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Biology subjects

Noor, A.

Publications and source records attributed to Noor, A..

6 recordsLinked to original sources

Seizures in a Dravet Syndrome mouse model inhibit the locus coeruleus but locally evoke supraphysiologic norepinephrine release

Locus coeruleus (LC) neurons are the primary source of norepinephrine / noradrenaline (NE) released to most brain structures, including seizure-prone neocortical and limbic regions. LC-NE networks regulate numerous physiological processes, including arousal, attention, and memory. Previous evidence suggests that LC-NE neurons may be involved in epilepsy and that their activation may have therapeutic effects on seizures, but the endogenous activity of the LC-NE network during seizures remains largely unclear. We combined electrocorticography recordings and in vivo imaging to measure somatic activity of LC-NE neurons as well as downstream NE release during hyperthermia-induced seizures in a well-characterized pre-clinical model of Dravet Syndrome. We found that population LC-NE somatic activity was inhibited during seizures, whereas downstream NE release was dramatically elevated. To reconcile these discordant findings, we established that activation of downstream regions is capable of locally evoking NE release, in part via activation of glutamate receptors, consistent with the Glutamate Amplifies Noradrenergic Effects (GANE) model. Finally, we confirmed that ictal NE release occurred across additional downstream brain regions, epilepsy models, and seizure induction methods. Thus, disruption of NE signaling is likely a widespread ictal signature, with implications for impaired consciousness during and after seizures.

neuroscience↗

Optimized Blue Laser Priming Improves Lettuce Seed Germination and Early Seedling Establishment Under Reduced Water Availability

Continuous-wave (CW) 450 nm blue diode-laser irradiation was evaluated as a physical seed-priming treatment for improving lettuce (Lactuca sativa L.) germination and early seedling establishment under reduced water availability. Dry seeds were irradiated at 50-250 mW for 2 min and at 100 mW for 0.5-10 min; each condition included three independent Petri-dish replicates with 100 seeds per replicate, and the replicates were monitored for 72 h. Laser treatment produced a dose-dependent biological response. The optimized condition, 100 mW for 2 min, increased final germination from approximately 65-70% to 90-95%, increased the germination speed index, and promoted root elongation more strongly than shoot elongation. Longer exposures reduced germination and seedling growth. Under reduced water availability (0.5-6 ml per Petri dish), laser-treated seeds germinated earlier, maintained final germination of 83-93% compared with 57-72% in controls, and produced better-developed seedlings. The relative benefit increased as water availability decreased, indicating that optimized blue laser priming partially compensated for low water supply during germination and early establishment. These results identify CW blue laser priming as a contactless, chemical-free approach for improving lettuce seed performance and early seedling vigor under limited water availability.

plant biology↗

D4: Deep Drug-drug interaction Discovery and Demystification

MotivationDrug-drug interactions (DDIs) are complex processes which may depend on many clinical and non-clinical factors. Identifying and distinguishing ways in which drugs interact remains a challenge. To minimize DDIs and to personalize treatment based on accurate stratification of patients, it is crucial that mechanisms of interaction can be identified. Most DDIs are a consequence of metabolic mechanisms of interaction, but DDIs with different mechanisms occur less frequently and are therefore more difficult to identify. ResultsWe developed a method (D4) for computationally identifying potential DDIs and determining whether they interact based on one of eleven mechanisms of interaction. D4 predicts DDIs and their mechanisms through features that are generated through a deep learning approach from phenotypic and functional knowledge about drugs, their side-effects and targets. Our findings indicate that our method is able to identify known DDIs with high accuracy and that D4 can determine mechanisms of interaction. We also identify numerous novel and potential DDIs for each mechanism of interaction and evaluate our predictions using DDIs from adverse event reporting systems. Availabilityhttps://github.com/bio-ontology-research-group/D4 Contactarnoor@kau.edu.sa and robert.hoehndorf@kaust.edu.sa

bioinformatics↗

Common DNA sequence variation influences 3-dimensional conformation of the human genome

The 3-dimensional (3D) conformation of chromatin inside the nucleus is integral to a variety of nuclear processes including transcriptional regulation, DNA replication, and DNA damage repair. Aberrations in 3D chromatin conformation have been implicated in developmental abnormalities and cancer. Despite the importance of 3D chromatin conformation to cellular function and human health, little is known about how 3D chromatin conformation varies in the human population, or whether DNA sequence variation between individuals influences 3D chromatin conformation. To address these questions, we performed Hi-C on Lymphoblastoid Cell Lines (LCLs) from 20 individuals. We identified thousands of regions across the genome where 3D chromatin conformation varies between individuals and found that this conformational variation is often accompanied by variation in gene expression, histone modifications, and transcription factor (TF) binding. Moreover, we found that DNA sequence variation influences several features of 3D chromatin conformation including loop strength, contact insulation, contact directionality and density of local cis contacts. We mapped hundreds of Quantitative Trait Loci (QTLs) associated with 3D chromatin features and found evidence that some of these same variants are associated at modest levels with other molecular phenotypes as well as complex disease risk. Our results demonstrate that common DNA sequence variants can influence 3D chromatin conformation, pointing to a more pervasive role for 3D chromatin conformation in human phenotypic variation than previously recognized.

genomics↗

Ontology-based prediction of cancer driver genes

Identifying and distinguishing cancer driver genes among thousands of candidate mutations remains a major challenge. Accurate identification of driver genes and driver mutations is critical for advancing cancer research and personalizing treatment based on accurate stratification of patients. Due to inter-tumor genetic heterogeneity, many driver mutations within a gene occur at low frequencies, which make it challenging to distinguish them from non-driver mutations. We have developed a novel method for identifying cancer driver genes. Our approach utilizes multiple complementary types of information, specifically cellular phenotypes, cellular locations, functions, and whole body physiological phenotypes as features. We demonstrate that our method can accurately identify known cancer driver genes and distinguish between their role in different types of cancer. In addition to confirming known driver genes, we identify several novel candidate driver genes. We demonstrate the utility of our method by validating its predictions in nasopharyngeal cancer and colorectal cancer using whole exome and whole genome sequencing.

bioinformatics↗

Mapping Autosomal Recessive Intellectual Disability: Combined Microarray and Exome Sequencing Identifies 26 Novel Candidate Genes in 192 Consanguineous Families

Approximately 1% of the global population is affected by intellectual disability (ID), and the majority receive no molecular diagnosis. Previous studies have indicated high levels of genetic heterogeneity, with estimates of more than 2500 autosomal ID genes, the majority of which are autosomal recessive (AR). Here, we combined microarray genotyping, homozygosity-by-descent (HBD) mapping, copy number variation (CNV) analysis, and whole exome sequencing (WES) to identify disease genes/mutations in 192 multiplex Pakistani and Iranian consanguineous families with non-syndromic ID. We identified definite or candidate mutations (or CNVs) in 51% of families in 72 different genes, including 26 not previously reported for ARID. The new ARID genes include nine with loss-of-function mutations (ABI2, MAPK8, MPDZ, PIDD1, SLAIN1, TBC1D23, TRAPPC6B, UBA7, and USP44), and missense mutations include the first reports of variants in BDNF or TET1 associated with ID. The genes identified also showed overlap with de novo gene sets for other neuropsychiatric disorders. Transcriptional studies showed prominent expression in the prenatal brain. The high yield of AR mutations for ID indicated that this approach has excellent clinical potential and should inform clinical diagnostics, including clinical whole exome and genome sequencing, for populations in which consanguinity is common. As with other AR disorders, the relevance will also apply to outbred populations.

genetics↗