Assessment of the hypoglycemic and anti-hemostasis effects of Paederia foetida (L.) in controlling diabetes and thrombophilia combining in vivo and computational analysis.

Paederia foetida is valued for its folk medicinal properties. This research aimed to assess the acute toxicity, hypoglycemic and anti-hemostasis properties of the methanolic extract of P. foetida leaves (PFLE). Acute toxicity of PFLE was performed on a mice model. Hypoglycemic and anti-hemostasis properties of PFLE were investigated on normal and streptozotocin-induced mice models. Deep learning, molecular docking, density functional theory, and molecular simulation techniques were employed to understand the underlying mechanisms through in silico study. Oral administration of PFLE at a dosage of 300 µg/kg body weight (BW) showed no signs of toxicity. Treatment with PFLE (300 µg/kg/BW) for 14 days resulted in a hypoglycemic condition and a 30.47% increase in body weight. Additionally, PFLE mixed with blood exhibited a 44.6% anti-hemostasis effect. Deep learning predicted the inhibitory concentration (pIC50, nM) of Cleomiscosins against SGLT2 and FXa to be 7.478 and 6.017, respectively. Molecular docking analysis revealed strong binding interactions of Cleomiscosins with crucial residues of the target proteins, exhibiting binding energies of -8.2 kcal/mol and -7.1 kcal/mol, respectively. ADME/Tox predictions indicated favorable pharmacokinetic properties of Cleomiscosins, and DFT calculations of frontier molecular orbitals analyzed the stability and reactivity of these compounds. Molecular simulation dynamics, principal component analysis and MM-PBSA calculation demonstrated the stable, compact, and rigid nature of the protein-ligand complexes. The methanolic PFLE exhibited significant hypoglycemic and anti-hemostasis properties. Cleomiscosin may have inhibitory properties for the development of novel drugs to manage diabetes and thrombophilia in the near future.

Development and Comparison of Dengue Vulnerability Indices Using GIS-Based Multi-Criteria Decision Analysis in Lao PDR and Thailand.

Dengue is a continuous health burden in Laos and Thailand. We assessed and mapped dengue vulnerability in selected provinces of Laos and Thailand using multi-criteria decision approaches. An ecohealth framework was used to develop dengue vulnerability indices (DVIs) that explain links between population, social and physical environments, and health to identify exposure, susceptibility, and adaptive capacity indicators. Three DVIs were constructed using two objective approaches, Shannon's Entropy (SE) and the Water-Associated Disease Index (WADI), and one subjective approach, the Best-Worst Method (BWM). Each DVI was validated by correlating the index score with dengue incidence for each spatial unit (district and subdistrict) over time. A Pearson's correlation coefficient (r) larger than 0.5 and a p-value less than 0.05 implied a good spatial and temporal performance. Spatially, DVIWADI was significantly correlated on average in 19% (4-40%) of districts in Laos (mean r = 0.5) and 27% (15-53%) of subdistricts in Thailand (mean r = 0.85). The DVISE was validated in 22% (12-40%) of districts in Laos and in 13% (3-38%) of subdistricts in Thailand. The DVIBWM was only developed for Laos because of lack of data in Thailand and was significantly associated with dengue incidence on average in 14% (0-28%) of Lao districts. The DVIWADI indicated high vulnerability in urban centers and in areas with plantations and forests. In 2019, high DVIWADI values were observed in sparsely populated areas due to elevated exposure, possibly from changes in climate and land cover, including urbanization, plantations, and dam construction. Of the three indices, DVIWADI was the most suitable vulnerability index for the study area. The DVIWADI can also be applied to other water-associated diseases, such as Zika and chikungunya, to highlight priority areas for further investigation and as a tool for prevention and interventions.

The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned?

OBJECTIVES: To provide an overview of the three major deadly coronaviruses and identify areas for improvement of future preparedness plans, as well as provide a critical assessment of the risk factors and actionable items for stopping their spread, utilizing lessons learned from the first two deadly coronavirus outbreaks, as well as initial reports from the current novel coronavirus (COVID-19) epidemic in Wuhan, China. METHODS: Utilizing the Centers for Disease Control and Prevention (CDC, USA) website, and a comprehensive review of PubMed literature, we obtained information regarding clinical signs and symptoms, treatment and diagnosis, transmission methods, protection methods and risk factors for Middle East respiratory syndrome (MERS), severe acute respiratory syndrome (SARS) and COVID-19. Comparisons between the viruses were made. RESULTS: Inadequate risk assessment regarding the urgency of the situation, and limited reporting on the virus within China has, in part, led to the rapid spread of COVID-19 throughout mainland China and into proximal and distant countries. Compared with SARS and MERS, COVID-19 has spread more rapidly, due in part to increased globalization and the focus of the epidemic. Wuhan, China is a large hub connecting the North, South, East and West of China via railways and a major international airport. The availability of connecting flights, the timing of the outbreak during the Chinese (Lunar) New Year, and the massive rail transit hub located in Wuhan has enabled the virus to perforate throughout China, and eventually, globally. CONCLUSIONS: We conclude that we did not learn from the two prior epidemics of coronavirus and were ill-prepared to deal with the challenges the COVID-19 epidemic has posed. Future research should attempt to address the uses and implications of internet of things (IoT) technologies for mapping the spread of infection.