Descemet’s stripping automated endothelial keratoplasty for congenital hereditary endothelial dystrophy

Congenital hereditary endothelial dystrophy (CHED), presents in infancy or early childhood with bilateral clouding of corneas. This condition has previously been managed surgically with penetrating keratoplasty (PKP). Performing PKP in pediatric patients has its own set of difficulties. More recently, there has been growing interest in treating this condition with Descemet’s stripping automated endothelial keratoplasty (DSAEK). The purpose of this study is to report our experience of successfully performing DSAEK in a child with CHED

Common MEFV mutations in Egyptian patients with familial Mediterranean fever

Background: Familial Mediterranean fever (FMF) which is an autosomal recessive condition that primarily affect population of the Mediterranean basin. If undiagnosed effectively and treated with colchicine for life it may lead to serious consequences in terms of renal amyloidosis and renal failure. Objectives: We aim to check for the presence of FMF mutations in clinically suspected Egyptian patients, as an important step for family counseling and case management. Subjects and Methods: The study is a pilot study to check for the presence of FMF mutations among suspected cases (24 cases) from Sharkia Governorate. The control subjects (24) were selected from healthy volunteers. We examined FMF mutations by PCR technique for MEFV gene analysis in order to establish a diagnosis of FMF by examining two mutations, M694V and E148Q. Results: We found 58.3% (14/24 cases) of cohort were positive for M694V mutation, and all cohort were negative for E148Q mutation. The normal controls were negative for previous two mutations. Conclusions: PCR technique provides a rapid, reliable, cost-effective, noninvasive, and sensitive test for establishing a diagnosis of FMF in symptomatic patients and also provides a rational basis for medical and genetic counseling of FMF patients and their families.Key Words: FMF, MEFV, mutations, Egypt

Enzootic patterns of Middle East respiratory syndrome coronavirus in imported African and local Arabian dromedary camels: a prospective genomic study

BACKGROUND: The Middle East respiratory syndrome coronavirus (MERS-CoV) is a lethal zoonotic pathogen endemic to the Arabian Peninsula. Dromedary camels are a likely source of infection and the virus probably originated in Africa. We studied the genetic diversity, geographical structure, infection prevalence, and age-associated prevalence among camels at the largest entry port of camels from Africa into the Arabian Peninsula. METHODS: In this prospective genomic study, we took nasal samples from camels imported from Sudan and Djibouti into the Port of Jeddah in Jeddah, Saudi Arabia, over an almost 2-year period and local Arabian camels over 2 months in the year after surveillance of the port. We determined the prevalence of MERS-CoV infection, age-associated patterns of infection, and undertook phylogeographical and migration analyses to determine intercountry virus transmission after local lineage establishment. We compared all virological characteristics between the local and imported cohorts. We compared major gene deletions between African and Arabian strains of the virus. Reproductive numbers were inferred with Bayesian birth death skyline analyses. FINDINGS: Between Aug 10, 2016, and May 3, 2018, we collected samples from 1196 imported camels, of which 868 originated from Sudan and 328 from Djibouti, and between May 1, and June 25, 2018, we collected samples from 472 local camels, of which 189 were from Riyadh and 283 were from Jeddah, Saudi Arabia. Virus prevalence was higher in local camels than in imported camels (224 [47·5%] of 472 vs 157 [13·1%] of 1196; p<0·0001). Infection prevalence peaked among camels older than 1 year and aged up to 2 years in both groups, with 255 (66·9%) of 381 positive cases in this age group. Although the overall geographical distribution of the virus corresponded with the phylogenetic tree topology, some virus exchange was observed between countries corresponding with trade routes in the region. East and west African strains of the virus appear to be geographically separated, with an origin of west African strains in east Africa. African strains of the virus were not re-sampled in Saudi Arabia despite sampling approximately 1 year after importation from Africa. All local Arabian samples contained strains of the virus that belong to a novel recombinant clade (NRC) first detected in 2014 in Saudi Arabia. Reproduction number estimates informed by the sequences suggest sustained endemicity of NRC, with a mean Re of 1·16. INTERPRETATION: Despite frequent imports of MERS-CoV with camels from Africa, African lineages of MERS-CoV do not establish themselves in Saudi Arabia. Arabian strains of the virus should be tested for changes in virulence and transmissibility. FUNDING: German Ministry of Research and Education, EU Horizon 2020, and Emerging Diseases Clinical Trials Partnership

A Distributed Trust Framework for Privacy-Preserving Machine Learning

When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust between data owners and data scientists. Data owners are justifiably reluctant to relinquish control of private information to third parties. Privacy-preserving techniques distribute computation in order to ensure that data remains in the control of the owner while learning takes place. However, architectures distributed amongst multiple agents introduce an entirely new set of security and trust complications. These include data poisoning and model theft. This paper outlines a distributed infrastructure which is used to facilitate peer-to-peer trust between distributed agents; collaboratively performing a privacy-preserving workflow. Our outlined prototype sets industry gatekeepers and governance bodies as credential issuers. Before participating in the distributed learning workflow, malicious actors must first negotiate valid credentials. We detail a proof of concept using Hyperledger Aries, Decentralised Identifiers (DIDs) and Verifiable Credentials (VCs) to establish a distributed trust architecture during a privacy-preserving machine learning experiment. Specifically, we utilise secure and authenticated DID communication channels in order to facilitate a federated learning workflow related to mental health care data.Comment: To be published in the proceedings of the 17th International Conference on Trust, Privacy and Security in Digital Business - TrustBus202

Interferon-λ rs12979860 genotype and liver fibrosis in viral and non-viral chronic liver disease

Tissue fibrosis is a core pathologic process that contributes to mortality in ∼45% of the population and is likely to be influenced by the host genetic architecture. Here we demonstrate, using liver disease as a model, that a single-nucleotide polymorphism (rs12979860) in the intronic region of interferon-λ4 (IFNL4) is a strong predictor of fibrosis in an aetiology-independent manner. In a cohort of 4,172 patients, including 3,129 with chronic hepatitis C (CHC), 555 with chronic hepatitis B (CHB) and 488 with non-alcoholic fatty liver disease (NAFLD), those with rs12979860CC have greater hepatic inflammation and fibrosis. In CHC, those with rs12979860CC also have greater stage-constant and stage-specific fibrosis progression rates (P<0.0001 for all). The impact of rs12979860 genotypes on fibrosis is maximal in young females, especially those with HCV genotype 3. These findings establish rs12979860 genotype as a strong aetiology-independent predictor of tissue inflammation and fibrosis

Characterizing the morbid genome of ciliopathies

Background Ciliopathies are clinically diverse disorders of the primary cilium. Remarkable progress has been made in understanding the molecular basis of these genetically heterogeneous conditions; however, our knowledge of their morbid genome, pleiotropy, and variable expressivity remains incomplete. Results We applied genomic approaches on a large patient cohort of 371 affected individuals from 265 families, with phenotypes that span the entire ciliopathy spectrum. Likely causal mutations in previously described ciliopathy genes were identified in 85% (225/265) of the families, adding 32 novel alleles. Consistent with a fully penetrant model for these genes, we found no significant difference in their “mutation load” beyond the causal variants between our ciliopathy cohort and a control non-ciliopathy cohort. Genomic analysis of our cohort further identified mutations in a novel morbid gene TXNDC15, encoding a thiol isomerase, based on independent loss of function mutations in individuals with a consistent ciliopathy phenotype (Meckel-Gruber syndrome) and a functional effect of its deficiency on ciliary signaling. Our study also highlighted seven novel candidate genes (TRAPPC3, EXOC3L2, FAM98C, C17orf61, LRRCC1, NEK4, and CELSR2) some of which have established links to ciliogenesis. Finally, we show that the morbid genome of ciliopathies encompasses many founder mutations, the combined carrier frequency of which accounts for a high disease burden in the study population. Conclusions Our study increases our understanding of the morbid genome of ciliopathies. We also provide the strongest evidence, to date, in support of the classical Mendelian inheritance of Bardet-Biedl syndrome and other ciliopathies

Predicting In Vivo Anti-Hepatofibrotic Drug Efficacy Based on In Vitro High-Content Analysis

Background/Aims Many anti-fibrotic drugs with high in vitro efficacies fail to produce significant effects in vivo. The aim of this work is to use a statistical approach to design a numerical predictor that correlates better with in vivo outcomes. Methods High-content analysis (HCA) was performed with 49 drugs on hepatic stellate cells (HSCs) LX-2 stained with 10 fibrotic markers. ~0.3 billion feature values from all cells in >150,000 images were quantified to reflect the drug effects. A systematic literature search on the in vivo effects of all 49 drugs on hepatofibrotic rats yields 28 papers with histological scores. The in vivo and in vitro datasets were used to compute a single efficacy predictor (Epredict). Results We used in vivo data from one context (CCl4 rats with drug treatments) to optimize the computation of Epredict. This optimized relationship was independently validated using in vivo data from two different contexts (treatment of DMN rats and prevention of CCl4 induction). A linear in vitro-in vivo correlation was consistently observed in all the three contexts. We used Epredict values to cluster drugs according to efficacy; and found that high-efficacy drugs tended to target proliferation, apoptosis and contractility of HSCs. Conclusions The Epredict statistic, based on a prioritized combination of in vitro features, provides a better correlation between in vitro and in vivo drug response than any of the traditional in vitro markers considered.Institute of Bioengineering and Nanotechnology (Singapore)Singapore. Biomedical Research CouncilSingapore. Agency for Science, Technology and ResearchSingapore-MIT Alliance for Research and Technology Center (C-185-000-033-531)Janssen Cilag (R-185-000-182-592)Singapore-MIT Alliance Computational and Systems Biology Flagship Project (C-382-641-001-091)Mechanobiology Institute, Singapore (R-714-001-003-271