Biology subjects

Mansoor, A.

Publications and source records attributed to Mansoor, A..

6 recordsLinked to original sources

bioRxiv2026

Spoken Recall Reveals Lexical and Mnemonic Function Differences in Temporal Lobe Epilepsy Patients

Background and Objectives: Word-finding difficulty is common in healthy aging and in neurologic disorders, including temporal lobe epilepsy (TLE) and early Alzheimer disease. Standard language measures have limited sensitivity for detecting subtle or longitudinal changes in spontaneous speech. We examined whether natural language processing and acoustic analysis of spoken biographical recall could identify lexical and temporal speech features associated with language and memory performance in TLE. Methods: We conducted a cross-sectional observational study of spoken recall during a Famous Faces biographical memory task. Adults with TLE and healthy controls (HCs) viewed 20 famous faces and spontaneously recalled biographical details. Speech was transcribed and diarized using automated tools. Lexical measures included word counts and lexical index (ratio of rare to common words). Acoustic measures included utterance and pause duration and pause frequency. Features were compared between groups and correlated with neuropsychological measures, including Montreal Cognitive Assessment (MoCA), Boston Naming Test (BNT), delayed recall, education, and biographical recall accuracy Results: Eighty-one adults participated (51 TLE, 30 HCs). Lexical measures did not differ between groups. In TLE, lexical index correlated with BNT performance (rs=0.62) and MoCA score (rs=0.35). Compared with HCs, participants with TLE produced shorter utterances (5.54 {+/-} 2.50 vs. 6.59 {+/-} 2.63; Cohen's d=0.41, 95% CI -0.05 to 0.86, p=0.041), shorter pauses (0.61 {+/-} 0.21 vs 0.67 {+/-} 0.22, Cohen's d=0.29, 95% CI -0.16 to 0.74, p=0.043), and more frequent pauses (10.81 {+/-} 3.30 vs 9.29 {+/-} 3.59, Cohen's d=-0.45, 95% CI -0.90 to 0.01, p=0.036). Higher education was associated with longer utterances, longer pauses, and lower pause frequency, without evidence of a diagnosis-by-education interaction. Faster utterance rate was associated with better biographical recall in both groups, while higher pause rate was associated with worse recall in TLE. Discussion: Speech-derived lexical and temporal features from naturalistic recall capture clinically relevant variation in language and memory-related performance. Although lexical output did not distinguish TLE from HCs, lexical richness tracked naming and global cognition in TLE, while temporal speech features related to recall performance. These findings support the potential of automated speech analysis as a digital behavioral biomarker for word-finding difficulty in neurologic populations.

neuroscience↗

bioRxiv2025

Functional genomics and tumor microenvironment analysis reveal prognostic biological subtypes in Mantle cell lymphoma

Mantle cell lymphoma (MCL) is a genetically and clinically heterogeneous B-cell malignancy. We studied two MCL cohorts with differing treatment patterns: one enriched for immunochemotherapy, the other for chemotherapy alone. TP53 alterations were consistently associated with poor prognosis, whereas ATM mutations correlated with improved outcomes following rituximab-based chemotherapy. Based on recurrent genetic events, six clusters were identified and refined into three prognostic groups: high-risk (TP53 mutations and deletions at 17p13.3, 13q14.2, and 19p13.3), intermediate-risk (ATM and epigenetic regulator mutations, or gains at 8q/17q/15q), and low-risk (lacking TP53 alterations, rare ATM mutations without 11q deletions, gains at 3q, deletions at 6q). Transcriptomic analysis revealed enrichment of proliferation, metabolism-promoting gene signatures in high-risk; angiogenesis and NOTCH signaling in intermediate-risk; and proinflammatory-related (i.e., IFN, TNF) in low-risk MCLs. Multi-proteomic spatial profiling using imaging mass cytometry (IMC) demonstrated enrichment of CD8 T cells with high expression of exhaustion markers and dominant population of myeloid cells skewed toward an M2-like phenotype. Compared to ATM-perturbed tumors, TP53-perturbed tumors exhibited enriched SOX11 tumor cells and enhanced tumor-immune cell interactions. Functional analysis revealed that p53 represses BCR signaling through PTPN6 activation. Collectively, these findings highlight distinct molecular and immune landscapes and reveal therapeutic vulnerabilities in high-risk TP53-altered MCL.

cancer biology↗

bioRxiv2024

Natural Language Processing Applied to Spontaneous Recall of Famous Faces Reveals Memory Dysfunction in Temporal Lobe Epilepsy Patients

Objective and BackgroundEpilepsy patients rank memory problems as their most significant cognitive comorbidity. Current clinical assessments are laborious to administer and score and may not always detect subtle memory decline. The Famous Faces Task (FF) has robustly demonstrated that left temporal lobe epilepsy (LTLE) patients remember fewer names and biographical details compared to right TLE (RTLE) patients and healthy controls (HCs). We adapted the FF task to capture subjects entire spontaneous spoken recall, then scored responses using manual and natural language processing (NLP) methods. We expected to replicate previous group level differences using spontaneous speech and semi-automated analysis. MethodsSeventy-three (N=73) adults (28 LTLE, 18 RTLE, and 27 HCs) were included in a case-control prospective study design. Twenty FF in politics, sports, and entertainment (active 2008-2017) were shown to subjects, who were asked if they could recognize and spontaneously recall as much biographical detail as possible. We created human-generated and automatically-generated keyword dictionaries for each celebrity, based on a randomly selected training set of half of the HC transcripts. To control for speech output, we measured the speech duration, total word count and content word count for the FF task and a Cookie Theft Control Task (CTT), in which subjects were merely asked to describe a visual scene. Subjects responses to FF and CTT tasks were recorded, transcribed, and analyzed in a blinded manner with a combination of manual and automated NLP approaches. ResultsFamous face recognition accuracy was similar between groups. LTLE patients recalled fewer biographical details compared to HCs and RTLEs using both the gold-standard human-generated dictionary (24%{+/-}12% vs. 31%{+/-}12% and 30%{+/-}12%, p=0.007) and the automated dictionary (24%{+/-}12% vs. 31%{+/-}12% and 32%{+/-}13%, p=0.007). There were no group level differences in speech duration, total word count, or content word count for either the FF and CTT to explain difference in recall performance. There was a positive, statistically significant relationship between MOCA score and FF recall performance as scored by the human-generated ({rho}= .327, p= .029) and automatically-generated dictionaries ({rho}= .422, p= .004) for TLE subjects, but not HCs, an effect that was driven by LTLE subjects. DiscussionLTLE patients remember fewer details of famous people than HCs or RTLE patients, as discovered by NLP analysis of spontaneous recall. Decreased biographical memory was not due to decreased speech output and correlated with lower MOCA scores. NLP analysis of spontaneous recall can detect memory dysfunction in clinical populations in a semi-automated, objective, and sensitive manner.

neuroscience↗

bioRxiv2020

Phylogenomic analysis of Clostridiodes difficile ribotype 106 strains reveals novel genetic islands and emergent phenotypes

BackgroundClostridioides difficile RT106 has emerged as a dominant molecular type in the USA in recent years, but the underlying factors contributing to its predominance remain undefined. As part of our ongoing C. difficile infection (CDI) surveillance in Arizona, we monitored RT106 frequency and characterized the genomic and phenotypic properties of the recovered isolates. ResultsFrom 2015-2018, RT106 was the second-most prevalent molecular type isolated from CDI patients in our surveillance. A representative RT106 strain displayed robust virulence and 100% lethality in the hamster model of acute CDI. We identified a unique 46 KB genomic island (GI1) in all RT106 strains, including those in public databases. GI1 was not found in its entirety in any other C. difficile clade, or indeed in any other microbial genome; however, smaller segments were detected in select Enterococcus faecium strains. Molecular clock analyses suggest that GI1 was horizontally acquired and sequentially assembled over time. Consistent with the presence of genes encoding homologs of VanZ and a SrtB-anchored collagen-binding adhesin in GI1, all tested RT106 strains had increased teicoplanin resistance and a majority displayed collagen-dependent biofilm formation. Two additional genomic islands (GI2 and GI3) were also present in a subset of RT106 strains. All three islands have features of mobile genetic elements and encode several putative virulence factors. ConclusionsConsistent with the known genetic plasticity of C. difficile, strains belonging to the RT106 clade harbor unique genetic islands. Correspondingly, emergent phenotypic properties may contribute to the relatively rapid shifts of strain distribution in patient populations.

genomics↗

bioRxiv2019

Pathognomonic and epistatic genetic alterations in B-cell non-Hodgkin lymphoma

B-cell non-Hodgkins lymphoma (B-NHL) encompasses multiple clinically and phenotypically distinct subtypes of malignancy with unique molecular etiologies. Common subtypes of B-NHL such as diffuse large B-cell lymphoma (DLBCL) have been comprehensively interrogated at the genomic level. But rarer subtypes such as mantle cell lymphoma (MCL) remain sparsely characterized. Furthermore, multiple B-NHL subtypes have thus far not been comprehensively compared using the same methodology to identify conserved or subtype-specific patterns of genomic alterations. Here, we employed a large targeted hybrid-capture sequencing approach encompassing 380 genes to interrogate the genomic landscapes of 685 B-NHL tumors at high depth; including DLBCL, MCL, follicular lymphoma (FL), and Burkitt lymphoma (BL). We identified conserved hallmarks of B-NHL that were deregulated in the majority of tumor from each subtype, including the frequent genetic deregulation of the ubiquitin proteasome system (UPS). In addition, we identified subtype-specific patterns of genetic alterations, including clusters of co-occurring mutations and DNA copy number alterations. The cumulative burden of mutations within a single cluster were more discriminatory of B-NHL subtypes than individual mutations, implicating likely patterns of genetic cooperation that contribute to disease etiology. We therefore provide the first cross-sectional analysis of mutations and DNA copy number alterations across major B-NHL subtypes and a framework of co-occurring genetic alterations that deregulate genetic hallmarks and likely cooperate in lymphomagenesis.

genomics↗

bioRxiv2018

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. This computational modeling approach addresses three major challenges in personalized cancer therapy, which we validate across multiple species via computationally-designed personalized synergistic drug combination predictions, identification of unifying therapeutic targets to overcome intra-tumor heterogeneity, and mitigation of cancer cell resistance and rewiring mechanisms. These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

bioinformatics↗