bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic diversity and population structure of six autochthonous pig breeds from Croatia, Serbia, and Slovenia
Authors: Zorc Minja , Škorput Dubravko , Gvozdanović Kristina , Margeta Polona , Karolyi Danijel , Luković Zoran , Salajpal Krešimir , Savić Radomir , Muñoz Maria , Bovo Samuele , Djurkin Kušec Ivona , Radović Čedomir , Kušec Goran , Čandek Potokar Marjeta , Dovč Peter 
Published: April 2022

Abstract
Background
The importance of local breeds as genetic reservoirs of valuable genetic variation is well established. Pig breeding in Central and South-Eastern Europe has a long tradition that led to the formation of several local pig breeds. In the present study, genetic diversity parameters were analysed in six autochthonous pig breeds from Slovenia, Croatia and Serbia (Banija spotted, Black Slavonian, Turopolje pig, Swallow-bellied Mangalitsa, Moravka and Krskopolje pig). Animals from each of these breeds were genotyped using microsatellites and single nucleotide polymorphisms (SNPs). The results obtained with these two marker systems and those based on pedigree data were compared. In addition, we estimated inbreeding levels based on the distribution of runs of homozygosity (ROH) and identified genomic regions under selection pressure using ROH islands and the integrated haplotype score (iHS).

Results
The lowest heterozygosity values calculated from microsatellite and SNP data were observed in the Turopolje pig. The observed heterozygosity was higher than the expected heterozygosity in the Black Slavonian, Moravka and Turopolje pig. Both types of markers allowed us to distinguish clusters of individuals belonging to each breed. The analysis of admixture between breeds revealed potential gene flow between the Mangalitsa and Moravka, and between the Mangalitsa and Black Slavonian, but no introgression events were detected in the Banija spotted and Turopolje pig. The distribution of ROH across the genome was not uniform. Analysis of the ROH islands identified genomic regions with an extremely high frequency of shared ROH within the Swallow-bellied Mangalitsa, which harboured genes associated with cholesterol biosynthesis, fatty acid metabolism and daily weight gain. The iHS approach to detect signatures of selection revealed candidate regions containing genes with potential roles in reproduction traits and disease resistance.

Conclusions
Based on the estimation of population parameters obtained from three data sets, we showed the existence of relationships among the six pig breeds analysed here. Analysis of the distribution of ROH allowed us to estimate the level of inbreeding and the extent of homozygous regions in these breeds. The iHS analysis revealed genomic regions potentially associated with phenotypic traits and allowed the detection of genomic regions under selection pressure.
Comparison of five supervised feature selection algorithms leading to top features and gene signatures from multi-omics data in cancer
Authors: Bhadra Tapas , Mallik Saurav , Hasan Neaj , Zhao Zhongming 
Published: April 2022

AbstractBackgroundAs many complex omics data have been generated during the last two decades, dimensionality reduction problem has been a challenging issue in better mining such data. The omics data typically consists of many features. Accordingly, many feature selection algorithms have been developed. The performance of those feature selection methods often varies by specific data, making the discovery and interpretation of results challenging.Methods and resultsIn this study, we performed a comprehensive comparative study of five widely used supervised feature selection methods (mRMR, INMIFS, DFS, SVM-RFE-CBR and VWMRmR) for multi-omics datasets. Specifically, we used five representative datasets: gene expression (Exp), exon expression (ExpExon), DNA methylation (hMethyl27), copy number variation (Gistic2), and pathway activity dataset (Paradigm IPLs) from a multi-omics study of acute myeloid leukemia (LAML) from The Cancer Genome Atlas (TCGA). The different feature subsets selected by the aforesaid five different feature selection algorithms are assessed using three evaluation criteria: (1) classification accuracy (Acc), (2) representation entropy (RE) and (3) redundancy rate (RR). Four different classifiers, viz., C4.5, NaiveBayes, KNN, and AdaBoost, were used to measure the classification accuary (Acc) for each selected feature subset. The VWMRmR algorithm obtains the best Acc for three datasets (ExpExon, hMethyl27 and Paradigm IPLs). The VWMRmR algorithm offers the best RR (obtained using normalized mutual information) for three datasets (Exp, Gistic2 and Paradigm IPLs), while it gives the best RR (obtained using Pearson correlation coefficient) for two datasets (Gistic2 and Paradigm IPLs). It also obtains the best RE for three datasets (Exp, Gistic2 and Paradigm IPLs). Overall, the VWMRmR algorithm yields best performance for all three evaluation criteria for majority of the datasets. In addition, we identified signature genes using supervised learning collected from the overlapped top feature set among five feature selection methods. We obtained a 7-gene signature (ZMIZ1, ENG, FGFR1, PAWR, KRT17, MPOandLAT2) for EXP, a 9-gene signature for ExpExon, a 7-gene signature for hMethyl27, one single-gene signature (PIK3CG) for Gistic2 and a 3-gene signature for Paradigm IPLs.ConclusionWe performed a comprehensive comparison of the performance evaluation of five well-known feature selection methods for mining features from various high-dimensional datasets. We identified signature genes using supervised learning for the specific omic data for the disease. The study will help incorporate higher order dependencies among features.
TCR-L: an analysis tool for evaluating the association between the T-cell receptor repertoire and clinical phenotypes
Authors: Liu Meiling , Goo Juna , Liu Yang , Sun Wei , Wu Michael C. , Hsu Li , He Qianchuan 
Published: April 2022

Abstract
Background
T cell receptors (TCRs) play critical roles in adaptive immune responses, and recent advances in genome technology have made it possible to examine the T cell receptor (TCR) repertoire at the individual sequence level. The analysis of the TCR repertoire with respect to clinical phenotypes can yield novel insights into the etiology and progression of immune-mediated diseases. However, methods for association analysis of the TCR repertoire have not been well developed.

Methods
We introduce an analysis tool, TCR-L, for evaluating the association between the TCR repertoire and disease outcomes. Our approach is developed under a mixed effect modeling, where the fixed effect represents features that can be explicitly extracted from TCR sequences while the random effect represents features that are hidden in TCR sequences and are difficult to be extracted. Statistical tests are developed to examine the two types of effects independently, and then the p values are combined.

Results
Simulation studies demonstrate that (1) the proposed approach can control the type I error well; and (2) the power of the proposed approach is greater than approaches that consider fixed effect only or random effect only. The analysis of real data from a skin cutaneous melanoma study identifies an association between the TCR repertoire and the short/long-term survival of patients.

Conclusion
The TCR-L can accommodate features that can be extracted as well as features that are hidden in TCR sequences. TCR-L provides a powerful approach for identifying association between TCR repertoire and disease outcomes.
Nutritional and genetic variation in a core set of Ethiopian Tef (Eragrostis tef) varieties
Authors: Ereful Nelzo C. , Jones Huw , Fradgley Nick , Boyd Lesley , Cherie Hirut Assaye , Milner Matthew J. 
Published: April 2022

Abstract
Background
Tef (Eragrostis tef) is a tropical cereal domesticated and grown in the Ethiopian highlands, where it has been a staple food of Ethiopians for many centuries. Food insecurity and nutrient deficiencies are major problems in the country, so breeding for enhanced nutritional traits, such as Zn content, could help to alleviate problems with malnutrition.

Results
To understand the breeding potential of nutritional traits in tef a core set of 24 varieties were sequenced and their mineral content, levels of phytate and protein, as well as a number of nutritionally valuable phenolic compounds measured in grain. Significant variation in all these traits was found between varieties. Genome wide sequencing of the 24 tef varieties revealed 3,193,582 unique SNPs and 897,272 unique INDELs relative to the tef reference var. Dabbi. Sequence analysis of two key transporter families involved in the uptake and transport of Zn by the plant led to the identification of 32 Zinc Iron Permease (ZIP) transporters and 14 Heavy Metal Associated (HMA) transporters in tef. Further analysis identified numerous variants, of which 14.6% of EtZIP and 12.4% of EtHMA variants were non-synonymous changes. Analysis of a key enzyme in flavanol synthesis, flavonoid 3′-hydroxylase (F3’H), identified a T-G variant in the tef homologue Et_s3159-0.29-1.mrna1 that was associated with the differences observed in kaempferol glycoside and quercetin glycoside levels.

Conclusion
Wide genetic and phenotypic variation was found in 24 Ethiopian tef varieties which would allow for breeding gains in many nutritional traits of importance to human health.
Genome-wide association mapping and genomic prediction for kernel color traits in intermediate wheatgrass (Thinopyrum intermedium)
Authors: Bajgain Prabin , Li Catherine , Anderson James A. 
Published: April 2022

Abstract
Background
Intermediate wheatgrass (IWG) is a novel perennial grain crop currently undergoing domestication. It offers important ecosystem benefits while producing grain suitable for human consumption. Several aspects of plant biology and genetic control are yet to be studied in this new crop. To understand trait behavior and genetic characterization of kernel color in IWG breeding germplasm from the University of Minnesota was evaluated for the CIELAB components (L*, a*, b*) and visual differences. Trait values were used in a genome-wide association scan to reveal genomic regions controlling IWG’s kernel color. The usability of genomic prediction in predicting kernel color traits was also evaluated using a four-fold cross validation method.

Results
A wide phenotypic variation was observed for all four kernel color traits with pairwise trait correlations ranging from − 0.85 to 0.27. Medium to high estimates of broad sense trait heritabilities were observed and ranged from 0.41 to 0.78. A genome-wide association scan with single SNP markers detected 20 significant marker-trait associations in 9 chromosomes and 23 associations in 10 chromosomes using multi-allelic haplotype blocks. Four of the 20 significant SNP markers and six of the 23 significant haplotype blocks were common between two or more traits. Evaluation of genomic prediction of kernel color traits revealed the visual score to have highest mean predictive ability (r2 = 0.53); r2 for the CIELAB traits ranged from 0.29–0.33. A search for candidate genes led to detection of seven IWG genes in strong alignment with MYB36 transcription factors from other cereal crops of the Triticeae tribe. Three of these seven IWG genes had moderate similarities with R-A1, R-B1, and R-D1, the three genes that control grain color in wheat.

Conclusions
We characterized the distribution of kernel color in IWG for the first time, which revealed a broad phenotypic diversity in an elite breeding germplasm. Identification of genetic loci controlling the trait and a proof-of-concept that genomic selection might be useful in selecting genotypes of interest could help accelerate the breeding of this novel crop towards specific end-use.
Efficacy and safety of glecaprevir and pibrentasvir in Japanese patients with hepatitis C virus infection aged 75 years or older
Authors: Komaki Yuri , Ozono Yoshinori , Nakamura Kenichi , Iwakiri Hisayoshi , Hasuike Satoru , Sueta Mitsue , Miike Tadashi , Yamamoto Shojiro , Uto Hirofumi , Kusumoto Kazunori , Ochiai Toshimasa , Kato Junya , Komada Naoto , Kuroki Kazuo , Eto Toshiharu , Shigehira Masafumi , Hirono Shuichi , Nagata Kenji , Kawakami Hiroshi 
Published: April 2022

Abstract
Background
It is estimated that approximately 50% of patients with hepatitis C virus (HCV) infection in Japan are currently over 75 years old. However, patients aged ≥ 75 years are typically underrepresented in clinical trials of direct-acting antivirals. This study aimed to evaluate the efficacy and safety of glecaprevir and pibrentasvir (G/P) treatment in Japanese patients with HCV infection aged ≥ 75 years.

Methods
This multicenter, retrospective study included 271 Japanese patients with HCV infection from 12 centers in Miyazaki Prefecture, Japan. Demographic, clinical, virological, and adverse events (AEs) data obtained during and after G/P treatment were collected from medical records. The patients were divided into two groups: younger (n = 199, aged < 75 years) and older (n = 72, aged ≥ 75 years). Virological data and AEs were analyzed according to the age group.

Results
In intention-to-treat (ITT) and per-protocol analyses, the overall sustained virological response 12 (SVR12) rates were 93% and 98.8%, respectively. Two patients in the older group and 14 patients in the younger group dropped out before SVR12 assessment. Although patients in the older group tended to have liver cirrhosis, 95.8% in the older group and 92% in the younger group achieved SVR12 in the ITT analysis (P = 0.404). In total, 48 (17.7%) patients experienced treatment-related AEs. Common AEs during treatment included pruritus, headache, and fatigue. The AEs were not significantly different between the two groups.

Conclusions
Compared with younger patients, older patients showed similar virological response and tolerance to G/P treatment.
Determinants of technology adoption and continued use among cognitively impaired older adults: a qualitative study
Authors: Dequanter Samantha , Fobelets Maaike , Steenhout Iris , Gagnon Marie-Pierre , Bourbonnais Anne , Rahimi Samira , Buyl Ronald , Gorus Ellen 
Published: April 2022

AbstractBackgroundTechnology offers opportunities to support older adults with mild cognitive impairments to remain independent and socially connected, but is often not used. Although determinants of technology use among older adults in general are well studied, much less is known about how these factors impact technology use behaviour in cognitively impaired older adults. This study aimed to bridge this gap in research by examining the factors underlying technology use in community-dwelling older adults with mild cognitive impairments.MethodsWe applied a generic qualitative design and used 16 semi-structured interviews to collect data from Belgian (Flemish) community-dwelling older adults diagnosed with Mild Cognitive Impairment or dementia and informal caregivers. To get data from different perspectives, a focus group with professional caregivers was added. We used thematic analysis with an inductive approach to identify and select themes from the data.ResultsWe identified two themes: introduction of technology and determinants of technology adoption and continued use. Successful technology adoption in cognitively impaired older adults is need-driven and subject to individual, technological and contextual characteristics. Specific for older adults with cognitive impairments are the importance of disease awareness and cognitive ability for adoption and continued use, respectively. Although social support can be a valuable alternative to technology, it is an important facilitator of continued technology use in these older adults. Similarly, integration of technologies in daily routines can buffer discontinuation of technologies.ConclusionsFuture research is encouraged to validate our findings in a postpandemic era and to further develop a novel theoretical framework for technology acceptance among older adults with cognitive impairments. Moreover, identification of crucial determinants as well as strategies to remove use barriers are also important future research tasks. Clinical practice should focus on improving disease awareness to facilitate technology adoption and policies should invest in training and support of professional caregivers and in reimbursement strategies to facilitate implementation of technology in practice.
Suicidal ideation and its related factors among older adults: a population-based study in Southwestern Iran
Authors: Shiraly Ramin , Mahdaviazad Hamideh , Zohrabi Roya , Griffiths Mark D. 
Published: April 2022

AbstractObjectivesSuicidal ideation is a major risk factor for suicide and can negatively affect self-care and health behaviors among the older adults. There are limited data on the prevalence and risk factors of suicidal ideation among the older population during the COVID-19 pandemic. The aim of the present study was to examine the prevalence and risk factors of suicidal ideations among Iranian older adults during the COVID-19 pandemic.MethodsA total of 803 older community adults in Shiraz (Southwestern Iran) were surveyed to determine potential factors influencing suicidal ideation, including demographic factors, physical health status, access to healthcare, current depression status, fear of COVID-19, perceived social support, and social engagement. Data were collected utilizing face-to-face interviews between November and December 2020. Multivariate logistic regression analysis was used to identify independent variables associated with suicidal ideations.ResultsAmong the 803 participants, 69 reported suicidal ideations (8.6%). Individuals with suicidal ideations were more likely to have greater fear of COVID-19. However, based on the results of multivariate logistic regression analysis, current depression (OR: 2.07, CI 95%: 1.18–3.65), not being married (OR: 1.82, CI 95%: 1.06–3.13), inability to pay for medical bills (OR: 2.16, CI 95%: 1.23–3.79), low perceived social support (OR: 2.03, CI95%: 1.11–3.71), and having limited social network (OR:1.77, CI 95%: 1.02–3.10) appeared to be more powerful influencing factors.ConclusionSuicidal ideation appears to be relatively common among Iranian older adults during the COVID-19 pandemic. A lack of longitudinal data makes it difficult to establish an association between suicidal ideations and the COVID-19 pandemic. Systematic monitoring of suicidal ideation is recommended among high-risk groups, particularly the older population.
Cognitive decline and poor social relationship in older adults during COVID-19 pandemic: can information and communications technology (ICT) use helps?
Authors: Li Yaya , Godai Kayo , Kido Michiko , Komori Susumu , Shima Ryoichi , Kamide Kei , Kabayama Mai 
Published: April 2022

Abstract
Background
To answer whether older adults' cognitive function benefits from ICT use, we (1) examined the relationship between ICT use and cognitive decline during the COVID-19 pandemic and (2) explored the potential role of ICT use in mitigating the relationship between loneliness, social isolation, and cognitive decline among community-dwelling older adults.

Methods
From February to March 2021, a mail survey was distributed to 1,400 older adults aged 70–89 years old. Responded participants were 1,003 (71.6% response rate). Subjective cognitive decline (SCD) was the independent variable. ICT use was assessed based on ICT use history and current ICT use activities. Loneliness was based on the Japanese version of the Three-Item Loneliness Scale. Social isolation was a total score of six items. Covariate-adjusted logistic regressions were performed and stratified by age groups (70–79 and ≥ 80 years).

Results
During the COVID-19 epidemic, the proportion of people aged ≥ 80 years who reported cognitive decline was twice that of 70s. Non-ICT use was independently associated with a higher risk of cognitive decline in participants aged ≥ 80 years. Furthermore, the significant associations between cognitive decline and interaction items (non-ICT use by loneliness or social isolation) were observed in the ≥ 80 age group. No association was found in the 70–79 age group.

Conclusions
Non-ICT users with high loneliness or social isolation scores were more likely to experience cognitive decline for adults age ≥ 80 years. For older adults who were vulnerable to poor social relationships, ICT use is potentially an efficient intervention. Further longitudinal investigations are needed.
The impact of a history of child abuse on cognitive performance: a cross-sectional study in older patients with a depressive, anxiety, or somatic symptom disorder
Authors: Tjoelker F. M. , Jeuring H. W. , Aprahamian I. , Naarding P. , Marijnissen R. M. , Hendriks G. J. , Rhebergen D. , Lugtenburg A. , Lammers M. W. , van den Brink R. H. S. , Oude Voshaar R. C. 
Published: April 2022

Abstract
Background
Child abuse is a major global burden with an enduring negative impact on mental and physical health. A history of child abuse is consistently associated with worse cognitive performance among adults; data in older age groups are inconclusive. Since affective symptoms and cognitive functioning are interrelated among older persons, a synergistic effect can be assumed in patients with affective symptoms who also have suffered from child abuse. This study examines the association between a history of child abuse and cognitive performance in such patients.

Methods
Cross-sectional data were collected from the ‘Routine Outcome Monitoring for Geriatric Psychiatry & Science’ project, including 179 older adults (age 60–88 years) with either a unipolar depressive, any anxiety, or somatic symptom disorder referred to specialized geriatric mental health care. A history of physical, sexual, and psychological abuse, and emotional neglect was assessed with a structured interview. Cognitive functioning was measured with three paper and pencils tests (10-words verbal memory test, Stroop Colour-Word test, Digit Span) and four tests from the computerized Cogstate Test Battery (Detection Test, Identification Test, One Card Learning Test, One Back Test). The association between a history of child abuse and cognitive performance was examined by multiple linear regression analyses adjusted for covariates.

Results
Principal component analyses of nine cognitive parameters revealed four cognitive domains, i.e., visual-verbal memory, psychomotor speed, working memory and interference control. A history of child abuse was not associated with any of these cognitive domains. However, when looking at the specific types of child abuse separately, a history of physical abuse and emotional neglect were associated with poorer interference control. A history of physical abuse was additionally associated with better visual-verbal memory.

Conclusions
The association between a history of child abuse and cognitive performance differs between the different types of abuse. A history of physical abuse might particularly be a key determinant of cognitive performance in older adults with a depressive, anxiety, or somatic symptom disorder. Future studies on the impact of these disorders on the onset of dementia should take child abuse into account.

Trial registration
ROM-GPS is registered at the Dutch Trial Register (NL6704 at www.trialregister.nl).