Objective:To perform routine plasma test, SARS-CoV-2 nucleic acid test, and respiratory pathogenic microorganism nucleic acid test on plasma samples collected from 1 040 healthy plasma donors in winter.Methods:Plasma samples were collected from 1 040 healthy plasma donors at Yunmeng Plasma Collection Station in the winter of 2020. Routine plasma test, HBV/HCV/HIV nucleic acid test, SARS-CoV-2 nucleic acid test, and 22 respiratory pathogenic microorganism nucleic acid test were performed to analyze the quality of blood plasmas.Results:All plasma samples were qualified in the routine tests, meeting the requirements of the Chinese Pharmacopoeia, and tested negative for SARS-CoV-2 nucleic acid. Respiratory pathogenic microorganism nucleic acids were detected in 29 samples with a positive rate of 2.79% (29/1 040). There were 21 cases of simple virus infections, including 17 cases of coronavirus subtype infection, three cases of parainfluenza virus type 2 infection, and one case of human bocavirus infection. Eight cases were mixed infections of viruses and bacteria, four of which were viral infection combined with Bordetella pertussis. The 29 positive samples were collected from people of different age groups, including two from 31-40 years old (1.96%, 2/102 ), three from 41-50 years old (1.59%, 3/189), five from 51-55 years old (1.94%, 5/257), and 19 from 56-60 years old (4.59%, 19/414). Samples from the people aged 56-60 years accounted for the most (39.81%, 414/1 040), as well as the infection rate in this age group. Conclusions:In autumn and winter, respiratory pathogenic microorganism nucleic acid test should be performed when collecting plasma samples from donors aged 56-60 years in addition to meeting the requirements of the Chinese Pharmacopoeia. It is also suggested to conduct respiratory pathogenic microorganism nucleic acid test on pooled plasma and blood products.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective:To perform routine plasma test, SARS-CoV-2 nucleic acid test, and respiratory pathogenic microorganism nucleic acid test on plasma samples collected from 1 040 healthy plasma donors in winter.Methods:Plasma samples were collected from 1 040 healthy plasma donors at Yunmeng Plasma Collection Station in the winter of 2020. Routine plasma test, HBV/HCV/HIV nucleic acid test, SARS-CoV-2 nucleic acid test, and 22 respiratory pathogenic microorganism nucleic acid test were performed to analyze the quality of blood plasmas.Results:All plasma samples were qualified in the routine tests, meeting the requirements of the Chinese Pharmacopoeia, and tested negative for SARS-CoV-2 nucleic acid. Respiratory pathogenic microorganism nucleic acids were detected in 29 samples with a positive rate of 2.79% (29/1 040). There were 21 cases of simple virus infections, including 17 cases of coronavirus subtype infection, three cases of parainfluenza virus type 2 infection, and one case of human bocavirus infection. Eight cases were mixed infections of viruses and bacteria, four of which were viral infection combined with Bordetella pertussis. The 29 positive samples were collected from people of different age groups, including two from 31-40 years old (1.96%, 2/102 ), three from 41-50 years old (1.59%, 3/189), five from 51-55 years old (1.94%, 5/257), and 19 from 56-60 years old (4.59%, 19/414). Samples from the people aged 56-60 years accounted for the most (39.81%, 414/1 040), as well as the infection rate in this age group. Conclusions:In autumn and winter, respiratory pathogenic microorganism nucleic acid test should be performed when collecting plasma samples from donors aged 56-60 years in addition to meeting the requirements of the Chinese Pharmacopoeia. It is also suggested to conduct respiratory pathogenic microorganism nucleic acid test on pooled plasma and blood products.

Osteoarthritis （OA） is a common degenerative joint disease with a rising incidence rate year by year. Treatment often relies on analgesics and non-steroidal anti-inflammatory drugs （NSAIDs）， which can lead to gastrointestinal damage with long-term use and the recurrence of symptoms. Chinese medicine has a long history of preventing and treating OA， with widespread application and fewer side effects. It offers unique advantages such as a broad treatment scope， multiple targets， and pathways. The effective components of Chinese medicine can reduce the content of reactive oxygen species （ROS）， relieve oxidative stress （OS） damage， and increase the antioxidant capacity of the body by interfering with the expression of biomarkers of OS response such as malondialdehyde （MDA） and superoxide dismutase （SOD）. Through the modulation of signaling pathways such as nuclear factor E₂-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1）， phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）， nuclear factor kappa B （NF-κB）， c-Jun N-terminal kinase （JNK）， NOD-like receptor protein 3 （NLRP3）， and osteoprotegerin （OPG）， they downregulated the expression of inflammatory factors such as interleukin-6 （IL-6）， interleukin-1β （IL-1β）， and tumor necrosis factor-α （TNF-α）， thereby effectively relieving local joint inflammation， protecting chondrocytes and bone tissue， inhibiting chondrocyte apoptosis， and further alleviating the progression of OA. Currently， there are still certain limitations in the medical research status and development trends of OA， necessitating the continued advancement of traditional Chinese medicine. This paper reviewed the literature on the regulation of OS response by effective components of Chinese medicine for the prevention and treatment of OA， providing new directions and ideas for future research.

Objective To investigate the effect of final vowel types on the voice onset time(VOT)of differ-ent stops in children with hearing impairment,and to provide a basis for the acquisition and correction of stop sounds.Methods A total of 22 hearing-impaired children aged 3～6 and 22 children with normal hearing were ran-domly selected-18 consonant-vowel(CV)syllables composed of 6 stops and 3 single finals were recorded,using first tone.Using Praat 6.1.29 software to analyze and extract the stops VOT.Two-way ANOVA was used for each stop,the dependent variable was VOT,and the independent variables were hearing status and final type.Results Children in the hearing-impaired group had articulation errors in/t/,/g/,and/k/.Hearing status had significant effect on the main effect of plosives/g/,/p/,/t/,/k/(P＜0.05),and the VOT of slurs/g/,/p/,/t/,/k/in the normal hearing group significantly greater than the hearing-impaired group(P＜0.05).The main effect of finals on the VOT of the stops/b/,/p/and/t/was significant(P＜0.05).Hearing status and final type had an interac-tive effect on the stop/t/,and the simple main effect showed that the difference in VOT of/ti/between the hear-ing-impaired group and the normal hearing group was greater than that of/ta/and/tu/.Conclusion The stops/g/,/p//t/,/k/VOT of hearing-impaired children are smaller than those of with normal hearing.The difference in VOT of/ti/sound between the hearing impaired group and the normal hearing group is greater than that of/ta/sound and/tu/sound.In the teaching of the initial/t/sound for hearing-impaired children,we can start with/ta/and/tu/with less difference,and the/ti/sound is consolidated later.Pay attention to breathing and oral exercise training,to lay a good foundation for clear pronunciation.

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia seen in clinical settings, which has been associated with substantial rates of mortality and morbidity. However, clinically available drugs have limited efficacy and adverse effects. We aimed to investigate the mechanisms of action of andrographolide (Andr) with respect to AF. We used network pharmacology approaches to investigate the possible therapeutic effect of Andr. To define the role of Andr in AF, HL-1 cells were pro-treated with Andr for 1 h before rapid electronic stimulation (RES) and rabbits were pro-treated for 1 d before rapid atrial pacing (RAP). Apoptosis, myofibril degradation, oxidative stress, and inflammation were determined. RNA sequencing (RNA-seq) was performed to investigate the relevant mechanism. Andr treatment attenuated RAP-induced atrial electrophysiological changes, inflammation, oxidative damage, and apoptosis both in vivo and in vitro. RNA-seq indicated that oxidative phosphorylation played an important role. Transmission electron microscopy and adenosine triphosphate (ATP) content assay respectively validated the morphological and functional changes in mitochondria. The translocation of nuclear factor erythroid 2-related factor 2 (Nrf2) to the nucleus and the molecular docking suggested that Andr might exert a therapeutic effect by influencing the Keap1-Nrf2 complex. In conclusions, this study revealed that Andr is a potential preventive therapeutic drug toward AF via activating the translocation of Nrf2 to the nucleus and the upregulation of heme oxygenase-1 (HO-1) to promote mitochondrial bioenergetics.
Animals ; Rabbits ; Atrial Fibrillation/metabolism* ; Kelch-Like ECH-Associated Protein 1/metabolism* ; Signal Transduction ; NF-E2-Related Factor 2/pharmacology* ; Molecular Docking Simulation ; Oxidative Stress ; Energy Metabolism ; Mitochondria/metabolism* ; Inflammation/metabolism* ; Heme Oxygenase-1

Objective:To explore the value of high-resolution CT (HRCT) visual scores and quantitative analysis in assessing pulmonary Langerhans cell histiocytosis (PLCH) in adults.Methods:In total 51 adult patients with PLCH confirmed by pathology in Peking Union Medical College Hospital from August 2014 to December 2021 were retrospectively analyzed. All patients underwent HRCT and pulmonary function tests (PFT). The involvement of the nodular and cystic lesions were evaluated by two experienced radiologists using CT visual scores. The cases were divided into three groups based on the nodular scores, and into four groups based on the cystic scores, respectively. Ratio of low attenuation areas (LAA%) was measured by an automatic post-processing software. Pulmonary function indices including forced expiratory volume in the first second (FEV 1), forced vital capacity (FVC), FEV 1/FVC, diffusion capacity for carbon monoxide of lung (D LCO), alveolar ventilation (V A), D LCO/V A, D LCO corrected for hemoglobin (D LCOc), D LCOc/V A were collected. FEV 1/FVC was expressed as measured values and other indices were expressed as percent predicted (%pred). Spearman correlation analysis was used to evaluate the correlation between HRCT visual scores, LAA% and PFT. The lung function indices among different nodular groups as well as among different cystic groups were compared using the Kruskal‐Wallis test. Results:Both nodular and cystic lesions were found on HRCT images of all 51 patients. There were no correlation between the visual scores of nodular lesions and lung function indices (all P>0.05). There were no significant differences in lung function indices among different nodular groups (all P>0.05). The visual scores of cystic lesions were negatively correlated with FEV 1/FVC, D LCO%pred, D LCO/V A%pred, D LCOc%pred, D LCOc/V A%pred ( r=-0.491, -0.347, -0.330, -0.373, -0.346, respectively, all P<0.05); the pulmonary function indices among different cystic groups had significant difference (all P<0.05). LAA% were negatively correlated with FEV 1/FVC, D LCO%pred, D LCO/V A%pred, D LCOc%pred, D LCOc/V A%pred ( r=-0.278, -0.378, -0.418, -0.395, -0.451, respectively, all P<0.05). Conclusion:HRCT visual scores of nodular lesions do not correlate with lung function in patients with PLCH. Visual scores and quantitative analysis of the cystic lesions can reflect the impairment degree of pulmonary ventilation and diffusion function to a certain extent, and may be used in assessment of patients with PLCH.

ObjectiveTo investigate the molecular mechanism of the anti-liver fibrosis effect of curcumol by observing the effect of curcumol on the TLR4/NF-κB signaling pathway in liver sinusoidal endothelial cells. MethodsA total of 50 mice were randomly divided into blank group, model group, and curcumol group, and cells were divided into blank control group, LPS positive control group, curcumol intervention group, and PDTC group. HE staining and Masson staining were used to observe the change in liver structure; Western blot and quantitative real-time PCR (RT-PCR) were used to measure the protein and mRNA expression of the key molecules TLR4 and NF-κB in the TLR4/NF-κB signaling pathway; immunofluorescence assay was used to observe the expression and nuclear import of NF-κB in cells. A one-way analysis of variance was used for comparison between multiple 　groups, and the least　significant difference t-test was used for further comparison between two groups.　ResultsRT-PCR showed that compared with the positive control group, the curcumol intervention group had significant reductions in the mRNA expression of TLR4 and NF-κB (both P＜0.05). Western blot showed that compared with the positive control group, the curcumol intervention group had significant reductions in the expression of TLR4 and NF-κB (both P＜005). Immunofluorescence assay showed that compared with the positive control group, the curcumol intervention group had significant improvement in NF-κB nuclear import. ConclusionCurcumol can exert an anti-liver fibrosis effect possibly by inhibiting the activity of the TLR4/NF-κB signaling pathway.

Objective:To investigate the promotion effect of 4,5,6,7-tetrabromobenzotriazole (TBB)on the apoptosis of human colon cancer SW480 cells,and to explore its possible mechanism.Methods:The human colon cancer SW480 cells at logarithmic growth phase were divided into control group (0 μmol·L-1 TBB)and experiment group (1,3,10,30,and 100 μmol·L-1 TBB).The viability of cells was measured by MTT assay;the apoptotic rate of the SW480 cells and the level of intracellular reactive oxygen species (ROS)were analyzed by Annexin Ⅴ-FITC/PI double staining and flow cytometry.The expression levels of anti-apoptotic proteins p-Akt and Bcl-2,and pro-apoptotic proteins Bad, pro-caspase-9 and cleaved-caspase-3 were detected by Western blotting method. Results:The MTT results showed that the viabilities of SW480 cells in experiment group were decreased in a dose-dependent manner,which were lower than that in control group (P < 0.05).The Annexin Ⅴ-FITC/PI double staining and flow cytometry results showed that the apoptotic rates of SW480 cells in experiment group (3,6,12, and 24 h)were significantly higher than that in control group (0 h)(P <0.05).The flow cytometry results showed the levels of ROS in SW480 cells after treated with TBB for 3,6,12 and 24 h were higher than that in 0 h group (P <0.05).The Western blotting results showed that the expression levels of anti-apoptotic proteins p-Akt and Bcl-2 in SW480 cells in experiment group (3,6,12,and 24 h)were decreased obviously,whereas the expression levels of the pro-apoptotic proteins Bad and cleaved-caspase-3 were increased and the expression level of pro-caspase-9 was decreased compared with those in control group (0 h) (P < 0.05 ).Conclusion: TBB could inhibit the cell proliferation and induce the apoptosis of human colon cancer SW480 cells,and its mechanism may be related to the inhibition of the activity of Akt and the promotion of the level of intracellular ROS.