Objective To report the diagnosis of a canine distemper virus outbreak among a colony of cynomolgus monkeys at an experimental monkey farm in 2019. MethodsA total of 46 samples were collected from 21 diseased cynomolgus monkeys (exhibiting symptoms such as facial rash, skin scurf, runny nose, and diarrhea) and from one deceased monkey at an experimental monkey breeding farm in South China in late 2019, including serum, skin rash swabs, and anticoagulated whole blood, liver, lung, and skin tissues were submitted for testing. All submitted samples were tested for canine distemper virus gene fragments using real-time quantitative PCR, while immunohistochemical staining was performed to detect canine distemper virus nucleoprotein in lung tissues. The skin tissue of the deceased monkey was ground and sieved. The filtrate was inoculated into a monolayer MDCK cell line for virus isolation. Then, whole-genome sequencing was performed to identify the isolated virus. The Clustal Omega tool was used to align and analyze the homology of different Asian canine distemper virus isolates. A phylogenetic tree was constructed, followed by genetic evolutionary analysis. ResultsClinical retrospective analysis revealed that the diseased cynomolgus monkeys exhibited symptoms similar to those observed in cynomolgus monkeys infected with measles virus. Necropsy findings showed red lesions in the lungs and significant hemorrhage in the colonic mucosa. Real-time quantitative PCR detected canine distemper virus nucleic acid in the serum, skin rash swabs of the infected monkeys, and various tissue samples of the deceased monkey, all of which tested positive. Calculation based on the standard curve formula indicated the viral load was highest in the skin tissue. Immunohistochemical staining of the deceased monkey's lung tissue demonstrated aggregation of CDV nucleoprotein in alveolar epithelial cells, bronchi, and bronchioles. A CDV strain was isolated from the skin tissue of the deceased monkey. Phylogenetic analysis indicated that this strain shares the closest relationship (98.86%) with the Asian-1 type canine distemper virus strain CDV/dog/HCM/33/140816, previously identified in dogs in Vietnam. ConclusionBased on comprehensive analysis of clinical symptoms, nucleic acid detection, viral protein immunohistochemistry, and whole-genome sequencing results, the diagnosis confirms that the cynomolgus monkeys in this facility are infected with canine distemper virus. It is recommended to include canine distemper virus as a routine surveillance target in captive monkey populations. Additionally, this study provides a foundation for further research on the molecular biological characteristics of canine distemper virus.

Objective To report the diagnosis of a canine distemper virus outbreak among a colony of cynomolgus monkeys at an experimental monkey farm in 2019. MethodsA total of 46 samples were collected from 21 diseased cynomolgus monkeys (exhibiting symptoms such as facial rash, skin scurf, runny nose, and diarrhea) and from one deceased monkey at an experimental monkey breeding farm in South China in late 2019, including serum, skin rash swabs, and anticoagulated whole blood, liver, lung, and skin tissues were submitted for testing. All submitted samples were tested for canine distemper virus gene fragments using real-time quantitative PCR, while immunohistochemical staining was performed to detect canine distemper virus nucleoprotein in lung tissues. The skin tissue of the deceased monkey was ground and sieved. The filtrate was inoculated into a monolayer MDCK cell line for virus isolation. Then, whole-genome sequencing was performed to identify the isolated virus. The Clustal Omega tool was used to align and analyze the homology of different Asian canine distemper virus isolates. A phylogenetic tree was constructed, followed by genetic evolutionary analysis. ResultsClinical retrospective analysis revealed that the diseased cynomolgus monkeys exhibited symptoms similar to those observed in cynomolgus monkeys infected with measles virus. Necropsy findings showed red lesions in the lungs and significant hemorrhage in the colonic mucosa. Real-time quantitative PCR detected canine distemper virus nucleic acid in the serum, skin rash swabs of the infected monkeys, and various tissue samples of the deceased monkey, all of which tested positive. Calculation based on the standard curve formula indicated the viral load was highest in the skin tissue. Immunohistochemical staining of the deceased monkey's lung tissue demonstrated aggregation of CDV nucleoprotein in alveolar epithelial cells, bronchi, and bronchioles. A CDV strain was isolated from the skin tissue of the deceased monkey. Phylogenetic analysis indicated that this strain shares the closest relationship (98.86%) with the Asian-1 type canine distemper virus strain CDV/dog/HCM/33/140816, previously identified in dogs in Vietnam. ConclusionBased on comprehensive analysis of clinical symptoms, nucleic acid detection, viral protein immunohistochemistry, and whole-genome sequencing results, the diagnosis confirms that the cynomolgus monkeys in this facility are infected with canine distemper virus. It is recommended to include canine distemper virus as a routine surveillance target in captive monkey populations. Additionally, this study provides a foundation for further research on the molecular biological characteristics of canine distemper virus.

Adaptive optics(AO)is a technology designed to enhance the performance of optical systems through real-time measurement and correction of optical aberrations. With continuous advancements in refractive surgery techniques and rising patient expectations for surgical outcomes, the precise implementation of personalized refractive corrections has become a critical focus. The integration of AO technology into refractive surgery provides novel technical support. Specifically, the adaptive optics vision simulator(VAO)facilitates accurate preoperative objective and subjective refraction by dynamically measuring and correcting ocular wavefront aberrations, thereby improving refractive efficiency. Additionally, it enables effective prediction of postoperative aberrations for personalized procedures, assists clinicians in making data-driven preoperative decisions, facilitates comparative analysis of different surgical techniques, and allows intuitive evaluation of postoperative visual quality. This review comprehensively examines the advances in VAO applications for refractive surgery and analyzes both its clinical advantages and technical limitations.

OBJECTIVE: To investigate the effects of 4-methylcatechol (4MC) on the migration and inflammatory response in rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS), as well as its underlying mechanisms of action. METHODS: RA-FLS was isolated from synovial tissue donated by RA patients, and the optimal concentration of 4MC was determined by cell counting kit 8 method for subsequent experiments, and the effect of 4MC on the migratory ability of RA-FLS was evaluated via a cell scratch assay. An inflammation model of RA-FLS was induced by tumor necrosis factor α (TNF-α). Real-time fluorescence quantitative PCR and ELISA were employed to detect the gene and protein expression levels of interleukin-1β (IL-1β) and IL-6 in RA-FLS and their culture supernatants, respectively, thereby investigating the anti-inflammatory effects of 4MC. Western blot was used to examine the expressions of nuclear factor κB (NF-κB) signaling pathway-related proteins, including inhibitor of NF-κB-α (IKBα), phosphorylated (P)-IκBα, NF-κB-inducing kinase α (IKKα), P-IKKαβ, P-p65, and p65. Cellular immunofluorescence was utilized to detect the expression and localization of p65 in RA-FLS, exploring whether 4MC exerts its anti-inflammatory effects by regulating the NF-κB signaling pathway. Finally, a collagen-induced arthritis (CIA) mouse model was established. The anti-RA effect of 4MC in vivo was evaluated by gross observation and histological examination. RESULTS: 4MC inhibited RA-FLS migration in a concentration-dependent manner. In the TNF-α-induced RA-FLS inflammation model, 4MC significantly decreased the gene and protein expression levels of IL-1β and IL-6. Furthermore, 4MC markedly reduced the ratios of P-IΚBα/IΚBα, P-IKKαβ/IKKα, and P-p65/p65, thereby blocking the transcriptional activity of p65 by inhibiting its nuclear translocation. This mechanism effectively suppressed the activation of the TNF-α-mediated NF-κB signaling pathway. Animal studies demonstrated that 4MC [10 mg/(kg·day)] significantly lowered serum levels of IL-1β, IL-6, and TNF-α, and alleviated arthritis severity and bone destruction in CIA mice. CONCLUSION 4MC not only inhibits the migration of RA-FLS but also mitigates their inflammatory response by suppressing the NF-κB signaling pathway, thereby effectively exerting its anti-RA effects.
Synoviocytes/metabolism* ; Arthritis, Rheumatoid/metabolism* ; Animals ; Cell Movement/drug effects* ; Humans ; Catechols/therapeutic use* ; Fibroblasts/drug effects* ; Mice ; Tumor Necrosis Factor-alpha/pharmacology* ; Interleukin-1beta/metabolism* ; Interleukin-6/metabolism* ; Signal Transduction/drug effects* ; NF-kappa B/metabolism* ; Transcription Factor RelA/metabolism* ; Synovial Membrane/cytology* ; Cells, Cultured ; Male ; Arthritis, Experimental ; Anti-Inflammatory Agents/pharmacology* ; NF-KappaB Inhibitor alpha ; Inflammation

Dengue fever is an acute mosquito-borne infectious disease caused by dengue virus and widely spread worldwide. Many factors, such as pathogens, vector organisms, climate, and social environment, affect its transmission and prevalence. The local dengue fever epidemic caused by imported cases in China shows a trend of increasing epidemic latitude and more widespread epidemic areas. However, the traditional monitoring and early warning models of dengue fever mainly focus on researching a single factor and a single area. Establishing a multi-factor forecast and early warning system is urgent to strengthen the early warning capability for the dengue fever epidemic. This paper mainly discusses the epidemic characteristics, the influencing factors, and the surveillance and early warning models of dengue fever in China to provide a reference for the effective prevention and control of dengue fever in China.

Objective:To analyze the epidemiological and clinical characteristics of respiratory syncytial virus (RSV) infection in children in Jiangsu Province from 2014 to 2023.Methods:The acute respiratory infection cases in children aged 0-14 years were selected from outpatient/emergency or inpatient departments in 2 surveillance sentinel hospitals, respectively, in Nanjing, Suzhou and Taizhou of Jiangsu from 1 July 2014 to 31 December 2023, and RSV nucleic acid test was conducted and the intensity of the RSV infection was accessed by WHO influenza epidemiological threshold method, and case information and clinical data were collected. χ2 test was used to compare the differences between groups, and the Bonferroni method was used for pairwise comparisons between groups. Results:In 4 946 cases of acute respiratory infections, the RSV positive rate was 8.21% (406/4 946), and the age M( Q1, Q3) of the cases was 1 (0, 3) years. The RSV positive rate was 10.92% (258/2 362) during 2014-2019 and 6.06% (118/1 948) during 2019-2023, the difference was significant ( χ2=31.74, P<0.001). RSV infection mainly occurred from October to March during 2014-2019, with the incidence peak in December and moderate or higher intensity. The seasonality of RSV infection was not obvious during 2019-2023, with low intensity. The RSV positive rate was highest in children in age group 0- years (17.85%, 151/846), and the positive rate declined gradually with age ( χ2=184.51, P<0.001). The RSV positive rate was higher in inpatient cases (9.84%, 244/2 480) than in outpatient/emergency cases (6.57%, 162/2 466) ( χ2=17.54, P<0.001). In the 155 RSV infection cases with complete clinical data, the clinical symptoms mainly included cough (99.35%, 154/155), fever (55.48%, 86/155), and shortness of breath (45.16%, 70/155). In the cases aged <6 months, the proportion of those with fever was low, but the proportion of those with shortness of breath, transferred to intensive care units, and receiving oxygen therapy were higher (all P<0.05). Children aged <6 months and those with underlying diseases were more likely to have severe RSV infection (all P<0.05). Conclusions:RSV infection in children in Jiangsu Province showed seasonal prevalence in winter from 2014 to 2019. Since 2020, the seasonal characteristics of the epidemic have changed, the epidemic period has been dispersed and the epidemic intensity has decreased. Infants <1 year old were at high risk for RSV infection, and those <6 months old and with underlying diseases might have severe infection.

Objective: To analyze the clinical distribution and drug resistance trends of clinical isolates ofKlebsiella pneumoniaefrom a tertiary hospital in Henan Province from 2017 to 2021, and to provide recommendations for the rational use of antibiotics in the hospital. Methods: A retrospective study was conducted to collect and organize the drug sensitivity test results and clinical data of clinical isolates ofKlebsiella pneumoniaein the hospital from 2017 to 2021. The data was analyzed using WHO NET 5.6 and SPSS 26.0 software. Results: A total of 1 379 strains ofKlebsiella pneumoniaewere isolated in the hospital from 2017 to 2021, with an isolation rate of 17.87%. There was no significant difference in the isolation rates ofKlebsiella pneumoniaeover the entire five-year period.The top three sources of isolates were sputum(65.99%), secretion(12.98%), and urine(8.85%). The main departments for collecting isolates were the respiratory department(26.03%) and the ICU(24.58%), with the isolation rate in other departments being less than 5%. The drug sensitivity results showed that, except for the resistance rate of cefoperazone, the resistance rates of other antibacterial drugs showed statistically differences over the five years, generally showing a stable or decreasing trend. The carbapenem drugs imipenem and meropenem decreased from 33.1% and 33.5% in 2017 to 13.7% and 14.4% in 2021, respectively. In addition, the resistance rates of chloramphenicol and tetracycline class minocycline showed an increasing trend. Conclusion Klebsiella pneumoniaeis still the main pathogen isolated in the hospital, mainly in the respiratory department and ICU, with sputum, urine, and blood being the main specimens. The resistance rates have shown a stable or decreasing trend over the past five years, with a significant decrease in carbapenem resistance rates. However, attention should still be paid to the increasing resistance rates of chloramphenicol and minocycline. Clinically, antibiotics should be used rationally based on drug sensitivity results.

In recent years, global outbreaks of infectious diseases, such as COVID-19, have triggered great concern about emerging infectious diseases. With the rapid development of next-generation sequencing technology and bioinformatic tools for viral metagenomics, there is now a widespread capability to detect and identify various known and unknown pathogenic microorganisms within both environmental and biological contexts. Furthermore, the continuous evolution of machine learning methods has led to the development and application of multiple rapid and highly accurate approaches for virus identification. Concurrently, owing to the continual progress in machine learning methods, several rapid and accurate virus identification techniques have been widely developed and applied. Therefore, this review aims to systematically summarize the key methodologies, frameworks, and the scope of applicability within the field of viral metagenomics, with a specific focus on virus identification and prediction. It could facilitate a deeper understanding of viral characteristics, identify potential novel pathogens, and provide technical support for the early prevention and control of infectious diseases.

In recent years, global outbreaks of infectious diseases, such as COVID-19, have triggered great concern about emerging infectious diseases. With the rapid development of next-generation sequencing technology and bioinformatic tools for viral metagenomics, there is now a widespread capability to detect and identify various known and unknown pathogenic microorganisms within both environmental and biological contexts. Furthermore, the continuous evolution of machine learning methods has led to the development and application of multiple rapid and highly accurate approaches for virus identification. Concurrently, owing to the continual progress in machine learning methods, several rapid and accurate virus identification techniques have been widely developed and applied. Therefore, this review aims to systematically summarize the key methodologies, frameworks, and the scope of applicability within the field of viral metagenomics, with a specific focus on virus identification and prediction. It could facilitate a deeper understanding of viral characteristics, identify potential novel pathogens, and provide technical support for the early prevention and control of infectious diseases.

Objective:To investigate the value of quantitative parameters of amide proton transfer-weighted (APTw) imaging and dynamic contrast-enhanced (DCE)-MRI for preoperative assessment of human epidermal growth factor receptor 2 (Her-2) gene expression in endometrial cancer (EC).Methods:This research conducted a diagnostic pilot study involving 68 patients with pathologically confirmed EC at the First Hospital of Dalian Medical University from August 2019 to August 2023. Patients were categorized into Her-2-positive group (33 cases) and Her-2-negative group (35 cases) based on postoperative Her-2 gene expression results. Utilizing the APTw and DCE-MRI sequences, quantitative parameters including the asymmetric magnetization transfer ratio (MTR asym) for APTw and the volumetric transfer constant (K trans), plasma volume fraction (V p), extracellular mesenchymal space (V e), and rate constant (K ep) for DCE-MRI were acquired for the lesion site. Statistical differences in the values of each quantitative parameter between the two groups were evaluated using two independent sample t test or Mann-Whitney U test. The study incorporated quantitative parameters and clinicopathological data of patients to identify independent predictors of EC Her-2 gene expression through logistic regression analysis. A diagnostic model was developed using binary logistic regression analysis. The effectiveness of the parameters and diagnostic model was evaluated using receiver operating characteristic curves. DeLong test was used to compare the differences between the areas under the curves (AUC). Results:The study found statistically significant differences in MTR asym, K trans, and V e between the Her-2-positive group and the Her-2-negative group ( Z=2.55, P=0.011; t=-2.03, P=0.047; t=-2.13, P=0.037). However, the differences in V p and K ep were not statistically significant ( Z=0.58, P=0.560; Z=0.19, P=0.849). MTR asym emerged as a significant independent predictor of Her-2 gene expression in EC ( OR=1.016, 95% CI 1.003-1.030, P=0.014). Incorporating MTR asym, K trans, and V e, the diagnostic model yielded an AUC (95% CI) of 0.745 (0.625-0.864). The AUC (95% CI) for MTR asym, K trans, and V e alone were 0.680 (0.551-0.808), 0.623 (0.485-0.760), and 0.656 (0.523-0.789) respectively. The differences in AUC between the diagnostic model and individual predictors MTR asym, K trans, and V e were not found to be statistically significant ( Z=1.40, 1.92, 1.37, P=0.163, 0.055, 0.171). Conclusion:The quantitative parameters of APTw and DCE-MRI sequences can preoperatively assess EC Her-2 gene expression from a different perspective, with MTR asym potentially serving as a valuable independent predictor.