Bayesian Adaptive Markov Chain Monte Carlo Estimation of Genetic Parameters

Accurate estimation of genetic parameters is crucial for an efficient genetic evaluation system. REML and Bayesian methods are commonly used for the estimation of genetic parameters. In Bayesian approach, the idea is to combine what is known about the parameter which is represented in terms of a prior probability distribution together with the information coming from the data, to obtain a posterior distribution of the parameter of interest. Here a new fast adaptive Markov Chain Monte Carlo (MCMC) sampling algorithm is proposed. It combines both hybrid Gibbs sampler and Metropolis-Hastings (M-H) algorithm, for the estimation of genetic parameters in the linear mixed models with several random effects. The new adaptive MCMC algorithm has two steps: in step 1 the hybrid Gibbs sampler is used to learn an efficient proposal covariance structure for the variance components, and in step 2 the M-H algorithm is used to propose new values based on the learned covariance structure from step 1. Normally the dependencies among the random effects slow down the convergence of the MCMC chain. So in the second step of the algorithm those random effects were marginalized from the likelihood to improve the mixing of the chain. The new algorithm showed good mixing properties and was about twice time faster than the hybrid Gibbs sampling to produce posterior for variance components. Also the new algorithm was able to detect different modes in the posterior distribution. Moreover, the new proposed exponential prior for variance components was able to provide estimated mode of the posterior dominance variance to be zero in case of no dominance. The performance of the method was illustrated with field data and simulated data sets.Eine exakte Schätzung von genetischen Parametern ist entscheidend für ein leistungsfähiges genetisches Evaluierungssystem. Normalerweise werden REML- und Bayes-Verfahren für die Schätzung von genetischen Einflussfaktoren angewendet. Bei der Bayes-Methode werden die Informationen, die über einen Parameter durch A-priori-Wahrscheinlichkeitseinschätzung bekannt sind mit den Daten und Erfahrungen aus aktuellen Studien kombiniert und in eine A-posteriori-Verteilung überführt. In der vorliegenden Arbeit wird ein neuer, schnell anpassungsfähiger Markov Chain Monte Carlo (MCMC) sampling Algorithmus vorgestellt, welcher die Vorteile des Hybrid-Gibbs sampler mit denen des Metropolis-Hastings Algorithmus zur Einschätzung von genetischen Einflussfaktoren in linear mixed models mit mehreren Zufallsvariablen in sich vereinigt. Dieser neue MCMC Algorithmus arbeitet in 2 Stufen: im ersten Schritt wird der Hybrid Gibbs sampler genutzt, um eine effiziente vorgeschlagene Kovarianzstruktur für die Varianzkomponenten zu erlernen, während im zweiten Schritt der M-H Algorithmus zur Aufstellung neuer Werte basierend auf der erlernten Kovarianzstruktur aus Schritt 1 zur Anwendung kommt. Normalerweise verzögern die Abhängigkeiten unter den Zufallsvariablen die Annäherung der Markov-Kette an einen stationären Zustand. Also wurden diese Zufallsvariablen in einem weiteren Schritt von der Wahrscheinlichkeitsschätzung ausgeschlossen, um das Gemisch der Kette zu verbessern. Der neue Algorithmus zeigte gute Mischeigenschaften und war zweimal schneller als der Hybrid-Gibbs sampler, um eine a-posteriori-Verteilung von Varianzkomponenten zu erstellen, außerdem können bei dieser Methode auch mehrere Modes festgestellt werden. Mit der vorgeschlagenen exponentiellen Vorbewertung für Varianzkomponenten ist es weiterhin möglich solche Maximalwerte bei der posterior Verteilung auf den Wert Null zu schätzen im Falle, dass keine Dominanz besteht. Die Durchführung der Methode wurde mit realen und simulierten Datensätzen veranschaulicht

NeuralLasso: Neural Networks Meet Lasso in Genomic Prediction

Prediction of complex traits based on genome-wide marker information is of central importance for both animal and plant breeding. Numerous models have been proposed for the prediction of complex traits and still considerable effort has been given to improve the prediction accuracy of these models, because various genetics factors like additive, dominance and epistasis effects can influence of the prediction accuracy of such models. Recently machine learning (ML) methods have been widely applied for prediction in both animal and plant breeding programs. In this study, we propose a new algorithm for genomic prediction which is based on neural networks, but incorporates classical elements of LASSO. Our new method is able to account for the local epistasis (higher order interaction between the neighboring markers) in the prediction. We compare the prediction accuracy of our new method with the most commonly used prediction methods, such as BayesA, BayesB, Bayesian Lasso (BL), genomic BLUP and Elastic Net (EN) using the heterogenous stock mouse and rice field data sets

Broodstock development, breeding and seed production of selected marine food fishes and ornamental fishes

In recent years the contribution of marine finfish in the global aquaculture production has been steadily increasing. Marine food fishes like groupers, snappers, siganids, pompano, cobia and ornamental fishes have great potential for domestic and export trade

Growth performance and nutritional profile of a cyclopoid copepod Oithona similis isolated from Kochi, south west coast of India

A series of experiments of each 25 days were conducted to evaluate the suitability of four microalgal diets for the culture of the tropical cyclopoid copepod Oithona similis. The mono-algal diets were Chaetoceros calcitrans, Isochrysis galbana, Chlorella marina and Nannochloropsis oculata. Present work was carried out in a Completely Randomized Design (CRD) with four treatments and three replicates. After feeding O. similis with the 4 algal diets for 25 days, population density of adults, copepodites, nauplii and egg bearers were determined. Density and population growth rate of all stages were the maximum when fed with C. calcitrans and it was confirmed as an excellent diet for O. similis. Growth performance as indicated by population density and growth rate was significantly (P<0.05) higher for all stages when fed with C. calcitrans compared to the rest of the diets. The biochemical profile of O. similis showed superiority in protein (55.6%), and lipid (33.4%) contents on feeding with C. calcitrans. Since the strain is cultivable with good nutritional profile and high survival rate, it gives an immense scope of high value larval feed for use in marine hatcheries. Based on the current results, it is suggested that among the diets tested, the diatom C.calcitrans was the best for enhanced production of all stages of O. similis in controlled conditions followed by I. galban

Major Novel QTL for Resistance to Cassava Bacterial Blight Identified through a Multi-Environmental Analysis

Cassava, Manihot esculenta Crantz, has been positioned as one of the most promising crops world-wide representing the staple security for more than one billion people mainly in poor countries. Cassava production is constantly threatened by several diseases, including cassava bacterial blight (CBB) caused by Xanthomonas axonopodis pv. manihotis (Xam), it is the most destructive disease causing heavy yield losses. Here, we report the detection and localization on the genetic map of cassava QTL (Quantitative Trait Loci) conferring resistance to CBB. An F1 mapping population of 117 full sibs was tested for resistance to two Xam strains (Xam318 and Xam681) at two locations in Colombia: La Vega, Cundinamarca and Arauca. The evaluation was conducted in rainy and dry seasons and additional tests were carried out under controlled greenhouse conditions. The phenotypic evaluation of the response to Xam revealed continuous variation. Based on composite interval mapping analysis, 5 strain-specific QTL for resistance to Xam explaining between 15.8 and 22.1% of phenotypic variance, were detected and localized on a high resolution SNP-based genetic map of cassava. Four of them show stability among the two evaluated seasons. Genotype by environment analysis detected three QTL by environment interactions and the broad sense heritability for Xam318 and Xam681 were 20 and 53%, respectively. DNA sequence analysis of the QTL intervals revealed 29 candidate defense-related genes (CDRGs), and two of them contain domains related to plant immunity proteins, such as NB-ARC-LRR and WRKY

Cerebral venous sinus thrombosis due to vaccine-induced immune thrombotic thrombocytopenia in middle-income countries

Background: Adenovirus-based COVID-19 vaccines are extensively used in low- and middle-income countries (LMICs). Remarkably, cases of cerebral venous sinus thrombosis due to vaccine-induced immune thrombotic thrombocytopenia (CVST-VITT) have rarely been reported from LMICs. Aims: We studied the frequency, manifestations, treatment, and outcomes of CVST-VITT in LMICs. Methods: We report data from an international registry on CVST after COVID-19 vaccination. VITT was classified according to the Pavord criteria. We compared CVST-VITT cases from LMICs to cases from high-income countries (HICs). Results: Until August 2022, 228 CVST cases were reported, of which 63 were from LMICs (all middle-income countries [MICs]: Brazil, China, India, Iran, Mexico, Pakistan, Turkey). Of these 63, 32 (51%) met the VITT criteria, compared to 103 of 165 (62%) from HICs. Only 5 of the 32 (16%) CVST-VITT cases from MICs had definite VITT, mostly because anti-platelet factor 4 antibodies were often not tested. The median age was 26 (interquartile range [IQR] 20–37) versus 47 (IQR 32–58) years, and the proportion of women was 25 of 32 (78%) versus 77 of 103 (75%) in MICs versus HICs, respectively. Patients from MICs were diagnosed later than patients from HICs (1/32 [3%] vs. 65/103 [63%] diagnosed before May 2021). Clinical manifestations, including intracranial hemorrhage, were largely similar as was intravenous immunoglobulin use. In-hospital mortality was lower in MICs (7/31 [23%, 95% confidence interval (CI) 11–40]) than in HICs (44/102 [43%, 95% CI 34–53], p = 0.039). Conclusions: The number of CVST-VITT cases reported from LMICs was small despite the widespread use of adenoviral vaccines. Clinical manifestations and treatment of CVST-VITT cases were largely similar in MICs and HICs, while mortality was lower in patients from MICs.</p

Sex differences in cerebral venous sinus thrombosis after adenoviral vaccination against COVID-19

Introduction: Cerebral venous sinus thrombosis associated with vaccine-induced immune thrombotic thrombocytopenia (CVST-VITT) is a severe disease with high mortality. There are few data on sex differences in CVST-VITT. The aim of our study was to investigate the differences in presentation, treatment, clinical course, complications, and outcome of CVST-VITT between women and men. Patients and methods: We used data from an ongoing international registry on CVST-VITT. VITT was diagnosed according to the Pavord criteria. We compared the characteristics of CVST-VITT in women and men. Results: Of 133 patients with possible, probable, or definite CVST-VITT, 102 (77%) were women. Women were slightly younger [median age 42 (IQR 28–54) vs 45 (28–56)], presented more often with coma (26% vs 10%) and had a lower platelet count at presentation [median (IQR) 50x109/L (28–79) vs 68 (30–125)] than men. The nadir platelet count was lower in women [median (IQR) 34 (19–62) vs 53 (20–92)]. More women received endovascular treatment than men (15% vs 6%). Rates of treatment with intravenous immunoglobulins were similar (63% vs 66%), as were new venous thromboembolic events (14% vs 14%) and major bleeding complications (30% vs 20%). Rates of good functional outcome (modified Rankin Scale 0-2, 42% vs 45%) and in-hospital death (39% vs 41%) did not differ. Discussion and conclusions: Three quarters of CVST-VITT patients in this study were women. Women were more severely affected at presentation, but clinical course and outcome did not differ between women and men. VITT-specific treatments were overall similar, but more women received endovascular treatment.</p

Sex differences in cerebral venous sinus thrombosis after adenoviral vaccination against COVID-19

Introduction: Cerebral venous sinus thrombosis associated with vaccine-induced immune thrombotic thrombocytopenia (CVST-VITT) is a severe disease with high mortality. There are few data on sex differences in CVST-VITT. The aim of our study was to investigate the differences in presentation, treatment, clinical course, complications, and outcome of CVST-VITT between women and men. Patients and methods: We used data from an ongoing international registry on CVST-VITT. VITT was diagnosed according to the Pavord criteria. We compared the characteristics of CVST-VITT in women and men. Results: Of 133 patients with possible, probable, or definite CVST-VITT, 102 (77%) were women. Women were slightly younger [median age 42 (IQR 28–54) vs 45 (28–56)], presented more often with coma (26% vs 10%) and had a lower platelet count at presentation [median (IQR) 50x109/L (28–79) vs 68 (30–125)] than men. The nadir platelet count was lower in women [median (IQR) 34 (19–62) vs 53 (20–92)]. More women received endovascular treatment than men (15% vs 6%). Rates of treatment with intravenous immunoglobulins were similar (63% vs 66%), as were new venous thromboembolic events (14% vs 14%) and major bleeding complications (30% vs 20%). Rates of good functional outcome (modified Rankin Scale 0-2, 42% vs 45%) and in-hospital death (39% vs 41%) did not differ. Discussion and conclusions: Three quarters of CVST-VITT patients in this study were women. Women were more severely affected at presentation, but clinical course and outcome did not differ between women and men. VITT-specific treatments were overall similar, but more women received endovascular treatment.</p

The Adverse Effect of COVID-19 towards UK Healthcare Workers Mental Health: Critical Review of the Literature

Background: The pandemic changed healthcare priorities all over the world, resulting in increased pressure on healthcare workers. Studies conducted in other countries reveal a significant mental health burden of the pandemic on healthcare workers. However, only a few studies have focused on UK healthcare workers, which can demonstrate variations in healthcare systems from one country to another. Purpose: To examine the mental health impacts of COVID-19 on frontline UK healthcare workers and point to interventions to mitigate and minimise mental health problems caused by the pandemic. Methods: This review article used an interpretivist philosophy and an inductive approach. Electronic bibliographic databases were searched using relevant search terms. Primary studies published between 2020 and 2021 were selected. Only studies conducted in the United Kingdom were considered for inclusion. Results: Ten studies were retrieved and critiqued. It was discovered that anxiety, depression, and Post Traumatic Stress Disorder were the most reported mental health issues among frontline UK healthcare workers during the pandemic. Healthcare workers who experienced moral injury, the situation where moral dilemmas make healthcare workers feel incompetent, were at higher risk of developing the above mental health issues. These mental health issues had a negative impact on the healthcare workers’ work performance. This was predominantly due to the burnout, stress, and low motivation. The health workers in UK preferred psychosocial support as the most favourable Mental Health support intervention. However, there were reported disparities in the provision and access of the mental health support intervention at various regions within UK health care system. Conclusions: It was concluded that the COVID-19 pandemic had a significant mental health burden on frontline UK healthcare workers.</p