Suppression of HIV-TAT and cocaine-induced neurotoxicity and inflammation by cell penetrable itaconate esters.

HIV-associated neurological disorder (HAND) is a serious complication of HIV infection marked by neurotoxicity induced by viral proteins like Tat. Substance abuse exacerbates neurocognitive impairment in people living with HIV. There is an urgent need for therapeutic strategies to combat HAND comorbid with Cocaine Use Disorder (CUD). Our analysis of HIV and cocaine-induced transcriptomes in primary cortical cultures revealed significant overexpression of the macrophage-specific gene aconitate decarboxylase 1 (Acod1). The ACOD1 protein converts the tricarboxylic acid intermediate cis-aconitate into itaconate during the activation of inflammation. Itaconate then facilitates cytokine production and activates anti-inflammatory transcription factors, shielding macrophages from infection-induced cell death. However, the immunometabolic function of itaconate was unexplored in HIV and cocaine-exposed microglia. We assessed the potential of 4-octyl-itaconate (4OI), a cell-penetrable ester form of itaconate known for its anti-inflammatory properties. When primary cortical cultures exposed to Tat and cocaine were treated with 4OI, microglial cell number increased and the morphological altercations induced by Tat and cocaine were reversed. Microglial cells also appeared more ramified, resembling the quiescent microglia. 4OI treatment inhibited secretion of the proinflammatory cytokines IL-1α, IL-1ß, IL-6, and MIP1-α induced by Tat and cocaine. Transcriptome profiling determined that Nrf2 target genes were significantly activated in Tat and 4OI treated cultures relative to Tat alone. Further, genes associated with cytoskeleton dynamics in inflammatory microglia were downregulated by 4OI treatment. Together, the results strongly suggest 4-octyl-itaconate holds promise as a potential candidate for therapeutic development to treat HAND coupled with CUD comorbidities.

Determining Gender by Raman Spectroscopy of a Bloodstain.

The development of novel methods for forensic science is a constantly growing area of modern analytical chemistry. Raman spectroscopy is one of a few analytical techniques capable of nondestructive and nearly instantaneous analysis of a wide variety of forensic evidence, including body fluid stains, at the scene of a crime. In this proof-of-concept study, Raman microspectroscopy was utilized for gender identification based on dry bloodstains. Raman spectra were acquired in mapping mode from multiple spots on a bloodstain to account for intrinsic sample heterogeneity. The obtained Raman spectroscopic data showed highly similar spectroscopic features for female and male blood samples. Nevertheless, support vector machines (SVM) and artificial neuron network (ANN) statistical methods applied to the spectroscopic data allowed for differentiating between male and female bloodstains with high confidence. More specifically, the statistical approach based on a genetic algorithm (GA) coupled with an ANN classification showed approximately 98% gender differentiation accuracy for individual bloodstains. These results demonstrate the great potential of the developed method for forensic applications, although more work is needed for method validation. When this method is fully developed, a portable Raman instrument could be used for the infield identification of traces of body fluids and to obtain phenotypic information about the donor, including gender and race, as well as for the analysis of a variety of other types of forensic evidence.

AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia.

Neurodegenerative pathologies such as Alzheimer's disease, Parkinson's disease, Huntington's disease, Amyotrophic lateral sclerosis, Multiple sclerosis, HIV-associated neurocognitive disorder, and others significantly affect individuals, their families, caregivers, and healthcare systems. While there are no cures yet, researchers worldwide are actively working on the development of novel treatments that have the potential to slow disease progression, alleviate symptoms, and ultimately improve the overall health of patients. Huge volumes of new scientific information necessitate new analytical approaches for meaningful hypothesis generation. To enable the automatic analysis of biomedical data we introduced AGATHA, an effective AI-based literature mining tool that can navigate massive scientific literature databases, such as PubMed. The overarching goal of this effort is to adapt AGATHA for drug repurposing by revealing hidden connections between FDA-approved medications and a health condition of interest. Our tool converts the abstracts of peer-reviewed papers from PubMed into multidimensional space where each gene and health condition are represented by specific metrics. We implemented advanced statistical analysis to reveal distinct clusters of scientific terms within the virtual space created using AGATHA-calculated parameters for selected health conditions and genes. Partial Least Squares Discriminant Analysis was employed for categorizing and predicting samples (122 diseases and 20889 genes) fitted to specific classes. Advanced statistics were employed to build a discrimination model and extract lists of genes specific to each disease class. Here we focus on drugs that can be repurposed for dementia treatment as an outcome of neurodegenerative diseases. Therefore, we determined dementia-associated genes statistically highly ranked in other disease classes. Additionally, we report a mechanism for detecting genes common to multiple health conditions. These sets of genes were classified based on their presence in biological pathways, aiding in selecting candidates and biological processes that are exploitable with drug repurposing. Author Summary: This manuscript outlines our project involving the application of AGATHA, an AI-based literature mining tool, to discover drugs with the potential for repurposing in the context of neurocognitive disorders. The primary objective is to identify connections between approved medications and specific health conditions through advanced statistical analysis, including techniques like Partial Least Squares Discriminant Analysis (PLSDA) and unsupervised clustering. The methodology involves grouping scientific terms related to different health conditions and genes, followed by building discrimination models to extract lists of disease-specific genes. These genes are then analyzed through pathway analysis to select candidates for drug repurposing.

Exposure to angiotensin-converting enzyme inhibitors that cross the blood-brain barrier and the risk of dementia among patients with human immunodeficiency virus.

More than one million people in the United States and over 38 million people worldwide are living with human immunodeficiency virus (HIV) infection. Antiretroviral therapy (ART) greatly improves the health of people living with HIV (PLWH); however, the increased life longevity of PLWH has revealed consequences of HIV-associated comorbidities. HIV can enter the brain and cause inflammation even in individuals with well-controlled HIV infection. The quality of life for PLWH can be compromised by cognitive deficits and memory loss, termed HIV-associated neurological disorders (HAND). HIV-associated dementia is a related but distinct diagnosis. Common causes of dementia in PLWH are similar to the general population and can affect cognition. There is an urgent need to identify treatments for the aging PWLH population. We previously developed AI-based biomedical literature mining systems to uncover a potential novel connection between HAND the renin-angiotensin system (RAAS), which is a pharmacological target for hypertension. RAAS-targeting anti-hypertensives are gaining attention for their protective benefits in several neurocognitive disorders. To our knowledge, the effect of RAAS-targeting drugs on the cognition of PLWH development of dementia has not previously been analyzed. We hypothesized that exposure to angiotensin-converting enzyme inhibitors (ACEi) that cross the blood brain barrier (BBB) reduces the risk/occurrence of dementia in PLWH. We report a retrospective cohort study of electronic health records (EHRs) to examine the proposed hypothesis using data from the United States Department of Veterans Affairs, in which a primary outcome of dementia was measured in controlled cohorts of patients exposed to BBB-penetrant ACEi versus those unexposed to BBB-penetrant ACEi. The results reveal a statistically significant reduction in dementia diagnosis for PLWH exposed to BBB-penetrant ACEi. These results suggest there is a potential protective effect of BBB ACE inhibitor exposure against dementia in PLWH that warrants further investigation.

Suppression of HIV and cocaine-induced neurotoxicity and inflammation by cell penetrable itaconate esters.

HIV-associated neurological disorder (HAND) is a serious complication of HIV infection, marked by neurotoxicity induced by viral proteins like Tat. Substance abuse exacerbates neurocognitive impairment in people living with HIV. There is an urgent need for effective therapeutic strategies to combat HAND comorbid with Cocaine Use Disorder (CUD). Our analysis of the HIV and cocaine-induced transcriptomes in primary cortical cultures revealed a significant overexpression of the macrophage-specific gene, aconitate decarboxylase 1 (Acod1), caused by the combined insults of HIV and cocaine. ACOD1 protein converts the tricarboxylic acid intermediate cis-aconitate into itaconate during the activation of inflammation. The itaconate produced facilitates cytokine production and subsequently activates anti-inflammatory transcription factors, shielding macrophages from infection-induced cell death. While the role of itaconate' in limiting inflammation has been studied in peripheral macrophages, its immunometabolic function remains unexplored in HIV and cocaine-exposed microglia. We assessed in this model system the potential of 4-octyl-itaconate (4OI), a cell-penetrable esterified form of itaconate known for its potent anti-inflammatory properties and potential therapeutic applications. We administered 4OI to primary cortical cultures exposed to Tat and cocaine. 4OI treatment increased the number of microglial cells in both untreated and Tat±Cocaine-treated cultures and also reversed the morphological altercations induced by Tat and cocaine. In the presence of 4OI, microglial cells also appeared more ramified, resembling the quiescent microglia. Consistent with these results, 4OI treatment inhibited the secretion of the proinflammatory cytokines IL-1α, IL-1ß, IL-6, and MIP1-α induced by Tat and cocaine. Transcriptome profiling further determined that Nrf2 target genes such as NAD(P)H quinone oxidoreductase 1 (Nqo1), Glutathione S-transferase Pi (Gstp1), and glutamate cysteine ligase catalytic (Gclc), were most significantly activated in Tat-4OI treated cultures, relative to Tat alone. Further, genes associated with cytoskeleton dynamics in inflammatory microglia were downregulated by 4OI treatment. Together, the results strongly suggest 4-octyl-itaconate holds promise as a potential candidate for therapeutic development aimed at addressing HAND coupled with CUD comorbidities.

Raman spectroscopy coupled with advanced statistics for differentiating menstrual and peripheral blood.

Body fluids are a common and important type of forensic evidence. In particular, the identification of menstrual blood stains is often a key step during the investigation of rape cases. Here, we report on the application of near-infrared Raman microspectroscopy for differentiating menstrual blood from peripheral blood. We observed that the menstrual and peripheral blood samples have similar but distinct Raman spectra. Advanced statistical analysis of the multiple Raman spectra that were automatically (Raman mapping) acquired from the 40 dried blood stains (20 donors for each group) allowed us to build classification model with maximum (100%) sensitivity and specificity. We also demonstrated that despite certain common constituents, menstrual blood can be readily distinguished from vaginal fluid. All of the classification models were verified using cross-validation methods. The proposed method overcomes the problems associated with currently used biochemical methods, which are destructive, time consuming and expensive.

Forensic identification of blood in the presence of contaminations using Raman microspectroscopy coupled with advanced statistics: effect of sand, dust, and soil.

Body fluid traces recovered at crime scenes are among the most common and important types of forensic evidence. However, the ability to characterize a biological stain at a crime scene nondestructively has not yet been demonstrated. Here, we expand the Raman spectroscopic approach for the identification of dry traces of pure body fluids to address the problem of heterogeneous contamination, which can impair the performance of conventional methods. The concept of multidimensional Raman signatures was utilized for the identification of blood in dry traces contaminated with sand, dust, and soil. Multiple Raman spectra were acquired from the samples via automatic scanning, and the contribution of blood was evaluated through the fitting quality using spectroscopic signature components. The spatial mapping technique allowed for detection of "hot spots" dominated by blood contribution. The proposed method has great potential for blood identification in highly contaminated samples.

Raman spectroscopic signature of vaginal fluid and its potential application in forensic body fluid identification.

Traces of human body fluids, such as blood, saliva, sweat, semen and vaginal fluid, play an increasingly important role in forensic investigations. However, a nondestructive, easy and rapid identification of body fluid traces at the scene of a crime has not yet been developed. The obstacles have recently been addressed in our studies, which demonstrated the considerable potential of Raman spectroscopy. In this study, we continued to build a full library of body fluid spectroscopic signatures. The problems concerning vaginal fluid stain identification were addressed using Raman spectroscopy coupled with advanced statistical analysis. Calculated characteristic Raman and fluorescent spectral components were used to build a multidimensional spectroscopic signature of vaginal fluid, which demonstrated good specificity and was able to handle heterogeneous samples from different donors.

Multidimensional Raman spectroscopic signature of sweat and its potential application to forensic body fluid identification.

This proof-of-concept study demonstrated the potential of Raman microspectroscopy for nondestructive identification of traces of sweat for forensic purposes. Advanced statistical analysis of Raman spectra revealed that dry sweat was intrinsically heterogeneous, and its biochemical composition varies significantly with the donor. As a result, no single Raman spectrum could adequately represent sweat traces. Instead, a multidimensional spectroscopic signature of sweat was built that allowed for the presentation of any single experimental spectrum as a linear combination of two fluorescent backgrounds and three Raman spectral components dominated by the contribution from lactate, lactic acid, urea and single amino acids.

Advanced statistical analysis of Raman spectroscopic data for the identification of body fluid traces: semen and blood mixtures.

Conventional confirmatory biochemical tests used in the forensic analysis of body fluid traces found at a crime scene are destructive and not universal. Recently, we reported on the application of near-infrared (NIR) Raman microspectroscopy for non-destructive confirmatory identification of pure blood, saliva, semen, vaginal fluid and sweat. Here we expand the method to include dry mixtures of semen and blood. A classification algorithm was developed for differentiating pure body fluids and their mixtures. The classification methodology is based on an effective combination of Support Vector Machine (SVM) regression (data selection) and SVM Discriminant Analysis of preprocessed experimental Raman spectra collected using an automatic mapping of the sample. This extensive cross-validation of the obtained results demonstrated that the detection limit of the minor contributor is as low as a few percent. The developed methodology can be further expanded to any binary mixture of complex solutions, including but not limited to mixtures of other body fluids.

Multidimensional Raman spectroscopic signatures as a tool for forensic identification of body fluid traces: a review.

The analysis of body fluid traces during forensic investigations is a critical step in determining the key details of a crime. Several confirmatory and presumptive biochemical tests are currently utilized. However, these tests are all destructive, and no single method can be used to analyze all body fluids. This review outlines recent progress in the development of a novel universal approach for the nondestructive, confirmatory identification of body fluid traces using Raman spectroscopy. The method is based on the use of multidimensional spectroscopic signatures of body fluids and accounts for the intrinsic heterogeneity of dry traces and donor variation. The results presented here demonstrate that Raman spectroscopy has potential for identifying traces of semen, blood, saliva, sweat, and vaginal fluid with high confidence.