Biology subjects

Mahmoud, A.

Publications and source records attributed to Mahmoud, A..

8 recordsLinked to original sources

bioRxiv2025

Orchestrating Spatial Transcriptomics Analysis with Bioconductor

Spatial transcriptomics technologies provide spatially-resolved measurements of gene expression through assays that can either target selected genes or capture transcriptome-wide expression profiles. The complexity and variability of these technologies and their associated data necessitate multi-step workflows integrating diverse computational methods and software packages. We provide a freely accessible, open-source, continuously updated and tested online book containing reproducible code examples, datasets, and discussion about data analysis workflows for spatial omics data using Bioconductor in R, including interoperability with Python.

bioinformatics↗

bioRxiv2025

Paired primary-metastasis patient-derived organoids and mouse models identify phenotypic evolution and druggable dependencies of peritoneal metastasis from appendiceal cancer

Peritoneal carcinomatosis is a common yet deadly manifestation of gastrointestinal cancers, with few effective treatments. To identify targetable determinants of peritoneal metastasis, we focused on appendiceal adenocarcinoma (AC), a gastrointestinal cancer that metastasizes almost exclusively to the peritoneum. Current treatments are extrapolated from colorectal cancer (CRC), yet AC has distinct genomic alterations, mucinous morphology and peritoneum restricted metastatic pattern. Further, no stable preclinical models of AC exist, limiting drug discovery and representing an unmet clinical need. We establish a first-in-class stable biobank of 16 long-term cultured AC patient-derived organoids (PDOs), including 3 matched, simultaneously resected primary AC-peritoneal carcinomatosis (AC-PC) pairs. By enriching for cancer cells, AC PDOs enable accurate genomic characterization relative to paucicellular AC tissue. We establish an organoid orthotopic intraperitoneal xenograft model that recapitulates diffuse peritoneal carcinomatosis and show that PC-organoids retain increased metastatic capacity, decreased growth factor dependency and sensitivity to standard of care chemotherapy relative to matched primary AC organoids. Single cell profiling of AC-PC pairs reveals dedifferentiation from mucinous differentiated states in primary AC into intestinal stem cell and fetal progenitor states in AC-PC, with upregulation of oncogenic signaling pathways. Through hypothesis-driven drug testing, we identify KRASMULTI-ON inhibitor RMC-7977 and Wnt-targeting tyrosine kinase inhibitor WNTinib as novel, clinically actionable strategies to target AC-PC more effectively.

cancer biology↗

bioRxiv2023

Sensitivity of the timing of Drosophila pupal wing morphogenesis to external perturbations

The morphogenesis of the pupal wing of Drosophila melanogaster is a powerful model for understanding the physical mechanisms of tissue morphogenesis. During this process, the wing undergoes a dramatic reshaping where the hinge region contracts and pulls on the blade region, triggering a dynamic pattern of cell elongation changes, cell divisions, and cell neighborhood changes Etournay et al. (2015). Over our several year study of this process, we noticed that sometime after the year 2016, the onset of morphogenesis became consistently delayed by [~]6 h compared to previous years. Thus, the peak of cell elongation was now observed at 28 hours after puparium formation (hAPF) rather than at 20-22 hAPF. We show here that this delay is independent of genetic background and that the speed of the overall process is relatively unchanged, implying that an environmental factor causes a shift in the onset of the process relative to the start of pupariation. We then investigated how various environmental factors influence the timing of pupal wing morphogenesis, using the dynamics of cell elongation as a proxy. We find that imaging conditions, temperature, diet, Wolbachia infection, and the light/dark cycle have relatively little effect. Preliminary data show that the spectra of light used to rear the flies affects cell elongation dynamics, although the delay was not completely reverted and more experiments are needed to know precisely how this variable affects morphogenesis. In sum, our work suggests the presence of a gate controlling the onset of pupal wing morphogenesis that is influenced by a specific, yet unclear, environmental factor. Once the gate is released, pupal wing morphogenesis occurs at a fairly constant rate, remarkably robust to many environmental variables.

developmental biology↗

bioRxiv2023

Retracing Human Genetic Histories and Natural Selection Using Precise Local Ancestry Inference

In an increasingly diverse world, including admixed individuals in genomic studies is imperative for equity and portability. A crucial first step is precise local ancestry inference (LAI). We have developed Orchestra, a LAI model with unprecedented accuracy, and trained on over 10,000 single-origin individuals from 35 worldwide populations. We employed Orchestra to delve into genetic relationships and demographic histories, with a focus on Latin Americans, a prime example of admixture, and the Ashkenazi Jewish, whose origins have long been debated. Finally, Orchestra enabled us to map signatures of selection, notably identifying trace Scandinavian ancestry in British samples and unveiling an immune-rich region linked to respiratory infections. Our work advances the field of LAI and holds promise for improvements in future applications for admixed populations. One-Sentence SummaryOrchestra unveils Latino and Ashkenazi ancestral roots and a candidate Viking locus under selection in the British population

genomics↗

bioRxiv2023

Progressive plasticity during colorectal cancer metastasis

Metastasis is the principal cause of cancer death, yet we lack an understanding of metastatic cell states, their relationship to primary tumor states, and the mechanisms by which they transition. In a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that while primary tumors largely adopt LGR5+ intestinal stem-like states, metastases display progressive plasticity. Loss of intestinal cell states is accompanied by reprogramming into a highly conserved fetal progenitor state, followed by non-canonical differentiation into divergent squamous and neuroendocrine-like states, which is exacerbated by chemotherapy and associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cancer cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues than their intestinal lineage-restricted primary tumor counterparts. We identify PROX1 as a stabilizer of intestinal lineage in the fetal progenitor state, whose downregulation licenses non-canonical reprogramming.

cancer biology↗

bioRxiv2020

GalaxyCloudRunner: enhancing scalable computing for Galaxy

SummaryThe existence of more than 100 public Galaxy servers with service quotas is indicative of the need for an increased availability of compute resources for Galaxy to use. The GalaxyCloudRunner enables a Galaxy server to easily expand its available compute capacity by sending user jobs to cloud resources. User jobs are routed to the acquired resources based on a set of configurable rules and the resources can be dynamically acquired from any of 4 popular cloud providers (AWS, Azure, GCP, or OpenStack) in an automated fashion. Availability and implementationGalaxyCloudRunner is implemented in Python and leverages Docker containers. The source code is MIT licensed and available at https://github.com/cloudve/galaxycloudrunner. The documentation is available at http://gcr.cloudve.org/. ContactEnis Afgan (enis.afgan@jhu.edu) Supplementary informationNone

bioinformatics↗

bioRxiv2019

Accurate detection of non-proliferative diabetic retinopathy in optical coherence tomography images using convolutional neural networks

Diabetic retinopathy (DR) is a disease that forms as a complication of diabetes, It is particularly dangerous since it often goes unnoticed and can lead to blindness if not detected early. Despite the clear importance and urgency of such an illness, there is no precise system for the early detection of DR so far. Fortunately, such system could be achieved using deep learning including convolutional neural networks (CNNs), which gained momentum in the field of medical imaging due to its capability of being effectively integrated into various systems in a manner that significantly improves the performance. This paper proposes a computer aided diagnostic (CAD) system for the early detection of non-proliferative DR (NPDR) using CNNs. The proposed system is developed for the optical coherence tomography (OCT) imaging modality. Throughout this paper, all aspects of deployment of the proposed system are studied starting from the preprocessing stage required to extract input data to train the CNN without resizing the image, to the use of transfer learning principals and how best to combine features in order to optimize performance. A novel patch extraction framework for preprocessing is presented, followed by fovea detection algorithm, in addition to investigating the various CNN parameters for optimal deployment. Optimum CNN parameters and promising results are achieved. To the best of our knowledge, this is the first CNN-based DR early detection CAD system for OCT images. It achieves a promising accuracy of 94% with transfer learning.

bioengineering↗

bioRxiv2019

Investigating Biomechanical Properties of A. tortilis as Related to their Habitat

The biomechanical properties of Acacia tortilis were investigated considering its habitat (wild vs. nursery). The plant materials were collected from partially urbanized area in Doha city and from Qatar Foundation Nursery. The results show that Acacia grown in field are more flexible than those grown in nursery. Youngs Modulus of Elasticity was found to be 191 MPa and 617 MPa and the Flexural Modulus was found to be 49 MPa and 575 MPa and the breaking force was found to be 210 and 550 N for nursery and field Acacia, respectively. The deflection angle was measured using sensitive flex sensors connected to Arduino boards and was found to be higher for field Acacia (50{circ}). Image processing techniques were used to mathematically describe the branch motion versus time diagrams.\n\nThe plant part being investigated was covered with red tape and videotaped while subjected to a force causing it to bend. The stem was divided into 745 successive points and the change in their position with time taken frame by frame was converted into a change in position expressed through mathematical parameters. The bending movement of the branch was found to follow a power function H = (4001 - e0.06m).\n\nHighlightField grown Acacia have higher values of Youngs and Flexural Moduli than nursery grown ones thus conferring them more elasticity and flexibility.

plant biology↗