bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing temporal and geographic contacts across the Adriatic Sea through the analysis of genome-wide data from Southern Italy
Authors: Raveane Alessandro , Molinaro Ludovica , Aneli Serena , Capodiferro Marco Rosario , Ongaro Linda , Migliore Nicola Rambaldi , Soffiati Sara , Scarano Teodoro , Torroni Antonio , Achilli Alessandro , Ventura Mario , Pagani Luca , Capelli Cristian , Olivieri Anna , Bertolini Francesco , Semino Ornella , Montinaro Francesco 
Published: March 2022

AbstractSouthern Italy was characterised by a complex prehistory that started with different Palaeolithic cultures, later followed by the Neolithic transition and the demic dispersal from the Pontic-Caspian Steppe during the Bronze Age. Archaeological and historical evidence points to demic and cultural influences between Southern Italians and the Balkans, starting with the initial Palaeolithic occupation until historical and modern times. To shed light on the dynamics of these contacts, we analysed a genome-wide SNP dataset of more than 700 individuals from the South Mediterranean area (102 from Southern Italy), combined with ancient DNA from neighbouring areas. Our findings revealed high affinities of South-Eastern Italians with modern Eastern Peloponnesians, and a closer affinity of ancient Greek genomes with those from specific regions of South Italy than modern Greek genomes. The higher similarity could be associated with the presence of a Bronze Age component ultimately originating from the Caucasus and characterised by high frequencies of Iranian and Anatolian Neolithic ancestries. Furthermore, to reveal possible signals of natural selection, we looked for extremely differentiated allele frequencies among Northern and Southern Italy, uncovering putatively adapted SNPs in genes involved in alcohol metabolism, nevi features and immunological traits, such as ALDH2,NID1andCBLB.
Salient 40 Hz sounds probe affective aversion and neural excitability
Authors: Schneefeld F , Doelling K , Marchesotti S , Schwartz S , Igloi K , Giraud A-L , Arnal LH 
Published: March 2022

AbstractThe human auditory system is not equally reactive to all frequencies of the audible spectrum. Emotional and behavioral reactions to loud or aversive acoustic features can vary from one individual to another, to the point that some exhibit exaggerated or even pathological responses to certain sounds. The neural mechanisms underlying these interindividual differences remain unclear. Whether distinct aversion profiles map onto neural excitability at the individual level needs to be tested. Here, we measured behavioral and EEG responses to click trains (from 10 to 250 Hz, spanning the roughness and pitch perceptual ranges) to test the hypothesis that interindividual variability in aversion to rough sounds is reflected in neural response differences between participants. Linking subjective aversion to 40 Hz steady-state EEG responses, we demonstrate that participants experiencing enhanced aversion to roughness also show stronger neural responses to this attribute. Interestingly, this pattern also correlates with inter-individual anxiety levels, suggesting that this personality trait might interact with subjective sensitivity and neural excitability to these sounds. These results support the idea that 40 Hz sounds can probe the excitability of non-canonical auditory systems involved in exogenous salience processing and aversive responses at the individual level. By linking subjective aversion to neural excitability, 40 Hz sounds provide neuromarkers relevant to a variety of pathological conditions, such as those featuring enhanced emotional sensitivity (hyperacusis, anxiety) or aberrant neural responses at 40 Hz (autism, schizophrenia).
UPP2: Fast and Accurate Alignment Estimation of Datasets with Fragmentary Sequences
Authors: Park Minhyuk , Ivanovic Stefan , Chu Gillian , Shen Chengze , Warnow Tandy 
Published: March 2022

AbstractMotivationMultiple sequence alignment (MSA) is a basic step in many bioinformatics pipelines. However, achieving highly accurate alignments on large datasets, especially those with sequence length heterogeneity, is a challenging task. UPP (Ultra-large multiple sequence alignment using Phylogeny-aware Profiles) is a method for MSA estimation that builds an ensemble of Hidden Markov Models (eHMM) to represent an estimated alignment on the full length sequences in the input, and then adds the remaining sequences into the alignment using selected HMMs in the ensemble. Although UPP provides good accuracy, it is computationally intensive on large datasets.ResultsWe present UPP2, a direct improvement on UPP. The main advance is a fast technique for selecting HMMs in the ensemble that allows us to achieve the same accuracy as UPP but with greatly reduced runtime. We show UPP2 produces more accurate alignments compared to leading MSA methods on datasets exhibiting substantial sequence length heterogeneity, and is among the most accurate otherwise.Availabilityhttps://github.com/gillichu/seppContactwarnow@illinois.edu
The role of floral traits in community assembly process at high elevations in Lesser Himalaya
Authors: Ahmad Mustaqeem , Rosbakh Sergey , Bucher Solveig Franziska , Sharma Padma , Rathee Sonia , Uniyal Sanjay Kr. , Batish Daizy R. , Singh Harminder P. 
Published: March 2022

AbstractEcological theory postulates that plant trait research should consider multiple traits related to different organs and/or ontogenetic stages as such traits represent different ecological niche axes. Particularly, floral traits have been suggested to play an important role in assembling plant communities along environmental gradients as they determine the reproductive success, one of the key functions in plants. Yet, the predictive power of floral traits in community assembly research remains largely unverified empirically.We analyzed the predictive power of six floral traits of 139 herbaceous species for inferring community assembly process in twenty-one sites located along an elevation gradient in Lesser Himalaya ranging from 2,000 to 4,000 meters above sea level. The floral trait variability along the gradient was analyzed using community-weighted trait mean (CWM) values and functional diversities (FD) calculated for each of the study communities.The CWM values for onset of flowering and flower display area increased significantly with increasing elevation, whereas specific flower area showed an opposite pattern. In combination with convergence in onset of flowering and specific area (i.e., lower FD values in high elevation sites), these patterns suggest that abiotic filtering and plant-pollinator interactions affected the floral trait composition of the communities studied. Increasing low-temperature stress towards high-elevation sites selected for late-flowering species that produce resource-intensive flowers with larger display areas.Low pollinator abundancy and activity in high elevation, could also explain why these traits were selected in the study communities. Delayed flowering with increasing elevations might facilitate the phenological overlap of plants and their pollinators, as pollinator activity at higher elevation peaks in the second half of the vegetation period. The dominance of species with low specific flower area and larger display area in high elevation communities were attributed to the increased flower longevity and attraction of pollinators, respectively, to maximize pollination success under pollinator scarcity.Synthesis. Our study provides empirical support of the recent argument that floral traits contribute considerably to the assembly of plant communities along environmental gradients. Thus, such traits should be included into community assembly research agenda as they represent key growth and survival ecological functions.
Enabling spatiotemporal regulation within biomaterials using DNA reaction-diffusion waveguides
Authors: Dorsey Phillip J. , Scalise Dominic , Schulman Rebecca 
Published: March 2022

AbstractIn multicellular organisms, cells and tissues coordinate biochemical signal propagation across length scales spanning microns to meters. Endowing synthetic materials with similar capacities for coordinated signal propagation could allow these systems to adaptively regulate themselves across space and over time. Here we combine ideas from cell signaling and electronic circuitry to design a biochemical waveguide that transmits information in the form of a concentration of a DNA species on a directed path. The waveguide can be seamlessly integrated into a soft material because there is virtually no difference between the chemical or physical properties of the waveguide and the material it is embedded within. We propose the design of DNA strand displacement reactions to construct the system and, using reaction-diffusion models, identify kinetic and diffusive parameters that enable super-diffusive transport of DNA species via autocatalysis. Finally, to support experimental waveguide implementation, we show how a sink reaction could mitigate the spurious amplification of an autocatalyst within the waveguide, allowing for controlled waveguide triggering. Chemical waveguides could facilitate the design of synthetic biomaterials with distributed sensing machinery integrated throughout their structure and enable coordinated self-regulating programs triggered by changing environmental conditions.
Intraspecific diversification and mitonuclear discordance in native versus introduced areas: co-introduction ofDolicirroplectanum lacustre, a monogenean gill parasite of the invasive Nile perchLates niloticus
Authors: Thys Kelly J. M. , Vanhove Maarten P.M. , Custers Jonas W. J. , Vranken Nathan , Van Steenberge Maarten , Kmentová Nikol 
Published: March 2022

AbstractThe Nile perch (Lates niloticus) is a notorious invasive species. The introductions of Nile perch into several lakes and rivers in the Lake Victoria region led to the impoverishment of the trophic food webs, particularly well documented in Lake Victoria. Along with the introductions of the Nile perch, its parasites were co-introduced.Dolicirroplectanum lacustre(Monogenea, Diplectanidae) is a gill parasite of latid fishes (Latesspp.) inhabiting several major African freshwater systems. We examined the intra-specific diversification ofD. lacustrefromL. niloticusin Lake Albert (native range) and Lake Victoria (introduced range) by assessing morphological and genetic differentiation, and microhabitat preference. We expected reduced morphological and genetic diversity forD. lacustrein Lake Victoria compared to Lake Albert, as a result of the historical introductions.Dolicirroplectanum lacustredisplays high morphological variability within and between African freshwaters. Mitonuclear discordance within the morphotypes ofD. lacustreindicates an incomplete reproductive barrier between the morphotypes. The diversification in the mitochondrial gene portion is directly linked with the morphotypes, while the nuclear gene portions indicate conspecificity. Based on our results, we reported reduced genetic and morphological diversity, potentially being a result of a founder effect in Lake Victoria.
Comparison of Rapid Antigen Tests’ Performance between Delta (B.1.61.7; AY.X) and Omicron (B.1.1.529; BA1) Variants of SARS-CoV-2: Secondary Analysis from a Serial Home Self-Testing Study
Authors: Soni Apurv , Herbert Carly , Filippaios Andreas , Broach John , Colubri Andres , Fahey Nisha , Woods Kelsey , Nanavati Janvi , Wright Colton , Orwig Taylor , Gilliam Karen , Kheterpal Vik , Suvarna Thejas , Nowak Chris , Schrader Summer , Lin Honghuang , O’Connor Laurel , Pretz Caitlin , Ayturk Didem , Orvek Elizabeth , Flahive Julie , Lazar Peter , Shi Qiming , Achenbach Chad , Murphy Robert , Robinson Matthew , Gibson Laura , Stamegna Pamela , Hafer Nathaniel , Luzuriaga Katherine , Barton Bruce , Heetderks William , Manabe Yukari C. , McManus David 
Published: March 2022

AbstractBackgroundThere is a need to understand the performance of rapid antigen tests (Ag-RDT) for detection of the Delta (B.1.61.7; AY.X) and Omicron (B.1.1.529; BA1) SARS-CoV-2 variants.MethodsParticipants without any symptoms were enrolled from October 18, 2021 to January 24, 2022 and performed Ag-RDT and RT-PCR tests every 48 hours for 15 days. This study represents a non-pre-specified analysis in which we sought to determine if sensitivity of Ag-RDT differed in participants with Delta compared to Omicron variant. Participants who were positive on RT-PCR on the first day of the testing period were excluded. Delta and Omicron variants were defined based on sequencing and date of first RT-PCR positive result (RT-PCR+). Comparison of Ag-RDT performance between the variants was based on sensitivity, defined as proportion of participants with Ag-RDT+ results in relation to their first RT-PCR+ result, for different duration of testing with rapid Ag-RDT. Subsample analysis was performed based on the result of participants’ second RT-PCR test within 48 hours of the first RT-PCR+ test.ResultsFrom the 7,349 participants enrolled in the parent study, 5,506 met the eligibility criteria for this analysis. A total of 153 participants were RT-PCR+ (61 Delta, 92 Omicron); among this group, 36 (23.5%) tested Ag-RDT+ on the same day, and 84 (54.9%) tested Ag-RDT+ within 48 hours as first RT-PCR+. The differences in sensitivity between variants were not statistically significant (same-day: Delta 16.4% [95% CI: 8.2-28.1] vs Omicron 28.2% [95% CI: 19.4-38.6]; and 48-hours: Delta 45.9% [33.1-59.2] vs. Omicron 60.9% [50.1-70.9]). This trend continued among the 86 participants who had consecutive RT-PCR+ result (48-hour sensitivity: Delta 79.3% [60.3-92.1] vs. Omicron: 89.5% [78.5-96.0]). Conversely, the 38 participants who had an isolated RT-PCR+ remained consistently negative on Ag-RDT, regardless of the variant.ConclusionsThe performance of Ag-RDT is not inferior among individuals infected with the SARS-CoV-2 Omicron variant as compared to the Delta variant. The improvement in sensitivity of Ag-RDT noted with serial testing is consistent between Delta and Omicron variant. Performance of Ag-RDT varies based on duration of RT-PCR+ results and more studies are needed to understand the clinical and public health significance of individuals who are RT-PCR+ for less than 48 hours.
GatorTron: A Large Language Model for Clinical Natural Language Processing
Authors: Yang Xi , PourNejatian Nima , Shin Hoo Chang , Smith Kaleb E , Parisien Christopher , Compas Colin , Martin Cheryl , Flores Mona G , Zhang Ying , Magoc Tanja , Harle Christopher A , Lipori Gloria , Mitchell Duane A , Hogan William R , Shenkman Elizabeth A , Bian Jiang , Wu Yonghui 
Published: March 2022

ABSTRACTObjectiveTo develop a large pretrained clinical language model from scratch using transformer architecture; systematically examine how transformer models of different sizes could help 5 clinical natural language processing (NLP) tasks at different linguistic levels.MethodsWe created a large corpus with >90 billion words from clinical narratives (>82 billion words), scientific literature (6 billion words), and general English text (2.5 billion words). We developed GatorTron models from scratch using the BERT architecture of different sizes including 345 million, 3.9 billion, and 8.9 billion parameters, compared GatorTron with three existing transformer models in the clinical and biomedical domain on 5 different clinical NLP tasks including clinical concept extraction, relation extraction, semantic textual similarity, natural language inference, and medical question answering, to examine how large transformer models could help clinical NLP at different linguistic levels.Results and ConclusionGatorTron scaled up transformer-based clinical language models to a size of 8.9 billion parameters and achieved state-of-the-art performance on 5 clinical NLP tasks of different linguistic levels targeting various healthcare information documented in unstructured electronic health records (EHRs). The proposed GatorTron models performed remarkably better in much complex clinical NLP tasks such as natural language inference (9.6% and 7.5% improvements) and question answering (9.5% and 7.77% improvements) compared with existing smaller clinical transformer models (i.e., BioBERT and ClinicalBERT), demonstrating the potential of large transformer-based clinical models for advanced medical artificial intelligent (AI) applications such as question answering.
Motor Neuron Disease is not clustered or associated with socioeconomic deprivation in Scotland
Authors: Chang Yuan-Ting , Kearns Patrick K.A. , Newton Judith , Larraz Juan , Forbes Deborah , Beswick Emily , Leighton Danielle , Langlands Gavin , Swingler Robert J. , Chandran Siddharthan , Pal Suvankar 
Published: March 2022

AbstractBackground and ObjectivesUnderstanding risk factors and spatial variation of risk may provide insights into the pathological mechanism of motor neuron disease (MND). Socioeconomic status (SES) has been hypothesised as a risk factor, but results from previous studies are inconsistent. No spatial epidemiology studies examining geographic clustering of MND have been performed in Scotland to date. We investigated the effect of SES and geography on MND risk in Scotland using the highly curated and nationally representative Scottish MND Register (CARE-MND) that has over 95% case ascertainment.MethodsPatients on the Scottish Clinical Audit Research Evaluation for Motor Neurone Disease platform, with date of diagnosis between 01 Jan 2015 and 28 Feb 2021 were included and geocoded with data zones using their residence at diagnosis. Indirectly standardised incidence ratio (SIR) accounting for age and sex was calculated for each health board. Poisson regression was used to examine the effect of SES on MND risk, adjusted for age and sex of population at risk. Geographic clustering was assessed using global Moran’s Index, Bayesian conditional autoregressive models and SaTScan software.ResultsAmong 1149 patients included, 1126 (98%) were successfully geocoded. Significantly lower SIR was shown in Highland (0.60, 95% CI 0.44 – 0.80, p<0.001). After adjusting for age and sex in Poisson regression, there was no significant effect of SES on MND risk. Moran’s Index indicated a weak but significant spatial autocorrelation (I=0.017, p=0.008). However, risk maps using Bayesian modelling showed a relatively homogeneous distribution without distinct patterns across Scotland. Similarly, SaTScan did not detect any significant cluster of high or low risks.DiscussionOur findings support the notion that MND risk is mostly random-distributed and independent of SES in Scotland. Our results are generalizable to other MND populations.
Phantom-based quantification of the spectral accuracy in dual-layer spectral CT for pediatric imaging at 100 kVp
Authors: Meyer Sebastian , Liu Leening P. , Litt Harold I. , Halliburton Sandra S. , Shapira Nadav , Noël Peter B. 
Published: March 2022

AbstractObjectivesTo determine the spectral accuracy in detector-based dual-energy CT (DECT) at 100 kVp and wide (8 cm) collimation width for dose levels and object sizes relevant to pediatric imaging.MethodsA spectral CT phantom containing tissue-equivalent materials and iodine inserts of varying concentrations was scanned on the latest generation detector-based DECT system. Two 3D-printed extension rings were used to mimic varying pediatric patient sizes. Scans were performed at 100 and 120 kVp, 4 and 8 cm collimation widths, and progressively reduced radiation dose levels, down to 10% of the nominal value for the standard pediatric abdominal protocol. Virtual mono-energetic, iodine density, effective atomic number, and electron density results were quantified and compared to their expected values for all acquisition settings and phantom sizes.ResultsDECT scans at 100 kVp provided highly accurate spectral results; however, a size dependence was observed for iodine quantification. For the medium phantom configuration (15 cm diameter), measurement errors in iodine density, effective atomic number, and electron density (ED) were below 0.3 mg/ml, 0.2 and 1.8 %EDwater, respectively. The average accuracy was slightly different from scans at 120 kVp; however, not statistically significant for all configurations. Collimation width had no substantial impact. Spectral results were accurate and reliable for radiation exposures down to 0.9 mGy CTDIvol.ConclusionsDetector-based DECT at 100 kVp can provide on-demand or retrospective spectral information with high accuracy even at extremely low doses, thereby making it an attractive solution for pediatric imaging.Key pointsDual-layer spectral CT at 100 kVp enables high-quality spectral imaging for smaller patientsLarger collimation width does not affect the accuracy of spectral resultsAccurate and reliable spectral quantification is achievable at radiation doses down to 0.9 mGy
Vaccine hesitancy strongly correlates with COVID-19 deaths underreporting
Authors: Sobieszek Adam , Lipniacka Miriam , Lipniacki Tomasz 
Published: March 2022

AbstractVaccine acceptance is a key factor in achieving high immunization coverage and reducing the death toll of COVID-19 pandemic. Analyzing data from Europe and Americas we demonstrated that vaccine hesitancy strongly correlates with underreporting of COVID-19 deaths and cases. This correlation cannot be explained by the differences in economic indexes: GDP and Gini coefficient (measure of income inequalities). There is no correlation of vaccination percentage and Gini coefficient and the correlation with GDP is decreasing in time. The most striking is the comparison of Eastern European and South American countries; the latter group of countries shows significantly higher vaccination percentage while having a lower or comparable GDP and higher Gini coefficient. The analysis suggests that timely and reliable information about the COVID-19 cases and the associated deaths plays a key role in achieving population-wide vaccine acceptance.
Development and validation of a cardiovascular diseases risk prediction model for Chinese males (CVDMCM)
Authors: Shan Ying , Zhang Yucong , Zhao Yanping , Lu Yueqi , Chen Bangwei , Yang Liuqiao , Tan Cong , Bai Yong , Sang Yu , Liu Juehan , Jian Min , Ruan Lei , Zhang Cuntai , Li Tao 
Published: March 2022

AbstractAimsDeath due to cardiovascular diseases (CVD) increased significantly in China. One way to reduce CVD is to identify people at risk and provide targeted intervention. We aim to develop and validate a CVD risk prediction model for Chinese males (CVDMCM) to help clinicians identify those at risk of CVD and provide targeted intervention.Methods and ResultsWe conducted a retrospective cohort study of 2331 Chinese males without prior CVD to develop and internally validate the CVDMCM. These participants had a baseline physical examination record (2008-2016) and one revisit record by September 2019. With the full cohort, we used single factor cox regression to examine each candidate predictor adjusted for age. 16 sequential prediction models were built on significant predictors. CVDMCM was selected based on the Akaike information criterion, the area under the ROC curve, and the percentage of variation in outcome values explained by the model (R2). This model, the Framingham CVD risk model, and the Wu’s simplified model were all validated by bootstrapping with 1000 repetitions. CVDMCM’s C statistics (0.779, 95% CI: 0.733-0.825), D statistic (4.738, 95% CI: 3.270-6.864), and calibration plot demonstrated that CVDMCM outperformed the other two models.ConclusionsWe developed and internally validated CVDMCM, which predicted 4-year CVD risk for Chinese males with a better performance than Framingham CVD model and Wu’s simplified model. In addition, we developed a web calculator for physicians to conveniently generate CVD risk scores and identify those with a higher risk of CVD. We believe CVDMCM had great potential for clinical usage.