ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

ObjectiveTo investigate the T lymphocyte subset levels and viral loads in newly human immunodeficiency virus (HIV) antibody-confirmed positive cases in Suzhou (2021‒2024), and to analyze potential influencing factors by integrating their demographic characteristics, immune status, and viral replication patterns, thereby providing evidence for HIV/acquired immune deficiency syndrome (AIDS) prevention and control. MethodsPeripheral whole blood samples were collected from newly confirmed HIV-positive cases in Suzhou from 2021 to 2024. T lymphocyte subset analysis and viral load testing were performed, and influencing factors were identified in combination with demographic characteristics. Logistic regression models were employed to identify factors associated with CD4⁺T lymphocyte counts ≤350 cells·μL^-1, and Spearman’s rank correlation test was used to analyze the correlation between logarithmic value of viral load and CD4⁺/CD8⁺ ratio. ResultsAmong the 3 022 confirmed HIV-positive samples, the median CD4⁺T lymphocyte count was 298.00 cells·μL^-1, with 882 cases (29.19%) showing CD4⁺ T lymphocyte counts <200 cells·μL^-1. The median CD8⁺T lymphocyte count was 1 011.00 cells·μL^-1. The median CD4⁺/CD8⁺ ratio was 0.28, with 32.46% of cases exhibiting CD4⁺/CD8⁺ ratios <0.20, and there were statistically significant differences in CD4⁺/CD8⁺ ratio among different genders, age groups, marital status, and sample sources (all P<0.05). Multivariate logistic regression analyses indicated that individuals aged ≥20 years, those who were divorced or widowed, and cases identified through medical institutions had a significantly higher proportion of CD4⁺T lymphocyte counts ≤350 cells·µL⁻¹ compared to those aged <20 years, unmarried individuals, and cases sourced from voluntary counseling and testing (VCT) clinics, respectively. The mean logarithmic value of viral load was (4.29±1.15) copies·mL^-1. The logarithmic value of viral load demonstrated a significantly negative correlation with both CD4⁺/CD8⁺ ratio (r=-0.43, P<0.001) and CD4⁺T lymphocyte count (r=-0.37, P<0.001). ConclusionA substantial proportion of newly diagnosed HIV/AIDS cases in Suzhou are late presenters with high viral load levels. Targeted interventions should prioritize high-risk populations through enhanced active surveillance and the implementation of combined T lymphocyte subsets analysis and viral load testing, which can enable earlier case-finding and timely antiretroviral therapy initiation.

Compared with matrix-assisted laser desorption ionization mass spectrometry(MALDI-MS)using organic small molecule matrix,surface-assisted laser desorption ionization mass spectrometry(SALDI-MS)based on nanomaterial matrix is more effective in analysis of small molecule compounds.Ion sputtering instruments have obvious advantages for applying inorganic nanomatrix.In this work,the carbon-platinum material was sputtered onto a glass cover slip using an ion sputtering instrument to form a carbon-platinum(C-Pt)composite nanomatrix,and an SALDI-MS analytical method was thus established based on the prefabricated C-Pt composite matrix.The experimental results showed that the C-Pt composite nanomatrix could significantly improve the signal intensity and signal-to-noise ratio of the mass spectrum peaks of the components to be measured.The ratio of carbon to platinum,the duration of ion sputtering,and the laser power in mass spectrometer were investigated to select the optimal C-Pt matrix prefabricated conditions and SALDI-MS experimental conditions.Using the prefabricated C-Pt composite matrix,the melittriose and daidzein sample solution were applied as sample to examine repeatability.The results showed that the intra-point repeatability(RSD)was≤4.8%and the inter-point repeatability(RSD)was≤6.4%.The quercetin and melitriose were applied as model samples,and a linearity between MS peak intensity and respective concentration in the range of 0.05-1.0 mg/mL was found,with linear correlation coefficients(R2)greater than 0.994,showing good potential for quantitative and imaging analysis.Then,the prefabricated C-Pt composite matrix was applied to SALDI-MS analysis of the 50%ethanol extract of soybean,and 15 kinds of compounds including oligosaccharides and triglycerides were identified from the mass spectra.Furthermore,the C-Pt matrix was employed in SALDI-MS imaging for the compositions in corn tissue section,and the results showed that diglycerides and triglycerides were mainly distributed in the corn embryo and around the embryo,and the distribution of oligosaccharides was relatively even.

BACKGROUND:Zinc-based alloy medical implant materials have excellent mechanical properties,complete degradability and good biocompatibility,and are mainly used in orthopedic implants,cardiovascular stents,bile duct stents,tracheal stents,nerve catheters,etc. OBJECTIVE:To review the research progress of biodegradable zinc-based alloys in bone defect repair and prospect the promising research direction and achievements of zinc-based materials. METHODS:After searching PubMed,Web of Science,WanFang Data,and CNKI databases from the establishment of the database to June 2023,various relevant articles on biodegradable zinc-based alloys for bone implant material research were collected.The basic characteristics of biodegradable zinc based alloys were summarized,and the role of zinc-based alloys in promoting bone tissue repair was sorted and summarized.The current research hotspots and shortcomings were discussed. RESULTS AND CONCLUSION:(1)Zinc-based alloys have good biocompatibility.Using zinc-based alloys as the matrix material,with the help of scaffold structure construction technology and coating optimization process,the bone conductivity of zinc-based alloys will be effectively improved,and their degradation products will have efficient bone induction to regulate the gene expression of osteoblasts and osteoclasts,thereby promoting the repair and reconstruction of bone defects.(2)However,in the research on optimizing zinc-based alloys,the coating process is relatively insufficient,and additive loading technology is still lacking.(3)Zinc-based alloys have excellent mechanical and biological properties.Through special processes,their bone conductivity and osteoinductivity can be increased to effectively improve their ability to promote bone repair and reconstruction,and it is expected to further achieve the development of personalized transplant materials.Further research and development are needed to optimize the integration of coating and additive loading technologies into zinc-based alloys.

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 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.

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 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.