Biology subjects

Rashid, S.

Publications and source records attributed to Rashid, S..

13 recordsLinked to original sources

bioRxiv2026

Frequency Shift Imaging Using an Adiabatic SLR Self-Refocused Pulse for Positive-Contrast SPION Imaging at 7T

Abstract: Purpose: Superparamagnetic iron oxide nanoparticles (SPION) are widely used as MRI contrast agents for cell tracking and molecular imaging. However, their detection using conventional T2/T2* weighted and susceptibility-weighted MRI relies on negative contrast (signal voids), which lacks specificity because similar hypointense signals can arise from other sources of magnetic susceptibility. This study introduces Frequency Shift Imaging (FSI), a positive-contrast technique based on an adiabatic Shinnar-Le Roux (SLR) self-refocused pulse that addresses the limited specificity of conventional SPION imaging. Methods: An adiabatic self-refocused RF pulse was designed using the SLR algorithm for frequency-selective positive-contrast imaging. The optimized pulse had a spectral bandwidth of 370 Hz, a peak RF amplitude of 14 T, and a duration of 15 ms. FSI data were acquired on a 7T MRI scanner. Phantom experiments used agarose-embedded 30 nm cell-labeled SPION at 0%, 25%, 75%, and 100% concentrations (pure). In vivo validation was performed following intramuscular SPION injection into the hind limb of a mouse. FSI images were compared with conventional acquisitions. Results: Quantitative phantom analysis showed normalized FSI signal intensities of 25.02% and 75.16% for samples containing 25% and 75% labeled cells, respectively, demonstrating an approximately proportional relationship between FSI signal and labeled-cell concentration. In vivo, FSI generated localized hyperintense positive contrast at the SPIO injection site, providing improved conspicuity and localization compared with the corresponding negative-contrast signal void. Discussion and Conclusion: FSI enables robust, B1-insensitive, positive-contrast SPION imaging at 7T with reduced echo time and SAR compared to paired adiabatic approaches, supporting its potential for quantitative cell tracking and molecular imaging applications.

bioengineering↗

bioRxiv2025

Integrative Omics Identifies Candidate Plasma Biomarkers and Cellular Targets Associated with Thoracic Aortic Aneurysm

ObjectivesTo define the cellular landscape of thoracic aortic aneurysm (TAA) and identify circulating biomarkers associated with disease burden. BackgroundTAA is marked by progressive aortic wall weakening and dilation, predisposing to rupture and dissection. However, its cellular architecture remains incompletely defined, and reliable circulating biomarkers are lacking. MethodsSingle-cell RNA sequencing was performed on 17 aortic tissue samples from 10 patients undergoing TAA repair and integrated with publicly available datasets to characterize disease-associated cell states. In parallel, tomographic imaging and plasma proteomics were used to identify biomarkers associated with aortic diameter. Key findings were further assessed through integration with single-cell data, external validation, and in vitro stimulation of primary human adventitial fibroblasts with fibroblast growth factor 23 (FGF-23). ResultsWe identified 25 cellular subsets, including macrophages, endothelial cells, vascular smooth muscle cells, and fibroblasts, with substantial heterogeneity in cellular composition and transcriptional state. Genome-wide association study candidate genes, including JUN and TPM3, showed cell type-specific upregulation. Plasma proteomics identified multiple biomarkers associated with aortic diameter, of which FGF-23 was independently validated in the UK Biobank as elevated in individuals with TAA. FGFR1, the receptor for FGF-23, was selectively expressed in fibroblasts and subsets of vascular smooth muscle cells, with strongest downstream signaling in fibroblasts. FGF-23 stimulation induced inflammatory and extracellular matrix remodeling programs in primary human adventitial fibroblasts. ConclusionsThese findings define the cellular landscape of TAA and identify the FGF-23-FGFR1 axis as a biomarker-linked pathway that may contribute to aneurysm progression. Condensed AbstractThoracic aortic aneurysm (TAA) is characterized by progressive aortic dilation and risk of rupture, yet its cellular architecture and circulating biomarkers remain incompletely defined. We performed single-cell RNA sequencing on 17 aortic samples from 10 patients and integrated these data with public datasets to define the cellular landscape of TAA. In parallel, imaging and plasma proteomics (n=10) were used to identify biomarkers associated with aortic diameter. We identified 25 cellular subsets, including macrophages, endothelial cells, vascular smooth muscle cells, and fibroblasts, with notable transcriptional heterogeneity and cell type-specific upregulation of GWAS-associated genes (e.g., JUN, TPM3). Plasma proteomics identified fibroblast growth factor 23 (FGF-23) as associated with aortic diameter and elevated in TAA in the UK Biobank. FGFR1, its receptor, was selectively expressed in fibroblasts and VSMCs, and FGF-23 stimulation induced inflammatory and extracellular matrix remodeling programs in fibroblasts. These findings link a circulating biomarker to stromal cell signaling in TAA. HighlightsO_LIIntegrative single-cell RNA sequencing defined a diverse cellular landscape in thoracic aortic aneurysm tissue, identifying 25 distinct cell populations. C_LIO_LICross-dataset harmonization revealed marked differences in cellular composition across studies while supporting shared stromal and immune programs in thoracic aortic aneurysm. C_LIO_LIPlasma proteomics identified FGF-23 as a candidate biomarker associated with aortic diameter and independently linked to thoracic aortic aneurysm presence in the UK Biobank C_LIO_LIFGFR1 was enriched in fibroblasts and subsets of vascular smooth muscle cells, and FGF-23 induced inflammatory and extracellular matrix remodeling programs in human primary adventitial fibroblasts. C_LI

cell biology↗

bioRxiv2025

AMPK modulates a DEAH Box RNA-helicase to attenuate TOR signaling and establish developmental quiescence

Developmental plasticity allows organisms to adapt to environmental stress and improve reproductive fitness. Caenorhabditis elegans adapts to starvation and other stressors by transiting through an alternate developmental stage called dauer, which allows them to remain quiescent for several months, and yet fully retain reproductive fitness when they resume development. The AMP-activated protein kinase (AMPK) is essential for this plasticity as its compromise leads to germline hyperplasia during the dauer stage, dramatically reducing post-dauer fertility upon recovery from this stage, while also shortening survival. We identified a putative RNA-binding helicase (HZL-1) that is targeted by AMPK, the compromise of which suppresses several AMPK mutant phenotypes. HZL-1 shares significant similarity with the conserved HELZ family of RNA helicases, possessing characteristic DEAH helicase motifs, a predicted ATP binding motif, and three intrinsically disordered regions that are crucial for its localization and function. Curiously, HZL-1 is expressed and exerts its function in the intestine, yet its elimination suppresses the aberrant germ cell proliferation, while restoring germline quiescence and subsequent post-dauer fertility. CLIP-seq data revealed that HZL-1 binds several mRNAs during the dauer stage, resulting in a pronounced germline hyperplasia in the dauer germ line of AMPK mutants. Among these, the most enriched RNA bound to HZL-1, argk-1, is required for fertility in HZL-1 mutants, and functions by suppressing TOR activity in the germ line of AMPK dauer larvae, thereby preserving germline quiescence. These findings underscore the intricate role of RNAs and RNA-binding helicases in the complex interplay of genetic signals that animals have acquired to ensure their effective transit through periods of environmental challenge.

genetics↗

bioRxiv2025

Turning blood to brain cells: a plasma mediated reprograming model

The lack of effective stem cell protocols for generating personalized neurovascular niches poses a critical challenge in precision medicine. While iPSC-based methods are explored, their clinical use is hindered by high costs, long timelines, and cancer risks. Recent advancements in plasma-driven differentiation, using circulating monocytes, offer a promising solution as they can be reprogrammed into neuron-like, endothelial-like, and hematopoietic cells without genetic manipulation, by inducing growth factors mediated transdifferentiation. Vasculature is integral to neurodevelopment, with early blood supply transitioning from the perineural to intrinsic vascular plexus, driven by neuro-hematovascular signaling. The choroid plexus selectively transports proteins and growth factors from blood to CSF, supporting neural proliferation and differentiation. Building on these insights, we leveraged the innate reprograming potential of blood-derived cells to generate neuro-hematovascular niches using a novel PITTRep methodology, devoid of transgene and growth factor mediated transdifferentiation opening new avenues for regenerative and investigative neurovascular studies.

cell biology↗

bioRxiv2024

Sex-specific thermoregulatory effects of estrogen signaling in Reprimo lineage cells

Estrogens have considerable impact on energy homeostasis and metabolic health. In mice, signaling through estrogen receptor alpha (ER) alters energy intake and multiple aspects of energy expenditure, effects that may be mediated by specific regions or neuronal sub-populations of the hypothalamus. This study investigates the function of ER in neurons of the lineage that expresses Rprm (Reprimo), a gene we previously linked to thermoregulation in females. Here, we engineered a novel ReprimoCre mouse to selectively knock out ER in Rprm lineage cells (Reprimo-specific estrogen receptor KO; RERKO) and report changes in core temperature in female mice, with no changes in movement or food intake. RERKO females have elevated brown adipose tissue (BAT) temperature and lower tail temperature relative to controls, suggesting increased heat production and reduced heat dissipation, respectively. Developmental expression of Rprm was detected in the brain, but not in BAT or white adipose tissue suggesting temperature changes may be mediated by the nervous system. To confirm centrally mediated effects on temperature, we ablated Rprm expressing cells in the mediobasal hypothalamus and observed a reduction in core temperature relative to controls. Taken together, these results indicate that estrogen signaling in the Rprm lineage is critical for thermoregulation, mainly through the modulation of brown adipose tissue thermogenesis in female, but not male, mice.

physiology↗

bioRxiv2024

Building neurovascular tissue from autologous blood for modeling brain-activity

There are no faithful individualized stem cell-based bioengineered neuro-vascularized models that can recapitulate the physiological hemodynamic phenomenon of neuro-vascular coupling (NVC)-the principal behind BOLD (blood oxygen level-dependent) signal in functional neuroimaging, thereby dissuading the research in exploring the brain activity-based investigative studies in neurological/neurosensory diseases. This encouraged us to establish a preclinical optoacoustic (Hb/dHb hemoglobin/deoxyhemoglobin) imaging-competent in vitro neuro-vascularized model by employing a novel cellular reprograming PITTRep (Plasma Induced Transcriptomics/ epi-Transcriptomics Reprograming) approach. The current reprograming approach is based on coaxing autologous blood components to ecto-mesodermal lineage intermediates that can subsequently self-pattern into neurovascular tissue by harnessing the hemorheological properties of RBCs. The nature of blood flow is non-Newtonian and is a function of RBC concentration /haematocrit when they flow through the regions of low shear rates as seen in cerebral microcirculation. The current reprograming approach is a modification of our previous cellular reprograming approach that employed a Newtonian plasma fluid. The autologous blood-derived neurovascular tissue is free from exogenous genetic modification, external growth factors, and induced pluripotent stem cell (iPSC) derivation. This model uniquely integrates functional vasculature and neurogenesis. The current reprogramming approach resulted (in part) serendipitously while testing a potential (yet completely unexplored) hypothesis of haemodynamic reprograming by leveraging the fluid mechanic feature of blood erythrocytes as seen in thrombus formation during cerebral ischemic stroke, that is characterized by physiologically intriguing yet clinically meaningful neurological recovery (neuroplasticity) during an early time window. The current study attempted to induce "a post stroke-like model" of adult neurogenesis with functional synaptogenesis by instructing autologous blood components into thrombus formation through incorporation of erythrocytes in varying concentrations. We tried to instruct adult neurogenesis and neuroplasticity (a relatively non-resilient phenomenon under in vitro conditions) by co-induction of a neuro-vascular niche (NVN). These NVNs are marked by dendrites, synapses, astrogliosis, microglia activation, and growth factor signaling, thus phenocopying molecular and cellular aspects of post-stroke recovery window. The induction of neuro-vascularized niches and functional neuro-vascular coupling (NVC) was characterized by confocal microscopy, scanning electron microscopy, proteomic profiling, and Hb/dHb spectra based optoacoustic imaging. The blood thrombus formation was checked by rotational thromboelastometry (ROTEM), and switching of adult-to-embryonic hemoglobin was confirmed by routine hemoglobin typing. We also attempted to establish patient-specific neuro-vascularized niches from autologous blood of sensorineural hearing loss (SNHL) patients. The individualized neovascularised tissues are intended to be employed for investigating deregulated synaptic plasticity/ long term potentiation underlying poor auditory comprehension outcomes in school going kids suffering from SNHL that greatly compromises their academic performance and socio-behavioural-cognitive development. The attendant multiomics of patient-specific NVNs may have potential implications in developing stem-cell based therapies for neurosensory and cerebrovascular diseases.

neuroscience↗

bioRxiv2023

Computational investigation of Scutellarein derivatives as an inhibitor against triple-negative breast cancer by Quantum calculation, and drug-designed approaches

Triple-negative breast cancer accounts for 10-15% of all breast tumors (TNBC). Triple-negative breast cancer lacks either estrogen or progesterone receptors (ER or PR), producing either too little or too much HER2. (All three tests result in "negative" results for the cells.) These cancers are more common in women under 40 who are Black or have the BRCA1 mutation. TNBC differs from other types of invasive breast cancer in that it has fewer treatment options, a worse prognosis, and grows and spreads more quickly (outcome). So, first of all, the protein of triple-negative breast cancer was collected from the PDB database having the most stable configuration, and a natural bioactive molecule, Scutellarein, was selected. Scutellarein is well-known to possess anti-cancer properties, so its derivatives were chosen to design anticancer drugs through computational tools. In this case, the functional group has applied and modified structural activity relationship methods. Then, the pass prediction score was taken, which indicates the probability of active (Pa) and the probability of inactive (Pi). After that, other in-silco approaches, such as the ADMET parameter, and quantum calculation by Density Functional Theory (DFT), have been conducted. Finally, molecular docking and dynamics have been evaluated against TNBC to determine the binding affinity and stability. Scutellarein derivatives (DM03 at -10.7 kcal/mol, DM04 at -11.0 kcal/mol) have been reported to have a maximum tendency for binding against TNBC. Besides, the molecular dynamic simulation was performed at 100ns and described by root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF), which are much more stable compounds. The pharmacokinetics specifications for a suitable therapeutic candidate were satisfied by these molecules, like as non-carcinogenic, minimal to aquatic and non-aquatic toxicity. Almost all the molecules are highly soluble in the aqueous system. These all-computational data suggested that they might be suitable as a medication for the inhibition of TNBC, and further experimental studies should be carried out.

bioinformatics↗

bioRxiv2022

Towards increased accuracy and reproducibility in SARS-CoV-2 next generation sequence analysis for public health surveillance

During the COVID-19 pandemic, SARS-CoV-2 surveillance efforts integrated genome sequencing of clinical samples to identify emergent viral variants and to support rapid experimental examination of genome-informed vaccine and therapeutic designs. Given the broad range of methods applied to generate new viral genomes, it is critical that consensus and variant calling tools yield consistent results across disparate pipelines. Here we examine the impact of sequencing technologies (Illumina and Oxford Nanopore) and 7 different downstream bioinformatic protocols on SARS-CoV-2 variant calling as part of the NIH Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Tracking Resistance and Coronavirus Evolution (TRACE) initiative, a public-private partnership established to address the COVID-19 outbreak. Our results indicate that bioinformatic workflows can yield consensus genomes with different single nucleotide polymorphisms, insertions, and/or deletions even when using the same raw sequence input datasets. We introduce the use of a specific suite of parameters and protocols that greatly improves the agreement among pipelines developed by diverse organizations. Such consistency among bioinformatic pipelines is fundamental to SARS-CoV-2 and future pathogen surveillance efforts. The application of analysis standards is necessary to more accurately document phylogenomic trends and support data-driven public health responses.

bioinformatics↗

bioRxiv2022

Virulence Network of Interacting Influenza-Host Protein Domains.

There exist several databases that provide virus-host protein interactions. While most provide curated records of interacting virus-host protein pairs, information on the strain-specific virulence factors or protein domains involved, is lacking. Some databases offer incomplete coverage of Influenza strains because of the need to sift through vast amounts of literature (including those of major viruses including HIV and Dengue, besides others). None have offered complete, strain specific protein-protein interaction records for the Influenza A group of viruses. In this paper, we present a comprehensive network of predicted domain-domain interaction(s) (DDI) between Influenza A virus (IAV) and mouse host proteins, that will allow the systematic study of disease factors by taking the virulence information (lethal dose) into account. From a previously published dataset of lethal dose studies of IAV infection in mice, we constructed an interacting domain network of mouse and viral protein domains as nodes with weighted edges. The edges were scored with the Domain Interaction Statistical Potential (DISPOT) to indicate putative DDI. The virulence network can be easily navigated via a web browser, with the associated virulence information (LD50 values) prominently displayed. The network will aid Influenza A disease modeling by providing strain-specific virulence levels with interacting protein domains. It can possibly contribute to computational methods for uncovering Influenza infection mechanisms mediated through protein domain interactions between viral and host proteins.

bioinformatics↗

bioRxiv2022

Jupytope: Computational extraction of structural properties of viral epitopes

Epitope residues located on viral surface proteins are of immense interest in immunology and related applications such as vaccine development, disease diagnosis and drug design. Most tools rely on sequence based statistical comparisons, such as information entropy of residue positions in aligned columns to infer location and properties of epitope sites. To facilitate cross-structural comparisons of epitopes on viral surface proteins, a python-based extraction tool implemented with Jupyter notebook is presented (Jupytope). Given a viral antigen structure of interest, a list of known epitope sites and a reference structure, the corresponding epitope structural properties can quickly be obtained. The tool integrates biopython modules for commonly used software such as NACCESS, DSSP as well as residue depth and outputs a list of structure derived properties such as dihedral angles, solvent accessibility, residue depth and secondary structure that can be saved in several convenient data formats. To ensure correct spatial alignment, Jupytope takes a list of given epitope sites and their corresponding reference structure and aligns them before extracting the desired properties. Examples are demonstrated for epitopes of Influenza and SARS-CoV2 viral strains. The extracted properties assist detection of two Influenza subtypes and show potential in distinguishing between four major clades of SARS-CoV2, as compared with randomized labels. The tool will facilitate analytical and predictive works on viral epitopes through the extracted structural information. Key MessagesO_LIJupytope combines existing 3D-structural software to extract the properties of viral epitopes into a convenient text or csv file format C_LIO_LIThe structural properties serve as parameters or features that quantitatively capture viral epitopes C_LIO_LIAssociation of structural properties to viral subtypes (for Influenza) or clades (SARS-CoV2) is demonstrated with a simple XGBoost model C_LIO_LIStructure datasets mapped to SARS-CoV2 WHO clades and Pango lineages, as well as chain annotations are available for download C_LI

bioinformatics↗

bioRxiv2020

A Rare Deletion in SARS-CoV-2 ORF6 Dramatically Alters the Predicted Three-Dimensional Structure of the Resultant Protein

The function of the SARS-CoV-2 accessory protein p6, encoded by ORF6, is not fully known. Based upon its similarity to p6 from SARS-CoV, it may play a similar role, namely as an antagonist of type I interferon (IFN) signaling. Here we report the sequencing of a SARS-CoV-2 strain passaged six times after original isolation from a clinical patient in Hong Kong. The genome sequence shows a 27 nt in-frame deletion ({Delta}27,264-27,290) within ORF6, predicted to result in a 9 aa deletion ({Delta}FKVSIWNLD) from the central portion of p6. This deletion is predicted to result in a dramatic alteration in the three-dimensional structure of the resultant protein (p6{Delta}22-30), possibly with significant functional implications. Analysis of the original clinical sample indicates that the deletion was not present, while sequencing of subsequent passages of the strain identifies the deletion as a majority variant. This suggests that the deletion originated ab initio during passaging and subsequently propagated into the majority, possibly due to the removal of selective pressure through the IFN-deficient Vero E6 cell line. The specific function of the SARS-CoV-2 p6 N-terminus, if any, has not yet been determined. However, this deletion is predicted to cause a shift from N-endo to N-ecto in the transmembrane localization of the SARS-CoV-2 p6{Delta}22-30 N-terminus, possibly leading to the ablation of its native function.

genomics↗

bioRxiv2020

CReSCENT: CanceR Single Cell ExpressioN Toolkit

CReSCENTCanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users.

bioinformatics↗

bioRxiv2017

Project Dhaka: Variational Autoencoder for Unmasking Tumor Heterogeneity from Single Cell Genomic Data

Intra-tumor heterogeneity is one of the key confounding factors in deciphering tumor evolution. Malignant cells will have variations in their gene expression, copy numbers, and mutation even when coming from a single tumor. Single cell sequencing of tumor cells is of paramount importance for unmasking the underlying the tumor heterogeneity. However extracting features from the single cell genomic data coherent with the underlying biology is computationally challenging, given the extremely noisy and sparse nature of the data. Here we are proposing Dhaka a variational autoencoder based single cell analysis tool to transform genomic data to a latent encoded feature space that is more efficient in differentiating between the hidden tumor subpopulations. This technique is generalized across different types of genomic data such as copy number variation from DNA sequencing and gene expression data from RNA sequencing. We have tested the method on two gene expression datasets having 4K to 6K tumor cells and two copy number variation datasets having 250 to 260 tumor cells. Analysis of the encoded feature space revealed sub-populations of cells bearing distinct genomic signatures and the evolutionary relationship between them, which other existing feature transformation methods like t-SNE and PCA fail to do.

genomics↗