11 research outputs found
Exploring computational approaches to design mRNA Vaccine against vaccinia and Mpox viruses
Background: Messenger RNA (mRNA) vaccines emerged as a powerful tool in the fight against infections. Unlike traditional vaccines, this unique type of vaccine elicits robust and persistent innate and humoral immune response with a unique host cellâmediated pathogen gene expression and antigen presentation. Methods: This offers a novel approach to combat poxviridae infections. From the genome of vaccinia and Mpox viruses, three key genes (E8L, E7R, and H3L) responsible for virus attachment and virulence were selected and employed for designing the candidate mRNA vaccine against vaccinia and Mpox viral infection. Various bioinformatics tools were employed to generate (B cell, CTL, and HTL) epitopes, of which 28 antigenic and immunogenic epitopes were selected and are linked to form the mRNA vaccine construct. Additional components, including a 5âČ cap, 5âČ UTR, adjuvant, 3âČ UTR, and poly(A) tail, were incorporated to enhance stability and effectiveness. Safety measures such as testing for human homology and in silico immune simulations were implemented to avoid autoimmunity and to mimics the immune response of human host to the designed mRNA vaccine, respectively. The mRNA vaccine's binding affinity was evaluated by docking it with TLRâ2, TLRâ3, TLRâ4, and TLRâ9 receptors which are subsequently followed by molecular dynamics simulations for the highest binding one to predict the stability of the binding complex. Results: With a 73% population coverage, the mRNA vaccine looks promising, boasting a molecular weight of 198 kDa and a molecular formula of C8901H13609N2431O2611S48 and it is said to be antigenic, nontoxic and nonallergic, making it safe and effective in preventing infections with Mpox and vaccinia viruses, in comparison with other insilicoâdesigned vaccine for vaccinia and Mpox viruses. Conclusions: However, further validation through in vivo and in vitro techniques is underway to fully assess its potential
Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke.
OBJECTIVE: For 3,670 stroke patients from the United Kingdom, United States, Australia, Belgium, and Italy, we performed a genome-wide meta-analysis of white matter hyperintensity volumes (WMHV) on data imputed to the 1000 Genomes reference dataset to provide insights into disease mechanisms. METHODS: We first sought to identify genetic associations with white matter hyperintensities in a stroke population, and then examined whether genetic loci previously linked to WMHV in community populations are also associated in stroke patients. Having established that genetic associations are shared between the 2 populations, we performed a meta-analysis testing which associations with WMHV in stroke-free populations are associated overall when combined with stroke populations. RESULTS: There were no associations at genome-wide significance with WMHV in stroke patients. All previously reported genome-wide significant associations with WMHV in community populations shared direction of effect in stroke patients. In a meta-analysis of the genome-wide significant and suggestive loci (p < 5 Ă 10(-6)) from community populations (15 single nucleotide polymorphisms in total) and from stroke patients, 6 independent loci were associated with WMHV in both populations. Four of these are novel associations at the genome-wide level (rs72934505 [NBEAL1], p = 2.2 Ă 10(-8); rs941898 [EVL], p = 4.0 Ă 10(-8); rs962888 [C1QL1], p = 1.1 Ă 10(-8); rs9515201 [COL4A2], p = 6.9 Ă 10(-9)). CONCLUSIONS: Genetic associations with WMHV are shared in otherwise healthy individuals and patients with stroke, indicating common genetic susceptibility in cerebral small vessel disease.Funding for collection, genotyping, and analysis of stroke samples was provided by Wellcome Trust Case Control Consortium-2, a functional genomics grant from the Wellcome Trust (DNA-Lacunar), the Stroke Association (DNA-lacunar), the Intramural Research Program of National Institute of Ageing (Massachusetts General Hospital [MGH] and Ischemic Stroke Genetics Study [ISGS]), National Institute of Neurological Disorders and Stroke (Siblings With Ischemic Stroke Study, ISGS, and MGH), the American Heart Association/Bugher Foundation Centers for Stroke Prevention Research (MGH), Deane Institute for Integrative Study of Atrial Fibrillation and Stroke (MGH), National Health and Medical Research Council (Australian Stroke Genetics Collaborative), and Italian Ministry of Health (Milan). Additional support for sample collection came from the Medical Research Council, National Institute of Health Research Biomedical Research Centre and Acute Vascular Imaging Centre (Oxford), Wellcome Trust and Binks Trust (Edinburgh), and Vascular Dementia Research Foundation (Munich). MT is supported by a project grant from the Stroke Association (TSA 2013/01). HSM is supported by an NIHR Senior Investigator award. HSM and SB are supported by the NIHR Cambridge University Hospitals Comprehensive Biomedical Research Centre. VT and RL are supported by grants from FWO Flanders. PR holds NIHR and Wellcome Trust Senior Investigator Awards. PAS is supported by an MRC Fellowship. CMLâs research is supported by the National Institute for Health Research Biomedical Research Centre (BRC) based at Guy's and St Thomas' NHS Foundation Trust and King's College London, and the BRC for Mental Health at South London and Maudsley NHS Foundation Trust and Kingâs College London.âThis is the final version of the article. It first appeared from Wolters Kluwer via http://dx.doi.org/10.1212/WNL.000000000000226
Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes
AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearsonâs r=0.77 and 0.76, respectively, across SNPs with p < 4.4 Ă 10â4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45Ă10â48), explaining âŒ20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p > 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec
Trauma-induced adiposis dolorosa (Dercum\u27s disease).
We present a case of a 39-year-old man who presented with chronic bilateral upper extremity pain associated with innumerable angiomyolipomas that developed 5âyears after a motor vehicle accident involving his upper extremities. Our case notes the rare nature of painful adipose tissue deposits and the diagnostic challenges
Discovery of putative natural compounds inhibitor of the germinant spore receptor CspC in Clostridioides difficile infection: Gaining insights via In silico and bioinformatics approach
A Gram-positive anaerobic bacillus known as Clostridioides difficile (C. difficile) present in the intestinal tract of humans is the causative organism for C. difficile infection (CDI). A prospective target for the therapy of CDI is the germinant spore receptor CspC, a key regulator of the germination mechanism. The detection of bile acids by CspC has been reported to initiate the germination and signaling pathways in CDI. Herein, we examined small molecule compounds with putative inhibitory efficacies on CspC using integrative computational modeling approach. Due to their higher binding affinities as compared to metronidazole (Reference drug), the computational analysis identified three compounds (Hesperetin, Galbanic acid, and Tomatidine) as potential therapeutics for the receptor target. At the end of the 100ns molecular dynamics simulation, the stability investigations revealed Tomatidine and Galbanic acid to be more stable compounds compared to other simulated natural compounds, including the reference drug (Metronidazole). They also exhibited acceptable drug-likeness and pharmacokinetic properties as determined by the Lipinskiâs rule of five. Notwithstanding the results of our study, it is still too premature to conclude that the drug candidates are appropriate for use among CDI patients without substantial clinical and preclinical research
The Causative Classification of Stroke system: An international reliability and optimization study
Background: Valid and reliable ischemic stroke subtype determination is crucial for well-powered multicenter studies. The Causative Classification of Stroke System (CCS, available at http://ccs.mgh.harvard.edu) is a computerized, evidence-based algorithm that provides both causative and phenotypic stroke subtypes in a rule-based manner. We determined whether CCS demonstrates high interrater reliability in order to be useful for international multicenter studies. Methods: Twenty members of the International Stroke Genetics Consortium from 13 centers in 8 countries, who were not involved in the design and development of the CCS, independently assessed the same 50 consecutive patients with acute ischemic stroke through reviews of abstracted case summaries. Agreement among ratings was measured by kappa statistic. Results: The kappa value for causative classification was 0.80 (95% confidence interval [ CI] 0.78-0.81) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.70 (95% CI 0.69-0.71) for the 16-subtype CCS. Correction of a software-related factor that generated ambiguity improved agreement: kappa = 0.81 (95% CI 0.79-0.82) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.79 (95% CI 0.78-0.80) for the 16-subtype CCS. The kappa value for phenotypic classification was 0.79 (95% CI 0.77-0.82) for supra-aortic large artery atherosclerosis, 0.95 (95% CI 0.93-0.98) for cardioembolism, 0.88 (95% CI 0.85-0.91) for small artery occlusion, and 0.79 (0.76-0.82) for other uncommon causes. Conclusions: CCS allows classification of stroke subtypes by multiple investigators with high reliability, supporting its potential for improving stroke classification in multicenter studies and ensuring accurate means of communication among different researchers, institutions, and eras. Neurology (R) 2010;75:1277-128
Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes
Objective: We sought to assess whether genetic risk factors for atrial fibrillation (AF) can explain cardioembolic stroke risk. Methods: We evaluated genetic correlations between a previous genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors. Results: We observed a strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson r = 0.77 and 0.76, respectively, across SNPs with p 0.1). Conclusions: Genetic risk of AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF