bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of two multi-trait association testing methods and sequence-based fine mapping of six QTL in Swiss Large White pigs
Authors: Nosková Adéla , Mehrotra Arnav , Kadri Naveen Kumar , Lloret-Villas Audald , Neuenschwander Stefan , Hofer Andreas , Pausch Hubert 
Published: February 2023

Abstract
Background
Genetic correlations between complex traits suggest that pleiotropic variants contribute to trait variation. Genome-wide association studies (GWAS) aim to uncover the genetic underpinnings of traits. Multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS enable detecting variants associated with multiple phenotypes. In this study, we used array-derived genotypes and phenotypes for 24 reproduction, production, and conformation traits to explore differences between the two methods and used imputed sequence variant genotypes to fine-map six quantitative trait loci (QTL).
Results
We considered genotypes at 44,733 SNPs for 5,753 pigs from the Swiss Large White breed that had deregressed breeding values for 24 traits. Single-trait association analyses revealed eleven QTL that affected 15 traits. Multi-trait association testing and the meta-analysis of the single-trait GWAS revealed between 3 and 6 QTL, respectively, in three groups of traits. The multi-trait methods revealed three loci that were not detected in the single-trait GWAS. Four QTL that were identified in the single-trait GWAS, remained undetected in the multi-trait analyses. To pinpoint candidate causal variants for the QTL, we imputed the array-derived genotypes to the sequence level using a sequenced reference panel consisting of 421 pigs. This approach provided genotypes at 16 million imputed sequence variants with a mean accuracy of imputation of 0.94. The fine-mapping of six QTL with imputed sequence variant genotypes revealed four previously proposed causal mutations among the top variants.
Conclusions
Our findings in a medium-size cohort of pigs suggest that multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS provide very similar results. Although multi-trait association methods provide a useful overview of pleiotropic loci segregating in mapping populations, the investigation of single-trait association studies is still advised, as multi-trait methods may miss QTL that are uncovered in single-trait GWAS.
The effect of stress control training through podcast on work-life conflict in female residents of Iran University of Medical Sciences 2020-2021
Authors: Norouzi Azam , Moghimi Zahra , Ramezani Ghobad , Pourbiramian Ghadir , Sohrabi Zohreh , Rasouli Davood 
Published: February 2023

Abstract
Introduction:
Given the increasing growth of information in the present age and the growth and development of educational programs and changes that have occurred in the concept of learning, changing the approach to education from traditional methods to e-learning has become important. The present study aimed at investigating the effect of podcast stress control training on work-life conflict in female residents of Iran University of Medical Sciences in 2020–2021.
Methods
This study was a two-group quasi-experimental study (with a pretest-posttest design and a control group). The samples consisted of female resident students of Iran University of Medical Sciences in 2020–2021. As many as 70 female residents were selected and investigated by quota sampling and simple random sampling method from among the first and the last year residents. The individual demographic characteristics questionnaire and the Carlson’s Work-Family Conflict Scale (WFC) were used to collect data. Data analysis was conducted using descriptive statistics and inferential tests in SPSS-23 and the significance level was considered to be p < 0.05.
Results
The two groups were similar in terms of background variables (p = 0.0001). There was no statistically significant difference between the two groups in terms of mean scores of work-life conflict before the intervention (p = 0.931). However, two months after the intervention, a statistically significant difference was observed in the mean scores of work-life conflict between the two groups (p = 0.0000).
Conclusion
According to the results of the present study, it seems that stress control training through podcasts has reduced work-life conflict. Stress control training can reduce the residents’ work stress and work-life conflict. Thus, training stress control skills seems to be of high significance in the residents’ managerial, clinical and educational domains.
Renoprotective effect of perioperative dexmedetomidine in kidney transplant patients: systematic review and meta-analysis
Authors: Tong Tao , Mei Guo-bing , Zhang Yi-xiong 
Published: February 2023

Abstract
Objective
To find whether dexmedetomidine has a renoprotective effect in kidney transplant patients.
Methods
We electronically searched Embase, PubMed, and the Cochrane Library from create database through September 10, 2022. Including studies compared dexmedetomidine and placebo in kidney transplant patients. Extract outcomes contain the incidence of delayed graft function (DGF), acute rejection, length of hospital stay (LOS), post-transplantation 2-day SCr and post-transplantation 7-day SCr. We use Stata SE 15 software to conduct meta-analysis. All outcome were used random effects models. The continuous data and categorical date respectively reported use weighted mean difference (WMD) and odds ratio (OR) with 95% confidence interval.
Results
This meta-analysis including four RCTS and one cohort study. The incidence of DGF were lower in dexmedetomidine group than placebo (OR 0.71, 95%CI 0.52–0.97, P = 0.032). Dexmedetomidine significant improve in Post-transplantation 2-day SCr than placebo (WMD=-0.36 95% CI -0.68–0.05, P = 0.024). Other outcomes were no significant effect compared with placebo.
Conclusion
Perioperative dexmedetomidine infusion can reduce the incidence of DGF and have a protective effect on renal function at least in the early postoperative period. Due to the limited number of included studies, the above conclusions need to be verified by more high-quality studies.
Multi-channel mass sensing based on multiple internal resonances in three electrostatically coupled resonators
Authors: Zhao Jian , Sun Rongjian , Kacem Najib , Lyu Ming , Liu Pengbo 
Published: February 2023

Abstract
Multiple internal resonances in three electrostatically coupled microbeams have been theoretically investigated and were utilized to multi-channel mass detection. The frequency ratio among the three electrostatically coupled resonators of different sizes can be tuned to satisfy the specific conditions for multiple internal resonances. A reduced order model considering quadratic nonlinearity and frequency commensurability is established, and solved by the method of multiple scales, and verified by the harmonic balance method combined with the asymptotic numerical method. The nonlinear dynamics involving pitchfork and saddle-node bifurcations were analyzed and utilized to detect single, dual, or even multiple masses simultaneously. The frequency shift of the bifurcation points or the amplitude shift of a specific operating frequency near the bifurcation point were introduced as an output sensitivity. And then, a multi-channel single output detection mechanism was proposed, in addition to a single mass detection, the proposed sensor enables dual or even multi-channel mass detections based on frequency and amplitude shifts of pitchfork and saddle-node bifurcation points of the coupled and uncoupled vibration states. Furthermore, the effects of driving and coupling voltages on the dynamic response of the system were obtained. This work not only proposes a new way for multi-channel mass detection, but also provides technical support for multi-channel detection of other signals.
An immunogenic cell death-associated gene signature predicts prognosis in hepatocellular carcinoma
Authors: Liu Tianliang , Chen Xiaonan , Peng Baozhou , Zhang Hongbo 
Published: February 2023

Abstract
Background: Liver cancer is the third leading cause of cancer-related mortality in the world, and hepatocellular carcinoma (HCC) accounts for approximately 90% of the incidence of all liver cancers.
Methods: The TCGA-LIHC datasets were obtained from TCGA database, LIRI-JP datasets were obtained from ICGC database and immunogenic cell death (ICD) genes were obtained from previous literature. WGCNA analysis identifies ICD-associated genes. Functional analysis was used to investigate the biological characteristics of ICD-associated genes. Univariate cox analysis and least absolute shrinkage and selection operator (LASSO) cox regression analysis was used to select prognostic ICD-associated genes and constructed a prognostic risk score. Prognostic independence of ICD risk scores was determined by univariate and multivariate cox regression analyses. Then constructed a nomogram and the diagnostic value was assessed using the decision curve analysis. Immune infiltration analysis and drug sensitivity analysis were used to investigate immune cell enrichment and drug response in HCC patients who were classified as low- or high-risk based on their risk score.
Results: Most of ICD genes were differentially expressed in normal and HCC patients, and some ICD genes were differentially expressed in different clinical groups. A total of 185 ICD-associated genes were identified by WGCNA. A nine-gene-based (CSN1S1, FGF9, PNLIPRP2, ISM2, FKBP6, BTNL9, CLEC3B, RAMP3, and SRL) prognostic risk score was developed. Based on the risk score, training cohort were divided into low- and high-risk groups, patients in the low-risk group had a better prognosis, and external independent data verified the reliability of the model. Univariate and multivariate Cox regression analysis showed independent prognostic factors for OS of ICD risk score. Diagnostic nomogram was constructed to predict prognosis. Immune infiltration analysis showed that some innate and adaptive immune cells were significantly different between low- and high-risk groups,
Conclusion: We developed and validated a novel prognostic predictive classification system for HCC based on nine ICD-associated genes. This stratification had significant clinical outcomes for estimating prognosis, as well as the immunotherapy of HCC patients.
A comparative analysis of rainwater harvesting system and conventional sources of water
Authors: Khan Abdul Salam 
Published: February 2023

Abstract
This study examines the sufficiency of water for potable and non-potable demand. Firstly, the challenges and sufficiency of existing water sources for potable and non-potable demand are examined by considering the water gallon delivery at the doorstep, government supply line, tanker-based supply, and extraction of water through bore wells. Secondly, the cost-effectiveness of several water sources is examined by using four models, i.e., Model 1-Model 4. Each model combines sources of water (i.e., government supply line, water tankers, bore wells, mineral water delivery, and rainwater harvesting system) for potable and non-potable demand. A comparison is drawn between the cost-effectiveness of current practices and the rainwater harvesting system. The rainwater harvesting system is designed based on average rainfall data for different catchment areas and a dynamic range of residents. The findings suggest that the rainwater harvesting system is more cost-effective compared to conventional sources of water; however, it needs to be coupled with the government supply line to meet the non-potable water demand. On average, five additional houses can be covered by the rainwater harvesting system (minimum = 3 and maximum = 9) with a mean profit of 462149 PKR (minimum = 233318 PKR and maximum = 754810 PKR). Thus, even if the harvested water is not sufficient to meet the non-potable demand, it can still be preferred as a source of potable water due to its cost-effectiveness. Implications are drawn to help government and practitioners in considering sustainable actions for social well-being and promoting rain harvesting through rebates.
Identifying spatiotemporal trends of SARS-CoV-2 RNA in wastewater: From the perspective of upstream and downstream wastewater-based epidemiology (WBE)
Authors: Tran Duyen P.H , You Bo-Cheng , Liu Chen-Wuing , Chen Yi-Ning , Wang Ya-Fen , Chung Shu-Nu , Lee Jin-Jing , You Sheng-Jie 
Published: February 2023

Abstract
Recently, many efforts have been made to address the rapid spread of newly identified COVID-19 virus variants . Wastewater-based epidemiology (WBE) is considered as a potential early warning tool for identifying the rapid spread of this virus. This study investigated the occurrence of SARS-CoV-2 in eight wastewater treatment plants (WWTPs) and their sewerage systems which serve most of the population in Taoyuan City, Taiwan. Across the entire study period, the wastewater viral concentrations were correlated with the number of COVID-19 cases in each WWTP (Spearman' r = 0.23 - 0.76). In addition, it is confirmed that several treatment technologies could effectively eliminate the virus RNA from WWTPs influent (> 90 %). On the other hand, further results revealed that an inverse distance weighted (IDW) interpolation and hot spot model combined with geographic information system (GIS) method could be applied to analyze the spatiotemporal variations of SARS-CoV-2 in wastewater from sewer system. In addition, socio-economic factors namely population density, land-use, and tax-income were successfully identified as the potentials drivers which substantially affect the onset of COVID-19 outbreak in Taiwan. Finally, the data obtained from this study can provide a powerful tool in public health decision-making not only in response to the current epidemic situation but also other epidemic issues in the future.
Environmental Challenges and Concurrent Trend of Weather Extremes over Uttarakhand Himalaya
Authors: Kumar Pramod , Patel Arbind , Rai Jaya , Kumar Prem 
Published: February 2023

Abstract
Environmental challenges, including climate change-influenced weather extremes over the hilly region, is a major issue for the sustenance/ livelihood of Uttarakhand Himalayan biodiversity. The very high maximum temperature during summer days makes the area vulnerable to frequent forest fires, while the increasing frequency of intense rainfall proves devastating to infrastructure and croplands. Such erratic climate patterns make it increasingly difficult for people to live in the mountains and thus lead to climate-forced migration towards the plains. This study focuses on weather/climate extremes and their impact on Uttarakhand Himalayan people. The extreme precipitation and temperature indices have been analysed concerning landslides and forest fire incidents. Strong decreasing trends have been found for total precipitation, total run-off, soil water content, and leaf area index (LAI) for 1981–2020 (40 years) of ERA5 reanalysis datasets over the entire Uttarakhand region. A persistent rise in the number of dry days that are consecutive during the winter and the summer season is observed over central to western Uttarakhand. However, very wet and extremely rainy days have been demonstrated to rise over the higher elevations of Uttarakhand. The climate and weather extremes are observed to increase with elevation-dependent warming (EDW) over Uttarakhand’s hilly region, making sustenance difficult. Intense rainfall events are a primary driver for landslides and flash floods over higher elevations. Thereafter, over the hilly region of Uttarakhand, the number of very warm days/nights is increasing, whereas the number of extremely cold days/nights is dropping. The Uttarakhand Himalayas have witnessed an increase in weather extremes in the past four decades. The community and policymakers, however, struggle to adapt to weather extremes triggered by climate change. The results of this research will help in formulating policies for the long-term development of Uttarakhand’s hilly areas.
β-amyloid monomer scavenging by an anticalin protein prevents neuronal hyperactivity
Authors: Zott Benedikt , Nästle Lea , Grienberger Christine , Knauer Manuel , Unger Felix , Keskin Aylin , Feuerbach Anna , Busche Marc Aurel , Skerra Arne , Konnerth Arthur 
Published: February 2023

Abstract

Hyperactivity mediated by synaptotoxic β-amyloid (Aβ) oligomers is one of the earliest forms of neuronal dysfunction in Alzheimer’s disease. In the search for a preventive treatment strategy, we tested the effect of scavenging Aβ peptides prior to Aβ plaque formation. We demonstrate that an Aβ binding anticalin protein (Aβ-anticalin) can suppress early neuronal hyperactivity. Unexpectedly, the sole targeting of Aβ monomers was sufficient for the hyperactivity-suppressing effect of the Aβ-anticalin. Biochemical and neurophysiological analysis suggest that Aβ-anticalin-dependent depletion of naturally secreted Aβ monomers interrupts aggregation to neurotoxic oligomers and, thereby, prevents synaptic dysfunction. Our results demonstrate that Aβ monomer scavenging can reverse early neuronal dysfunction and, thus, offers a promising strategy for the preventive treatment of AD.
An implantable wireless tactile sensing system
Authors: Richardson Andrew , Du Lin , Hao Han , Ding Yixiao , Gabros Andrew , Mier Thomas , Spiegel Jan Van der , Lucas Timothy , Aflatouni Firooz , Allen Mark 
Published: February 2023

Abstract
The sense of touch is critical to dexterous use of the hands and thus an essential component to efforts to restore hand function after amputation or paralysis. Prosthetic systems have focused on wearable tactile sensors. But wearable sensors are suboptimal for neuroprosthetic systems designed to reanimate a patient’s own paralyzed hand. Here, we developed an implantable tactile sensing system intended for subdermal placement. The system is composed of a microfabricated capacitive force sensor, a custom integrated circuit supporting wireless powering and data transmission, and a laser-fused hermetic silica package. The miniature device was validated through simulations, benchtop testing, and ex vivo testing in a primate hand. The sensor implanted in the fingertip accurately measured skin forces with a resolution of 4.3 mN. The output from this novel sensor could be encoded in the brain with microstimulation to provide tactile feedback. More broadly, the materials, system design, and fabrication approach establish new foundational capabilities for various applications of implantable sensing systems.
Inbreeding effects on the performance and genomic prediction for polysomic tetraploid potato offspring grown at high Nordic latitudes
Authors: Ortiz Rodomiro , Reslow Fredrik , Vetukuri Ramesh , García-Gil M. Rosario , Pérez-Rodríguez Paulino , Crossa José 
Published: February 2023

Abstract
Background. Inbreeding depression (ID) is caused by an increased homozygosity in the offspring after selfing. Although the self-compatible, highly heterozygous, tetrasomic polyploid potato (Solanum tuberosum L.) suffers from ID, some argue that the potential genetic gains from using inbred lines in a sexual propagation system of potato are too large to be ignored. The aim of this research was to assess the effects of inbreeding in potato offspring performance under a high latitude and the accuracy of genomic prediction of breeding values (GEBV) for further use in selection.
Results. There were 16 parents (6 breeding clones and 10 cultivars) used in the crossing block. Four of them underwent selfing producing 113 ± 42 S1 seeds, while the seed set in the F1 hybrid offspring was 149 ± 29, suggesting inbreeding did not affect the crossing outcome but may have influenced the seed set. Four inbred (S1) and two hybrid (F1) offspring, and their parents (S0) were used in the experiment, with a field layout of an augmented design with the four S0 replicated in nine incomplete blocks comprising 100, 4-plant plots at Umeå (63°49′30″N 20°15′50″E), Sweden. The S0 was significantly (P < 0.01) better than both S1 and F1 offspring for tuber weight (total and according to five grading sizes), tuber shape and size uniformity, tuber eye depth and reducing sugars in the tuber flesh, while the F1 was significantly (P < 0.01) better than S1 for all tuber weight and uniformity traits. Some F1 hybrid offspring (15–19%) had better total tuber yield than the best performing parent. The GEBV accuracy ranged from -0.3928 to 0.4436. Overall, tuber shape uniformity had the highest GEBV accuracy, while tuber weight traits exhibited the lowest. The F1 full sib’s GEBV accuracy was higher, on average, than that of the S1.
Conclusion. Accuracy estimates suggest a non-related training population (either S1 or F1) should not be used for early stages of genomic selection in potato breeding population. Genomic prediction may facilitate eliminating undesired inbred or hybrid offspring for further use in the genetic betterment of potato.
A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data
Authors: Mathew Jino , Kshirsagar Rohit , Abidin Dzariff Z , Griffin James , Kanarachos Stratis , James Jithin , Alamaniotis Miltos , Fitzpatrick Michael E 
Published: February 2023

Abstract
The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.
The region interior to the event horizon of rotating regular black holes
Authors: Gonzalez-Morales B. Angelica , Breton Nora , Perez-Roman Ivan 
Published: February 2023

Abstract
The interior of two regular rotating black holes is analyzed, Hayward and Simpson-Visser, through the velocities and fall times of a free particle toward their center when it penetrates the event horizon. The particle traverses the event horizon with the velocity of light, then it increases for a certain lapse, decreases, and at the inner horizon it is light's; the speed continues decreasing as the particle approaches the origin; in Hayward and Kerr black holes it reaches the origin with zero speed while for Simpson-Visser black hole it traverses the wormhole throat located at r=0 with finite velocity. The measurements of two different observers are compared, one falling down and the other being a distant observer. Travel time intervals from the event horizon to the origin, and from a distant point to the horizon are calculated and compared with Kerr's.