Global One Health index for zoonoses: A performance assessment in 160 countries and territories.

The One Health (OH) approach is used to control/prevent zoonotic events. However, there is a lack of tools for systematically assessing OH practices. Here, we applied the Global OH Index (GOHI) to evaluate the global OH performance for zoonoses (GOHI-Zoonoses). The fuzzy analytic hierarchy process algorithm and fuzzy comparison matrix were used to calculate the weights and scores of five key indicators, 16 subindicators, and 31 datasets for 160 countries and territories worldwide. The distribution of GOHI-Zoonoses scores varies significantly across countries and regions, reflecting the strengths and weaknesses in controlling or responding to zoonotic threats. Correlation analyses revealed that the GOHI-Zoonoses score was associated with economic, sociodemographic, environmental, climatic, and zoological factors. Additionally, the Human Development Index had a positive effect on the score. This study provides an evidence-based reference and guidance for global, regional, and country-level efforts to optimize the health of people, animals, and the environment.

Precision Prediction for Dengue Fever in Singapore: A Machine Learning Approach Incorporating Meteorological Data.

OBJECTIVE: This study aimed to improve dengue fever predictions in Singapore using a machine learning model that incorporates meteorological data, addressing the current methodological limitations by examining the intricate relationships between weather changes and dengue transmission. METHOD: Using weekly dengue case and meteorological data from 2012 to 2022, the data was preprocessed and analyzed using various machine learning algorithms, including General Linear Model (GLM), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Performance metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2) were employed. RESULTS: From 2012 to 2022, there was a total of 164,333 cases of dengue fever. Singapore witnessed a fluctuating number of dengue cases, peaking notably in 2020 and revealing a strong seasonality between March and July. An analysis of meteorological data points highlighted connections between certain climate variables and dengue fever outbreaks. The correlation analyses suggested significant associations between dengue cases and specific weather factors such as solar radiation, solar energy, and UV index. For disease predictions, the XGBoost model showed the best performance with an MAE = 89.12, RMSE = 156.07, and R2 = 0.83, identifying time as the primary factor, while 19 key predictors showed non-linear associations with dengue transmission. This underscores the significant role of environmental conditions, including cloud cover and rainfall, in dengue propagation. CONCLUSION: In the last decade, meteorological factors have significantly influenced dengue transmission in Singapore. This research, using the XGBoost model, highlights the key predictors like time and cloud cover in understanding dengue's complex dynamics. By employing advanced algorithms, our study offers insights into dengue predictive models and the importance of careful model selection. These results can inform public health strategies, aiming to improve dengue control in Singapore and comparable regions.

Risk assessment of imported malaria in China: a machine learning perspective.

BACKGROUND: Following China's official designation as malaria-free country by WHO, the imported malaria has emerged as a significant determinant impacting the malaria reestablishment within China. The objective of this study is to explore the application prospects of machine learning algorithms in imported malaria risk assessment of China. METHODS: The data of imported malaria cases in China from 2011 to 2019 was provided by China CDC; historical epidemic data of malaria endemic country was obtained from World Malaria Report, and the other data used in this study are open access data. All the data processing and model construction based on R, and map visualization used ArcGIS software. RESULTS: A total of 27,088 malaria cases imported into China from 85 countries between 2011 and 2019. After data preprocessing and classification, clean dataset has 765 rows (85 * 9) and 11 cols. Six machine learning models was constructed based on the training set, and Random Forest model demonstrated the best performance in model evaluation. According to RF, the highest feature importance were the number of malaria deaths and Indigenous malaria cases. The RF model demonstrated high accuracy in forecasting risk for the year 2019, achieving commendable accuracy rate of 95.3%. This result aligns well with the observed outcomes, indicating the model's reliability in predicting risk levels. CONCLUSIONS: Machine learning algorithms have reliable application prospects in risk assessment of imported malaria in China. This study provides a new methodological reference for the risk assessment and control strategies adjusting of imported malaria in China.

Analysis of Epidemiological and Issues Encountered in Case Reports on Echinococcosis - China, 2022.

What is already known about this topic?: Echinococcosis is classified as a Class C infectious disease in China. It is endemic in 370 counties located in the agricultural and pastoral regions of western China. What is added by this report?: This report provides a comprehensive overview of the cases of echinococcosis reported in China in 2022. Following a thorough evaluation conducted by provincial CDCs, it was identified that 105 new cases were not reported through the National Notifiable Disease Reporting System. Furthermore, there were 1,051 cases that were reported among patients who had been previously diagnosed with echinococcosis. What are the implications for public health practice?: The reported cases of echinococcosis in non-endemic counties of provincial-level administrative divisions where the disease is endemic need to be given more attention, as there is a potential risk of it spreading within the non-endemic areas. Inadequate reporting practices by clinical medical institutions are hindering the subsequent investigations carried out by CDCs. It is important to implement enhanced health promotion efforts that focus on high-risk populations to address unhealthy lifestyles.

LncRNA SNHG14 activates autophagy via regulating miR-493-5p/Mef2c axis to alleviate osteoporosis progression.

Osteoporosis is a progressive bone disease caused by impaired function of endogenous bone marrow-derived mesenchymal stem cells (BMSCs). Herein, we investigated the mechanism of lncRNA SNHG14 in osteoporosis progression. BMSCs were isolated from BALB/c mice. The osteogenic ability of BMSCs was assessed by Alkaline phosphatase (ALP) and Alizarin Red S Staining (ARS) staining. The interaction between miR-493-5p and SNHG14 or myocyte enhancer factor 2 C (Mef2c) was confirmed by dual-luciferase reporter assay. Bone histomorphometry changes were evaluated to analyze SNHG14'roles in osteoporosis in vivo. Our results illustrated SNHG14 and Mef2c levels were increased in a time-dependent manner in BMSCs, and miR-493-5p expression was decreased. SNHG14 knockdown inhibited osteogenic differentiation of BMSCs, and SNHG14 upregulation had the opposite effect. SNHG14 overexpression elevated bone mineral density and bone trabecular number, and alleviated osteoporosis progression in vivo. Mechanically, miR-493-5p was a target of SNHG14, and miR-493-5p targeted the Mef2c gene directly. SNHG14 overexpression reversed the inhibition of miR-493-5p on the osteogenic ability of BMSCs, and miR-493-5p silencing accelerated BMSCs osteogenesis by activating Mef2c-mediated autophagy to accelerate BMSCs osteogenesis. In short, SNHG14 activated autophagy via regulating miR-493-5p/Mef2c axis to alleviate osteoporosis progression, which might provide a new molecular target for osteoporosis treatment.

Field validation of different intervention modes for the potential transmission risk of schistosomiasis during post-transmission interruption phase.

OBJECTIVE: Precision interventions have been proposed in transmission-interrupted areas to further reduce the potential transmission risk of schistosomiasis. This study aimed to evaluate the effects of different interventions modes for potential transmission risk control. METHODS: Three groups of schistosomiasis-endemic villages were selected in Jiangling county, Hubei province. After baseline surveys in 2020, three intervention models were employed in 2021 and 2022. In Model 1, Oncomelania hupensis snail control in key settings and an integrated strategy with an emphasis on the infectious sources managing was employed. In Model 2, an integrated health education-led strategy with an emphasis on infectious source management was employed. In Model 3, only the integrated strategy with an emphasis on infectious source management was employed. The effects of the different intervention models were examined with multiple indicators after 2 years of intervention using the entropy-weighted technique for order of preference by similarity to ideal solution (TOPSIS), rank-sum ratio (RSR) and fuzzy combination model of entropy-weighted TOPSIS and RSR. RESULTS: Entropy-weighted TOPSIS modeling showed that the Ci values of Model 2 were 0.4434, 0.2759, and 0.3069 in the three pilot villages, Ci values were larger, with top comprehensive ranking. The results of the RSR method showed that the RSR values of Model 2 were 0.75, 0.708, and 0.736 in the three pilot villages, with top comprehensive ranking. The results from the fuzzy combination model of entropy-weighted TOPSIS and RSR showed that implementation of Model 2 resulted in the highest comprehensive ranking among the three models in the three pilot villages under Ci: RSR = 0.1: 0.9, Ci: RSR = 0.5: 0.5 and Ci: RSR = 0.9: 0.1. CONCLUSION: The integrated health education-led strategy with an emphasis on infectious source management was the optimal model to manage the risk of transmission of schistosomiasis during the post-transmission interruption phase.

Tackling global health security by building an academic community for One Health action.

BACKGROUND: One Health approach is crucial to tackling complex global public health threats at the interface of humans, animals, and the environment. As outlined in the One Health Joint Plan of Action, the international One Health community includes stakeholders from different sectors. Supported by the Bill & Melinda Gates Foundation, an academic community for One Health action has been proposed with the aim of promoting the understanding and real-world implementation of One Health approach and contribution towards the Sustainable Development Goals for a healthy planet. MAIN TEXT: The proposed academic community would contribute to generating high-quality scientific evidence, distilling local experiences as well as fostering an interconnected One Health culture and mindset, among various stakeholders on different levels and in all sectors. The major scope of the community covers One Health governance, zoonotic diseases, food security, antimicrobial resistance, and climate change along with the research agenda to be developed. The academic community will be supported by two committees, including a strategic consultancy committee and a scientific steering committee, composed of influential scientists selected from the One Health information database. A workplan containing activities under six objectives is proposed to provide research support, strengthen local capacity, and enhance global participation. CONCLUSIONS: The proposed academic community for One Health action is a crucial step towards enhancing communication, coordination, collaboration, and capacity building for the implementation of One Health. By bringing eminent global experts together, the academic community possesses the potential to generate scientific evidence and provide advice to local governments and international organizations, enabling the pursuit of common goals, collaborative policies, and solutions to misaligned interests.

Spatiotemporal distribution of schistosomiasis transmission risk in Jiangling County, Hubei Province, P.R. China.

OBJECTIVE: This study aims to explore the spatiotemporal distribution of schistosomiasis in Jiangling County, and provide insights into the precise schistosomiasis control. METHODS: The descriptive epidemiological method and Joinpoint regression model were used to analyze the changes in infection rates of humans, livestock, snails, average density of living snails and occurrence rate of frames with snails in Jiangling County from 2005 to 2021. Spatial epidemiology methods were used to detect the spatiotemporal clustering of schistosomiasis transmission risk in Jiangling county. RESULTS: The infection rates in humans, livestock, snails, average density of living snails and occurrence rate of frames with snails in Jiangling County decreased from 2005 to 2021 with statistically significant. The average density of living snails in Jiangling County was spatially clustered in each year, and the Moran's I varied from 0.10 to 0.26. The hot spots were mainly concentrated in some villages of Xionghe Town, Baimasi Town and Shagang Town. The mean center of the distribution of average density of living snails in Jiangling County first moved from northwest to southeast, and then returned from southeast to northwest after 2014. SDE azimuth fluctuated in the range of 111.68°-124.42°. Kernal density analysis showed that the high and medium-high risk areas of Jiangling County from 2005 to 2021 were mainly concentrated in the central and eastern of Jiangling County, and the medium-low and low risk areas were mainly distributed in the periphery of Jiangling County. CONCLUSIONS: The epidemic situation of schistosomiasis decreased significantly in Jiangling County from 2005 to 2021, but the schistosomiasis transmission risk still had spatial clustering in some areas. After transmission interruption, targeted transmission risk intervention strategies can be adopted according to different types of schistosomiasis risk areas.

Effect of Health Education on Schistosomiasis Control Knowledge, Attitude, and Practice after Schistosomiasis Blocking: Results of a Longitudinal Observational Study in the Field.

OBJECTIVES: Schistosomiasis is a zoonotic infectious disease that seriously harms people's physical and mental health. As early as 1985, the WHO suggested that health education and health promotion should be the focus of schistosomiasis prevention work. This study aimed to explore the effect of health education on controlling the risk of schistosomiasis transmission after schistosomiasis blocking and to provide a scientific basis for the further improvement of intervention strategies after schistosomiasis interruption in China and other endemic countries. METHODS: In Jiangling County, Hubei Province, China, one severe, one moderate, and one mildly endemic village were selected as the intervention group; two severe, two moderate, and two mildly endemic villages were selected as the control group. In towns with different epidemic types, a primary school was randomly selected for intervention. In September 2020, a baseline survey was carried out through a questionnaire survey to understand the knowledge, attitudes, and practices (KAP) of adults and students concerning schistosomiasis control. Next, two rounds of health education interventions for schistosomiasis control were carried out. The evaluation survey was conducted in September 2021 and the follow-up survey conducted in September 2022. RESULTS: Compared with the baseline survey, the qualified rate of the KAP on schistosomiasis prevention of the control group in the follow-up survey increased from 79.1% (584/738) to 81.0% (493/609) (p > 0.05); in the intervention group, the qualified rate of the KAP on schistosomiasis control increased from 74.9% (286/382) to 88.1% (260/295) (p < 0.001). In the baseline survey, the qualified rate of the KAP of the intervention group was lower than that of the control group, and in the follow-up survey, the qualified rate of the KAP of the intervention group was 7.2% higher than that of the control group (p < 0.05). Compared with the baseline survey, the accuracy rates of the KAP of the intervention group's adults were higher than those of the control group, with statistical significance (p < 0.001). Compared with the baseline survey, the qualified rate of the students' KAP in the follow-up survey increased from 83.8% (253/302) to 97.8% (304/311) (p < 0.001). In the follow-up survey, the accuracy rate of the knowledge, attitudes, and practices of the students was significantly different from the baseline accuracy (p < 0.001). CONCLUSION: a health education-led risk control model of schistosomiasis can significantly improve schistosomiasis control knowledge among adults and students, establishing correct attitudes and leading to the development of correct hygiene habits.

Long-distance spread of Tembusu virus, and its dispersal in local mosquitoes and domestic poultry in Chongming Island, China.

BACKGROUND: Chongming Island in China serves as a breeding and shelter point on the East Asian-Australasian Flyway. The resting frequency of migratory birds, abundance of mosquito populations, and the popular domestic poultry industry pose a potential risk of mosquito-borne zoonotic diseases. The aim of this study is to explore the role of migratory birds in the spread of mosquito-borne pathogens and their prevalent status on the island. METHODS: We conducted a mosquito-borne pathogen surveillance in 2021, in Chongming, Shanghai, China. Approximately 67,800 adult mosquitoes belonging to ten species were collected to investigate the presence of flaviviruses, alphaviruses, and orthobunyaviruses by RT-PCR. Genetic and phylogenetic analyses were conducted to explore the virus genotype and potential nature source. Serological survey was performed by ELISA to characterize Tembusu virus (TMUV) infection among domestic poultry. RESULTS: Two strains of TMUV and Chaoyang virus (CHAOV) and 47 strains of Quang Binh virus (QBV) were detected in 412 mosquito pools, with the infection rate of 0.16, 0.16, and 3.92 per 1000 Culex tritaeniorhynchus, respectively. Furthermore, TMUVs viral RNA was found in serum samples of domestic chickens and faecal samples of migratory birds. Antibodies against TMUV were detected in domestic avian serum samples, generally ranging from 44.07% in pigeons to 55.71% in ducks. Phylogenetic analyses indicated that the TMUV detected in Chongming belonged to Cluster 3, Southeast Asia origin, and most closely related to the CTLN strain, which caused a TMUV outbreak in chickens in Guangdong Province in 2020, but distant from strains obtained previously in Shanghai, which were involved in the 2010 TMUV outbreak in China. CONCLUSIONS: We speculate that the TMUV was imported to Chongming Island through long-distance spreading by migratory birds from Southeast Asia, followed by spill over and transmission in mosquitoes and domestic avian species, threatening the local domestic poultry. In addition, the expansion and prevalence of insect-specific flaviviruses and its simultaneous circulation with mosquito-borne virus are worthy of close attention and further study.

Assessment of integrated patterns of human-animal-environment health: a holistic and stratified analysis.

BACKGROUND: Data-driven research is a very important component of One Health. As the core part of the global One Health index (GOHI), the global One Health Intrinsic Drivers index (IDI) is a framework for evaluating the baseline conditions of human-animal-environment health. This study aims to assess the global performance in terms of GOH-IDI, compare it across different World Bank regions, and analyze the relationships between GOH-IDI and national economic levels. METHODS: The raw data among 146 countries were collected from authoritative databases and official reports in November 2021. Descriptive statistical analysis, data visualization and manipulation, Shapiro normality test and ridge maps were used to evaluate and identify the spatial and classificatory distribution of GOH-IDI. This paper uses the World Bank regional classification and the World Bank income groups to analyse the relationship between GOH-IDI and regional economic levels, and completes the case studies of representative countries. RESULTS: The performance of One Health Intrinsic Driver in 146 countries was evaluated. The mean (standard deviation, SD) score of GOH-IDI is 54.05 (4.95). The values (mean SD) of different regions are North America (60.44, 2.36), Europe and Central Asia (57.73, 3.29), Middle East and North Africa (57.02, 2.56), East Asia and Pacific (53.87, 5.22), Latin America and the Caribbean (53.75, 2.20), South Asia (52.45, 2.61) and sub-Saharan Africa (48.27, 2.48). Gross national income per capita was moderately correlated with GOH-IDI (R2 = 0.651, Deviance explained = 66.6%, P < 0.005). Low income countries have the best performance in some secondary indicators, including Non-communicable Diseases and Mental Health and Health risks. Five indicators are not statistically different at each economic level, including Animal Epidemic Disease, Animal Biodiversity, Air Quality and Climate Change, Land Resources and Environmental Biodiversity. CONCLUSIONS: The GOH-IDI is a crucial tool to evaluate the situation of One Health. There are inter-regional differences in GOH-IDI significantly at the worldwide level. The best performing region for GOH-IDI was North America and the worst was sub-Saharan Africa. There is a positive correlation between the GOH-IDI and country economic status, with high-income countries performing well in most indicators. GOH-IDI facilitates researchers' understanding of the multidimensional situation in each country and invests more attention in scientific questions that need to be addressed urgently.

Recognizing and monitoring infectious sources of schistosomiasis by developing deep learning models with high-resolution remote sensing images.

BACKGROUND: China is progressing towards the goal of schistosomiasis elimination, but there are still some problems, such as difficult management of infection source and snail control. This study aimed to develop deep learning models with high-resolution remote sensing images for recognizing and monitoring livestock bovine, which is an intermediate source of Schistosoma japonicum infection, and to evaluate the effectiveness of the models for real-world application. METHODS: The dataset of livestock bovine's spatial distribution was collected from the Chinese National Platform for Common Geospatial Information Services. The high-resolution remote sensing images were further divided into training data, test data, and validation data for model development. Two recognition models based on deep learning methods (ENVINet5 and Mask R-CNN) were developed with reference to the training datasets. The performance of the developed models was evaluated by the performance metrics of precision, recall, and F1-score. RESULTS: A total of 50 typical image areas were selected, 1125 bovine objectives were labeled by the ENVINet5 model and 1277 bovine objectives were labeled by the Mask R-CNN model. For the ENVINet5 model, a total of 1598 records of bovine distribution were recognized. The model precision and recall were 81.9% and 80.2%, respectively. The F1 score was 0.81. For the Mask R-CNN mode, 1679 records of bovine objectives were identified. The model precision and recall were 87.3% and 85.2%, respectively. The F1 score was 0.87. When applying the developed models to real-world schistosomiasis-endemic regions, there were 63 bovine objectives in the original image, 53 records were extracted using the ENVINet5 model, and 57 records were extracted using the Mask R-CNN model. The successful recognition ratios were 84.1% and 90.5% for the respectively developed models. CONCLUSION: The ENVINet5 model is very feasible when the bovine distribution is low in structure with few samples. The Mask R-CNN model has a good framework design and runs highly efficiently. The livestock recognition models developed using deep learning methods with high-resolution remote sensing images accurately recognize the spatial distribution of livestock, which could enable precise control of schistosomiasis.

Assessment of performance for a key indicator of One Health: evidence based on One Health index for zoonoses in Sub-Saharan Africa.

BACKGROUND: Zoonoses are public health threats that cause severe damage worldwide. Zoonoses constitute a key indicator of One Health (OH) and the OH approach is being applied for zoonosis control programmes of zoonotic diseases. In a very recent study, we developed an evaluation system for OH performance through the global OH index (GOHI). This study applied the GOHI to evaluate OH performance for zoonoses in sub-Saharan Africa. METHODS: The framework for the OH index on zoonoses (OHIZ) was constructed including five indicators, 15 subindicators and 28 datasets. Publicly available data were referenced to generate the OHIZ database which included both qualitative and quantitative indicators for all sub-Sahara African countries (n = 48). The GOHI algorithm was used to estimate scores for OHIZ. Indicator weights were calculated by adopting the fuzzy analytical hierarchy process. RESULTS: Overall, five indicators associated with weights were generated as follows: source of infection (23.70%), route of transmission (25.31%), targeted population (19.09%), capacity building (16.77%), and outcomes/case studies (15.13%). Following the indicators, a total of 37 sub-Sahara African countries aligned with OHIZ validation, while 11 territories were excluded for unfit or missing data. The OHIZ average score of sub-Saharan Africa was estimated at 53.67/100. The highest score was 71.99 from South Africa, while the lowest score was 40.51 from Benin. It is also worth mentioning that Sub-Sahara African countries had high performance in many subindicators associated with zoonoses, e.g., surveillance and response, vector and reservoir interventions, and natural protected areas, which suggests that this region had a certain capacity in control and prevention or responses to zoonotic events. CONCLUSIONS: This study reveals that it is possible to perform OH evaluation for zoonoses in sub-Saharan Africa by OHIZ. Findings from this study provide preliminary research information in advancing knowledge of the evidenced risks to strengthen strategies for effective control of zoonoses and to support the prevention of zoonotic events.

Fuzheng Huayu Recipe and its active compounds inhibited HBeAg production by promoting TOMM34 gene expression in HBV-infected hepatocytes.

Background and aim: Fuzheng Huayu Recipe (FZHY) is a Chinese patent medicine (approval No. Z20020074) included in the national medical insurance catalogue, which is mainly used for anti-hepatic fibrosis treatment of hepatitis B virus (HBV) induced liver fibrosis and liver cirrhosis. In clinical practice, we discovered that FZHY might also have a direct anti-HBV effect on inhibiting HBeAg production, but the mechanism underlying was unclear. This study aimed to clarify the molecular mechanism of the inhibition effect of FZHY on HBeAg production. Methods: The decrease degree of serum HBeAg titer in FZHY + entecavir (ETV) group patients were analyzed through clinical data. C57BL/6N-Tg (1.28HBV)/Vst HBV transgenic mice were used for in vivo experiments. HepG2. 2.15 cells (wild-type HBV replication cells) were used for in vitro experiments. Results: The clinical study results showed that the decrease degree of serum HBeAg titer in FZHY+ETV group was significantly higher than that in ETV group after 48 weeks treatment. In vivo experiments results showed that FZHY could significantly reduce the serum HBeAg titer in HBV transgenic mice, and promote HBeAg seroconversion. In vitro experiments results showed that FZHY could reduce HBeAg titer dependently, but it did not significantly inhibit the expression of HBsAg and HBV-DNA. Further cell experiments in vitro discovered that TOMM34 might be the key target for FZHY to inhibit HBeAg production. The subsequent pharmacological screening experiment of 20 active compounds in FZHY showed that quercetin, baicalin and cordycepin could promote the expression of TOMM34 gene and reduce the production of HBeAg. Conclusion: In conclusion, FZHY and its active compounds quercetin, baicalin and cordycepin could inhibit HBeAg production by promoting the expression of TOMM34 gene in HBV-infected hepatocytes.

Epidemiology of Mosquito-Borne Viruses in Egypt: A Systematic Review.

There are at least five common mosquito-borne viruses (MBVs) recorded in Egypt, including dengue virus (DENV), Rift Valley fever virus (RVFV), West Nile virus (WNV), Chikungunya virus, and Sindbis virus. Unexpected outbreaks caused by MBVs reflect the deficiencies of the MBV surveillance system in Egypt. This systematic review characterized the epidemiology of MBV prevalence in Egypt. Human, animal, and vector prevalence studies on MBVs in Egypt were retrieved from Web of Science, PubMed, and Bing Scholar, and 33 eligible studies were included for further analyses. The monophyletic characterization of the RVFV and WNV strains found in Egypt, which spans about half a century, suggests that both RVFV and WNV are widely transmitted in this nation. Moreover, the seropositive rates of DENV and WNV in hosts were on the rise in recent years, and spillover events of DENV and WNV to other countries from Egypt have been recorded. The common drawback for surveillance of MBVs in Egypt is the lack of seroprevalence studies on MBVs, especially in this century. It is necessary to evaluate endemic transmission risk, establish an early warning system for MBVs, and develop a sound joint system for medical care and public health for managing MBVs in Egypt.

An Herbal Product Alleviates Bleomycin-Induced Pulmonary Fibrosis in Mice via Regulating NF-κB/TNF-α Signaling in Macrophages.

Background and aim: Pro-inflammatory macrophages aggravated progress of pulmonary fibrosis (PF) both in patients and animal models. Fuzheng Huayu (FZHY) formula, a Chinese herbal product, is effective in treating pulmonary fibrosis in our previous study. But its action mechanism against PF relating to macrophage activation was unclear. This study was designed to evaluate the anti-fibrotic and anti-inflammatory roles of FZHY in pulmonary fibrosis and to elucidate the potential mechanisms. Methods: Network pharmacology was employed to identify the interrelationships among compounds of FZHY, potential targets and putative pathways on anti-pulmonary fibrosis. According to the data of bioinformatics analysis, the key pharmacological target for FZHY against PF was screened. The network pharmacological prediction was validated by a series of experimental assays, including CCK8, western blot and immunofluorescence staining. Then molecular mechanism of FZHY on relating to the predictive target were studied in bleomycin induced pulmonary fibrosis in mice with methylprednisolone as a positive control, and in lipopolysaccharide (LPS) stimulated cultured macrophages in culture, respectively. Results: The network pharmacology analysis reveal that a total of 12 FZHY-PF crossover proteins were filtered into a protein-protein interaction network complex and designated as the potential targets of FZHY against pulmonary fibrosis, while TNF-α signal pathway ranked at the top. FZHY and methylprednisolone could attenuate the lung fibrosis and decrease pulmonary TNF-α expression in bleomycin induced fibrotic mice, without difference between two treatments. While TNF-α was mainly originated from macrophages identified by double fluorescent staining of TNF-α and F4/80. LPS stimulated cultured macrophage polarization and activation demonstrated by the enhance contents of TNF-α and iNOS but decreased level of Arg-1. FZHY could alleviate the LPS stimulated macrophage polarization and activation demonstrated by decreasing TNF-α and iNOS and increasing Arg-1. In particular, FZHY could significantly reduce the production of p65 and the nuclear translocation of phosphorylated p65. Conclusion: Fuzheng Huayu formula has a good effect against pulmonary fibrosis induced by bleomycin in mice, whose action mechanism was associated with down-regulation of NF-κB/TNF-α signaling pathway in pro-inflammatory macrophages. These findings provided an important strategy for developing new agents against lung fibrosis and accelerated FZHY product application on patients with lung fibrosis.

Towards a global One Health index: a potential assessment tool for One Health performance.

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.

Transmission Risks of Mountain-Type Zoonotic Visceral Leishmaniasis - Six Endemic Provincial-Level Administrative Divisions, China, 2015-2020.

What is already known about this topic?: Mountain-type zoonotic visceral leishmaniasis (MT-ZVL) cases in China have increased significantly between 2015 and 2020. A total of 25 regions had re-emerged yielding 88 MT-ZVL indigenous cases, while the total number of visceral leishmaniasis cases declined. What is added by this report?: The transmission risk of MT-ZVL showed a trend of patchy dissemination centered on major endemic areas and medium-high risk occurrence areas of Phlebotomus chinensis with discrete foci. Multi-point re-emergence and local outbreaks of MT-ZVL were trending in historically endemic areas. What are the implications for public health practice?: Risk identification and early warnings of MT-ZVL are essential in formulating precise prevention and control strategies in China. More frequent monitoring, establishing a mechanism of joint prevention and control, and highlighting health education are recommended.

IL-17 in intervertebral disc degeneration: Mechanistic insights and therapeutic implications.

Intervertebral disc degeneration (IDD) serves as an independent risk factor for lower back pain and is closely associated with spinal musculoskeletal disorders, including lumbar disc herniation, radiculopathy, and myelopathy. Interleukin-17 (IL-17), also named IL-17A, is a critical signature cytokine of T-helper 17 cells. Upon binding to the IL-17 receptor A/C heterodimeric complex, IL-17 can trigger multiple signal transduction pathways to stimulate gene transcription and increase messenger RNA stability. IL-17 expression is significantly increased in degenerative disc tissue and shows a positive correlation with disease severity. IL-17 has been shown to accelerate the development of IDD by promoting extracellular matrix degradation, enhancing inflammatory response, inducing neoangiogenesis, and inhibiting nucleus pulposus cell autophagy and proliferation. Targeting IL-17 represents a novel and promising approach for the therapeutic intervention of IDD. In this review, we summarized the recent progression about the role of IL-17 in IDD and highlighted its therapeutic implications.