Biology subjects

Ali, S.

Publications and source records attributed to Ali, S..

118 records · Page 7Linked to original sources

bioRxiv2019

Quantitative assessment of fecal contamination in multiple environmental sample types in urban communities in Dhaka, Bangladesh using SaniPath microbial approach

Rapid urbanization has led to a growing sanitation crisis in urban areas of Bangladesh and potential exposure to fecal contamination in the urban environment due to inadequate sanitation and poor fecal sludge management. Limited data are available on environmental fecal contamination associated with different exposure pathways in urban Dhaka. We conducted a cross-sectional study to explore the magnitude of fecal contamination in the environment in low-income, high-income, and transient/floating neighborhoods in urban Dhaka. Ten samples were collected from each of 10 environmental compartments in 10 different neighborhoods (4 low-income, 4 high-income and 2 transient/floating neighborhoods). These 1,000 samples were analyzed with the IDEXX-Quanti-Tray technique to determine most-probable-number (MPN) of E. coli. Samples of open drains (6.91 log10 MPN/100 mL), surface water (5.28 log10 MPN/100 mL), floodwater (4.60 log10 MPN/100 mL), produce (3.19 log10 MPN/serving), soil (2.29 log10 MPN/gram), and street food (1.79 log10 MPN/gram) had the highest mean log10 E. coli contamination compared to other samples. The contamination concentrations did not differ between low-income and high-income neighborhoods for shared latrine swabs, open drains, municipal water, produce, and street foodsamples. E. coli contamination were significantly higher (p <0.05) in low-income neighborhoods compared to high-income for soil (0.91 log10 MPN/gram, 95% CI, 0.39, 1.43), bathing water (0.98 log10 MPN/100 mL, 95% CI, 0.41, 1.54), non-municipal water (0.64 log10 MPN/100 mL, 95% CI, 0.24, 1.04), surface water (1.92 log10 MPN/100 mL, 95% CI, 1.44, 2.40), and floodwater (0.48 log10 MPN/100 mL, 95% CI, 0.03, 0.92) samples. E. coli contamination were significantly higher (p<0.05) in low-income neighborhoods compared to transient/floating neighborhoods for drain water, bathing water, non-municipal water and surface water. Future studies should examine behavior that brings people into contact with the environment and assess the extent of exposure to fecal contamination in the environment through multiple pathways and associated risks.

microbiology↗

bioRxiv2019

Automated Cytogenetic Biodosimetry at Population-Scale

IntroductionThe dicentric chromosome (DC) assay accurately quantifies exposure to radiation, however manual and semi-automated assignment of DCs has limited its use for a potential large-scale radiation incident. The Automated Dicentric Chromosome Identifier and Dose Estimator Chromosome (ADCI) software automates unattended DC detection and determines radiation exposures, fulfilling IAEA criteria for triage biodosimetry. We present high performance ADCI (ADCI-HT), with the requisite throughput to stratify exposures of populations in large scale radiation events.\n\nMethodsADCI-HT streamlines dose estimation by optimal scheduling of DC detection, given that the numbers of samples and metaphase cell images in each sample vary. A supercomputer analyzes these data in parallel, with each processor handling a single image at a time. Processor resources are managed hierarchically to maximize a constant stream of sample and image analysis. Metaphase data from populations of individuals with clinically relevant radiation exposures after simulated large nuclear incidents were analyzed. Sample counts were derived from US Census data. Analysis times and exposures were quantified for 15 different scenarios.\n\nResultsProcessing of metaphase images from 1,744 samples (500 images each) used 16,384 CPUs and was completed in 1hr 11min 23sec, with radiation dose of all samples determined in 32 sec with 1,024 CPUs. Processing of 40,000 samples with varying numbers of metaphase cells, 10 different exposures from 5 different biodosimetry labs met IAEA accuracy criteria (dose estimate differences were < 0.5 Gy; median = 0.07) and was completed in ~25 hours. Population-scale metaphase image datasets within radiation contours of nuclear incidents were defined by exposure levels (either >1 Gy or >2 Gy). The time needed to analyze samples of all individuals receiving exposures from a high yield airborne nuclear device ranged from 0.6-7.4 days, depending on the population density.\n\nConclusionADCI-HT delivers timely and accurate dose estimates in a simulated population-scale radiation incident.

bioinformatics↗

bioRxiv2019

Transmembrane 163 (TMEM163) protein effluxes zinc

Recent investigations of rodent Tmem163 suggest that it binds to and transports zinc as a dimer, and that alanine mutagenesis of its two species-conserved aspartate (D123A/D127A) residues proposed to bind zinc perturbs protein function. Direct corroboration, however, is lacking whether it is an influx or efflux transporter in cells. We hypothesized that human TMEM163 is a zinc effluxer based on its predicted protein characteristics. We used cultured human cell lines that either stably or transiently expressed TMEM163, and pre-loaded the cells with zinc to determine transport activity. We found that TMEM163-expressing cells exhibited significant reduction of intracellular zinc levels as evidenced by two zinc-specific fluorescent dyes and radionuclide zinc-65. The specificity of the fluorescence signal was confirmed upon treatment with TPEN, a high-affinity zinc chelator. Multiple sequence alignment and phylogenetic analyses showed that TMEM163 is related to distinct members of the cation diffusion facilitator (CDF) protein family. To further characterize the efflux function of TMEM163, we substituted alanine in two homologous aspartate residues (D124A/D128A) and performed site-directed mutagenesis of several conserved amino acid residues identified as non-synonymous single nucleotide polymorphism (S61R, S95C, S193P, and E286K). We found a significant reduction of zinc efflux upon cellular expression of D124A/D128A or E286K protein variant when compared with wild-type, suggesting that these particular amino acids are important for normal protein function. Taken together, our findings demonstrate that TMEM163 effluxes zinc and should now be designated ZNT11, as a new member of the mammalian CDF family of zinc efflux transporters.

cell biology↗

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

Identification of key regulators in Prostate cancer from gene expression datasets of patients

Identification of key regulators and regulatory pathways is an important step in the discovery of genes involved in cancer. Here, we propose a method to identify key regulators in prostate cancer (PCa) from a network constructed from gene expression datasets of PCa patients. Overexpressed genes were identified using BioXpress, having a mutational status according to COSMIC, followed by the construction of PCa Interactome network using the curated genes. The topological parameters of the network exhibited power law nature indicating hierarchical scale-free properties and five levels of organization. Highest degree hubs (k[≥]65) were selected from the PCa network, traced, and 19 of them were identified as novel key regulators, as they participated at all network levels serving as backbone. Of the 19 hubs, some have been reported in literature to be associated with PCa and other cancers. Based on participation coefficient values most of these are connector or kinless hubs suggesting significant roles in modular linkage. The observation of non-monotonicity in the rich club formation suggested the importance of intermediate hubs in network integration, and they may play crucial roles in network stabilization. The network was self-organized as evident from fractal nature in topological parameters of it and lacked a central control mechanism.

systems biology↗

bioRxiv2019

Functional dissection of TADs reveals non-essential and instructive roles in regulating gene expression

The genome is organized in megabase-sized three-dimensional units, called Topologically Associated Domains (TADs), that are separated by boundaries. TADs bring distant cis-regulatory elements into proximity, a process dependent on the cooperative action of cohesin and the DNA binding factor CTCF. Surprisingly, genome-wide depletion of CTCF has little effect on transcription, yet structural variations affecting TADs have been shown to cause gene misexpression and congenital disease. Here, we investigate TAD function in vivo in mice by systematically editing components of TAD organization at the Sox9/Kcnj locus. We find that TADs are formed by a redundant system of CTCF sites requiring the removal of all major sites within the TAD and at the boundary for two neighboring TADs to fuse. TAD fusion resulted in leakage of regulatory activity from the Sox9 to the Kcnj TAD, but no major changes in gene expression. This indicates that TAD structures provide robustness and precision, but are not essential for developmental gene regulation. Gene misexpression and resulting disease phenotypes, however, were attained by re-directing regulatory activity through inversions and/or the re-positioning of boundaries. Thus, efficient re-wiring of enhancer promoter interaction and aberrant disease causing gene activation is not induced by a mere loss of insulation but requires the re-direction of contacts.

genetics↗

bioRxiv2019

ApicoTFdb: The comprehensive web repository of apicomplexan transcription factors and regulators.

Despite significant progress in apicomplexans genome sequencing and genomics, the current list of experimentally validated TFs in these genomes is incomplete and mainly consists of AP2 family of proteins, with only a limited number of non-AP2 family TFs and TAFs. We have performed systematic bioinformatics aided prediction of TFs and TAFs in apicomplexan genomes, and developed ApicoTFdb database which consists of experimentally validated as well as computationally predicted TFs and TAFs in 14 apicomplexan species. The predicted TFs are manually curated to complement the existing annotations. The current version of the database includes 1310 TFs, out of which 833 are novel and computationally predicted TFs, representing 22 distinct families across 14 apicomplexan species. The predictions include TFs of TUB, NAC, BSD, CCAAT, HTH, Cupin/Jumonji, winged-helix, and FHA family proteins, not reported earlier in the genomes. Apart from TFs, ApicoTFdb also classifies TAFs into three main subclasses-TRs, CRRs and RNARs, representing 3047 TAFs in 14 apicomplexan species are analyzed in this study. The database is equipped with a set of useful tools for comparative analysis of a user-defined list of the proteins. ApicoTFdb will be useful to the researchers interested in less-studied gene regulatory mechanisms mediating the complex life cycle of the apicomplexan parasites. The database will aid the discovery of novel drug targets to much needed combat the growing drug resistance in the parasites.

bioinformatics↗

bioRxiv2018

Stage specific classification of DEGs via statistical profiling and network analysis reveals potential biomarker associated with various stages of TB

BackgroundTuberculosis (TB) is a deadly transmissible disease that can infect almost any body-part of the host but is mostly infect the lungs. It is one of the top 10 causes of death worldwide. In the 30 high TB burden countries, 87% of new TB cases occurred in 2016. Seven countries: India, Indonesia, China, Philippines, Pakistan, Nigeria, and South Africa accounted for 64% of the new TB cases. To stop the infection and progression of the disease, early detection of TB is important. In our study, we used microarray data set and compared the gene expression profiles obtained from blood samples of patients with different datasets of Healthy control, Latent infection, Active TB and performed network-based analysis of DEGs to identify potential biomarker.\n\nObjectivesWe want to observe the transition of genes from normal condition to different stages of the TB and identify, annotate those genes/pathways/processes that play key role in the progression of TB disease during its cyclic interventions in human body.\n\nResultsWe identified 319 genes that are differentially expressed in various stages of TB (Normal to LTTB, Normal to Active TB and LTTB to active TB) and allocated to pathways from multiple databases which comprised of curated class of associated genes. These pathways importance was then evaluated according to the no. of DEGs present in the pathway and these genes show the broad spectrum of processes that take part in every state. In addition, we studied the regulatory networks of these classified genes, network analysis does consider the interactions between genes (specific for TB) or proteins provide us new facts about TB disease, which in turn can be used for potential biomarkers identification. We identified total 29 biomarkers from various comparison groups of TB stages in which 14 genes are over expressed as host responses against pathogen, but 15 genes are down regulated that means these genes has allowed the process of host defense to cease and give time to pathogen for its progression.\n\nConclusionsThis study revealed that gene-expression profiles can be used to identify and classified the genes on stage specific pattern among normal, LTTB and active TB and network modules associated with various stages of TB were elucidated, which in turn provided a basis for the identification of potential pathways and key regulatory genes that may be involved in progression of TB disease.

systems biology↗

bioRxiv2018

Retronasal Habituation: Characterization and Impact on Flavor Perception using Time-Intensity

Olfactory habituation results from prolonged exposure to an odor, leading to perceptual changes defined by several characteristics. To date, human habituation research has focused on orthonasal olfaction which is perceived externally while ignoring internal routes of odor perception related to flavor. In our study, we conducted two experiments to characterize retronasal olfactory habituation and measured its impact on flavor perception. In Experiment 1, 22 participants rhythmically breathed a food odor (lime), non-food odor (lavender), and blank (propylene glycol) that was presented using an orally-adhered strip, while rating the odor intensity using the time-intensity procedure. After a 10-minute exposure, the participants ate a lime-flavored gummy and rated the lime flavor. In Experiment 2, the same procedure was performed for a low-level lime odor, a simple (lime oil) and complex (lime oil + sucrose + citric acid) beverage as the flavor stimuli. Our results demonstrated two known principles of habituation for retronasally presented odors: 1) prolonged exposure lead to decreased perception, 2) weaker stimuli lead to more rapid habituation. Additionally, we found that the non-food odor habituated slower than the food odor; however, the participants seemed to recover simultaneously upon food and beverage consumption leading to no change in flavor perception.

neuroscience↗

bioRxiv2017

Quantitative variation and evolution of spatially explicit morphogen expression in Drosophila

Robustness in development allows for the accumulation of neutral genetically based variation in expression, and here will be termed genetic stochasticity . This largely neutral variation is potentially important for both evolution and complex disease phenotypes. However, it has generally only been investigated as variation exhibited in the response to large genetic perturbations. In addition, work on variation in gene expression has similarly generally been limited to being spatial, or quantitative, but because of technical restrictions not both. Here we bridge these gaps by investigating replicated quantitative spatial gene expression using rigorous statistical models, in different genotypes, sexes, and species (Drosophila melanogaster and D. simulans). Using this type of quantitative approach with developmental data allows for effective comparison among conditions, including health versus disease. We apply this approach to the morphogenetic furrow, a wave of differentiation that sweeps across the developing eye disc. Within the morphogenetic furrow, we focus on four conserved morphogens, hairy, atonal, hedgehog, and Delta. Hybridization chain reaction quantitatively measures spatial gene expression, co-staining for all four genes simultaneously and with minimal effort. We find considerable variation in the spatial expression pattern of these genes in the eye between species, genotypes, and sexes. We also find that there has been evolution of the regulatory relationship between these genes. Lastly, we show that the spatial interrelationships of these genes evolved between species in the morphogenetic furrow. This is essentially the first population genetics of development as we are able to evaluate wild type differences in spatial and quantitative gene expression at the level of genotype, species and sex.

developmental biology↗