Unlocking Biological Activity and Metabolomics Insights: Primary Screening of Cyanobacterial Biomass from a Tropical Reservoir.

Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography-mass spectrometry (LC-MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54-0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC-MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;43:2222-2231. © 2024 SETAC.

HPV16 Genomes: In Silico Analysis of E6 and E7 Oncoproteins in 20 South American Variants.

Background: Human papillomavirus (HPV) is the main risk factor for the development of squamous cell cervical cancer, and E6 oncoprotein and E7 oncoprotein are important components of the viral genome and its oncogenic potential. It is known that different viral variants of HPV16 have different pathology and impact on the development of neoplasia, although few studies have been performed on South American variants. Objective: Therefore, the present study aimed to analyze in silico the genomic diversity of HPV16 in 20 complete genome variants of South America in the National Center for Biotechnology Information (NCBI) database. Methods: We performed a descriptive study to characterize the polymorphic regions of the E6 and E7 genes in HPV16 variants, using software for genomic data and single nucleotide polymorphism (SNP) analysis and others for phylogenetic analysis. Results: The variants analyzed included six SNPs linked to cancer (A131G, G145T, C335T, T350G, C712A, and T732C) and significant variation (798 nucleotide substitutions). Despite this, the variants showed low genetic diversity. Eighteen variants of unclear significance (VUS) were identified, 10 of which were in the coding E6 regions and 8 in the coding E7 regions. The prevalence of lineage D variants is of concern due to their pathology in cervical cancer and requires more research and epidemiological vigilance regarding their prevalence in the population. Conclusion: The data obtained in this study may contribute to future research on South American variants of HPV16, their pathogenicity, and the development of treatments.

Identification of differentially expressed genes, pathways, and immune infiltration in diabetes.

This study aimed to perform exhaustive bioinformatic analysis by using GSE29221 micro-array maps obtained from healthy controls and Type 2 Diabetes (T2DM) patients. Raw data are downloaded from the Gene Expression Omnibus database and processed by the limma package in R software to identify Differentially Expressed Genes (DEGs). Gene ontology functional analysis and Kyoto Gene Encyclopedia and Genome Pathway analysis are performed to determine the biological functions and pathways of DEGs. A protein interaction network is constructed using the STRING database and Cytoscape software to identify key genes. Finally, immune infiltration analysis is performed using the Cibersort method. This study has implications for understanding the underlying molecular mechanism of T2DM and provides potential targets for further research.

Characterization of SUSD3 as a novel prognostic biomarker and therapeutic target for breast cancer.

BACKGROUND: Breast cancer (BC) remains a significant global health challenge, contributing substantially to cancer-related deaths worldwide. Its prevalence and associated death rates remain alarmingly high, highlighting the persistent public health burden. The objective of this study was to systematically examine the involvement of SUSD3 (Sushi Domain-Containing 3) in BC, highlighting its crucial role in the pathogenesis and progression of this disease. METHODS: BC-related gene microarray data, along with corresponding clinicopathological information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Leveraging TIMER and HPA databases, we conducted comparative analyses to evaluate SUSD3 expression in BC. We then analyzed the association between SUSD3 and clinical traits, as well as the prognostic value of SUSD3. SUSD3-related differential expression genes (DEGs) were sent for analysis utilizing GO, KEGG, and GSEA. We utilized SUSD3 mRNA expression to assess immune cells' scores in BC tissues calculated by single-sample enrichment analyses based on "CIBERSORT" R package. Drug sensitivity analysis was used to screen potential drugs sensitive to SUSD3. R software was used for statistical analyses and graphical representation of the data. RESULTS: Our findings confirmed a significant upregulation of SUSD3 expression in BC, which correlated with a favorable prognosis. Clinical correlation analysis further emphasized the strong association between SUSD3 expression and key clinical parameters like estrogen receptor (ER) status, progesterone receptor (PR) status, stage, and T classification in breast cancer. Univariate and multivariate Cox regression analyses showed that SUSD3 could be used as an independent prognostic factor for BC. Differentially expressed genes (DEGs) co-expressed with SUSD3 were significantly associated with various biological processes, such as the cell cycle, DNA replication, p53 signaling pathway, cancer-related pathways, and Wnt signaling pathway, as indicated by gene set enrichment analysis (GSEA). Furthermore, our analysis demonstrated that SUSD3 generally exhibited negative associations with immune modulators. Drug sensitivity analysis revealed positive correlations between SUSD3 and the efficacy of Fulvestrant, Raloxifene, and Fluphenazine. CONCLUSION: The research emphasizes the significance of SUSD3 as a potential marker for BC, providing insights into the underlying molecular mechanisms implicated in tumorigenesis. SUSD3 holds promise in helping the classification of breast cancer pathological groups, predicting prognosis, and facilitating targeted therapy.

In silico analysis of Ffp1, an ancestral Porphyromonas spp. fimbrillin, shows differences with Fim and Mfa.

Background. Scant information is available regarding fimbrillins within the genus Porphyromonas, with the notable exception of those belonging to Porphyromonas gingivalis, which have been extensively researched for several years. Besides fim and mfa, a third P. gingivalis adhesin called filament-forming protein 1 (Ffp1) has recently been described and seems to be pivotal for outer membrane vesicle (OMV) production. Objective. We aimed to investigate the distribution and diversity of type V fimbrillin, particularly Ffp1, in the genus Porphyromonas. Methods. A bioinformatics phylogenomic analysis was conducted using all accessible Porphyromonas genomes to generate a domain search for fimbriae, using hidden Markov model profiles. Results. Ffp1 was identified as the sole fimbrillin present in all analysed genomes. After manual verification (i.e. biocuration) of both structural and functional annotations and 3D modelling, this protein was determined to be a type V fimbrillin, with a closer structural resemblance to a Bacteroides ovatus fimbrillin than to FimA or Mfa1 from P. gingivalis. Conclusion. It appears that Ffp1 is an ancestral fimbria, transmitted through vertical inheritance and present across all Porphyromonas species. Additional investigations are necessary to elucidate the biogenesis of Ffp1 fimbriae and their potential role in OMV production and niche adaptation.

On the PhyloQuant protein expression profiles approach to the taxonomic problem.

Inferring evolutionary relationships among organisms has been a fundamental problem in evolutionary biology. The current phylogenetic molecular methods serve as the baseline model to test new evolutionary hypotheses with taxonomic purposes. Leishmaniinae trypanosomatids subfamily includes protozoan parasites of clinical importance to humans. They have an intricate taxonomic history defined by morphological elements, host range, and molecular phylogenies. Unraveling the increasing diversity of this group has shown limitations in reconstructing the true evolutionary relationships among Trypanosomatidae species. Toward the goal of inferring evolutionary relationships that help to resolve phylogenetic and taxonomic controversies among parasites of the subfamily Leishmaniinae, Mule et al. propose the method PhyloQuant as a valuable approach, based on differential protein expression obtained from high throughput mass spectrometry data. Employing a pioneering methodological approach, Mule et al. assess the taxonomic problem for species hypothesis within Leishmaniinae, from quantitative phenetic protein expression profiles, in contrast to the standard multilocus phylogenetic approaches.

Exploring the osteogenic potential of semisynthetic triterpenes from Combretum leprosum: An in vitro and in silico study.

Combretum leprosum Mart. is a plant of the Combretaceae family, widely distributed in the Northeast region of Brazil, popularly used as an anti-inflammatory agent, and rich in triterpenes. This study evaluated in vitro and in silico potential osteogenic of two semisynthetic triterpenes (CL-P2 and CL-P2A) obtained from the pentacyclic triterpene 3ß,6ß,16ß-trihydroxylup-20(29)-ene (CL-1) isolated from C. leprosum. Assays were carried out in cultured murine osteoblasts (OFCOL II), first investigating the possible toxicity of the compounds on these cells through viability assays (MTT). Cell proliferation and activation were investigated by immunohistochemical evaluation of Ki-67, bone alkaline phosphatase (ALP) activity, and mineralization test by Von Kossa. Molecular docking analysis was performed to predict the binding affinity of CL-P2 and CL-P2A to target proteins involved in the regulation of osteogenesis, including: bone morphogenetic protein 2 (BMP-2), proteins related to Wingless-related integration (WNT) pathway (Low-density lipoprotein receptor-related protein 6-LRP6 and sclerostin-SOST), and receptor activator of nuclear factor (NF)-kB-ligand (RANK-L). Next, Western Blot and immunofluorescence investigated BMP-2, WNT, RANK-L, and OPG protein expressions in cultured murine osteoblasts (OFCOL II). None of the CL-P2 and CL-P2A concentrations were toxic to osteoblasts. Increased cell proliferation, ALP activity, and bone mineralization were observed. Molecular docking assays demonstrated interactions with BMP-2, LRP6, SOST, and RANK-L/OPG. There was observed increased expression of BMP-2, WNT, and RANK-L/OPG proteins. These results suggest, for the first time, the osteogenic potential of CL-P2 and CL-P2A.

Transcriptome and microbiome-immune changes across preinvasive and invasive anal cancer lesions.

Anal squamous cell carcinoma (ASCC) is a rare gastrointestinal malignancy linked to high-risk human papillomavirus (HPV) infection, which develops from precursor lesions like low-grade squamous intraepithelial lesions and high-grade squamous intraepithelial lesions (HGSILs). ASCC incidence varies across populations and poses increased risk for people living with HIV. Our investigation focused on transcriptomic and metatranscriptomic changes from squamous intraepithelial lesions to ASCC. Metatranscriptomic analysis highlighted specific bacterial species (e.g., Fusobacterium nucleatum, Bacteroides fragilis) more prevalent in ASCC than precancerous lesions. These species correlated with gene-encoding enzymes (Acca, glyQ, eno, pgk, por) and oncoproteins (FadA, dnaK), presenting potential diagnostic or treatment markers. Unsupervised transcriptomic analysis identified distinct sample clusters reflecting histological diagnosis, immune infiltrate, HIV/HPV status, and pathway activities, recapitulating anal cancer progression's natural history. Our study unveiled molecular mechanisms in anal cancer progression, aiding in stratifying HGSIL cases based on low or high risk of progression to malignancy.

Long Non-Coding RNAs Differentially Expressed in Swine Fetuses.

Long non-coding RNAs (lncRNAs) are non-coding transcripts involved in various biological processes. The Y chromosome is known for determining the male sex in mammals. LncRNAs on the Y chromosome may play important regulatory roles. However, knowledge about their action mechanisms is still limited, especially during early fetal development. Therefore, we conducted this exploratory study aiming to identify, characterize, and investigate the differential expression of lncRNAs between male and female swine fetuses at 35 days of gestation. RNA-Seq libraries from 10 fetuses were prepared and sequenced using the Illumina platform. After sequencing, a data quality control was performed using Trimmomatic, alignment with HISAT2, and transcript assembly with StringTie. The differentially expressed lncRNAs were identified using the limma package of the R software (4.3.1). A total of 871 potentially novel lncRNAs were identified and characterized. Considering differential expression, eight lncRNAs were upregulated in male fetuses. One was mapped onto SSC12 and seven were located on the Y chromosome; among them, one lncRNA is potentially novel. These lncRNAs are involved in diverse functions, including the regulation of gene expression and the modulation of chromosomal structure. These discoveries enable future studies on lncRNAs in the fetal stage in pigs.

Protein C Pretreatment Protects Endothelial Cells from SARS-CoV-2-Induced Activation.

SARS-CoV-2 can induce vascular dysfunction and thrombotic events in patients with severe COVID-19; however, the cellular and molecular mechanisms behind these effects remain largely unknown. In this study, we used a combination of experimental and in silico approaches to investigate the role of PC in vascular and thrombotic events in COVID-19. Single-cell RNA-sequencing data from patients with COVID-19 and healthy subjects were obtained from the publicly available Gene Expression Omnibus (GEO) repository. In addition, HUVECs were treated with inactive protein C before exposure to SARS-CoV-2 infection or a severe COVID-19 serum. An RT-qPCR array containing 84 related genes was used, and the candidate genes obtained were evaluated. Activated protein C levels were measured using an ELISA kit. We identified at the single-cell level the expression of several pro-inflammatory and pro-coagulation genes in endothelial cells from the patients with COVID-19. Furthermore, we demonstrated that exposure to SARS-CoV-2 promoted transcriptional changes in HUVECs that were partly reversed by the activated protein C pretreatment. We also observed that the serum of severe COVID-19 had a significant amount of activated protein C that could protect endothelial cells from serum-induced activation. In conclusion, activated protein C protects endothelial cells from pro-inflammatory and pro-coagulant effects during exposure to the SARS-CoV-2 virus.

BioPipeline Creator-a user-friendly Java-based GUI for managing and customizing biological data pipelines.

Bioinformatics tools are essential for performing analyses in the omics sciences. Given the numerous experimental opportunities arising from advances in the field of omics and easier access to high-throughput sequencing platforms, these tools play a fundamental role in research projects. Despite the considerable progress made possible by the development of bioinformatics tools, some tools are tailored to specific analytical goals, leading to challenges for non-bioinformaticians who need to integrate the results of these specific tools into a customized pipeline. To solve this problem, we have developed the BioPipeline Creator, a user-friendly Java-based GUI that allows different software tools to be integrated into the repertoire while ensuring easy user interaction via an accessible graphical interface. Consisting of client and server software components, BioPipeline Creator provides an intuitive graphical interface that simplifies the use of various bioinformatics tools for users without advanced computer skills. It can run on less sophisticated devices or workstations, allowing users to keep their operating system without having to switch to another compatible system. The server is responsible for the processing tasks and can perform the analysis in the user's local or remote network structure. Compatible with the most important operating systems, available at https://github.com/allanverasce/bpc.git .

A Bioinformatic Assay of Quercetin in Gastric Cancer.

Gastric cancer (GC) remains a significant global health challenge, with high mortality rates, especially in developing countries. Current treatments are invasive and have considerable risks, necessitating the exploration of safer alternatives. Quercetin (QRC), a flavonoid present in various plants and foods, has demonstrated multiple health benefits, including anticancer properties. This study investigated the therapeutic potential of QRC in the treatment of GC. We utilized advanced molecular techniques to assess the impact of QRC on GC cells, examining its effects on cellular pathways and gene expression. Our findings indicate that QRC significantly inhibits GC cell proliferation and induces apoptosis, suggesting its potential as a safer therapeutic option for GC treatment. Further research is required to validate these results and explore the clinical applications of QRC in cancer therapy.

An overview of key online resources for human genomics: a powerful and open toolbox for in silico research.

Recent advances in high-throughput molecular methods have led to an extraordinary volume of genomics data. Simultaneously, the progress in the computational implementation of novel algorithms has facilitated the creation of hundreds of freely available online tools for their advanced analyses. However, a general overview of the most commonly used tools for the in silico analysis of genomics data is still missing. In the current article, we present an overview of commonly used online resources for genomics research, including over 50 tools. This selection will be helpful for scientists with basic or intermediate skills in the in silico analyses of genomics data, such as researchers and students from wet labs seeking to strengthen their computational competencies. In addition, we discuss current needs and future perspectives within this field.

The mobilome landscape of biocide-resistance in Brazilian ESKAPE isolates.

The increasing frequency of antibiotic-resistant bacteria is a constant threat to global human health. Therefore, the pathogens of the ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, and Enterobacter spp.) are among the most relevant causes of hospital infections responsible for millions of deaths every year. However, little has been explored about the danger of microorganisms resistant to biocides such as antiseptics and disinfectants. Widely used in domestic, industrial, and hospital environments, these substances reach the environment and can cause selective pressure for resistance genes and induce cross-resistance to antibiotics, further aggravating the problem. Therefore, it is necessary to use innovative and efficient strategies to monitor the spread of genes related to resistance to biocides. Whole genome sequencing and bioinformatics analysis aiming to search for sequences encoding resistance mechanisms are essential to help monitor and combat these pathogens. Thus, this work describes the construction of a bioinformatics tool that integrates different databases to identify gene sequences that may confer some resistance advantage about biocides. Furthermore, the tool analyzed all the genomes of Brazilian ESKAPE isolates deposited at NCBI and found a series of different genes related to resistance to benzalkonium chloride, chlorhexidine, and triclosan, which were the focus of this work. As a result, the presence of resistance genes was identified in different types of biological samples, environments, and hosts. Regarding mobile genetic elements (MGEs), around 52% of isolates containing genes related to resistance to these compounds had their genes identified in plasmids, and 48.7% in prophages. These data show that resistance to biocides can be a silent, underestimated danger spreading across different environments and, therefore, requires greater attention.

How does the age of control individuals hinder the identification of target genes for Huntington's disease?

Several studies have compared the transcriptome across various brain regions in Huntington's disease (HD) gene-positive and neurologically normal individuals to identify potential differentially expressed genes (DEGs) that could be pharmaceutical or prognostic targets for HD. Despite adhering to technical recommendations for optimal RNA-Seq analysis, none of the genes identified as upregulated in these studies have yet demonstrated success as prognostic or therapeutic targets for HD. Earlier studies included samples from neurologically normal individuals older than the HD gene-positive group. Considering the gradual transcriptional changes induced by aging in the brain, we posited that utilizing samples from older controls could result in the misidentification of DEGs. To validate our hypothesis, we reanalyzed 146 samples from this study, accessible on the SRA database, and employed Propensity Score Matching (PSM) to create a "virtual" control group with a statistically comparable age distribution to the HD gene-positive group. Our study underscores the adverse impact of using neurologically normal individuals over 75 as controls in gene differential expression analysis, resulting in false positives and negatives. We conclusively demonstrate that using such old controls leads to the misidentification of DEGs, detrimentally affecting the discovery of potential pharmaceutical and prognostic markers. This underscores the pivotal role of considering the age of control samples in RNA-Seq analysis and emphasizes its inclusion in evaluating best practices for such investigations. Although our primary focus is HD, our findings suggest that judiciously selecting age-appropriate control samples can significantly improve best practices in differential expression analysis.

Prognosis recovery score of apical surgery Guided Bone Regeneration using cone beam computed tomography and digital bioinformatics.

Objective: Guided Bone Regeneration (GBR) is a dental surgical procedure that uses barrier membranes to prevent soft tissue invasion and conduct new bone growth. This study aimed to define a Prognosis Recovery score (PR score) to objectively classify post-surgery responders from non-responder patients who underwent GBR using Cone Beam Computed Tomography (CBCT). Methods: This prospective-observational-longitudinal-cohort study recruited 250 individuals who were assigned to: Conventional-Apical-Surgery (CAS, n = 39), Apical-Surgery using human fascia lata Membrane placement (ASM, n = 42), and Apical-Surgery using human fascia lata Membrane placement and lyophilized allograft Bone powder (ASMB, n = 39); and Apical-Surgery using collagen membrane Porcine origin and Bovine Bone-matrix (ASPBB, n = 130), an independent external validation cohort. Surgery was performed, and evolution was monitored by CBCTs at 0, 6-, 12-, 18-, and 24 months post-surgery. Results: Normalized lesion volumes were calculated, and non-linear time evolution morphology curves were characterized. The three-time evolution bone growth patterns were: a linear tendency (PR0), "S'' shaped log-logistic (PR1), and "C" cellular growth (PR2). The treatment success rates were PR2-46 %, PR2-88 %, and PR2-95 %/PR1-5% for CAS, ASM, and ASMB groups. The xenograft ASPBB counterpart achieved PR2-92 % and PR1-8%. The score PR had a sensitivity, specificity, and accuracy of 100 %. Conclusions: Patients' treatment success can be quantitatively, objectively, and precisely predicted with the Prognosis Recovery score (using only two CBCTs), according to their biological response to allograft or xenograft materials (time-evolution bone growth curves), reducing cost and radiation exposure. Clinical significance: Through digital imaging and bioinformatic analysis of bone regeneration observed in CBCTs, we defined a Prognosis Recovery (PR) score using only two CBCT volume assessments (0 and 6 months). The PR score allowed us to define three time-evolution curves depending on the biomaterials used and to classify patients in a quantitative, objective, and accurate way.

Genome-wide identification of the GDSL-type esterase/lipase protein (GELP) gene family in Ricinus communis and its transcriptional regulation during germination and seedling establishment under different abiotic stresses.

GDSL-type esterase/lipase protein (GELP) genes are crucial in the specialized lipid metabolism, in the responses to abiotic stresses, and in the regulation of plant homeostasis. R. communis is an important oilseed crop species that can sustain growth and productivity when exposed to harsh environmental conditions. Herein, we raised the question of whether the GELP gene family could be involved in the acquisition of R. communis tolerance to abiotic stresses during seed germination and seedling establishment. Thus, we used bioinformatics and transcriptomics to characterize the R. communis GELP gene family. R. communis genome possesses 96 GELP genes that were characterized by extensive bioinformatics, including phylogenetic analysis, subcellular localization, exon-intron distribution, the analysis of regulatory cis-elements, tandem duplication, and physicochemical properties. Transcriptomics indicated that numerous RcGELP genes are readily responsive to high-temperature and salt stresses and might be potential candidates for genome editing techniques to develop abiotic stress-tolerant crops.

Aloe vera: capacidad antioxidante y uso potencial como agente terapéutico en el tratamiento del Alzheimer mediante evaluación in silico / Aloe vera: antioxidant capacity and potential use as therapeutic agent in the treatment of Alzheimer's through in silico evaluation

Resumen: El gel de Aloe vera es considerado una fuente natural de múltiples beneficios, originados por la acción combinada de vitaminas, aminoácidos, compuestos fenólicos, enzimas, minerales, ácidos orgánicos, lípidos y carbohidratos, que se relacionan con la mejora de enfermedades neuro-degenerativas como Alzheimer. Los ensayos in vitro e in silico permiten confirmar e identificar posibles beneficios de esta planta y sus compuestos en enfermedades. El objetivo del presente trabajo fue evaluar la actividad antioxidante del gel de A. vera y mediante análisis in silico, establecer el potencial terapéutico de sus compuestos bioactivos en la enfermedad de Alzheimer. Se obtuvieron hojas de A. vera, de las que se extrajo el gel, retirando el exocarpio, se liofilizó y almacenó hasta su uso. Se caracterizó la capacidad antioxidante, se cuantificaron los compuestos fenólicos y flavonoides y se analizó la relación que existe entre los parámetros mediante correlación de Pearson. Mediante análisis in silico se evaluó el potencial de interacción de 8 compuestos del gel con la proteína gamma secretasa. El gel de A. vera obtuvo alta capacidad antioxidante por ABTS, DPPH, radical OH y poder reductor, usando bajas concentraciones para inhibir el 50 % de los radicales, y correlaciones positivas con fenoles totales y flavonoides. En el estudio in silico el compuesto que presentó mejor unión con gamma secretasa fue aloe-emodina, con menor energía libre de unión y menor concentración de constante de inhibición, sugiriendo su potencial uso como coadyuvante en el tratamiento de la enfermedad de Alzheimer.

Abstract: Aloe vera gel is considered a natural source of multiple benefits, originated by the combined action of vitamins, amino acids, phenolic compounds, enzymes, minerals, organic acids, lipids and carbohydrates, which are related to the improvement of neuro-degenerative diseases such as Alzheimer's. In vitro and in silico tests allow us to confirm and identify possible benefits of this plant and its compounds in diseases. The objective of the present study was to evaluate the antioxidant activity of A. vera gel and, through in silico analysis, to establish the therapeutic potential of its bioactive compounds in Alzheimer's disease. A. vera leaves were obtained, from which the gel was extracted, removing the exocarp, lyophilized and stored until use. The antioxidant capacity was characterized, the phenolic compounds and flavonoids were quantified, and the relationship between the parameters was analyzed using Pearson correlation. The interaction potential of 8 compounds in the gel with the gamma secretase protein was evaluated through in silico analysis. The A. vera gel obtained high antioxidant capacity due to ABTS, DPPH, OH radical and reducing power, using low concentrations to inhibit 50 % of the radicals, and positive correlations with total phenols and flavonoids. In the in silico study, the compound that showed the best binding with gamma secretase was aloe-emodin, with lower binding free energy and lower inhibition constant concentration, suggesting its potential use as an adjuvant in the treatment of Alzheimer's disease.

Drug to genome to drug: a computational large-scale chemogenomics screening for novel drug candidates against sporotrichosis.

Sporotrichosis is recognized as the predominant subcutaneous mycosis in South America, attributed to pathogenic species within the Sporothrix genus. Notably, in Brazil, Sporothrix brasiliensis emerges as the principal species, exhibiting significant sapronotic, zoonotic and enzootic epidemic potential. Consequently, the discovery of novel therapeutic agents for the treatment of sporotrichosis is imperative. The present study is dedicated to the repositioning of pharmaceuticals for sporotrichosis therapy. To achieve this goal, we designed a pipeline with the following steps: (a) compilation and preparation of Sporothrix genome data; (b) identification of orthologous proteins among the species; (c) identification of homologous proteins in publicly available drug-target databases; (d) selection of Sporothrix essential targets using validated genes from Saccharomyces cerevisiae; (e) molecular modeling studies; and (f) experimental validation of selected candidates. Based on this approach, we were able to prioritize eight drugs for in vitro experimental validation. Among the evaluated compounds, everolimus and bifonazole demonstrated minimum inhibitory concentration (MIC) values of 0.5 µg/mL and 4.0 µg/mL, respectively. Subsequently, molecular docking studies suggest that bifonazole and everolimus may target specific proteins within S. brasiliensis- namely, sterol 14-α-demethylase and serine/threonine-protein kinase TOR, respectively. These findings shed light on the potential binding affinities and binding modes of bifonazole and everolimus with their probable targets, providing a preliminary understanding of the antifungal mechanism of action of these compounds. In conclusion, our research advances the understanding of the therapeutic potential of bifonazole and everolimus, supporting their further investigation as antifungal agents for sporotrichosis in prospective hit-to-lead and preclinical investigations.

Pregnant Women with Multiple Sclerosis: An Overview of Gene Expression and Molecular Interaction Using Bioinformatics Analysis.

Multiple sclerosis (MS) is a common disease in young women of reproductive age, characterized by demyelination of the central nervous system (CNS). Understanding how genes related to MS are expressed during pregnancy can provide insights into the potential mechanisms by which pregnancy affects the course of this disease. This review article presents evidence-based studies on these patients' gene expression patterns. In addition, it constructs interaction networks using bioinformatics tools, such as STRING and KEGG pathways, to understand the molecular role of each of these genes. Bioinformatics research identified 25 genes and 21 signaling pathways, which allows us to understand pregnancy patients' genetic and biological phenomena and formulate new questions about MS during pregnancy.