Inheritance of high prolificacy of the Olkuska sheep (preliminary results)

Studies are being conducted on the mode of inheritance of high reproductive performance of the Olkuska (O) sheep, a local Polish breed. Ten O were used in crosses with Polish Merino (PM) ewes. The ovulation rate of 60 F1 ewes (O x PM) and 129 pure PM ewes was stated by means of laparoscopy. The prolificacy of female ancestors, full-sisters and progeny of 3 O rams was extensively analysed

Applications for next-generation sequencing in fish ecotoxicogenomics

The new technologies for next-generation sequencing (NGS) and global gene expression analyses that are widely used in molecular medicine are increasingly applied to the field of fish biology. This has facilitated new directions to address research areas that could not be previously considered due to the lack of molecular information for ecologically relevant species. Over the past decade, the cost of NGS has decreased significantly, making it possible to use non-model fish species to investigate emerging environmental issues. NGS technologies have permitted researchers to obtain large amounts of raw data in short periods of time. There have also been significant improvements in bioinformatics to assemble the sequences and annotate the genes, thus facilitating the management of these large datasets.The combination of DNA sequencing and bioinformatics has improved our abilities to design custom microarrays and study the genome and transcriptome of a wide variety of organisms. Despite the promising results obtained using these techniques in fish studies, NGS technologies are currently underused in ecotoxicogenomics and few studies have employed these methods. These issues should be addressed in order to exploit the full potential of NGS in ecotoxicological studies and expand our understanding of the biology of non-model organisms

Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data

<p>Abstract</p> <p>Background</p> <p>Normalization is essential in dual-labelled microarray data analysis to remove non-biological variations and systematic biases. Many normalization methods have been used to remove such biases within slides (Global, Lowess) and across slides (Scale, Quantile and VSN). However, all these popular approaches have critical assumptions about data distribution, which is often not valid in practice.</p> <p>Results</p> <p>In this study, we propose a novel assumption-free normalization method based on the Generalized Procrustes Analysis (GPA) algorithm. Using experimental and simulated normal microarray data and boutique array data, we systemically evaluate the ability of the GPA method in normalization compared with six other popular normalization methods including Global, Lowess, Scale, Quantile, VSN, and one boutique array-specific housekeeping gene method. The assessment of these methods is based on three different empirical criteria: across-slide variability, the Kolmogorov-Smirnov (K-S) statistic and the mean square error (MSE). Compared with other methods, the GPA method performs effectively and consistently better in reducing across-slide variability and removing systematic bias.</p> <p>Conclusion</p> <p>The GPA method is an effective normalization approach for microarray data analysis. In particular, it is free from the statistical and biological assumptions inherent in other normalization methods that are often difficult to validate. Therefore, the GPA method has a major advantage in that it can be applied to diverse types of array sets, especially to the boutique array where the majority of genes may be differentially expressed.</p

Inhibition of the mitochondrial pyruvate carrier protects from excitotoxic neuronal death.

Glutamate is the dominant excitatory neurotransmitter in the brain, but under conditions of metabolic stress it can accumulate to excitotoxic levels. Although pharmacologic modulation of excitatory amino acid receptors is well studied, minimal consideration has been given to targeting mitochondrial glutamate metabolism to control neurotransmitter levels. Here we demonstrate that chemical inhibition of the mitochondrial pyruvate carrier (MPC) protects primary cortical neurons from excitotoxic death. Reductions in mitochondrial pyruvate uptake do not compromise cellular energy metabolism, suggesting neuronal metabolic flexibility. Rather, MPC inhibition rewires mitochondrial substrate metabolism to preferentially increase reliance on glutamate to fuel energetics and anaplerosis. Mobilizing the neuronal glutamate pool for oxidation decreases the quantity of glutamate released upon depolarization and, in turn, limits the positive-feedback cascade of excitotoxic neuronal injury. The finding links mitochondrial pyruvate metabolism to glutamatergic neurotransmission and establishes the MPC as a therapeutic target to treat neurodegenerative diseases characterized by excitotoxicity

Disease network data for the pesticide fipronil in rat dopamine cells

Transcriptome data were collected in rat dopamine cells exposed to fipronil for 24 h using microarray analysis. Fipronil is a phenylpyrazole pesticide that acts to inhibit gamma-aminobutyric acid (GABA), blocking inhibitory synaptic transmission in the central nervous system. Transcriptome data were subjected to pathway analysis and subnetwork enrichment analysis. We report that 25 mu M fipronil altered transcriptional networks in dopamine-synthesizing cells that are associated with Alzheimer's Disease, Huntington Disease, and Schizophrenia. Data analysis revealed that nerve fibre degeneration, nervous system malformations, neurofibrillary tangles, and neuroinflammation were all disease processes related to the transcriptome profile observed in the rat neuronal cells. Other disease networks altered by fipronil exposure at the transcript level were associated with the mitochondria, including mitochondrial DNA depletion syndrome and mitochondrial encephalomyopathies. These data, along with those presented in Souders et al. (2021), are significant because they increase understanding into the molecular mechanisms underlying human disease following exposures to neuroactive pesticides. These data can be reused to inform adverse outcome pathways for neurotoxic pesticides

Hybrid Quantum Machine Learning Assisted Classification of COVID-19 from Computed Tomography Scans

Practical quantum computing (QC) is still in its infancy and problems considered are usually fairly small, especially in quantum machine learning when compared to its classical counterpart. Image processing applications in particular require models that are able to handle a large amount of features, and while classical approaches can easily tackle this, it is a major challenge and a cause for harsh restrictions in contemporary QC. In this paper, we apply a hybrid quantum machine learning approach to a practically relevant problem with real world-data. That is, we apply hybrid quantum transfer learning to an image processing task in the field of medical image processing. More specifically, we classify large CT-scans of the lung into COVID-19, CAP, or Normal. We discuss quantum image embedding as well as hybrid quantum machine learning and evaluate several approaches to quantum transfer learning with various quantum circuits and embedding techniques

Lighting conditions in home office and occupant's perception: Exploring drivers of satisfaction

This paper depicts lighting home office conditions within different countries and continents, emphasizing the user's satisfaction with the visual environment. The scope of this article is to investigate the drivers of participants' satisfaction with the lighting conditions at the home office. The study was developed by a team of international experts working together on Subtask A: User perspective and requirements, Task 61 IEA (International Energy Agency): Solutions for daylighting and electric lighting. An online survey was launched in December 2020 and closed on March 2021. The survey was implemented in the native languages of six participant countries (Brazil, Colombia, Denmark, Italy, Poland, and Japan) using Google Forms, and its dissemination was via various social media platforms. Measures of association between variables and predictive tests were run to explore which investigated aspects drove participants' satisfaction with the lighting conditions at the home office. We found some differences in satisfaction due to participants' sex, occupation, and participants' continent of residence. Females were more satisfied with daylight than males. Associations between the perception of seven light descriptors and satisfaction showed differences between East Asians and the rest of the participants, which might be related to the high dependence of the formers on electric lighting even when daylight is available. Design features as southern facades, the distance from the working area to the window, type of internal sun shading were related to daylighting satisfaction. Moreover, satisfaction with the general light level and the electric light was higher for those participants who did not need to switch on the ceiling, floor, or desk lamp when daylight was available. We found that an external view composed of 3 layers and the sky's visibility afforded a higher satisfaction with the window view. Having an independent room for the home office appeared to be related to a higher willingness to continue in the home office. Likewise, higher satisfaction with the overall visual environment and window view appeared to increase the willingness to continue working from home. Bridging the gap amid cultural differences and daylighting and lighting satisfaction is needed, particularly, relational studies between design features –as a response of cultural, climatic, and local practices- and occupants' preferences and acceptability. Thus, our understanding of occupants' responses will be more comprehensive. Engaging further research and measures to improve the visual environment and overall indoor environmental quality in dwellings is now a necessary step

Evaluation Of Elastic Modulus And Stress Gradient Of PECVD Silicon Nitride Thin Films

This study investigated the techniques for determining the elastic modulus and estimating the stress gradient of plasma-enhanced chemical vapor deposition (PECVD) silicon nitride thin films. The experimentally determined elastic modulus was then used in a finite element beam model to compute the stress distribution inside the thin films using a commercial finite element analysis package. The computed beam displacement caused by a given stress gradient was compared with the displacement experimentally evaluated using optical interference microscopy. This comparison allows the stress gradient of the PECVD silicon nitride membrane introduced by the fabrication process to be evaluated

Microbiome Composition and Function in Aquatic Vertebrates: Small Organisms Making Big Impacts on Aquatic Animal Health

Aquatic ecosystems are under increasing stress from global anthropogenic and natural changes, including climate change, eutrophication, ocean acidification, and pollution. In this critical review, we synthesize research on the microbiota of aquatic vertebrates and discuss the impact of emerging stressors on aquatic microbial communities using two case studies, that of toxic cyanobacteria and microplastics. Most studies to date are focused on host-associated microbiomes of individual organisms, however, few studies take an integrative approach to examine aquatic vertebrate microbiomes by considering both host-associated and free-living microbiota within an ecosystem. We highlight what is known about microbiota in aquatic ecosystems, with a focus on the interface between water, fish, and marine mammals. Though microbiomes in water vary with geography, temperature, depth, and other factors, core microbial functions such as primary production, nitrogen cycling, and nutrient metabolism are often conserved across aquatic environments. We outline knowledge on the composition and function of tissue-specific microbiomes in fish and marine mammals and discuss the environmental factors influencing their structure. The microbiota of aquatic mammals and fish are highly unique to species and a delicate balance between respiratory, skin, and gastrointestinal microbiota exists within the host. In aquatic vertebrates, water conditions and ecological niche are driving factors behind microbial composition and function. We also generate a comprehensive catalog of marine mammal and fish microbial genera, revealing commonalities in composition and function among aquatic species, and discuss the potential use of microbiomes as indicators of health and ecological status of aquatic ecosystems. We also discuss the importance of a focus on the functional relevance of microbial communities in relation to organism physiology and their ability to overcome stressors related to global change. Understanding the dynamic relationship between aquatic microbiota and the animals they colonize is critical for monitoring water quality and population health