scholarly journals Exploring the potential genetic heterogeneity in the incidence of hoof and leg disorders in Austrian Fleckvieh and Braunvieh cattle

2020 ◽  
Author(s):  
Barbara Kosinska-Selbi ◽  
Tomasz Suchocki ◽  
Christa Egger-Danner ◽  
Hermann Schwarzenbacher ◽  
Magdalena Fraszczak ◽  
...  
Keyword(s):  
Genetic Heterogeneity ◽  
Significant Snps ◽  
Current Data ◽  
Large Sample Size ◽  
Linkage Phase ◽  
Data Set ◽  
Differential Selection ◽  
Higher Power ◽  
Limited Power ◽  
Selection Of

AbstractBackgroundGenetic heterogeneity denotes the situation when different genetic architectures underlying diverse populations result in the same phenotype. In this study, we explore the nature of differences in the incidence of the number of hoof and leg disorders between Braunvieh and Fleckvieh cattle in the context of genetic heterogeneity between the breeds.ResultsDespite potentially higher power of testing due to twice as large sample size, none of the SNPs was significantly associated with the number of hoof and leg disorders in Fleckvieh, while 16 SNPs were significant in Braunvieh. The most promising candidate genes in Braunvieh are: CBLB on BTA01, which causes arthritis in rats; CAV2 on BTA04, which in effects mouse skeletal muscles; PTHLH on BTA05, which causes disease phenotypes related to the skeleton in humans, mice and zebrafish; SORCS2 on BTA06, which causes decreased susceptibility to injury in the mouse. Some of the significant SNPs (BTA01, BTA04, BTA05, BTA13, BTA16) reveal allelic heterogeneity – i.e. differences due to different allele frequencies between Fleckvieh and Braunvieh. Some of the significant regions (BTA01, BTA05, BTA13, BTA16) correlate to inter-breed differences in LD structure and may thus represent false-positive heterogeneity. However, positions on BTA06 (SORCS2), BTA14 and BTA24 mark Braunvieh-specific regions.ConclusionsWe hypothesise that the observed genetic heterogeneity of hoof and leg disorders is a by-product of multigenerational differential selection of the breeds – towards dairy production in the case of Braunvieh and towards beef production in the case of Fleckvieh. Based on the current data set it is no possibly to unequivocally confirm/exclude the hypothesis of genetic heterogeneity in the susceptibility to leg disorders between Fleckvieh and Braunvieh because only explore it through associations and not the causal mutations. Rationales against genetic heterogeneity comprise a limited power of detection of true associations as well as differences in the length of LD blocks and in linkage phase between breeds. On the other hand, multigenerational differential selection of the breeds and no systematic differences in LD structure between the breeds favour the heterogeneity hypothesis at some of the significant sites.

scholarly journals Age estimation and the best growth model selection of the tentacled blenny Parablennius tentacularis (Brünnich, 1768) in the southeastern Black Sea

2021 ◽  
Vol 38 (2) ◽  
pp. 229-236
Author(s):  
Ayşe Van ◽  
Aysun Gümüş ◽  
Melek Özpiçak ◽  
Serdar Süer
Keyword(s):  
Growth Model ◽  
Black Sea ◽  
Growth Parameters ◽  
Growth Models ◽  
Information Criterion ◽  
Current Data ◽  
Logistic Growth ◽  
Data Set ◽  
Frequency Distributions ◽  
Selection Of

By the study's coverage, 522 individuals of tentacled blenny (Parablennius tentacularis (Brünnich, 1768)), were caught with the bottom trawl operations (commercial fisheries and scientific field surveys) between May 2010 and March 2012 from the southeastern Black Sea. The size distribution range of the sample varied between 4.8-10.8 cm. The difference between sex length (K-S test, Z=3.729, P=0.000) and weight frequency distributions (K-S test, Z=3.605, P=0.000) was found to be statistically significant. The length-weight relationship models were defined as isometric with W = 0.009L3.034 in male individuals and positive allometric with W = 0.006L3.226 in female individuals. Otolith and vertebra samples were compared for the selection of the most accurate hard structure that can be used to determine the age. Otolith was chosen as the most suitable hard structure. The current data set was used to predict the best growth model. For this purpose, the growth parameters were estimated with the widely used von Bertalanffy, Gompertz and Logistic growth functions. Akaike's Information Criterion (AIC), Lmak./L∞ ratio, and R2 criteria were used to select the most accurate growth models established through these functions. Model averaged parameters were calculated with multi-model inference (MMI): L'∞ = 15.091 cm, S.E. (L'∞) = 3.966, K'= 0.232 year-1, S.E. (K') = 0.122.

scholarly journals Car braking effectiveness after adaptation for drivers with motor dysfunctions

2021 ◽  
Vol 11 (1) ◽  
pp. 617-623
Author(s):  
Adam Sowiński ◽  
Tomasz Szczepański ◽  
Grzegorz Koralewski
Keyword(s):  
Efficiency Index ◽  
Mathematical Function ◽  
Test Results ◽  
Braking Performance ◽  
Braking System ◽  
System Adaptation ◽  
Parametric Description ◽  
Limited Power ◽  
Braking Force ◽  
Selection Of

Abstract This article presents the results of measurements of the braking efficiency of vehicles adapted to be operated by drivers with motor dysfunctions. In such cars, the braking system is extended with an adaptive device that allows braking with the upper limb. This device applies pressure to the original brake in the car. The braking force and thus its efficiency depend on the mechanical ratio in the adapting device. In addition, braking performance depends on the sensitivity of the car’s original braking system and the maximum force that a disabled person can exert on the handbrake lever. Such a person may have limited power in the upper limbs. The force exerted by the driver can also be influenced by the position of the driver’s seat in relation to the handbrake lever. This article describes the research aimed at understanding the influence of the above-mentioned factors on the car braking performance. As a part of the analysis of the test results, a mathematical function was proposed that allows a parametric description of the braking efficiency index on the basis of data on the braking system, adaptation device, driver’s motor limitations, and the position of the driver’s seat. The information presented in this article can be used for the preliminary selection of adaptive devices to the needs of a given driver with a disability and to the vehicle construction.

scholarly journals PROMIS Scales for Assessment of Persistent Post-COVID Symptoms: A Cross Sectional Study

2021 ◽  
Vol 12 ◽  
pp. 215013272110304
Author(s):  
Ravindra Ganesh ◽  
Aditya K. Ghosh ◽  
Mark A. Nyman ◽  
Ivana T. Croghan ◽  
Stephanie L. Grach ◽  
...  
Keyword(s):  
Health Status ◽  
Social Roles ◽  
Disease Process ◽  
Cross Sectional Study ◽  
Large Sample Size ◽  
Sectional Study ◽  
Cross Sectional ◽  
Data Set ◽  
Patient Reported ◽  
The Impact

Objective Persistent post-COVID symptoms are estimated to occur in up to 10% of patients who have had COVID-19. These lingering symptoms may persist for weeks to months after resolution of the acute illness. This study aimed to add insight into our understanding of certain post-acute conditions and clinical findings. The primary purpose was to determine the persistent post COVID impairments prevalence and characteristics by collecting post COVID illness data utilizing Patient-Reported Outcomes Measurement Information System (PROMIS®). The resulting measures were used to assess surveyed patients physical, mental, and social health status. Methods A cross-sectional study and 6-months Mayo Clinic COVID recovered registry data were used to evaluate continuing symptoms severity among the 817 positive tested patients surveyed between March and September 2020. The resulting PROMIS® data set was used to analyze patients post 30 days health status. The e-mailed questionnaires focused on fatigue, sleep, ability to participate in social roles, physical function, and pain. Results The large sample size (n = 817) represented post hospitalized and other managed outpatients. Persistent post COVID impairments prevalence and characteristics were determined to be demographically young (44 years), white (87%), and female (61%). Dysfunction as measured by the PROMIS® scales in patients recovered from acute COVID-19 was reported as significant in the following domains: ability to participate in social roles (43.2%), pain (17.8%), and fatigue (16.2%). Conclusion Patient response on the PROMIS® scales was similar to that seen in multiple other studies which used patient reported symptoms. As a result of this experience, we recommend utilizing standardized scales such as the PROMIS® to obtain comparable data across the patients’ clinical course and define the disease trajectory. This would further allow for effective comparison of data across studies to better define the disease process, risk factors, and assess the impact of future treatments.

scholarly journals Indirect $$ \mathcal{CP} $$ probes of the Higgs-top-quark interaction: current LHC constraints and future opportunities

2020 ◽  
Vol 2020 (11) ◽  
Author(s):  
Henning Bahl ◽  
Philip Bechtle ◽  
Sven Heinemeyer ◽  
Judith Katzy ◽  
Tobias Klingl ◽  
...  
Keyword(s):  
Higgs Boson ◽  
Standard Model ◽  
Top Quark ◽  
Decay Channel ◽  
New Physics ◽  
Current Data ◽  
Quark Interaction ◽  
The Standard Model ◽  
Vector Bosons ◽  
Selection Of

Abstract The $$ \mathcal{CP} $$ CP structure of the Higgs boson in its coupling to the particles of the Standard Model is amongst the most important Higgs boson properties which have not yet been constrained with high precision. In this study, all relevant inclusive and differential Higgs boson measurements from the ATLAS and CMS experiments are used to constrain the $$ \mathcal{CP} $$ CP -nature of the top-Yukawa interaction. The model dependence of the constraints is studied by successively allowing for new physics contributions to the couplings of the Higgs boson to massive vector bosons, to photons, and to gluons. In the most general case, we find that the current data still permits a significant $$ \mathcal{CP} $$ CP -odd component in the top-Yukawa coupling. Furthermore, we explore the prospects to further constrain the $$ \mathcal{CP} $$ CP properties of this coupling with future LHC data by determining tH production rates independently from possible accompanying variations of the $$ t\overline{t}H $$ t t ¯ H rate. This is achieved via a careful selection of discriminating observables. At the HL-LHC, we find that evidence for tH production at the Standard Model rate can be achieved in the Higgs to diphoton decay channel alone.

scholarly journals Data Set for the Reporting of Malignant Odontogenic Tumors: Explanations and Recommendations of the Guidelines From the International Collaboration on Cancer Reporting

2018 ◽  
Vol 143 (5) ◽  
pp. 587-592 ◽  
Author(s):  
Pieter J. Slootweg ◽  
Edward W. Odell ◽  
Daniel Baumhoer ◽  
Roman Carlos ◽  
Keith D. Hunter ◽  
...  
Keyword(s):  
International Collaboration ◽  
Case Series ◽  
Initial Step ◽  
Odontogenic Tumors ◽  
Data Set ◽  
Expert Opinions ◽  
Organ Systems ◽  
Standardized Reporting ◽  
Selection Of ◽  
Cancer Reporting

A data set has been developed for the reporting of excisional biopsies and resection specimens for malignant odontogenic tumors by members of an expert panel working on behalf of the International Collaboration on Cancer Reporting, an international organization established to unify and standardize reporting of cancers. Odontogenic tumors are rare, which limits evidence-based support for designing a scientifically sound data set for reporting them. Thus, the selection of reportable elements within the data set and considering them as either core or noncore is principally based on evidence from malignancies affecting other organ systems, limited case series, expert opinions, and/or anecdotal reports. Nevertheless, this data set serves as the initial step toward standardized reporting on malignant odontogenic tumors that should evolve over time as more evidence becomes available and functions as a prompt for further research to provide such evidence.

Computer model of the maintenance and selection of genetic heterogeneity in polygamous helminths

Parasitology ◽  
1995 ◽  
Vol 111 (4) ◽  
pp. 531-536 ◽  
Author(s):  
A. Saul
Keyword(s):  
Genetic Drift ◽  
Computer Model ◽  
Genetic Heterogeneity ◽  
Host Selection ◽  
Selection Pressure ◽  
Intestinal Helminths ◽  
Infection Rates ◽  
Stochastic Fluctuations ◽  
Stochastic Simulation Model ◽  
Selection Of

SUMMARYA stochastic simulation model of the transmission and maintenance of genetic heterogeneity in the absence and presence of external selection pressures is presented for polygamous intestinal helminths such as Ascaris. The model assumes that the density distribution of the adult parasites is highly aggregated and that density-dependent effects on fecundity are important. The model gives rise to stable infection rates in the host. Where the parasite population contains genetic heterogeneity, with the exception of stochastic fluctuations which models genetic drift, the ratio of the different alleles remained constant over extended periods of time. This result contrasts with that of an earlier analytical model (Anderson, R. M., May, M. R. & Gutpa S. (1989) Parasitology 99, S59–S79), in which uneven mating probabilities for the different combinations of worm possible in a host was postulated to inevitably lead to fixation of the most abundant allele. New results suggest that in spite of the restricted choice of mating available to a worm in the confines of a host, selection pressure always leads to enrichment of the parasites carrying resistant alleles.

scholarly journals A Proposed Heuristic Optimization Algorithm for Detecting Network Attacks

2019 ◽  
Vol 2 (4) ◽  
pp. 530
Author(s):  
Amr Hassan Yassin ◽  
Hany Hamdy Hussien
Keyword(s):  
Neural Network ◽  
Heuristic Algorithms ◽  
Feed Forward Neural Network ◽  
Data Set ◽  
Network Attacks ◽  
Security Issues ◽  
Proposed Model ◽  
Network Intrusions ◽  
Attack Patterns ◽  
Selection Of

Due to the exponential growth of E-Business and computing capabilities over the web for a pay-for-use groundwork, the risk factors regarding security issues also increase rapidly. As the usage increases, it becomes very difficult to identify malicious attacks since the attack patterns change. Therefore, host machines in the network must continually be monitored for intrusions since they are the final endpoint of any network. The purpose of this work is to introduce a generalized neural network model that has the ability to detect network intrusions. Two recent heuristic algorithms inspired by the behavior of natural phenomena, namely, the particle swarm optimization (PSO) and gravitational search (GSA) algorithms are introduced. These algorithms are combined together to train a feed forward neural network (FNN) for the purpose of utilizing the effectiveness of these algorithms to reduce the problems of getting stuck in local minima and the time-consuming convergence rate. Dimension reduction focuses on using information obtained from NSL-KDD Cup 99 data set for the selection of some features to discover the type of attacks. Detecting the network attacks and the performance of the proposed model are evaluated under different patterns of network data.

scholarly journals Towards Neurosubtypes in Autism

2019 ◽  
Author(s):  
Seok-Jun Hong ◽  
Joshua Tzvi Vogelstein ◽  
Alessandro gozzi ◽  
Boris C. Bernhardt ◽  
B.T. Thomas Yeo ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Current Data ◽  
System Level ◽  
Diagnostic Labels ◽  
Study Results ◽  
Brain Structure And Function ◽  
Diagnostic Samples ◽  
And Function ◽  
Substantial Heterogeneity ◽  
Selection Of

There is a general consensus that substantial heterogeneity underlies the neurobiology in autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular-, cellular-, and system-level domains is a prerequisite for identifying biomarkers and developing more targeted therapeutic strategies in ASD. Advances in neuroimaging approaches to characterizing atypical brain patterns have recently motivated their application as viable tools to delineate more homogenous ASD subgroups at the level of brain structure and function - i.e., neurosubtyping. This review assesses and critically discusses the current data-driven neurosubtyping in ASD. It breaks this pursuit into key methodological steps: the selection of diagnostic samples, neuroimaging features, algorithm and validation approaches. For each step, we appraise the current literature in terms of progress, as well as remaining challenges and potential solutions. Convergence across findings is discussed and biological implications are highlighted. Although preliminary and with limited methodological overlap, results from this literature illustrate the feasibility of neurosubtyping. Across studies, there is general agreement that distinct neurosubtypes exist, but the exact number and their definitions vary depending on the specific features and approach utilized in a given study. Results also suggest the utility of subtypes in predicting symptom severity and diagnostic labels above and beyond group-average comparison designs. This review concludes with a discussion of future avenues towards a comprehensive understanding of the mechanisms underlying ASD heterogeneity.

scholarly journals Multivariate analysis of quantitative traits can effectively classify rapeseed germplasm

Genetika ◽  
2014 ◽  
Vol 46 (2) ◽  
pp. 545-559 ◽  
Author(s):  
Mirjana Jankulovska ◽  
Sonja Ivanovska ◽  
Ana Marjanovic-Jeromela ◽  
Snjezana Bolaric ◽  
Ljupcho Jankuloski ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Vegetative Growth ◽  
Quantitative Traits ◽  
Principal Component ◽  
Breeding Program ◽  
Oil Yield ◽  
Growth Duration ◽  
Data Set ◽  
Combined Application ◽  
Selection Of

In this study, the use of different multivariate approaches to classify rapeseed genotypes based on quantitative traits has been presented. Tree regression analysis, PCA analysis and two-way cluster analysis were applied in order todescribe and understand the extent of genetic variability in spring rapeseed genotype by trait data. The traits which highly influenced seed and oil yield in rapeseed were successfully identified by the tree regression analysis. Principal predictor for both response variables was number of pods per plant (NP). NP and 1000 seed weight could help in the selection of high yielding genotypes. High values for both traits and oil content could lead to high oil yielding genotypes. These traits may serve as indirect selection criteria and can lead to improvement of seed and oil yield in rapeseed. Quantitative traits that explained most of the variability in the studied germplasm were classified using principal component analysis. In this data set, five PCs were identified, out of which the first three PCs explained 63% of the total variance. It helped in facilitating the choice of variables based on which the genotypes? clustering could be performed. The two-way cluster analysissimultaneously clustered genotypes and quantitative traits. The final number of clusters was determined using bootstrapping technique. This approach provided clear overview on the variability of the analyzed genotypes. The genotypes that have similar performance regarding the traits included in this study can be easily detected on the heatmap. Genotypes grouped in the clusters 1 and 8 had high values for seed and oil yield, and relatively short vegetative growth duration period and those in cluster 9, combined moderate to low values for vegetative growth duration and moderate to high seed and oil yield. These genotypes should be further exploited and implemented in the rapeseed breeding program. The combined application of these multivariate methods can assist in deciding how, and based on which traits to select the genotypes, especially in early generations, at the beginning of a breeding program.

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