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Alzheimer's disease (AD), a prevalent neurodegenerative disorder, presents significant challenges in drug development due to its multifactorial nature and complex pathophysiology. The AlzyFinder Platform, introduced in this study, addresses these challenges by providing a comprehensive, free web-based tool for parallel ligand-based virtual screening and network pharmacology, specifically targeting over 85 key proteins implicated in AD. This innovative approach is designed to enhance the identification and analysis of potential multitarget ligands, thereby accelerating the development of effective therapeutic strategies against AD. AlzyFinder Platform incorporates machine learning models to facilitate the ligand-based virtual screening process. These models, built with the XGBoost algorithm and optimized through Optuna, were meticulously trained and validated using robust methodologies to ensure high predictive accuracy. Validation included extensive testing with active, inactive, and decoy molecules, demonstrating the platform's efficacy in distinguishing active compounds. The models are evaluated based on balanced accuracy, precision, and F1 score metrics. A unique soft-voting ensemble approach is utilized to refine the classification process, integrating the strengths of individual models. This methodological framework enables a comprehensive analysis of interaction data, which is presented in multiple formats such as tables, heat maps, and interactive Ligand-Protein Interaction networks, thus enhancing the visualization and analysis of drug-protein interactions. AlzyFinder was applied to screen five molecules recently reported (and not used to train or validate the ML models) as active compounds against five key AD targets. The platform demonstrated its efficacy by accurately predicting all five molecules as true positives with a probability greater than 0.70. This result underscores the platform's capability in identifying potential therapeutic compounds with high precision. In conclusion, AlzyFinder's innovative approach extends beyond traditional virtual screening by incorporating network pharmacology analysis, thus providing insights into the systemic actions of drug candidates. This feature allows for the exploration of ligand-protein and protein-protein interactions and their extensions, offering a comprehensive view of potential therapeutic impacts. As the first open-access platform of its kind, AlzyFinder stands as a valuable resource for the AD research community, available at http://www.alzyfinder-platform.udec.cl with supporting data and scripts accessible via GitHub https://github.com/ramirezlab/AlzyFinder.

Background: Ticks are obligate hematophagous ectoparasites involved in transmitting viruses of public health importance. The objective of this work was to identify the Jingmen tick virus in hard ticks from the Colombian Caribbean, an arbovirus of importance for public health., Methods: Ticks were collected in rural areas of Córdoba and Cesar, Colombia. Taxonomic identification of ticks was carried out, and pools of 13 individuals were formed. RNA extraction was performed. Library preparation was performed with the MGIEasy kit, and next-generation sequencing (NGS) with MGI equipment. Bioinformatic analyses and taxonomic assignments were performed using the Galaxy platform, and phylogenetic analyses were done using IQ-TREE2., Results: A total of 766 ticks were collected, of which 87.33% (669/766) were Rhipicephalus microplus, 5.4% (42/766) Dermacentor nitens, 4.2% (32/766) Rhipicephalus linnaei, and 3.0% (23/766) Amblyomma dissimile. Complete and partial segments 1, 2, 3, and 4 of Jingmen tick virus (JMTV) were detected in the metatranscriptome of the species R. microplus, D. nitens, and A. dissimile. The JMTVs detected are phylogenetically related to JMTVs detected in Aedes albopictus in France, JMTVs detected in R. microplus in Trinidad and Tobago, JMTVs in R. microplus and A. variegatum in the French Antilles, and JMTVs detected in R. microplus in Colombia. Interestingly, our sequences clustered closely with JMTV detected in humans from Kosovo., Conclusions: JMTV was detected in R. microplus, D. nitens, and A. dissimile. JMTV could pose a risk to humans. Therefore, it is vital to establish epidemiological surveillance measures to better understand the possible role of JMTV in tropical diseases., (© 2024. The Author(s).)

Chikungunya fever, an acute and often chronic arthralgic disease caused by the mosquito-borne alphavirus, chikungunya virus (CHIKV), spread into the Americas in late 2013. Since then it has caused epidemics in nearly all New World countries, the second largest being Colombia with over 450,000 suspected cases beginning in September, 2014, and focused in Bolivar Department in the north. We examined 32 human sera from suspected cases, including diverse age groups and both genders, and sequenced the CHIKV envelope glycoprotein genes, known determinants of vector host range. As expected for Asian lineage CHIKV strains, these isolates lacked known Aedes albopictus-adaptive mutations. All the Colombian strains were closely related to those from the Virgin Islands, Saint Lucia, Mexico, Puerto Rico, and Brazil, consistent with a single, point-source introduction from the southeast Asia/Pacific region. Two substitutions in the E2 and E1 envelope glycoprotein genes were found in the Colombian strains, especially E1-K211E involving a residue shown previously to affect epistatically the penetrance of the E1-A226V A. albopictus-adaptive substitution. We also identified two amino acid substitutions unique to all American CHIKV sequences: E2-V368A and 6K-L20M. Only one codon, 6K-47, had a high nonsynonymous substitution rate suggesting positive selection., (© The American Society of Tropical Medicine and Hygiene.)

The presence of sand flies naturally infected with trypanosomatid parasites was determined in Los Montes de Maria, Colombia, a region considered endemic for visceral and cutaneous leishmaniasis. Phlebotomines were collected using CDC light-traps, and sticky traps soaked with castor oil placed in the peri and intradomestic habitats. Six species of Lutzomyia were morphologically identified among the 159 sand flies captured: Lu. evansi, Lu. cayennensis cayennensis, Lu. trinidadensis, Lu. atroclavata, Lu. gomezi and Lu. dubitans. A DNA band of 800 pb corresponding to the small-subunit ribosomal RNA gene (ssrRNA) of the family Trypanosomatidae was amplified in one pool of nine females of Lu. cayennensis cayennensis. This finding constitutes the first evidence of natural infection of this sand fly species with trypanosomatid parasites in Los Montes de Maria.