Biology subjects

Aftab, W.

Publications and source records attributed to Aftab, W..

5 recordsLinked to original sources

bioRxiv2024

Optimizing biomedical information retrieval with a keyword frequency-driven Prompt Enhancement Strategy

BackgroundMining the enormous pool of biomedical literature to extract accurate responses and relevant references is a daunting challenge, made more difficult by the domains interdisciplinary nature, specialized jargon, and continuous evolution. Early natural language processing (NLP) approaches faced considerable hurdles in comprehending the nuances of natural language which frequently led to false answers. However, the discovery of transformer models has immensely boosted the cause by enabling researchers to create larger and more potent language models known as large language models (LLMs). These LLMs have opened up new possibilities for enhancing question-answering (QA) tasks. Even with these technological advances, the current LLM-based solutions for querying specialized domains like biology and biomedicine still have issues in generating up to date responses while preventing "hallucination" or the generation of plausible but factually incorrect responses. ResultsThis paper focuses on prompt enhancement using retrieval-augmented architecture as a strategy to guide LLMs towards generating more meaningful responses for biomedical question-answering tasks. We evaluated two prompt enhancement approaches using GPT-3 and GPT-4, examining their effectiveness in retrieving relevant information from complex landscape of biomedical literature. Our proposed approach leverages explicit signals in user queries to extract meaningful contexts from a vast pool of information, addressing the shortcomings of traditional text embedding-based prompt enhancement methods. We developed a QA bot WeiseEule (https://github.com/wasimaftab/WeiseEule-LocalHost) utilizing these prompt enhancement methods and allowing for comparative analysis of their performances. ConclusionsOur findings highlight the importance of prompt enhancement methods that utilize explicit signals in users query over traditional text embedding based counterparts to improve LLM-generated responses in specialized domains such as biology and biomedicine. By providing users complete control over the information that goes into the LLM, our approach tackles some of the major drawbacks of existing web-based chatbots and LLM-based QA systems including hallucinations and the generation of irrelevant or outdated responses.

bioinformatics↗

bioRxiv2021

The Integrity of the Speciation Core Complex is necessary for centromeric binding and reproductive isolation in Drosophila

Postzygotic isolation by genomic conflict is a major cause for the formation of species. Despite its importance, the molecular mechanisms that result in the lethality of interspecies hybrids are still largely unclear. The genus Drosophila, which contains over 1600 different species, is one of the best characterized model systems to study these questions. We showed in the past that the expression levels of the two hybrid incompatibility factors Hmr and Lhr diverged in the two closely related Drosophila species, D. melanogaster and D. simulans, resulting in an increased level of both proteins in interspecies hybrids. This overexpression leads to mitotic defects, a misregulation in the expression of transposable elements and a decreased fertility. In this work, we describe a distinct six subunit Speciation Core Complex (SCC) containing HMR and LHR and analyse the effect of Hmr mutations on complex function and integrity. Our experiments suggest that HMR acts as a bridging factor between centromeric chromatin and pericentromeric heterochromatin, which is required for both its physiological function and its ability to cause hybrid male lethality.

biochemistry↗

bioRxiv2020

Systematic analysis of innate immune antagonism reveals vulnerabilities of SARS-CoV-2

The innate immune system constitutes a powerful barrier against viral infections. However, it may fail because successful emerging pathogens, like SARS-CoV-2, evolved strategies to counteract it. Here, we systematically assessed the impact of 29 SARS-CoV-2 proteins on viral sensing, type I, II and III interferon (IFN) signaling, autophagy and inflammasome formation. Mechanistic analyses show that autophagy and type I IFN responses are effectively counteracted at different levels. For example, Nsp14 induces loss of the IFN receptor, whereas ORF3a disturbs autophagy at the Golgi/endosome interface. Comparative analyses revealed that antagonism of type I IFN and autophagy is largely conserved, except that SARS-CoV-1 Nsp15 is more potent in counteracting type I IFN than its SARS-CoV-2 ortholog. Altogether, however, SARS-CoV-2 counteracts type I IFN responses and autophagy much more efficiently than type II and III IFN signaling. Consequently, the virus is relatively resistant against exogenous IFN-/{beta} and autophagy modulation but remains highly vulnerable towards IFN-{gamma} and -{lambda} treatment. In combination, IFN-{gamma} and -{lambda} act synergistically, and drastically reduce SARS-CoV-2 replication at exceedingly low doses. Our results identify ineffective type I and II antagonism as weakness of SARS-CoV-2 that may allow to devise safe and effective anti-viral therapies based on targeted innate immune activation.

microbiology↗

bioRxiv2020

Imaging mass spectrometry and shotgun proteomics reveal dysregulated pathways in male infertility

Spermatogenesis is a complex multi-step process involving intricate interactions between different cell types in the male testis. Disruption of these interactions results in infertility. Combination of shotgun tissue proteomics with MALDI imaging mass spectrometry is markedly potent in revealing topological maps of molecular processes within tissues. Here, we use a combinatorial approach on a characterized mouse model of hormone induced male infertility to uncover misregulated pathways. Comparative testicular proteome of wildtype and mice overexpressing human P450 aromatase (AROM+) with pathologically increased estrogen levels unravels gross dysregulation of spermatogenesis and emergence of proinflammatory pathways in AROM+ testis. In situ MS allowed us to localize misregulated proteins/peptides to defined regions within the testis. Results suggest that infertility is associated with substantial loss of proteomic heterogeneity, which define distinct stages of seminiferous tubuli in healthy animals. Importantly, considerable loss of mitochondrial factors, proteins associated with late stages of spermatogenesis and steroidogenic factors characterise AROM+ mice. Thus, the novel proteomic approach pinpoints in unprecedented ways the disruption of normal processes in testis and provides a signature for male infertility.

biochemistry↗

bioRxiv2018

A Novel Computational Framework to Predict the Impact of a Point Mutation on PDZ Domain Classification

PDZ domains represent one of the most common protein homology regions playing key roles in several diseases. Point mutations (PM) in amino acid primary sequence of PDZ domains can alter domain functions by affecting for example, downstream phosphorylation, a pivotal process in biology. Our goal in this present study was to introduce a novel approach to investigate how point mutations within the Class 1, Class 2 and Class 1-2 PDZ domains could affect the changes in binding with their partner ligands and hence affect their classification. We focused on features in PDZ domains of various species including human, rat and mouse. However, our work represents a generic computational framework that could be used to analyze PM in any given PDZ sequence. We have adopted two different approaches to investigate the impact of PM. In the first approach, we have developed a statistical model using bigram frequencies of amino acids and employed six different similarity measures to contrast the bigram frequency distribution of a wild type sequence relevant to its point mutants. In the next approach, we developed a statistical method that incorporates the impact of bigram frequency history associated with each mutational site that we call history weighted conditional change in probabilities. In this PM study, we observed that the history weighted method performs best when compared to all other methods studied in terms of picking up sites in PDZ domain where a PM could flip the class. We anticipate that this method will present a step forward towards computational techniques unveiling PDZ domain point mutants that largely affect the protein-ligand binding, specificity and affinity. We hope that this and future studies could aid therapy in which PDZ mutations have been implicated as the main disease drivers such as the Usher syndrome.

bioinformatics↗