bluuebunny/crossref_metadata_2025 huggingface dataset:
High-intensity interval training among middle-aged and older adults for body composition and muscle strength: A systematic review
Authors: Alzar-Teruel María , Aibar-Almazán Agustín , Hita-Contreras Fidel , Carcelén-Fraile María del Carmen , Martínez-Amat Antonio , Jiménez-García José Daniel , Fábrega-Cuadros Raquel , Castellote-Caballero Yolanda
Published: September 2022

Background

The aging of population is leading to the investigation of new options to achieve healthy aging. One of these options is high-intensity interval training (HIIT), although its effects on body composition and muscle strength are currently unclear. The objective of this systematic review is to examine the scientific publications on the effects of HIIT on the body composition and muscle strength of middle-aged and older adults.

Methods

The search was carried out in the PubMed, Cochrane Plus, Web of Science, CINAHL and SciELO databases without limitation of publication dates. The literature search, data extraction and systematic review were performed following the PRISMA standards and the risk of bias of the selected studies was assessed using the Cochrane Collaboration Risk-of-Bias.

Results

Initially 520 publications were identified, out of which a total of 8 articles were finally selected to be included in this systematic review. Improvements in body composition were seen in six of the selected items and an increase in muscle strength in seven of the eight. Regarding physical function, improvements were found in both gait speed and balance.

Conclusions

This systematic review found that HIIT is effective in improving body composition and increasing muscle strength. However, when comparing HIIT to moderate-intensity continuous training, it is not clear that HIIT is more beneficial; a firm conclusion cannot be drawn due to the scarcity of published studies, their variety in methodology and the ambiguity of their results, so it is suggested to carry out more research in this area.
Machine learning corroborates subjective ratings of walking and balance difficulty in multiple sclerosis
Authors: Hu Wenting , Combden Owen , Jiang Xianta , Buragadda Syamala , Newell Caitlin J. , Williams Maria C. , Critch Amber L. , Ploughman Michelle
Published: September 2022

Machine learning can discern meaningful information from large datasets. Applying machine learning techniques to raw sensor data from instrumented walkways could automatically detect subtle changes in walking and balance. Multiple sclerosis (MS) is a neurological disorder in which patients report varying degrees of walking and balance disruption. This study aimed to determine whether machine learning applied to walkway sensor data could classify severity of self-reported symptoms in MS patients. Ambulatory people with MS (n = 107) were asked to rate the severity of their walking and balance difficulties, from 1-No problems to 5-Extreme problems, using the MS-Impact Scale-29. Those who scored less than 3 (moderately) were assigned to the “mild” group (n = 35), and those scoring higher were in the “moderate” group (n = 72). Three machine learning algorithms were applied to classify the “mild” group from the “moderate” group. The classification achieved 78% accuracy, a precision of 85%, a recall of 90%, and an F1 score of 87% for distinguishing those people reporting mild from moderate walking and balance difficulty. This study demonstrates that machine learning models can reliably be applied to instrumented walkway data and distinguish severity of self-reported impairment in people with MS.
Unraveling feed and nutrient use efficiencies in grassland-based dairy farms
Authors: Oenema Jouke , Oenema Oene
Published: September 2022

Grassland-based dairy farms are important for the provisioning of milk and ecosystem services. However, the key factors and interactions that influence the feed use efficiency of grassland-based dairy farms in practice are not well known and understood, and as a consequence no well-targeted recommendations can be provided. This paper addresses the question ‘what are the main factors that determine the variations in calculated feed efficiency and N and P use efficiencies on dairy farms subjected to agri-environmental regulations’. Monitoring and modeling data from ~12000 grassland-based dairy farms in The Netherlands over a 4 year period (2017–2020), collected through the KringloopWijzer model, were analyzed and the data from 2020 were statistically analyzed in detail. Farms greatly differed in milk production intensity (range < 10 to >25 Mg per ha per yr) and in the amount of purchased feed. The 5 and 95 percentile values of frequency distribution of the calculated annual mean feed efficiency at herd level were 0.9 and 1.3 kg milk per kg feed dry matter, respectively. Feed efficiency was statistically related to milk yield and number of young stock per cow, the share of concentrates and silage maize in the ration, and the net energy content of silage grass. At herd level, the 5 and 95 percentile values of the calculated annual mean N use efficiency increased with feed efficiency from 21 to 28%, and those of the annual mean P use efficiency from 32 to 40%. Contrary to expectations, mean surpluses of N andPat farm level remained more or less constant with feed efficiency and the intensity of milk production, but the amounts of purchased feed and manure export strongly increased with the intensity of milk production. The N and P surpluses and use efficiencies at farm level were sensitive to accounting for the externalization of feed production and manure utilization. The modeled ammonia and methane emissions per kg milk produced were relatively low on farms with high feed efficiency. In conclusion, feed use and N and P use efficiencies are key indicator for the profitability and environmental performance of dairy farms. Differences between farms in these key indicators were large, and these differences were related to a limited number of explanatory variables. Our study provides lessons for improving the profitability and environmental performance of grassland-based dairy farms.
Integrated analysis of competitive endogenous ribose nucleic acids (ceRNAs)-related regulatory networks in invasive and non-invasive non-functioning pituitary adenomas (NFPAs)
Authors: Liu Jiangtao , Wang Kaixuan , Ji Hongming , Zhang Gangli , Chen Shengli , Zhang Shiyuan , Lu Fake , Hu Changchen
Published: September 2022

Background

This study aims to identify the differentially expressed (DE) non-coding ribose nucleic acids (ncRNAs), messenger RNA (mRNA) expression profiles, and competitive endogenous RNA (ceRNA)-related regulatory networks in invasive and non-invasive nonfunctioning pituitary adenomas (NFPAs).

Methods

A full-transcriptome sequencing of invasive and non-invasive NFPAs is carried out to evaluate the expression profiles of circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and mRNA expression profiles.

Results

The screening criteria resulted in 118 DEcircRNAs (88 up-regulated and 30 down-regulated), 105 DElncRNAs (68 up-regulated and 37 down-regulated), 43 DEmiRNAs (22 up-regulated and 21 down-regulated), and 268 DEmRNAs (194 up-regulated and 74 down-regulated). Accordingly, a ceRNA regulatory network related to invasive NFPA is constructed. Further, the Gene Ontology and Kyoto Encylopedia of Genes and Genomes analyses showed that circRNAs and lncRNAs in the network are related to chromatin remodeling, participating in the Janus kinase/signal transducer and activator of transcription (JAK-STAT) and calcium signaling pathways. Hsa-miR-1248 showed exceptional connectivity in the ceRNA regulatory network, which could be closely related to the invasiveness of NFPAs.

Conclusions

Together, these findings clarified the regulatory mechanisms of invasive and non-invasive NFPAs, providing innovative research avenues and therapeutic targets for invasive NFPAs.
Estimation of basic reproduction number (R0) of African swine fever (ASF) in mid-size commercial pig farms in Vietnam
Authors: Mai Nguyen Tuan Anh , Trinh Thi Bich Ngoc , Nguyen Van Tam , Lai Thi Ngoc Ha , Le Nam Phuong , Nguyen Thi Thu Huyen , Nguyen Thi Lan , Ambagala Aruna , Do Duc Luc , Le Van Phan
Published: September 2022

African swine fever (ASF) is a devastating disease affecting the global swine industry. Recently, it has spread to many countries in Africa, Europe, Asia, and the Caribbean, leaving severe damage to local, regional, national, and global economies. Due to its highly complex molecular characteristics and pathogenesis, the development of a successful vaccine has been an unmet challenge. Therefore, ASF control relies solely on biosecurity, rapid detection, and elimination. Epidemiological information obtained from natural ASF outbreaks is critical for designing and implementing ASF control measures. Basic reproduction number (R0), an epidemiological metric used to describe the contagiousness or transmissibility of infectious agents, is an important epidemiological tool. In this study, we have calculated R0 for the in-farm spread of ASF among fattening pigs and sows in two midsize commercial pig farms, HY1 and HY2, that practice the spot removal approach in controlling ASF outbreaks in Vietnam. The R0 values for the sows and fattening pigs were 1.78 (1.35–2.35) and 4.76 (4.18–5.38) for HY1 and 1.55 (1.08–2.18) and 3.8 (3.33–4.28) for HY2. This is the first study to evaluate the transmission potential of ASF in midsize commercial pig farms in Vietnam. Based on the R0 values, we predict that the spot removal approach could be used to successfully control ASF outbreaks in midsize commercial sow barns but not in fattening pens.
International Comparison of Self-Concept, Self-Perception and Lifestyle in Adolescents: A Systematic Review
Authors: Palenzuela-Luis Natacha , Duarte-Clíments Gonzalo , Gómez-Salgado Juan , Rodríguez-Gómez José Ángel , Sánchez-Gómez Maria Begoña
Published: September 2022

Objectives:Adolescence is considered a vital time to address healthy attitudes and values towards an effective transition to adulthood. The aim of this review was to analyse self-concept, self-perception, physical exercise, and lifestyle in the late adolescent population.

Methods:Systematic review of studies assessing the results by the Rosenberg Self-Esteem Scale, the General Health Questionnaire, the Activity Questionnaire for Adolescents, and the Health Behaviour in School-aged Children questionnaires in late adolescents. The PRISMA recommendations were followed. The CASPe quality-check system was applied, excluding articles with a score <8.

Results:1589 studies were found, and 69 articles were selected. Adolescents with high self-concept and self-perception tend to be emotionally stable, sociable, and responsible. No significant differences were found regarding self-concept and self-perception between different countries, but there were differences between men and women. Physical activity and healthy diet improve self-concept and perception of body image.

Conclusion:Self-concept and self-perception are associated with responsibility, stability, and mental strength. Most healthy behaviours during adolescence are followed during adulthood. Socio-cultural level of Health Science students is a differential factor for overweight and obesity.
Determinants of COVID-19 Vaccine Hesitancy During the Pandemic: A Cross-Sectional Survey in the Canton of Vaud, Switzerland
Authors: Veys-Takeuchi Caroline , Gonseth Nusslé Semira , Estoppey Sandrine , Zuppinger Claire , Dupraz Julien , Pasquier Jérôme , Faivre Vincent , Scuderi Renzo , Vassaux Sophie , Bochud Murielle , D’Acremont Valérie
Published: September 2022

Objectives: COVID-19 vaccine hesitancy is a major obstacle in the fight against the pandemic. This study aimed to identify the local determinants of vaccine hesitancy in the context of COVID-19 to better inform future immunization campaigns.

Methods: The study, conducted in February 2021, included 1,189 randomly selected inhabitants of the canton of Vaud, Switzerland. Online questionnaires investigated determinants of the intention to vaccinate. Previously validated scores (Cronbach’s alphas >0.70) were applied to our data for inclusion in the ordinal logistic regression model.

Results: Individuals were more likely to vaccinate if they were 40 years or older, wealthy, reported a high educational attainment, or reported comorbidities. Doubts regarding vaccine safety and efficacy, mistrust in authorities and a propensity for natural immunity were identified as the main local hindrances to the COVID-19 vaccination.

Conclusion: Outreach to people at risk of severe COVID-19 is particularly relevant in the pandemic context to help mitigate vaccine hesitancy in the canton of Vaud, and should take into consideration the level of education. Further investigation is needed to better understand reasons for mistrust in authorities.
There and Back Again – Six Fiscal Tales from the Past Decades
Authors: P. Kiss Gábor
Published: September 2022

A phenomenon known in the international literature that is nevertheless unaddressed is that the standard indicators used for analysing fiscal policy can yield misleading results. Creative accounting can distort basic statistics, dividing data into groups of “revenue” and “expenditure” leads to the same distorted results, and the common indicators of the cyclically adjusted balance are also misleading. Based on the indicators adjusted for the impact of these distortions, six fiscal episodes are defined in Hungary between 1995 and 2016. The first episode is the adjustment in 1995–1996. The structure of spending changed then between 1997 and 2001. In 2002–2006, consolidation was delayed after a sudden, major round of fiscal expansion. After this, several approaches were tried to ensure consolidation, in two steps, between 2007 and 2009 and then between 2010 and 2012. Finally, between 2013 and 2016 the structure of spending was changed once again.
Using Explainable AI (XAI) for the Prediction of Falls in the Older Population
Authors: Tang Yue Ting , Romero-Ortuno Roman
Published: September 2022

The prevention of falls in older people requires the identification of the most important risk factors. Frailty is associated with risk of falls, but not all falls are of the same nature. In this work, we utilised data from The Irish Longitudinal Study on Ageing to implement Random Forests and Explainable Artificial Intelligence (XAI) techniques for the prediction of different types of falls and analysed their contributory factors using 46 input features that included those of a previously investigated frailty index. Data of participants aged 65 years and older were fed into four random forest models (all falls or syncope, simple fall, complex fall, and syncope). Feature importance rankings were based on mean decrease in impurity, and Shapley additive explanations values were calculated and visualised. Female sex and a previous fall were found to be of high importance in all of the models, and polypharmacy (being on five or more regular medications) was ranked high in the syncope model. The more ‘accidental’ (extrinsic) nature of simple falls was demonstrated in its model, where the presence of many frailty features had negative model contributions. Our results highlight that falls in older people are heterogenous and XAI can provide new insights to help their prevention.
Coordinate Descent for Variance-Component Models
Authors: Mathur Anant , Moka Sarat , Botev Zdravko
Published: September 2022

Variance-component models are an indispensable tool for statisticians wanting to capture both random and fixed model effects. They have applications in a wide range of scientific disciplines. While maximum likelihood estimation (MLE) is the most popular method for estimating the variance-component model parameters, it is numerically challenging for large data sets. In this article, we consider the class of coordinate descent (CD) algorithms for computing the MLE. We show that a basic implementation of coordinate descent is numerically costly to implement and does not easily satisfy the standard theoretical conditions for convergence. We instead propose two parameter-expanded versions of CD, called PX-CD and PXI-CD. These novel algorithms not only converge faster than existing competitors (MM and EM algorithms) but are also more amenable to convergence analysis. PX-CD and PXI-CD are particularly well-suited for large data sets—namely, as the scale of the model increases, the performance gap between the parameter-expanded CD algorithms and the current competitor methods increases.
Defuzzify Imprecise Numbers Using the Mellin Transform and the Trade-Off between the Mean and Spread
Authors: Chen Chin-Yi , Huang Jih-Jeng
Published: September 2022

Uncertainty or vagueness is usually used to reflect the limitations of human subjective judgment on practical problems. Conventionally, imprecise numbers, e.g., fuzzy and interval numbers, are used to cope with such issues. However, these imprecise numbers are hard for decision-makers to make decisions, and, therefore, many defuzzification methods have been proposed. In this paper, the information of the mean and spread/variance of imprecise data are used to defuzzify imprecise data via Mellin transform. We illustrate four numerical examples to demonstrate the proposed methods, and extend the method to the simple additive weighting (SAW) method. According to the results, our method can solve the problem of the inconsistency between the mean and spread, compared with the center of area (CoA) and bisector of area (BoA), and is easy and efficient for further applications.
Tailored Quantum Alternating Operator Ansätzes for Circuit Fault Diagnostics
Authors: Leipold Hannes , Spedalieri Federico M. , Rieffel Eleanor
Published: September 2022

The quantum alternating operator ansatz (QAOA) and constrained quantum annealing (CQA) restrict the evolution of a quantum system to remain in a constrained space, often with a dimension much smaller than the whole Hilbert space. A natural question when using quantum annealing or a QAOA protocol to solve an optimization problem is to select an initial state for the wavefunction and what operators to use to evolve it into a solution state. In this work, we construct several ansatzes tailored to solve the combinational circuit fault diagnostic (CCFD) problem in different subspaces related to the structure of the problem, including superpolynomially smaller subspaces than the whole Hilbert space. We introduce a family of dense and highly connected circuits that include small instances but can be scaled to larger sizes as a useful collection of circuits for comparing different quantum algorithms. We compare the different ansätzes on instances randomly generated from this family under different parameter selection methods. The results support that ansätzes more closely tailored to exploiting the structure of the underlying optimization problems can have better performance than more generic ansätzes.
Towards Sentiment Analysis for Romanian Twitter Content
Authors: Neagu Dan Claudiu , Rus Andrei Bogdan , Grec Mihai , Boroianu Mihai Augustin , Bogdan Nicolae , Gal Attila
Published: September 2022

With the increased popularity of social media platforms such as Twitter or Facebook, sentiment analysis (SA) over the microblogging content becomes of crucial importance. The literature reports good results for well-resourced languages such as English, Spanish or German, but open research space still exists for underrepresented languages such as Romanian, where there is a lack of public training datasets or pretrained word embeddings. The majority of research on Romanian SA tackles the issue in a binary classification manner (positive vs. negative), using a single public dataset which consists of product reviews. In this paper, we respond to the need for a media surveillance project to possess a custom multinomial SA classifier for usage in a restrictive and specific production setup. We describe in detail how such a classifier was built, with the help of an English dataset (containing around 15,000 tweets) translated to Romanian with a public translation service. We test the most popular classification methods that could be applied to SA, including standard machine learning, deep learning and BERT. As we could not find any results for multinomial sentiment classification (positive, negative and neutral) in Romanian, we set two benchmark accuracies of ≈78% using standard machine learning and ≈81% using BERT. Furthermore, we demonstrate that the automatic translation service does not downgrade the learning performance by comparing the accuracies achieved by the models trained on the original dataset with the models trained on the translated data.
Cicada Species Recognition Based on Acoustic Signals
Authors: Tey Wan Teng , Connie Tee , Choo Kan Yeep , Goh Michael Kah Ong
Published: September 2022

Traditional methods used to identify and monitor insect species are time-consuming, costly, and fully dependent on the observer’s ability. This paper presents a deep learning-based cicada species recognition system using acoustic signals to classify the cicada species. The sound recordings of cicada species were collected from different online sources and pre-processed using denoising algorithms. An improved Härmä syllable segmentation method is introduced to segment the audio signals into syllables since the syllables play a key role in identifying the cicada species. After that, a visual representation of the audio signal was obtained using a spectrogram, which was fed to a convolutional neural network (CNN) to perform classification. The experimental results validated the robustness of the proposed method by achieving accuracies ranging from 66.67% to 100%.
Modifications of Flower Pollination, Teacher-Learner and Firefly Algorithms for Solving Multiextremal Optimization Problems
Authors: Sorokovikov Pavel , Gornov Alexander
Published: September 2022

The article offers a possible treatment for the numerical research of tasks which require searching for an absolute optimum. This approach is established by employing both globalized nature-inspired methods as well as local descent methods for exploration and exploitation. Three hybrid nonconvex minimization algorithms are developed and implemented. Modifications of flower pollination, teacher-learner, and firefly algorithms are used as nature-inspired methods for global searching. The modified trust region method based on the main diagonal approximation of the Hessian matrix is applied for local refinement. We have performed the numerical comparison of variants of the realized approach employing a representative collection of multimodal objective functions. The implemented nonconvex optimization methods have been used to solve the applied problems. These tasks utilize an optimization of the low-energy metal Sutton-Chen clusters potentials with a very large number of atoms and the parametric identification of the nonlinear dynamic model. The results of this research confirms the performance of the suggested algorithms.
Sensor for Determining Single Droplet Acidities in the Venusian Atmosphere
Authors: Kaasik Laila , Rahu Ida , Roper Ellen Marigold , Seeba Riika , Rohtsalu Agnes , Pajusalu Mihkel
Published: September 2022

The cloud layers of Venus are known to have pressures and temperatures comparable to those on Earth, but, at the same time, many details about the environment inside them are unknown. The early consensus was that Venusian clouds are composed of droplets of near concentrated sulfuric acid with very limited water availability; newer models, however, suggest a pH range between −1 and 1, and these imply some form of a neutralizing agent and potentially complex chemical cycles. It is also possible that different populations of cloud particles have different acidities. To answer these questions, we propose an in situ acidity sensor that can statistically determine the acidities of individual cloud droplets from concentrated sulfuric acid (18 M) to deionized water, based on the fluorescence of a pigment that is immobilized in a film and read out using a set of excited LEDs and a camera. Here, we present the preliminary research and prototyping results and suggest a possible design for this sensor.
A Time Cooperation Guidance for Multi-Hypersonic Vehicles Based on LSTM Network and Improved Artificial Potential Field Method
Authors: Song Jia , Xu Xiaowei , Tong Xindi , Zhao Kai
Published: September 2022

Time cooperation guidance is a key technology which can greatly increase the success rate of flight missions. However, it is difficult to satisfy all the strict constraints when designing the guidance system for multiple hypersonic vehicles. To solve these problems, a time cooperation framework is proposed. In this paper, the longitudinal predictor–corrector guidance law is firstly applied to meet the terminal and path constraints simultaneously. To settle the inaccurate estimation problem of residual flight time, a long short-term memory network (LSTM network) is trained and adopted in a time decision module, whose inputs are selected as six-dimensional feature vectors combined with the features of the sequential ballistics. In the time control module, the traditional artificial potential field method is modified to handle the no-fly zone constraints problem. Furthermore, the time potential field as a new type of potential field is added to indirectly control the flight time of hypersonic vehicles. The final simulation results show that the novel time potential field is compatible with the traditional potential field, which can satisfy the no-fly zone and flight time constraints at the same time. Meanwhile, compared with other time cooperative guidance, the algorithm proposed in this paper performs better in terms of time adjustable range.
Design and Test of the Structure of Extractor Negative Pressure Zone of Sugarcane Chopper Harvester
Authors: Ren Jiahui , Wu Tao , Liu Qingting , Zou Xiaoping , Li Ke
Published: September 2022

Given the problems of the high trash content and loss rate for mechanized sugarcane harvesting, taking the HN4GDL-194 sugarcane chopper harvester extractor developed by South China Agricultural University as the research object, three types of extractor negative pressure structures were designed and internal flow field simulation analysis was conducted. Simulation results showed that the aerodynamic performance of the flow field in the negative pressure area of the extractor negative pressure structure two is the best and the wind velocity and negative pressure are the largest. The measurement results of wind velocity, wind pressure, and flow showed that the changing trend in the actual value of wind velocity and wind pressure is basically consistent with the simulation value. The relative error between the actual flow of the air outlet and the simulation value is less than 10% under different speeds, indicating that the simulation has high accuracy. Field tests of the original extractor and the optimal extractor were conducted. The test results for the trash content showed that when the feeding rate was 1.5 kg/s, there was no significant difference in the trash content between the optimal extractor and the original extractor under various fan speeds. When the feeding rate increased to 7.5 kg/s and the fan speed was low (950 r/min) and medium (1100 r/min), the trash content of the optimal extractor was significantly lower than that of the original extractor, decreasing 2.5% and 1.63%, respectively. The loss rate test results showed that when the fan speed is low and high (1250 r/min), there is no significant difference between the loss rate of the optimal extractor and the original extractor. When the fan speed was 1100 r/min and the feeding rate was 1.5, 4.5, and 7.5 kg/s, compared with the original extractor, the loss rate of the optimal extractor decreased by 0.53%, 0.21%, and 0.19%, respectively.
Morphology and Nitrogen Uptake and Distribution of Wheat Plants as Influenced by Applying Remedial Urea Prior to or Post Low-Temperature Stress at Seedling Stage
Authors: Li Chunyan , Liu Mingmin , Dai Cunhu , Zhu Yangyang , Zhu Min , Ding Jinfeng , Zhu Xinkai , Zhou Guisheng , Guo Wenshan
Published: September 2022

Wheat production is dramatically influenced by temperature. Low-temperature stress that frequently occurs seriously hampers the growth and development of wheat seedlings. In order to alleviate the damage of low temperature to wheat plant growth, remedial nitrogen was applied prior to or post low-temperature stress at seedling stage using controlled-temperature incubators to explore the difference in wheat morphology and nitrogen absorption and utilization efficiency. Nitrogen amendment significantly increased the leaf area, seedling height, tiller number and dry matter weight of wheat plants as compared with the treatment without nitrogen amendment under temperature stress. Remedial nitrogen applied prior to low-temperature stress (N-LT) was more conducive to increase the above parameters than that applied post low-temperature stress (LT-N). In addition, N-LT enhanced the ability of roots to absorb remedial 15N urea, promoted the growth and development of wheat plants under low-temperature stress, resulting in higher leaf SPAD readings, more new tillers, as well as increased dry weight of roots and above-ground organs. This study suggested that remedial nitrogen should be applied prior to low-temperature stress because it is more effective in restoring the growth of wheat plants under low-temperature stress.
Interaction of MdWRKY24 and MdRGL in Response to Tree Dwarfing in Malus domestica
Authors: Zhang He , Yang Zhichang , Shao Jianzhu , Sun Jianshe , Zha Qian , Zhang Xueying
Published: September 2022

In apple cultivation, dwarf rootstocks are chosen for dense planting and intensive cultivation, which is beneficial to production management. Dwarf rootstocks are widely used in apple production in China. However, the dwarfing mechanisms of dwarf interstock are still unclear. Here, M9 and SH40 were selected as the dwarf interstocks for potted Fuji apples. The key transcription factor MdWRKY24 was screened via transcriptional sequencing. The open reading frame sequence of the MdWRKY24 gene was 657 bp in length, encoded 218 amino acids, and was located on the cell membrane. The MdWRKY24-overexpressing Arabidopsis line showed a dwarf phenotype and delayed flowering. The DELLA protein RGA-like (RGL) gene is a repressor of the gibberellin signaling pathway. Yeast two-hybrid analysis revealed that MdWRKY24 could interact with MdRGL1/2/3. The results indicated that MdWRKY24 might affect plant dwarfing through the synergistic effect of MdRGL1/2/3. The MdWRKY24-MdRGL may be an important pathway underlying the gibberellin-mediated regulation of apple dwarfing.
Profiling Analysis of N6-Methyladenosine mRNA Methylation Reveals Differential m6A Patterns during the Embryonic Skeletal Muscle Development of Ducks
Authors: Chen Biao , Liu Shuibing , Zhang Wentao , Xiong Ting , Zhou Mingfang , Hu Xiaolong , Mao Huirong , Liu Sanfeng
Published: September 2022

N6-Methyladenosine is a reversible epigenetic modification that influences muscle development. However, the m6A modification profile during poultry skeletal muscle development is poorly understood. Here, we utilized m6A-specific methylated RNA immunoprecipitation sequencing to identify m6A sites during two stages of breast muscle development in ducks: embryonic days 13 (E13) and E19. MeRIP-seq detected 19,024 and 18,081 m6A peaks in the E13 and E19 groups, respectively. Similarly to m6A distribution in mammalian transcripts, our results revealed GGACU as the main m6A motif in duck breast muscle; they also revealed that m6A peaks are mainly enriched near the stop codons. In addition, motif sequence analysis and gene expression analysis demonstrated that m6A modification in duck embryo skeletal muscles may be mediated by the methyltransferase-like 14. GO and KEGG analysis showed that m6A peaks containing genes at E19 were mainly enriched in muscle-differentiation- and muscle-growth-related pathways, whereas m6A peaks containing genes in E13 were mainly enriched in embryonic development and cell proliferation pathways. Combined analysis of MeRIP-seq and RNA-seq showed that the mRNA expression may be affected by m6A modification. Moreover, qRT-PCR analysis of the expression of METTL14 and its cofactors (WTAP, ZC3H13, RBM15 and VIRMA) during duck embryonic skeletal muscle development in breast and leg muscle samples revealed a significant downward trend as the developmental age progressed. Our results demonstrated that m6A mRNA methylation modifications control muscle development in ducks. This is the first study of m6A modification patterns in duck muscle tissue development, and it lays the foundation for the study of the effects of RNA modification on poultry skeletal muscle development.
Changes in the Dog’s and Cat’s Behaviors, as Reported by the Owners, before and during the Lockdown in China
Authors: Platto Sara , Serres Agathe , Normando Simona , Wang Yanqing , Turner Dennis C.
Published: September 2022

Considering the effects that the COVID-19 pandemic had and still has on human psychological health, it is expected that it might also affect household dogs’ and cats’ welfare. The current study explores the behavioral changes in dogs and cats before (BL) and during the lockdown (DL), as reported by their owners in China. Besides demographic parameters, variables related to the daily management of dogs and cats were analyzed in relation to behavioral problems, stress-related behaviors, and anxiety-related behaviors before and during the lockdown. A total of 261 questionnaires were collected. In general, behavioral problems and stress-related behaviors in dogs (p < 0.001) and cats (p < 0.001) decreased DL compared to BL, while anxiety-related behaviors in cats did not show any differences between the two periods considered. On the other hand, anxiety-related behaviors were more frequent in dogs DL (36.3%) compared to BL (35%), which were associated with reduced frequency of play activities with the owners (p = 0.016) and altered sleeping habits (p < 0.01). During the lockdown, dogs’ and cats’ daily routines and management (feeding and sleeping habits, dogs’ walks, dogs’ and cats’ play activities, litter box management, and cats’ lifestyle) experienced changes, but they were not associated with any behavioral issues. On the other hand, the behavioral issues considered for dogs and cats were more frequent BL, which were influenced by the daily management of the pets. The current study showed how critical the attention the owners can provide to the pets could be, to improve their companion animals’ welfare. Therefore, it is important to provide pet owners with behavioral management support both during particularly difficult periods such as a lockdown and during regular daily routines.
Inclusion of Grape Pomace in Finishing Cattle Diets: Carcass Traits, Meat Quality and Fatty Acid Composition
Authors: Arend Frances A. , Murdoch Gordon K. , Doumit Matt E. , Chibisa Gwinyai E.
Published: September 2022

Because of its high content of polyphenolic compounds, dietary inclusion of grape pomace (GP) in finishing cattle diet could possibly enhance product quality and the health value of beef lipids. Therefore, the aim of this study was to evaluate the effects of feeding a high amount of grape pomace in finishing cattle diets on carcass traits, product quality, and fatty acid (FA) composition of beef. Jersey × Holstein crosses (n = 24) were fed either a typical finishing diet (CON) or a finishing diet containing 58% grape pomace (DM basis; HGP). Following the feeding period, animals were harvested, and carcass traits measured. Longissimus lumborum (LL) and semimembranosus (SM) muscle were then collected from each carcass for sensory quality evaluation and FA profile analysis. Hot carcass weight, backfat thickness, and preliminary and final yield grades were greater (p ≤ 0.04) for CON than HGP steers. However, there was no diet effect on rib eye area (REA), kidney, pelvic, and heart (KPH) fat, and marbling. Feeding the HGP compared to CON diet reduced lipid oxidation of LL and SM steaks over time; the malondialdehyde (MDA) concentration, which did not differ on d 0 and 2 of 8-d simulated retail display, was lower on d 4, 6 and 8 for HGP than CON steers (treatment × day of simulated display interaction; p < 0.01). Brightness (L* values) and redness (b*) were greater for LL steaks from HGP than CON steers on most days of simulated display (treatment × day of simulated display interaction; p < 0.01). In addition, the LL and SM muscle content of several FA linked to positive health outcomes in humans including 18:2 n-6, 18:2 c9t11, total conjugated linoleic acid (CLA) and total polyunsaturated fatty acid (PUFA) was also greater (p ≤ 0.02) for steers fed the HGP compared to the CON diet. In summary, current findings suggest that although it could possibly limit growth performance, feeding a high amount of grape pomace to finishing cattle could enhance both the sensory quality and the health value of beef lipids, which are key in increasing consumer acceptability of beef.
Whole-Genome Survey and Microsatellite Marker Detection of Antarctic Crocodile Icefish, Chionobathyscus dewitti
Authors: Kim Jinmu , Lee Seung-Jae , Jo Euna , Choi Eunkyung , Cho Minjoo , Choi Soyun , Kim Jeong-Hoon , Park Hyun
Published: September 2022

The crocodile icefish, Chionobathyscus dewitti, belonging to the family Channichthyidae, is an endemic species of the Southern Ocean. The study of its biological features and genetics is challenging as the fish inhabits the deep sea around Antarctic waters. The icefish, the sole cryopelagic species, shows unique physiological and genetic features, unlike other teleosts. It lacks hemoglobin and has evolved antifreeze proteins. Here, we report the genome sequencing data of crocodile icefish produced using the Illumina Novaseq 6000 platform. The estimated genome size was 0.88 Gb with a K-value of 19, and the unique sequence, heterozygosity, error, and duplication rates were 57.4%, 0.421%, 0.317%, and 0.738%, respectively. A genome assembly of 880.69 Mb, with an N50 scaffold length of 2401 bp, was conducted. We identified 2,252,265 microsatellite motifs from the genome assembly data, and dinucleotide repeats (1,920,127; 85.25%) had the highest rate. We selected 84 primer pairs from the genome survey assembly and randomly selected 30 primer pairs for validation. As a result, 15 primer pairs were validated as microsatellite markers.
Optimization of the Thawing Protocol for Iberian Boar Sperm
Authors: Tomás-Almenar Cristina , de Mercado Eduardo
Published: September 2022

Thawing protocols have been barely studied, and their modifications may lead to a substantial improvement in post-thawing sperm quality, which could be of great relevance to existing sperm banks, such as those for Iberian pig breeds with varieties in danger of extinction. For that, the study aimed to evaluate different thawing rates and to evaluate modifications in the composition of the thawing extender (basic pH to 8–8.2, incorporation of cyclodextrins loaded with cholesterol [CLC] and the incorporation of ion chelators [EDTA and EGTA]). After thawing, overall sperm motility and kinematic parameters, acrosome status and sperm membrane integrity were evaluated. The most optimal results were obtained with the thawing rate reaching 70 °C for 8 s with the inclusion of 12.5 mg of CLC/500 × 106 spermatozoa in the thawing extender, which showed an improvement compared to the control at 70 °C. In conclusion, to adapt the thawing conditions may be relevant, especially for endangered species or breeds such as some varieties of Iberian pig, since this process could also be used in samples cryopreserved in gene banks.
Behavioural Traits in Bos taurus Cattle, Their Heritability, Potential Genetic Markers, and Associations with Production Traits
Authors: Titterington Frances Margaret , Knox Rachel , Morrison Steven James , Shirali Masoud
Published: September 2022

People who work with cattle are at severe risk of serious injury due to the size and strength of the cattle. This risk can be minimised by breeding less dangerous cattle, which have a more favourable reaction to humans. This study provides a systematic review of literature pertaining to cattle genetics relating to behaviour. The review protocol was developed using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework, with Population, Exposure and Outcome components identified as Bovine, Genetics and Behaviour respectively. Forty-nine studies were identified in the sifting and assigned non-exclusively to groups of heritability (22), genomic associations (13) and production traits related to behaviour (24). Behavioural traits were clustered into the following groups: “temperament, disposition and/ or docility”, “aggression”, “chute score”, “flight speed”, “milking temperament”, “non-restrained methods” and “restrained methods”. Fourteen papers reported high accuracy (Standard Error ≤ 0.05) estimates of heritability, the majority (n = 12) of these studies measured over 1000 animals. The heritability estimates were found to vary between studies. Gene associations with behavioural traits were found on all chromosomes except for chromosome 13, with associated SNPs reported on all chromosomes except 5, 13, 17, 18 and 23. Generally, it was found that correlations between behaviour and production traits were low or negligible. These studies suggest that additive improvement of behavioural traits in cattle is possible and would not negatively impact performance. However, the variation between studies demonstrates that the genetic relationships are population specific. Thus, to assess the heritability, genetic associations with production and genomic areas of interest for behavioural traits, a large-scale study of the population of interest would be required.
Macromolecules Influence Cellular Competence and Expression Level of IGFs Genes in Bovine Oocytes In Vitro
Authors: Şen Uğur , Şirin Emre , Önder Hasan , Özyürek Selçuk , Kolenda Magdalena , Sitkowska Beata
Published: September 2022

In vitro maturation (IVM) of mammalian oocytes, which influences subsequent in vitro development of embryos, is affected by the macromolecule content in culture media for the success of oocyte maturation competence, in which the cytoplasmic and nuclear reprogramming events occur. The insulin-like growth factor family (IGFs) promotes the maturation of bovine oocytes and the expansion of cumulus cells and also inhibits apoptosis. This study was, therefore, designed to examine the effects of macromolecules (bovine serum albumin, BSA; fetal calf serum, FCS; and polyvinyl alcohol, PVA) on in vitro nuclear maturation, total cellular protein, glutathione peroxidase (GPx) enzyme activity, and the gene expression level of IGF1, IGF2, and their receptor in bovine oocytes. Oocytes obtained from bovine ovaries were cultured in bicarbonate-buffered medium 199 supplemented with 4 mg/mL BSA, 10% FCS, 1 mg/mL PVA, and without macromolecule supplement (control) during 22 h in the air with a humidified atmosphere and 5% CO2 at 38.5 °C temperature. Supplementation of BSA and FCS increased (χ2 = 9.84; p < 0.05) the percentages of oocytes that reached metaphase II compared to the control and PVA. The amount of protein per ml of cell extracts of oocytes matured in FCS supplemented culture media was higher (p < 0.05) than the oocytes in the PVA and control. The levels of GPx enzyme activity in cell extracts isolated from oocytes in each experimental group did not change over time, but the GPx enzyme activity in oocytes matured in PVA-supplemented culture media was lower (p < 0.05) than in oocytes in the other experimental groups. Transcript for the IGF1 gene was not detected in all experimental groups, but the supplementation of BSA and FCS significantly elevated the transcript level of the IGF2 gene. In addition, the maturation of oocytes with BSA-supplemented media increased the transcript level of the IGF1R gene, whereas the transcript level of the IGF2R gene was similar among macromolecule supplementation groups. The current study concluded that BSA and FCS could improve in vitro bovine oocyte development due to supporting nuclear maturation and increasing the total cellular protein content, GPx enzyme, and transcript activity.
Nutritional Metabolites as Biomarkers of Previous Feed Intake in European Rabbit (Oryctolagus cuniculus): Applications on Conservation
Authors: Marín-García Pablo Jesús , Llobat Lola , Rouco Carlos , Aguayo-Adán Juan Antonio , Larsen Torben , Cambra-López María , Blas Enrique , Pascual Juan José
Published: September 2022

European wild rabbit (Oryctolagus cuniculus) populations have drastically reduced, and recently, rabbits have been classed as “endangered” by the IUCN. This animal plays an important ecological role in Mediterranean ecosystems and its introduction could significantly contribute to ecological restoration. Rabbits have high nutrient requirements that apparently cannot be covered in all ecosystems, and there are clues that nutrition can limit their abundance and density. On the other hand, some studies reflect the effects of food availability on the metabolomic status of other animal species, but there are no specific studies on this keystone species. The main aim of this work is to find biomarkers to assess the previous levels of ingestion of European rabbits (Oryctolagus cuniculus). To address this gap, gastric content and blood samples were collected from European rabbits (n = 99) in a Mediterranean area for the analysis of glucose, non-esterified fatty acids (NEFA), plasmatic urea nitrogen (PUN), albumin, glutamate and total protein metabolites. Depending on their previous feed intake (gastric content and the ratio between the gastric content and the weight of the animal), the animals were divided into two groups (lower and normal previous feed intake). Our work shows that the metabolomic profiles of the animals were affected. Levels of glucose (+82%; p = 0.0003), NEFA (−61%; p = 0.0040) and PUN (+139%; p < 0.001) were different in the animals with lower previous feed intake than the animals with normal previous feed intake. This work summarises that metabolic phenotype can be interesting when seeking to discover the limiting nutrients and food availability in diets that could affect the ecological fitness and conservation of European wild rabbits. It is important to mention that in this work, only the effects on six different metabolites have been analysed and more studies are necessary to complement the knowledge of possible metabolites that indicate the level of ingestion in this species and others. These (and new) biomarkers could be used as a tool to provide information about individual or population characteristics that other physiological parameters cannot detect, improving the conservation physiology field.