the Sham group,the Model group showed severe retinal edema,a significant decrease in the number of ganglion cells,vacuolar changes in cells with disordered arrangement,and widened cell gaps.With increasing doses of Rem,the degree of retinal edema gradually decreased,the number of ganglion cells increased,and their arrangement became more orderly in RIRI rats.Compared with the Sham group,the Model group exhibited increased ret-inal cell apoptosis rate,serum levels of IL-1 β,IL-6,and TNF-α and increased expression levels of MDA,HMGB1,RAGE,NF-κB,HIF-1α and VEGF in retinal tissue,while the expression levels of SOD and GSH-PX decreased(P＜0.05).Compared with the Model group,the Rem-L,Rem-M,and Rem-H groups showed dose-dependent decreases in retinal cell apoptosis rate,serum levels of IL-1 β,IL-6,and TNF-α,and expression levels of MDA,HMGB1,RAGE,NF-κB,HIF-1α and VEGF in retinal tissue,with dose-dependent increases in the expression levels of SOD and GSH-PX(P＜0.05).Compared with the Rem-H group,the Rem-H+DEX group showed reversed trends in the above indicators.Conclusion Rem can inhibit the occurrence of RIRI in rats,and its mecha-nism of action may be related to the regulation of the HMGB1/RAGE/NF-κB signaling pathway.

Objective: To construct a hypertension risk prediction model for residents aged 18-79 years, so as to provide an assessment tool for early screening and prevention of hypertension in high-risk groups. Methods: The permanent residents aged 18-79 years from 6 townships (streets) in Fangshan District of Beijing Municipality were selected as the study subjects using a multi-stage stratified random sampling method from March to June 2023. Demographic information, lifestyle, body mass index (BMI), blood pressure, fasting blood glucose, and blood lipid were collected through questionnaire survey, physical examination, and laboratory tests. Subjects were randomly divided into training and validation sets at a 7∶3 ratio. The logistic regression model was used to screen the risk factors of hypertension, and a hypertension risk prediction nomogram was constructed. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis were used to verify the discrimination, fit, and clinical application value of the model. Results: A total of 4 438 subjects were included, including 2 365 males (53.29%) and 2 073 females (46.71%), with a mean age of (44.99±14.90) years. The prevalence of hypertension was 35.29% (1 566 cases), and the standardized prevalence was 24.74%. The logistic regression model screened out 9 influencing factors of hypertension. The nomogram was established as ln[p/ (1-p)]= -2.873 + 0.935×40-<50 years + 1.463×50-<60 years + 1.908×60-<70 years + 2.346×70-79 years + 0.298×male-0.675×college degree or above + 0.384×smoking + 0.227×drinking + 0.572×overweight + 1.449×obesity + 0.557×heart rate ≥80 beats/min + 0.428×diabetes + 0.484×dyslipidemia. The area under the ROC curve of the validation set was 0.821 (95%CI: 0.798-0.843), and the calibration curve results showed that the calibration curve fitted the actual curve well. Decision curve analysis showed that the threshold probability was in the range of 0.10 to 0.70, and the model had good predictive value and clinical application value. Conclusion The nomogram based on age, gender, educational level, smoking, drinking, body mass index, heart rate, diabetes, and dyslipidemia can be used to predict the risk of hypertension among residents aged 18-79 years.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence