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"Zhang, Li-Li"
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Features extraction based on Naive Bayes algorithm and TF-IDF for news classification
The rapid proliferation of online news demands robust automated classification systems to enhance information organization and personalized recommendation. Although traditional methods like TF-IDF with Naive Bayes provide foundational solutions, their limitations in capturing semantic nuances and handling real-time demands hinder practical applications. This study proposes a hybrid news classification framework that integrates classical machine learning with modern advances in NLP to address these challenges. Our methodology introduces three key innovations: (1) Domain-Specific Feature Engineering, combining tailored n-grams and entity-aware TF-IDF weighting to amplify discriminative terms; (2) BERT-Guided Feature Selection, leveraging distilled BERT to identify contextually important words and resolve rare-term ambiguities; and (3) Computationally Efficient Deployment, achieving 95.2% of the accuracy of BERT at 1/52.4th of the inference cost. Evaluated on a balanced corpus of Sina News articles in 11 categories, the system demonstrates a test precision of 95.12% (vs. 84.43% for SVM+TF-IDF baseline), with statistically significant improvements confirmed by 5-fold cross-validation( p < 0.01). The critical findings reveal strong performance in distinguishing semantically distinct categories, while exposing challenges in fine-grained differentiation. The efficiency of the framework (2.1 inference latency) and scalability (linear utilization of CPU resources) validate its practicality for real-world deployment. This work bridges the gap between traditional feature engineering and transformer-based models, offering a cost-effective solution for news platforms. Future research will explore hierarchical classification and the adaptation of dynamic topics to further refine semantic boundaries.
Journal Article
The Role of Gut Microbiota in Some Liver Diseases: From an Immunological Perspective
Gut microbiota is a microecosystem composed of various microorganisms. It plays an important role in human metabolism, and its metabolites affect different tissues and organs. Intestinal flora maintains the intestinal mucosal barrier and interacts with the immune system. The liver is closely linked to the intestine by the gut-liver axis. As the first organ that comes into contact with blood from the intestine, the liver will be deeply influenced by the gut microbiota and its metabolites, and the intestinal leakage and the imbalance of the flora are the trigger of the pathological reaction of the liver. In this paper, we discuss the role of gut microbiota and its metabolites in the pathogenesis and development of autoimmune liver diseases((including autoimmune hepatitis, primary biliary cirrhosis, primary sclerosing cholangitis), metabolic liver disease such as non-alcoholic fatty liver disease, cirrhosisits and its complications, and liver cancer from the perspective of immune mechanism. And the recent progress in the treatment of these diseases was reviewed from the perspective of gut microbiota.
Journal Article
Post-infection cognitive impairments in a cohort of elderly patients with COVID-19
Background
Understanding the long-term effects of coronavirus disease 2019 (COVID-19) on cognitive function is essential for monitoring the cognitive decline in the elderly population. This study aims to assess the current cognitive status and the longitudinal cognitive decline in elderly patients recovered from COVID-19.
Methods
This cross-sectional study recruited 1539 COVID-19 inpatients aged over 60 years who were discharged from three COVID-19-designated hospitals in Wuhan, China, from February 10 to April 10, 2020. In total, 466 uninfected spouses of COVID-19 patients were selected as controls. The current cognitive status was assessed using a Chinese version of the Telephone Interview of Cognitive Status-40 (TICS-40) and the longitudinal cognitive decline was assessed using an Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). Cognitive assessments were performed 6 months after patient discharge.
Results
Compared with controls, COVID-19 patients had lower TICS-40 scores and higher IQCODE scores [TICS-40 median (IQR): 29 (25 to 32) vs. 30 (26 to 33),
p
< 0.001; IQCODE median (IQR): 3.19 (3.00 to 3.63) vs. 3.06 (3.00 to 3.38),
p
< 0.001]. Severe COVID-19 patients had lower TICS-40 scores and higher IQCODE scores than non-severe COVID-19 patients [TICS-40 median (IQR): 24 (18 to 28) vs. 30 (26 to 33),
p
< 0.001; IQCODE median (IQR): 3.63 (3.13 to 4.31) vs. 3.13 (3.00 to 3.56),
p
< 0.001] and controls [TICS-40 median (IQR): 24 (18 to 28) vs. 30 (26 to 33),
p
< 0.001; IQCODE median (IQR) 3.63 (3.13 to 4.31) vs. 3.06 (3.00 to 3.38),
p
< 0.001]. Severe COVID-19 patients had a higher proportion of cases with current cognitive impairment and longitudinal cognitive decline than non-severe COVID-19 patients [dementia: 25 (10.50 %) vs. 9 (0.69 %),
p
< 0.001; Mild cognitive impairment (MCI): 60 (25.21 %) vs. 63 (4.84 %),
p
< 0.001] and controls [dementia: 25 (10.50 %) vs. 0 (0 %),
p
< 0.001; MCI: 60 (25.21 %) vs. 20 (4.29 %),
p
< 0.001)]. COVID-19 severity, delirium and COPD were risk factors of current cognitive impairment. Low education level, severe COVID-19, delirium, hypertension and COPD were risk factors of longitudinal cognitive decline.
Conclusions
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with an increased risk of long-term cognitive decline in elderly population. COVID-19 patients, especially severe patients, should be intensively monitored for post-infection cognitive decline.
Journal Article
حوكمة الصين في التنمية الخضراء
إن رؤية شي جين بينغ تؤكد أن الطبيعة بما فيها من غابات وأنهار وجداول وجبال وحيوانات ثروة لا تدانيها أية ثروة أخرى. لذلك، يجب الحفاظ عليها من خلال خطة ابتكارية توفق بين متطلبات الصناعة الحديثة ومتطلبات الحفاظ على البيئة، وتركز على وضع قوانين تمنع من أن تمتد يد العبث إليها. إن شي جين بينغ يركز على أهمية الابتكار في كل شيء، ولا سيما في تحقيق الازدهار البيئي في الصين وفي العالم كله، وبناء ما سماه ب «مجتمع المصير المشترك للبشرية.
A phase 1, open-label study of LCAR-B38M, a chimeric antigen receptor T cell therapy directed against B cell maturation antigen, in patients with relapsed or refractory multiple myeloma
Background
Chimeric antigen receptor (CAR) T cell therapy has demonstrated proven efficacy in some hematologic cancers. We evaluated the safety and efficacy of LCAR-B38M, a dual epitope-binding CAR T cell therapy directed against 2 distinct B cell maturation antigen epitopes, in patients with relapsed/refractory (R/R) multiple myeloma (MM).
Methods
This ongoing phase 1, single-arm, open-label, multicenter study enrolled patients (18 to 80 years) with R/R MM. Lymphodepletion was performed using cyclophosphamide 300 mg/m
2
. LCAR-B38M CAR T cells (median CAR+ T cells, 0.5 × 10
6
cells/kg [range, 0.07 to 2.1 × 10
6
]) were infused in 3 separate infusions. The primary objective is to evaluate the safety of LCAR-B38M CAR T cells; the secondary objective is to evaluate the antimyeloma response of the treatment based on the general guidelines of the International Myeloma Working Group.
Results
At data cutoff, 57 patients had received LCAR-B38M CAR T cells. All patients experienced ≥ 1 adverse events (AEs). Grade ≥ 3 AEs were reported in 37/57 patients (65%); most common were leukopenia (17/57; 30%), thrombocytopenia (13/57; 23%), and aspartate aminotransferase increased (12/57; 21%). Cytokine release syndrome occurred in 51/57 patients (90%); 4/57 (7%) had grade ≥ 3 cases. One patient reported neurotoxicity of grade 1 aphasia, agitation, and seizure-like activity. The overall response rate was 88% (95% confidence interval [CI], 76 to 95); 39/57 patients (68%) achieved a complete response, 3/57 (5%) achieved a very good partial response, and 8/57 (14%) achieved a partial response. Minimal residual disease was negative for 36/57 (63%) patients. The median time to response was 1 month (range, 0.4 to 3.5). At a median follow-up of 8 months, median progression-free survival was 15 months (95% CI, 11 to not estimable). Median overall survival for all patients was not reached.
Conclusions
LCAR-B38M CAR T cell therapy displayed a manageable safety profile and demonstrated deep and durable responses in patients with R/R MM.
Trial registration
ClinicalTrials.gov
,
NCT03090659
; Registered on March 27, 2017, retrospectively registered
Journal Article
Electricity generation using wind power
\"Is wind power the answer to our energy supply problems? Is there enough wind for everyone? Is offshore generation better than onshore generation? Can a roof-mounted wind turbine generate enough electricity to supply a typical domestic household? Electricity Generation Using Wind Power (2nd Edition) answers these pressing questions through its detailed coverage of the different types of electrical generator machines used, as well as the power electronic converter technologies and control principles employed. Also covered is the integration of wind farms into established electricity grid systems, plus environmental and economic aspects of wind generation. Written for technically minded readers, especially electrical engineers concerned with the possible use of wind power for generating electricity, it incorporates some global meteorological and geographical features of wind supply plus a survey of past and present wind turbines. Included is a technical assessment of the choice of turbine sites. The principles and analysis of wind power conversion, transmission and efficiency evaluation are described. This book includes worked numerical examples in some chapters, plus end of chapter problems and review questions, with answers.\" -- Publisher's description
BOOK
Lower Circulating Interferon-Gamma Is a Risk Factor for Lung Fibrosis in COVID-19 Patients
Cytokine storm resulting from SARS-CoV-2 infection is one of the leading causes of acute respiratory distress syndrome (ARDS) and lung fibrosis. We investigated the effect of inflammatory molecules to identify any marker that is related to lung fibrosis in coronavirus disease 2019 (COVID-19). Seventy-six COVID-19 patients who were admitted to Youan Hospital between January 21 and March 20, 2020 and recovered were recruited for this study. Pulmonary fibrosis, represented as fibrotic volume on chest CT images, was computed by an artificial intelligence (AI)-assisted program. Plasma samples were collected from the participants shortly after admission, to measure the basal inflammatory molecules levels. At discharge, fibrosis was present in 46 (60.5%) patients whose plasma interferon-γ (IFN-γ) levels were twofold lower than those without fibrosis (
> 0.05). The multivariate-adjusted logistic regression analysis demonstrated the inverse association risk of having lung fibrosis and basal circulating IFN-γ levels with an estimate of 0.43 (
= 0.02). Per the 1-SD increase of basal IFN-γ level in circulation, the fibrosis volume decreased by 0.070% (
= 0.04) at the discharge of participants. The basal circulating IFN-γ levels were comparable with c-reactive protein in the discrimination of the occurrence of lung fibrosis among COVID-19 patients at discharge, unlike circulating IL-6 levels. In conclusion, these data indicate that decreased circulating IFN-γ is a risk factor of lung fibrosis in COVID-19.
Journal Article