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.

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.

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.

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 evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective·To evaluate the predictive value of anti-neutrophil cytoplasmic antibodies(ANCA)in Kawasaki disease(KD)complicated with coronary artery lesions(CALs)and to construct a nomogram prediction model.Methods·A retrospective study was conducted to collect the clinical data of 340 children with KD admitted to Shanghai Children's Medical Center from January 2018 to May 2024.All patients were randomly divided in a 7:3 ratio into a training set(n=237)and a validation set(n=103).Univariate analysis and least absolute shrinkage and selection operator(LASSO)were applied to screen the risk factors of CALs,which were incorporated into multifactorial Logistic regression analysis to develop the nomogram model.The model's discrimination,calibration and clinical practicability were evaluated using the receiver operating characteristic(ROC)curve,calibration curve,Hosmer-Lemeshow goodness-of-fit test,and decision curve analysis(DCA).A new predictive scoring system was obtained by assigning scores to each variable based on the coefficients of the independent variables in the Logistic regression equation,and its predictive efficacy was then compared with that of three commonly used scoring systems,Kobayashi,Egami,and Sano scoring models.Results·Male,low serum albumin level,ANCA positivity,and intravenous immunoglobulin resistance were risk factors for the development of CALs in children with KD,based on which a nomogram model was constructed.The area under the ROC curve for the nomogram in the training set and validation set were 0.747(95%CI 0.667?0.821)and 0.645(95%CI 0.500?0.794),respectively,indicating good effectiveness.The model was verified to have good predictive accuracy through the calibration curve and Hosmer-Lemeshow goodness-of-fit test(training set:χ2=5.105,P=0.746;validation set:χ2=13.549,P=0.094).The DCA showed its clinical usefulness.A predictive scoring system for CALs was developed based on the coefficients of the Logistic regression equation,which demonstrated higher sensitivity(58.4%)and specificity(78.7%)compared to the Kobayashi,Egami,and Sano scoring models.Conclusion·This study developed a new scoring model based on ANCA to effectively predict the risk of CALs in KD patients.The model provides valuable reference for clinicians to identify high-risk patients early,and to formulate personalized treatment plans and management strategies.

In patients with heart failure with reduced ejection fraction(HFrEF),some individuals demonstrate significant improvement in left ventricular ejection fraction(LVEF)during subsequent evaluations after treatment.The 2022 American Heart Association/American College of Cardiology/Heart Failure Society of America(AHA/ACC/HFSA)heart failure management guidelines introduced the term"heart failure with improved ejection fraction(HFimpEF)"to describe patients with prior LVEF≤40%that subsequently increased above 40%during follow-up.Studies indicate that HFimpEF patients exhibit lower all-cause mortalities and heart failure rehospitalization rates,with a significantly better prognosis compared to HFrEF patients,establishing HFimpEF as a staged therapeutic target for HFrEF.Current discussion on HFimpEF primarily focuses on two aspects:characteristics of the target population and effective methods for LVEF improvement,and maintenance strategies for cardiac function preservation in HFimpEF patients;particularly the latter lacks clear clinical-guideline recommendations.Therefore,reviewing existing research to systematically summarize therapeutic strategies that promote the HFrEF-to-HFimpEF transition and effective maintenance approaches for HFimpEF becomes crucial.This article comprehensively reviews the LVEF-improving effects of current pharmacological,device-based,and surgical interventions,along with monitoring and management strategies for HFimpEF patients.In HFrEF patients,clinical evidence suggests that β-blockers and cardiac resynchronization therapy can significantly improve LVEF beyond 40%.Regarding HFimpEF management,sodium-glucose cotransporter-2 inhibitors(SGLT2i)and renin-angiotensin system inhibitors(RASi)demonstrate efficacy in maintaining LVEF and cardiac function.Additionally,this review identifies current research limitations in HFimpEF and proposes potential future research directions.

Objective:To investigate the predictive value of microRNA-1(miR-1),brain natriuretic peptide(BNP)and ischemia-modified albumin(IMA)for unstable angina pectoris(UAP).Methods:We enrolled 237 UAP patients admitted to Xining Second People's Hospital between June 2018 and December 2020 as UAP group.Another 86 healthy subjects undergoing physical examination simultaneously were enrolled as control group.MiR-1 expression,BNP and IMA levels were measured.General data between UAP group and control group,serum miR-1 expression,BNP and IMA levels among different Braunwald class and prognosis were compared.Receiver operat-ing characteristic(ROC)curve was employed to analyze predictive value of miR-1,BNP,IMA and their combina-tion for prognosis in UAP patients.Results:Compared with participants in the control group,those in UAP group had significant higher serum miR-1 expression[(1.80±0.59)vs.(0.93±0.11)],BNP[(107.34±37.46)pg/ml vs.(52.31±10.64)pg/ml]and IMA[(79.76±19.29)g/L vs.(53.16±6.43)g/L](P＜0.001 all).As Braun-wald class increased(class Ⅰ～Ⅲ),serum miR-1 expression,BNP and IMA levels elevated(P＜0.001 all).Com-pared with patients in favorable outcome group,those in unfavorable outcome group had significant higher serum miR-1 expression[(2.31±0.54)vs.(1.53±0.41)],BNP[(147.03±29.63)pg/ml vs.(85.95±19.46)pg/ml]and IMA[(97.24±15.35)g/L vs.(70.35±13.88)g/L](P＜0.001 all).ROC curve indicated that AUC of com-bined detection for predicting unfavorable outcome in UAP patients was 0.925(95％CI 0.884～0.955),which was significantly higher than miR-1(AUC=0.880,95％CI 0.831～0.918),BNP(AUC=0.863,95％CI 0.813～0.904)and IMA(AUC=0.900,95％CI 0.854～0.935)alone(Z=2.884,3.130,2.090,P＜0.05 or＜0.01).Conclusion:MiR-1 expression,BNP and IMA levels significantly increase in UAP patients,and they are associated with the severity of disease.Combined detection has good predictive value for unfavorable outcome in UAP pa-tients.