Biology subjects

Hassan, M.

Publications and source records attributed to Hassan, M..

51 records · Page 3Linked to original sources

bioRxiv2020

The dynamic modular fingerprints of the human brain at rest

The human brain is a dynamic modular network that can be decomposed into a set of modules and its activity changes permanently over time. At rest, several brain networks, known as Resting-State Networks (RSNs), emerge and cross-communicate even at sub-second temporal scale. Here, we seek to decipher the fast reshaping in spontaneous brain modularity and its relationship to RSNs. We use Electro/Magneto-Encephalography (EEG/MEG) to track dynamics of modular brain networks, in three independent datasets (N= 568) of healthy subjects at rest. We show the presence of striking spatiotemporal network pattern consistent over participants. We also show that some RSNs, such as default mode network and temporal network, are not necessary unified units but rather can be divided into multiple sub-networks over time. Using the resting state questionnaire, our results revealed also that brain network dynamics are strongly correlated to mental imagery at rest. These findings add new perspectives to brain dynamic analysis and highlight the importance of tracking fast reconfiguration of electrophysiological networks at rest.

neuroscience↗

bioRxiv2020

Clinical and genomic epidemiology of carbapenem-non-susceptible Citrobacter spp. at a tertiary healthcare center over two decades

Carbapenem-non-susceptible Citrobacter spp. (CNSC) are increasingly recognized as healthcare-associated pathogens. Information regarding their clinical epidemiology, genetic diversity, and mechanisms of carbapenem resistance is lacking. We examined microbiology records of adult patients at the University of Pittsburgh Medical Center (UMPC) Presbyterian Hospital (PUH) from 2000-2018 for CNSC, as defined by ertapenem non-susceptibility. Over this timeframe, the proportion of CNSC increased from 4% to 10% (P=0.03), as did carbapenem daily defined doses/1000 patient days (6.52 to 34.5, R2=0.831, P<0.001), which correlated with the observed increase in CNSC (lag=0 years, R2=0.660). Twenty CNSC isolates from 19 patients at PUH and other UPMC hospitals were available for further analysis, including whole-genome short-read sequencing and additional antimicrobial susceptibility testing. Of the 19 patients, nearly all acquired CNSC in the healthcare setting and over half had polymicrobial cultures containing at least one other organism. Among the 20 CNSC isolates, C. freundii was the predominant species identified (60%). CNSC genomes were compared with genomes of carbapenem-susceptible Citrobacter spp. from UPMC, and with other publicly available CNSC genomes. Isolates encoding carbapenemases (blaKPC-2, blaKPC-3, and blaNDM-1) were also long-read sequenced, and their carbapenemase-encoding plasmid sequences were compared with one another and with publicly available sequences. Phylogenetic analysis of 102 UPMC Citrobacter spp. genomes showed that CNSC from our setting did not cluster together. Similarly, a global phylogeny of 64 CNSC genomes showed a diverse population structure. Our findings suggest that both local and global CNSC populations are genetically diverse, and that CNSC harbor carbapenemase-encoding plasmids found in other Enterobacterales.

microbiology↗

bioRxiv2020

Bayesian copy number detection and association in large-scale studies

Germline copy number variants (CNVs) increase risk for many diseases, yet detection of CNVs and quantifying their contribution to disease risk in large-scale studies is challenging. We developed an approach called CNPBayes to identify latent batch effects, to provide probabilistic estimates of integer copy number across the estimated batches, and to fully integrate the copy number uncertainty in the association model for disease. We demonstrate this approach in a Pancreatic Cancer Case Control study of 7,598 participants where the major sources of technical variation were not captured by study site and varied across the genome. Candidate associations aided by this approach include deletions of 8q24 near regulatory elements of the tumor oncogene MYC and of Tumor Supressor Candidate 3 (TUSC3). This study provides a robust Bayesian inferential framework for estimating copy number and evaluating the role of copy number in heritable diseases.

genetics↗

bioRxiv2019

Multi-epitope Peptide Vaccine Prediction for Candida albicans targeting Pyruvate Kinase Protein; an Immunoinformatics Approach

The fungus Candida albicans is an opportunistic pathogen that causes a wide range of infections. Its the primary cause of candidiasis and the fourth most common cause of nosocomial infection. In addition, disseminated invasive candidiasis which is a major complication of the disease has an estimated mortality rate of 40%-60% even with the use of antifungal drugs. Over the last decades, several different anti-Candida vaccines have been suggested with different strategies for immunization against candidiasis such as, live-attenuated fungi, recombinant proteins, and glycoconjugates but none has been approved by the FDA, yet. This study aims to introduce a new possible vaccine for C. albicans through analyzing peptides of its pyruvate kinase (PK) protein as an immunogenic stimulant computationally.\n\nA total number of 28 C. albicans, pyruvate kinase proteins were obtained from NCBI on the 9th of February 2019 and were subjected to multiple sequence alignment using Bioedit for conservancy. The main analytical tool was IEDB, Chimera for homology modelling, and MOE for docking.\n\nAmong the tested peptides, fifteen promising T-cell peptides were predicted. Five peptides were more important than the others (HMIFASFIR, YRGVYPFIY, AVAAVSAAY, LRWAVSEAV, and IFASFIRTA) They show high Binding Affinity to MHC molecules, low binding energy required indicating more stable bonds, and their ideal length of nine peptides. (PTRAEVSDV) peptide is the most promising linear B-cell peptide due to its physiochemical parameters and optimal length (nine amino acids). Its highly recommended to have these five strong candidates in future in vivo and in vitro analysis studies.

bioinformatics↗

bioRxiv2019

Brain network dynamics correlates with personality traits

IntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks. ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits. MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated. ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks. ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.

bioinformatics↗

bioRxiv2019

FxR-modulates the gut-vascular barrier by regulating the entry sites for bacterial translocation in experimental cirrhosis

Background and aimsPathological bacterial translocation (PBT) in liver cirrhosis (LC) is the hallmark for spontaneous bacterial infections increasing mortality several-fold. Factors known to contribute to PBT in LC are among others an increased intestinal permeability of which however, the mucus layer has not been addressed so far in detail. A clear route of translocation for luminal intestinal bacteria is yet to be defined but we hypothesize that the recently described gut vascular barrier (GVB) is impaired in experimental portal hypertension leading to increased accessibility of the vascular compartment for translocating bacteria.\n\nResultsHealthy and pre-hepatic portal-hypertensive (PPVL) mice lack translocation of FITC-dextran and GFP-Escherichia coli from the small intestine to the liver whereas bile-duct-ligated (BDL) and CCl4-induced cirrhotic mice demonstrate pathological translocation which is not altered by prior thoracic-duct ligation. Mucus layer is reduced in thickness with loss of goblet-cells and Muc2-staining and expression in cirrhotic but not PPVL-mice associated with bacterial overgrowth in inner mucus layer and pathological translocation of GFP-E.coli through the ileal epithelium. GVB is profoundly altered in BDL and CCl4-mice with Ileal extravasation of large-sized 150 kDa-FITC-dextran but only minor in PPVL-mice. This pathological endothelial permeability and accessibility in cirrhotic mice associates with an augmented expression of PV1 in intestinal vessels. OCA but not fexaramine stabilizes the GVB whereas both FXR-agonists ameliorate gut-liver-translocation of GFP-E.coli.\n\nConclusionsLiver cirrhosis but not portal hypertension per se grossly impairs the endothelial and muco-epithelial barriers promoting PBT to the portal-venous circulation. Both barriers appear FXR-modulated with -agonists reducing PBT via the portal-venous route.

physiology↗

bioRxiv2019

Removing zero-lag functional connections can alter EEG source space networks at rest

Electro-encephalography (EEG) source connectivity is an emerging approach to estimate brain networks with high time/space resolution. Here, we aim to evaluate the effect of different functional connectivity (FC) methods on the EEG-source space networks at rest. The two main families of FC methods tested are: i) the FC methods that do not remove the zero-lag connectivity including the Phase Locking Value (PLV) and the Amplitude Envelope Correlation (AEC) and ii) the FC methods that remove the zero-lag connections such as the Phase Lag Index (PLI) and orthogonalisation approach combined with PLV (PLVorth) and AEC (AECorth). Methods are evaluated on resting state dense-EEG signals recorded from 20 healthy participants. Networks obtained by each FC method are compared with fMRI networks at rest (from the Human Connectome Project -HCP-, N=487). Results show low correlations for all the FC methods, however PLV and AEC networks are significantly correlated with fMRI networks ({rho} = 0.12, p = 1.93x10-8 and {rho} = 0.06, p = 0.007, respectively), while other methods are not. These observations are consistent for each EEG frequency bands and for different FC matrices threshold. Furthermore, the effect of electrode density was also tested using four EEG montages (dense-EEG 256 electrodes, 128, 64 and 32 electrodes). Results show no significant differences between the four EEG montages in terms of correlations with the fMRI networks. Our main message here is to be careful when selecting the FC methods and mainly those that remove the zero-lag connections as they can affect the network characteristics. More comparative studies (based on simulation and real data) are still needed in order to make EEG source connectivity a mature technique to address questions in cognitive and clinical neuroscience.

neuroscience↗

bioRxiv2019

Detecting M/EEG modular brain states in rest and task

The human brain is a dynamic networked system that continually reconfigures its connectivity patterns over time. Thus, developing approaches able to adequately detect fast brain dynamics is critical. Of particular interest are the methods that analyze the modular structure of brain networks, i.e. the presence of clusters of regions that are densely inter-connected. In this paper, we propose a novel framework to identify fast modular states that dynamically fluctuate over time during rest and task. We validated our method using MEG data recorded during a finger movement task, identifying modular states linking somatosensory and primary motor regions. The algorithm was also validated on dense-EEG data recorded during picture naming task, revealing the sub-second transition between several modular states which relate to visual processing, semantic processing and language. Next, we validated our method on a dataset of resting state dense-EEG signals recorded from 124 patients with Parkinson disease and different cognitive phenotypes. Results disclosed brain modular states that differentiate cognitively intact patients, patients with moderate cognitive deficits and patients with severe cognitive deficits. Our new approach tracks the brain modular states, in healthy subjects and patients, on an adequate task-specific timescale.

neuroscience↗

bioRxiv2018

Decreased integration of EEG source-space networks in disorders of consciousness

Increasing evidence links disorders of consciousness (DOC) with disruptions in functional connectivity between distant brain areas. However, to which extent the balance of brain network segregation and integration is modified in DOC patients remains unclear. Using high-density electroencephalography (EEG), the objective of our study was to characterize the local and global topological changes of DOC patients functional brain networks.\n\nResting state high-density-EEG data were collected and analyzed from 82 participants: 61 DOC patients recovering from coma with various levels of consciousness (EMCS (n=6), MCS+ (n=29), MCS- (n=17) and UWS (n=9)), and 21 healthy subjects (i.e., controls). Functional brain networks in five different EEG frequency bands and the broadband signal were estimated using an EEG connectivity approach at the source level. Graph theory-based analyses were used to evaluate group differences between healthy volunteers and patient groups.\n\nResults showed that networks in DOC patients are characterized by impaired global information processing (network integration) and increased local information processing (network segregation) as compared to controls. The large-scale functional brain networks had integration decreasing with lower level of consciousness.

neuroscience↗

bioRxiv2018

Probing the circuits of conscious perception with magnetophosphenes

BackgroundConscious perception is thought to involve the large-scale, coordinated activation of distant brain regions, a process termed ignition in the Global Workspace Theory and integration in Integrated Information Theory, which are two of the major theories of consciousness.\n\nMethodsHere, we provide evidence for this process in humans by combining a magnetically-induced phosphene perception task with electroencephalography. Functional cortical networks were identified and characterized using graph theory to quantify the impact of conscious perception on local (segregation) and distant (integration) processing.\n\nResultsConscious phosphene perception activated frequency-specific networks, each associated with a specific spatial scale of information processing. Integration increased within an alpha-band functional network, while segregation occurred in the beta band.\n\nConclusionsThese results bring novel evidence for the functional role of distinct brain oscillations and confirm the key role of integration processes for conscious perception in humans.

neuroscience↗

bioRxiv2018

Immunoinformatics Prediction of Epitope Based Peptide Vaccine Against Madurella mycetomatis Translationally Controlled Tumor Protein

BackgroundMadurella. mycetomatis is most common causative agent of mycetoma in Sudan and worldwide. No vaccines are available till now so design of effective vaccine is essential as protection tool. Peptide vaccine can overcome the common side effects of the conventional vaccines. The aim of this study was to design peptide based vaccine for M.Mycetomatis Translationally Controlled Tumor Protein (TCTP) using immunoinformatics tools.\n\nMaterials and methodsTCTP sequences were retrieved from NCBI and then processed using BioEdit program to determine conserved regions and different immunoinformatics tools from IEDB. Population coverage analysis was performed for the most promising epitopes. Homology modelling was performed to show their structural positions in TCTP. Protein analysis was done using Expasy (ProtParamsotware).\n\nResults and conclusionFour epitopes passed the Bepipred, Emini, Kolaskar and Tongaonkar tools. 111 epitopes were predicted to interact with MHCI alleles with IC50 < 500 nM, three of them were most promising. 274 predicted epitopes were interacted with MHCII alleles with IC50 < 100 nM, four of them were most promising. The epitope (YMKSVKKAL) was the most promising one concerning its binding with MHCI alleles, while (FRLQSTSFD) was the most promising for MHC II. The epitope (YLKAYMKSV) is shared betweenMHC I and II. For the population coverage of M. Mycetomatis TCTP vaccine Sudan (90.39%) had the highest percentage for MHC I. This is the first computational vaccinology study conducted in mycetoma caused by M. Mycetomatis using TCTP.

bioinformatics↗

bioRxiv2018

Psychological resilience correlates with EEG source-space brain network flexibility

ObjectiveWe aimed at identifying the potential relationship between the dynamical properties of the human functional network at rest and one of the most prominent traits of personality, namely resilience.\n\nApproachTo tackle this issue, we used resting-state EEG data recorded from 45 healthy subjects. Resilience was quantified using the 10-items Connor-Davidson Resilience Scale (CD-RISC). Using a sliding windows approach, brain networks in each EEG frequency band (delta, theta, alpha and beta) were constructed using the EEG source-space connectivity method. Brain networks dynamics were evaluated using the network flexibility, linked with the tendency of a given node to change its modular affiliation over time.\n\nMain ResultsThe results revealed a negative correlation between the psychological resilience and the brain network flexibility for a limited number of brain regions within the delta, alpha and beta bands.\n\nSignificanceThis study provides evidence that network flexibility, a metric of dynamic functional networks, is strongly correlated with psychological resilience as assessed from personality testing. Beyond this proof-of-principle that reliable EEG-based quantities representative of personality traits can be identified, this motivates further investigation regarding the full spectrum of personality aspects and their relationship with functional networks.

neuroscience↗

bioRxiv2018

Novel deleterious nsSNPs within MEFV gene that could be used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using bioinformatics analysis

BackgroundFamilial Mediterranean Fever (FMF) is the most common auto inflammatory disease (AID) affecting mainly the ethnic groups originating from Mediterranean basin, we aimed to identify the pathogenic SNPs in MEFV by computational analysis software.\n\nMethodsWe carried out in silico prediction of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structure and function.\n\nResult23 novel mutations out of 857 nsSNPs that are found to be deleterious effect on the MEFV structure and function.\n\nConclusionThis is the first in silico analysis in MEFV gene to prioritize SNPs for further genetic mapping studies. After using multiple bioinformatics tools to compare and rely on the results predicted, we found 23 novel mutations that may cause FMF disease and it could be used as diagnostic markers for Mediterranean basin populations.

bioinformatics↗

bioRxiv2018

Diagnostic Use of PCR in Carbapenamase-producing Enterobacteriaceae (CPE): An Improved Method to Overcome the presence of inhibitors for DNA Extraction from Blood Cultures

BackgroundCarpanenamase-producing Enterobacteriaceae (CPE) has emerged as a threat to hospitalized patients. Phenotypic test such as Modified hodge test was less sensitive and specific especially to detect blaNDM-1 which is the most predominant genotype in this region. Nucleic acid amplification technology offers improved specificity and sensitivity. However, there is limitation in this method which is failed amplification due to the presence of inhibitors. In this study, we try to use previous method described by Villumseen et al with some modification using another DNA extraction kit.\n\nMethodology/Principle findingsThree confirmed isolates of blaNDM-1 carbapenamase-producing Klebsiella pneumoniae was spiked with 10 mls sterile whole blood in an aerobic Bactec Plus until the growth was detected. The blood specimen was taken and was subjected to DNA extraction method using two commercialized kits followed with multiplex PCR. All the three isolates revealed blaNDM-1 genotypes. Internal control was amplified in all three isolates.\n\nConclusion/significanceThis study proved that we can get a specific and early diagnosis of CPE by using nucleic acid amplification technique directly from blood culture bottle and eliminate the effect of inhibitors.

microbiology↗

bioRxiv2018

Competing endogenous RNA network: Potential entrants to gene editing in Hepatocellular Carcinoma

BackgroundHepatocellular Carcinoma (HCC) is the leading cause of cancer deaths worldwide as well as in Egypt. We aimed to use Clustered Regulatory Interspaced Short Palindromic Repeats (CRISPR) gene editing technique to induce forced down-regulation of the circRNA which consequently modified miRNA expression in HepG2 cell line to prove the regulatory relationship between the RNA parts of an in silico-detected competing endogenous RNA network in HCC\n\nMethodWe first retrieved hsa_circ_0000064-miR-1285-TRIM2 mRNA from public microarray databases followed by in silico modelling to mimic the regulation kinetics of cirRNA associated ceRNA network. Secondly, we performed polymerase chain reaction (PCR)-based amplification of synthetic fragments, Gibson assembly of both CRISPR and non CRISPR based circuits, E-coli transformation, plasmid purification, HePG2 cell line transfection. Finally Expression levels of the chosen RNAs in hepatocellular carcinoma (HCC) cell line, HepG2, were examined by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and the cytotoxic effect was validated by viability assay.TRIM2 protein expression was proved by immunohistochemistry and flowcytometry.\n\nResultsInduction of hsa_circ_0000064 into HepG2 cell line via CRISPR-and non-CRISPR mediated synthetic circuit resulted in statistically significant decrease in cell number and, then, cellular viability with marked increase in hsa_circ_0000064 and TRIM2 mRNA levels and concomitant decrease in miR-1285 expression in HepG2 cell line compared with control (p<0.0). Moreover exogenous expression of hsa_circ_0000064 in HepG2 cell line showed increased expression of the tumor suppressor protein, TRIM2.\n\nConclusionsOur integrative approach, including in silico data analysis and experimental validation proved that CRISPR-mediated synthetic circuit-based overexpression of hsa_circ_0000064 was more efficient than conventional transient transfection, representing a promising therapeutic strategy for HCC.\n\nData AvailabilityOur Data was made available online on the IGEM wiki of team AFCM-EGYPT: http://2017.igem.org/Team:AFCM-Egypt. Synthetic parts have been submitted to IGEM Parts Registry.\n\nFinancial DisclosureThe project was funded by Armed Forces College of Medicine AFCM, Zewail City of Science and Technology, National Research Center NRC, VitaBiotics, PHARCO Pharmaceuticals, Sim Era and DANUB Paintings. IDT provided 20 kb of DNA synthesis. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

bioengineering↗