Biology subjects

Parmar, H.

Publications and source records attributed to Parmar, H..

4 recordsLinked to original sources

bioRxiv2025

Systematic characterization of cancer-associated SPOP mutants reveals novel and reprogrammable degradative activities

Speckle-type POZ protein (SPOP) functions as the substrate adaptor of the Cullin3-RING ligase (CRL3) complex and is recurrently mutated in multiple cancer types. Among these, F102C and F133L are frequent prostate cancer mutations within the substrate-binding domain, yet their biochemical consequences remain incompletely understood. Using quantitative proteomics, we show that SPOP-F133L, unlike SPOP-F102C, retains degradative activity toward the nuclear basket proteins NUP153 and TPR, indicating substrate-dependent loss-of-function. Moreover, SPOP-F133L induces partial down-regulation of p53 through a CRL-dependent, post-translational mechanism, revealing a potential neo-substrate relationship. Finally, we demonstrate that both SPOP-F102C and SPOP-F133L support targeted protein degradation (TPD) in an engineered cellular system. These findings define the degradative capacities of SPOP mutants and highlight opportunities to repurpose these variants as mutant-selective E3 ligases for therapeutic applications.

biochemistry↗

bioRxiv2025

Factorial variation of saccade vigor with dual decision processes

Canonical stochastic models of decision-making treats decision and action as independent and sequential processes. However, studies involving limb movements consistently show that movement duration and kinematics are influenced by the quality of evidence. We tested whether saccade velocity varies with the quality of evidence in monkeys performing a visual search GO/NOGO task in which singleton elongation cued the GO/NOGO stimulus-response rule and the location of a color singleton specified saccade endpoint. We factorially manipulated the efficiency of stimulus-response cue discrimination by varying the elongation of the singleton and the efficiency of singleton localization by varying the color similarity between the singleton and distractors. The effectiveness of the manipulations was revealed by the response times on correct trials that were separately modified by the singleton localizability and stimulus-response cue discriminability, by the incidence of localization and response selection errors with separately modified error response times. Saccade velocity was higher on correct relative to error trials and was inversely proportional to response time. Saccade velocity was separately modified by singleton localizability and stimulus-response cue discriminability. Distinct patterns of error rates and saccade velocity across monkeys indicated individual differences in decision-making strategies. These findings demonstrate that the process selecting endpoints can influence both the timing and dynamics of saccadic eye movements. Incorporating saccade vigor can provide valuable constraints on biologically plausible decision models and help address the persistent challenge of model mimicry.

neuroscience↗

bioRxiv2024

A Novel Artificial Intelligence (AI) Method to Classify and Predict the Progression of Alzheimers Disease

PurposeThe objective of this study was to develop a novel AI-ensembled network based on the most important features and affected brain regions to accurately classify and exhibit the pattern of progression of the stages of Cognitive Impairment (CI). MethodsWe proposed a novel ensembled architecture, 3D ResNet-18 - RF (Random Forest), and used this network to categorize the stages of Alzheimers disease (AD). The residual unit (blocks of ResNet) was introduced to the 3D Convolutional Neural network (CNN) to solve the degradation problem. It was considered an innovative strategy since the combination with fine-tuning resulted in higher accuracy. This network was trained on selected features and affected brain regions. The structured magnetic resonance images (MRI) were collected from the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset, and the random forest was used for determining the importance of the features and affected regions from the parcellated 170 regions of interest (ROIs) using Atlas, automated anatomical labeling 3(AAL-3). This framework classified five categories of AD and detected the progression pattern. ResultsThe proposed network showed promising results with a 66% F-1 score, 76% sensitivity, and 93.5% specificity, which outperformed the performance of conventional methods for categorizing five categories. Ventral Posterolateral and Pulvinar lateral regions were the regions most affected, indicating the progression from early MCI to AD. The five-fold validation accuracy for the developed model was 60.02%. ConclusionThe results showed that the gray matter to white matter ratio was the most significant feature, which also accurately predicted the progression pattern. The performance metrics fluctuated with different hyperparameters, but they never exceeded 0.05% of the estimated results, indicating the validity and originality of the suggested methodology.

bioinformatics↗

bioRxiv2020

Xpert MTB/XDR: A ten-color reflex assay suitable for point of care settings to detect isoniazid-, fluoroquinolone-, and second line injectable drug-resistance directly from Mycobacterium tuberculosis positive sputum.

We describe the design, development, analytical performance and a limited clinical evaluation of the 10-color Xpert MTB/XDR assay (CE-IVD only, not for sale in the US). This assay is intended as a reflex test to detect resistance to Isoniazid (INH), Fluoroquinolones (FLQ), Ethionamide (ETH) and Second Line Injectable Drugs Drugs (SLID) on unprocessed sputum samples and concentrated sputum sediments which are positive for Mycobacterium tuberculosis. The Xpert MTB/XDR assay simultaneously amplifies eight genes and promoter regions in M. tuberculosis and analyzes melting temperatures (Tms) using sloppy molecular beacon probes (SMB) to identify mutations associated with INH, FLQ, ETH and SLID resistance. Results can be obtained under 90 minutes and requires 10-color GeneXpert modules. The assay can differentiate low versus high-level resistance to INH and FLQ as well as cross-resistance versus individual resistance to SLIDs by identifying mutation-specific Tms or Tm patterns generated by the SMB probes. The assay has a Limit of Detection comparable to the Xpert MTB/RIF assay and succesfully detected 16 clinically significant mutations in a challenge set of clinical isolate DNA. In a clinical study performed at two sites with 100 sputum and 214 clinical isolates, the assay showed a sensitivity of 94-100% and a specificity of 100% for all drugs except for ETH when compared to sequencing. The sensitivity and specificity when compared to phenotypic drug susceptibility testing were in the same range. Used in combination with a primary tuberculosis diagnostic test, this assay is expected to expand the capacity for detection of drug-resistant tuberculosis.

microbiology↗