Objective To analyze the newly reported HIV-1 infection in several prefectures of Hubei Province，and analyze its influencing factors. Methods The limiting antigen avidity enzyme immunoassay(LAg-avidity EIA,LAg) was conducted on HIV-1 positive samples confirmed by Western blot of Hubei in 2017-2022. The demographic characteristics of the newly infected samples were analyzed by χ2 test.Logistic regression model was used to analyze influencing factors of new infection rate and predict the factors associated with the HIV-1 recent infection. Results There were 403 new cases of HIV-1 from 2017 to 2022 in several prefectures of Hubei Province, of which 77 were newly infected sorted by LAg,with a new infection rate of 19.11%. The newly confirmed HIV-1 persons of whom aged ≤24 years (40.00% new infection ratio), unmarried (29.41%), college or above (31.37%), and from Voluntary counseling and testing testing(VCT) clinics (40.00%) had a higher proportion of new infections, and the difference was statistically significant. Multivariate Logistic regression analysis showed that age ≤24 years old (aOR=4.346,95%CI: 1.342-14.075) and screening from the VCT clinic (aOR=6.761,95%CI: 1.460-31.319) were more likely to be newly infected. Conclusion The proportion of new HIV infection in several prefectures of Hubei province is relatively low in recent years.Further effective publicity and intervention measures for young students and the construction of VCT clinic should be continuously promoted to achieve early diagnosis and treatment.

Natural products have shown great potential in the research and development of antitumor drugs. However， their clinical application is severely limited by inherent drawbacks such as poor water solubility， low stability， and low bioavailability. Cell membrane biomimetic nanoparticles， as a novel drug delivery system， have provided new strategies to overcome this bottleneck. This review systematically summarizes the preparation methods （e.g.， membrane extrusion， ultrasonic fusion， and microfluidic electroporation） and characterization techniques （e.g.， particle size， Zeta potential， and membrane surface protein detection） of cell membrane biomimetic nanoparticles， with a focus on the application of these derived from various sources in delivering antitumor natural products. Cell membrane biomimetic nanoparticles are endowed with unique biological functions， including low immunogenicity conferred by stem cell membranes， prolonged systemic circulation enabled by red blood cell membranes， and homologous targeting facilitated by tumor cell membranes. Despite these advancements， the technology still faces challenges such as difficulties in large-scale production， high costs， and limited characterization methods. Future research needs to further optimize the relevant processes to promote the clinical translation of cell membrane-biomimetic nanoparticles， thereby offering an efficient and safe novel delivery approach for antitumor therapy using natural products.

ObjectiveHyperlipidemia （HLP） is a chronic metabolic disease characterized by abnormal lipid metabolism and is one of the important risk factors for the occurrence of cardiovascular and cerebrovascular diseases. Its incidence has increased year by year， showing a trend toward younger onset. The overall prevalence of HLP among adults in China is as high as 40.40%. Although existing animal models provide important tools for research on the mechanisms of HLP， they generally show insufficient clinical concordance and lack the combined disease-syndrome characteristics of traditional Chinese medicine （TCM） and Western medicine. This article systematically reviews the research progress of HLP animal models， integrates the clinicopathological characteristics of TCM and Western medicine， and proposes new model construction strategies， aiming to provide an experimental basis for accurately analyzing the pathogenesis of HLP and developing integrated TCM-Western medicine therapies. MethodsBased on literature included in PubMed， CNKI， and Wanfang databases over the past 30 years， the construction methods and evaluation systems of HLP animal models were systematically retrieved and summarized. The concordance of existing animal models was calculated according to the new animal model evaluation method proposed by Professor MIAO Mingsan. ResultsAmong existing Western medicine modeling approaches， genetically modified models showed the highest concordance （72%）， followed by dietary induction （66%） and chemical drug induction （60%）. The dietary induction method is the most widely used in practice because of its simple operation and mature technology. Existing TCM modeling approaches are classified into three types， i.e.， spleen deficiency type， phlegm syndrome type， and liver-kidney yin deficiency type. Among them， the phlegm syndrome type shows a high degree of concordance. However， all three types have the problem of non-objective evaluation indicators and insufficient application of tongue and pulse assessment. ConclusionThe construction of existing HLP disease-syndrome combined animal models is still mainly based on Western medicine modeling methods and lacks adequate reflection of TCM syndromes. In the future， HLP animal models that conform to the clinical disease-syndrome characteristics of both TCM and Western medicine may be constructed through multifactor composite modeling strategies， intelligent tongue image analysis via robot learning， objective pulse detection， the establishment of objective evaluation systems for TCM syndromes through big data computing， and the application of cutting-edge technologies.

ObjectiveTo investigate the epidemiological and clinical characteristics of human bocavirus (HBoV) in hospitalized children with acute lower respiratory tract infection (ALRTI) at a single-center children’s hospital in Shanghai, thereby providing evidence for the diagnosis, treatment, and prevention of HBoV infection. MethodsA retrospective study was conducted on 19 537 hospitalized children with ALRTI at Shanghai Children’s Hospital from January 2021 to December 2023. Multiplex polymerase chain reaction (PCR) combined with capillary electrophoresis was used to detect HBoV and 12 other common respiratory viruses /atypical pathogens. The positive detection rate, demographic characteristics (sex, age), temporal distribution (year, season) of HBoV, as well as the clinical characteristics of severe and non-severe pneumonia were analyzed. ResultsThe overall HBoV-positive rate was 2.57% (503/19 537), with 59.44% (299/503) being single infections and 40.56% (204/503) being co-infections. The positive detection rate was significantly higher in boys than that in girls (2.78% vs 2.33%, χ²=3.88, P=0.049). The highest infection rate was observed in toddlers, followed by infants (χ²=379.57, P<0.001). The positive rate peaked in 2021 and reached its lowest point in 2023 (χ²=45.49, P<0.001), with epidemics mainly prevalent in summer and autumn. The main clinical symptoms were cough (90.06%, 453/503), fever (75.94%, 382/503), and wheezing (39.96%, 201/503). Children with severe pneumonia showed a higher incidence of wheezing compared with the non-severe group (P<0.001), while underlying diseases and co-infections had no significant association with disease severity (P>0.05). ConclusionHBoV was an important pathogen of ALRTI in children, predominantly affecting infants and toddlers, with higher susceptibility in boys and seasonal peaks in autumn and summer. The main clinical manifestations included cough, fever, and wheezing, with wheezing being more prevalent in children with severe pneumonia.

Objective: To investigate the situation and influencing factors of school bullying experienced by primary and middle school students, so as to provide the basis for formulating school bullying intervention measures and promoting students' physical and mental health development. Methods: All the counties (cities, districts) in Zhejiang Province were stratified to urban and suburban areas, primary, junior high and senior high school students were selected using a stratified cluster sampling method. Basic information, lifestyle and school bullying were collected through questionnaire surveys. Factors affecting school bullying experienced by primary and middle school students were analyzed using a multivariable logistic regression model. Results: Totally 137 846 valid questionnaires were recovered, with an effective recovery rate of 97.17%. There were 72 526 males (52.61%) and 65 320 females (47.39%). There were 47 561 primary school students (34.50%), 47 701 junior high school students (34.61%) and 42 584 senior high school students (30.89%). A total of 3 987 students suffered from school bullying, accounting for 2.89%. The proportions of being maliciously teased, being intentionally excluded from group activities/isolated, being teased about physical defects or appearance, being hit/kicked/pushed/shoved/locked in a room, being threatened, and being extorted for money were 2.04%, 1.18%, 1.11%, 0.86%, 0.84% and 0.83%, respectively. Multivariable logistic regression analysis showed that the students who were males (OR=1.122, 95%CI: 1.048-1.202), lived in suburban areas (OR=1.322, 95%CI: 1.233-1.418), lived in areas with medium (OR=1.086, 95%CI: 1.006-1.173) or underdeveloped (OR=1.298, 95%CI: 1.191-1.415) economic level, had higher academic levels (junior high school, OR=1.380, 95%CI: 1.270-1.499; senior high school, OR=1.210, 95%CI: 1.083-1.351), lived on campus (OR=1.489, 95%CI: 1.372-1.616), engaged in fights (OR=6.029, 95%CI: 5.585-6.509), attempted to smoke (OR=1.320, 95%CI: 1.128-1.545), drank (OR=1.735, 95%CI: 1.575-1.912), were scolded and beaten by parents (OR=1.972, 95%CI: 1.822-2.135) and were obese (OR=1.240, 95%CI: 1.132-1.360) were more likely to experience school bullying. Conclusion The harm of school bullying to the physical and mental health of primary and middle school students should be taken seriously, and active policy measures should be adopted to strengthen intervention.

ObjectiveEarly blight is a common destructive disease in the growth process of Solanaceae crops, which can lead to crop failure and serious losses. Traditional crop disease detection methods are difficult to detect disease characteristics in a timely manner during the incubation period of disease, and thus take scientific and effective prevention and control measures. This study obtained hyperspectral images of early blight of peppers at different infection stages through continuous monitoring with a hyperspectral imager. The earliest identifiable time during the incubation period of early blight in peppers (the earliest identifiable time during the incubation period in this experiment was 24 h after inoculation) was determined using the spectral angle cosine-correlation coefficient and Chebyshev distance. MethodsTaking the symptoms of the latent period of early blight in peppers as the research object, 13 characteristic wavelengths were selected using a genetic algorithm. An identification model of crop disease latent period symptoms based on spectral features was established through optimized combinations of characteristic wavelengths combined with a logistic regression model. Simultaneously, a recognition model of the latent period of early blight in peppers based on image texture features was established using local binary patterns. ResultsThe experiment was tested with 120 samples. The accuracy of the identification model of crop disease latent period symptoms based on spectral features reached over 93% in both the training set and the test set. The accuracy of the identification model of crop disease latent period symptoms based on texture features reached 98.96% and 100% in the training set and test set, respectively. ConclusionBoth spectral features and texture features can be used to detect and identify crop disease latent period symptoms. Texture features more significantly revealed the characteristics of the latent period of the disease compared to spectral features, effectively improving the detection performance of the model. The research results in this article can provide theoretical references for monitoring and identifying other crop disease latent period symptoms.

Objective To develop and validate a model to predict the risk of radiation-induced lung injury (RILI) and assess its clinical feasibility. Methods Clinical data from 125 patients with non-small cell lung cancer (NSCLC) were included in the study. The patients were divided into training group (88 cases) and validation group (38 cases). Key predictive factors were identified using univariate and multivariate logistic regression analyses combined with least absolute shrinkage and selection operator (LASSO) regression. A predictive model was constructed and evaluated using a nomogram, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results The key variables identified by the model were tumor volume (P = 0.017), Eastern Cooperative Oncology Group performance status score (P = 0.035), 95% of the minimum dose to the target volume (P = 0.028), percentage of bilateral lung volume receiving 20 Gy of radiation (P < 0.001), and neutrophil-to-lymphocyte ratio (P = 0.021). The ROC curve showed that the areas under the curve (AUC) for the model in the training and validation groups were 0.987 and 0.992, respectively, indicating good predictive ability. The calibration curve and decision curve further confirmed the accuracy and clinical practicability of the model. Conclusion The predictive model proposed in this study can accurately assess the risk of developing RILI in patients with NSCLC who have undergone radiotherapy, demonstrating its potential value in clinical practice.

Objective:To explore clinical validation standard for intelligent ventilation mode of ventilator and promote ventilator's clinical application.Methods:By real-time quantification of physiological parameters related to patient's ventilation and oxygenation,the change of respiratory function was analyzed,and the settings of ventilator's parameters were adjusted synchronously by using feedback signals to realize personalized support of ventilation.Combining with artificial intelligence(AI)technique,the clinical validation standard for intelligent ventilation mode was investigated from three aspects:requirements of clinical application and function of intelligent ventilation mode of ventilator,validation for platform of simulation experiment,and early clinical evaluation and interventional trials.Results:The clinical validation standards for intelligent ventilation mode of ventilator should meet the requirements of clinical application and function,and should complete preclinical evaluation of intelligent ventilation mode of ventilator,and assess safety and usability of that by the platform of simulation trials,and should conduct early clinical evaluations and interventional clinical trials so as to further assess safety and effectiveness of that before it was used formally in clinical application.Conclusion:The clinical validation standard of intelligent ventilation mode of ventilator can form standard validation process for intelligent ventilation mode,and promote the construction of standard validation platform,and facilitate clinical application and iterative optimization of intelligent ventilation mode,and improve medical quality.

AIM To explore the clinical effects of Supplemented Baihe Gujin Decoction on elderly patients with postoperative pulmonary infection following non-small cell lung cancer surgery.METHODS Ninety-two patients were randomly assigned into control group(46 cases)for 1-week intervention of conventional treatment,and observation group(46 cases)for 1-week intervention of both Supplemented Baihe Gujin Decoction and conventional treatment.The changes in clinical effects,TCM syndrome scores,immune function indices(CD3+,CD4+,CD8+,CD4+/CD8+),inflammatory indices(CRP,PCT,TNF-α),serum indices(sTREM-1,CD40L,NLR)and incidence of adverse reactions were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05).After the treatment,the two groups displayed decreased TCM syndrome scores,CD8+,inflammatory indices,serum indices(P＜0.05),and increased CD3+,CD4+,CD4+/CD8+(P＜0.05),especially for the observation group(except for CD4+,CD8+)(P＜0.05).CONCLUSION For the elderly patients with postoperative pulmonary infection following non-small cell lung cancer surgery,Supplemented Baihe Gujin Decoction can safely and effectively relieve clinical symptoms,enhance immune functions,reduce serum sTREM-1,CD40L levels and NLR,and control inflammatory responses.