bluuebunny/crossref_metadata_2025_split huggingface dataset:
Explainability in transformer models for functional genomics
Authors: Clauwaert Jim , Menschaert Gerben , Waegeman Willem 
Published: February 2021

Abstract
The effectiveness of deep learning methods can be largely attributed to the automated extraction of relevant features from raw data. In the field of functional genomics, this generally concerns the automatic selection of relevant nucleotide motifs from DNA sequences. To benefit from automated learning methods, new strategies are required that unveil the decision-making process of trained models. In this paper, we present a new approach that has been successful in gathering insights on the transcription process in Escherichia coli. This work builds upon a transformer-based neural network framework designed for prokaryotic genome annotation purposes. We find that the majority of subunits (attention heads) of the model are specialized towards identifying transcription factors and are able to successfully characterize both their binding sites and consensus sequences, uncovering both well-known and potentially novel elements involved in the initiation of the transcription process. With the specialization of the attention heads occurring automatically, we believe transformer models to be of high interest towards the creation of explainable neural networks in this field.
DECO: a framework for jointly analyzingde novoand rare case/control variants, and biological pathways
Authors: Nguyen Tan-Hoang , He Xin , Brown Ruth C , Webb Bradley T , Kendler Kenneth S , Vladimirov Vladimir I , Riley Brien P , Bacanu Silviu-Alin 
Published: February 2021

AbstractMotivation: Rare variant-based analyses are beginning to identify risk genes for neuropsychiatric disorders and other diseases. However, the identified genes only account for a fraction of predicted causal genes. Recent studies have shown that rare damaging variants are significantly enriched in specific gene-sets. Methods which are able to jointly model rare variants and gene-sets to identify enriched gene-sets and use these enriched gene-sets to prioritize additional risk genes could improve understanding of the genetic architecture of diseases.Results: We propose DECO (Integrated analysis of de novo mutations, rare case/control variants and omics information via gene-sets), an integrated method for rare-variant and gene-set analysis. The method can (i) test the enrichment of gene-sets directly within the statistical model, and (ii) use enriched gene-sets to rank existing genes and prioritize additional risk genes for tested disorders. In simulations, DECO performs better than a homologous method that uses only variant data. To demonstrate the application of the proposed protocol, we have applied this approach to rare-variant datasets of schizophrenia. Compared with a method which only uses variant information, DECO is able to prioritize additional risk genes.Availability: DECO can be used to analyze rare-variants and biological pathways or cell types for any disease. The package is available on Github https://github.com/hoangtn/DECO.
Identification of active molecules againstMycobacterium tuberculosisthrough machine learning
Authors: Ye Qing , Chai Xin , Jiang Dejun , Yang Liu , Shen Chao , Zhang Xujun , Li Dan , Cao Dongsheng , Hou Tingjun 
Published: February 2021

AbstractTuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb) and it has been one of the top 10 causes of death globally. Drug-resistant tuberculosis (XDR-TB), extensively resistant to the commonly used first-line drugs, has emerged as a major challenge to TB treatment. Hence, it is quite necessary to discover novel drug candidates for TB treatment. In this study, based on different types of molecular representations, four machine learning (ML) algorithms, including support vector machine, random forest (RF), extreme gradient boosting (XGBoost) and deep neural networks (DNN), were used to develop classification models to distinguish Mtb inhibitors from noninhibitors. The results demonstrate that the XGBoost model exhibits the best prediction performance. Then, two consensus strategies were employed to integrate the predictions from multiple models. The evaluation results illustrate that the consensus model by stacking the RF, XGBoost and DNN predictions offers the best predictions with area under the receiver operating characteristic curve of 0.842 and 0.942 for the 10-fold cross-validated training set and external test set, respectively. Besides, the association between the important descriptors and the bioactivities of molecules was interpreted by using the Shapley additive explanations method. Finally, an online webserver called ChemTB (http://cadd.zju.edu.cn/chemtb/) was developed, and it offers a freely available computational tool to detect potential Mtb inhibitors.
Statistical inference on shape and size indexes for counting processes
Authors: Sun Yifei , Chiou Sy Han , Marr Kieren A , Huang Chiung-Yu 
Published: February 2021

Summary
Single-index models have gained increased popularity in time-to-event analysis owing to their model flexibility and advantage in dimension reduction. We propose a semiparametric framework for the rate function of a recurrent event counting process by modelling its size and shape components with single-index models. With additional monotone constraints on the two link functions for the size and shape components, the proposed model possesses the desired directional interpretability of covariate effects and encompasses many commonly used models as special cases. To tackle the analytical challenges arising from leaving the two link functions unspecified, we develop a two-step rank-based estimation procedure to estimate the regression parameters with or without informative censoring. The proposed estimators are asymptotically normal, with a root-$n$ convergence rate. To guide model selection, we develop hypothesis testing procedures for checking shape and size independence. Simulation studies and a data example on a hematopoietic stem cell transplantation study are presented to illustrate the proposed methodology.
Capturing Practice Wisdom: Advancing the Empowerment of Women from Refugee and Migrant Backgrounds
Authors: Whitaker Louise , Hughes Mandy , Rugendyke Barbara 
Published: February 2021

AbstractInternationally, the evidence about the successful design of refugee settlement programs is limited. To help address this gap, we examined staff practices within a program that aimed to advance the education, employment and empowerment of women from refugee and migrant backgrounds in communities in Northern New South Wales and South East Queensland in Australia. We engaged staff in collaborative critical reflection about their practice. Viewed through intersectionality, our findings revealed the empowering practice of staff in program design, in the ways that they worked together as a team and in their collaboration with broader supportive social networks. This practice was crucial to the program’s success and informed staff’ conceptualisation of what constituted that success. In brief, this study revealed the complex, often subtle features of professional practice that strives to be empowering in both the delivery of social service programs in this field and in the conceptualisation of program success. Future research is needed to acknowledge and support the developing practice wisdom in this field.
Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts
Authors: Dimitrova Ralica , Arulkumaran Sophie , Carney Olivia , Chew Andrew , Falconer Shona , Ciarrusta Judit , Wolfers Thomas , Batalle Dafnis , Cordero-Grande Lucilio , Price Anthony N , Teixeira Rui P A G , Hughes Emer , Egloff Alexia , Hutter Jana , Makropoulos Antonios , Robinson Emma C , Schuh Andreas , Vecchiato Katy , Steinweg Johannes K , Macleod Russell , Marquand Andre F , McAlonan Grainne , Rutherford Mary A , Counsell Serena J , Smith Stephen M , Rueckert Daniel , Hajnal Joseph V , O’Muircheartaigh Jonathan , Edwards A David 
Published: February 2021

Abstract
The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.
A Stronger Innate Immune Response During Hyperacute Human Immunodeficiency Virus Type 1 (HIV-1) Infection Is Associated With Acute Retroviral Syndrome
Authors: Hassan Amin S , Hare Jonathan , Gounder Kamini , Nazziwa Jamirah , Karlson Sara , Olsson Linnéa , Streatfield Claire , Kamali Anatoli , Karita Etienne , Kilembe William , Price Matt A , Borrow Persephone , Björkman Per , Kaleebu Pontiano , Allen Susan , Hunter Eric , Ndung’u Thumbi , Gilmour Jill , Rowland-Jones Sarah , Esbjörnsson Joakim , Sanders Eduard J 
Published: February 2021

AbstractBackgroundAcute retroviral syndrome (ARS) is associated with human immunodeficiency virus type 1 (HIV-1) subtype and disease progression, but the underlying immunopathological pathways are poorly understood. We aimed to elucidate associations between innate immune responses during hyperacute HIV-1 infection (hAHI) and ARS.MethodsPlasma samples obtained from volunteers (≥18.0 years) before and during hAHI, defined as HIV-1 antibody negative and RNA or p24 antigen positive, from Kenya, Rwanda, Uganda, Zambia, and Sweden were analyzed. Forty soluble innate immune markers were measured using multiplexed assays. Immune responses were differentiated into volunteers with stronger and comparatively weaker responses using principal component analysis. Presence or absence of ARS was defined based on 11 symptoms using latent class analysis. Logistic regression was used to determine associations between immune responses and ARS.ResultsOf 55 volunteers, 31 (56%) had ARS. Volunteers with stronger immune responses (n = 36 [65%]) had increased odds of ARS which was independent of HIV-1 subtype, age, and risk group (adjusted odds ratio, 7.1 [95% confidence interval {CI}: 1.7–28.8], P = .003). Interferon gamma-induced protein (IP)-10 was 14-fold higher during hAHI, elevated in 7 of the 11 symptoms and independently associated with ARS. IP-10 threshold &gt;466.0 pg/mL differentiated stronger immune responses with a sensitivity of 84.2% (95% CI: 60.4–96.6) and specificity of 100.0% (95% CI]: 90.3–100.0).ConclusionsA stronger innate immune response during hAHI was associated with ARS. Plasma IP-10 may be a candidate biomarker of stronger innate immunity. Our findings provide further insights on innate immune responses in regulating ARS and may inform the design of vaccine candidates harnessing innate immunity.
Schlafen 11 Is a Novel Target for Mucosal Regeneration in Ulcerative Colitis
Authors: Watanabe Sho , Nishimura Ryu , Shirasaki Tomoaki , Katsukura Nobuhiro , Hibiya Shuji , Kirimura Susumu , Negi Mariko , Okamoto Ryuichi , Matsumoto Yuka , Nakamura Tetsuya , Watanabe Mamoru , Tsuchiya Kiichiro 
Published: February 2021

Abstract

Background and Aims
Ulcerative colitis [UC] is a chronic inflammatory disease of the colon with an intractable course. Although the goal of UC therapy is to achieve mucosal healing, the pathogenesis of mucosal injury caused by chronic inflammation remains unknown. We therefore aim to elucidate molecular mechanisms of mucosal injury by establishing in vitro and in vivo humanised UC-mimicking models.

Methods
An in vitro model using human colon organoids was established by 60 weeks of inflammatory stimulation. The key gene for mucosal injury caused by long-term inflammation was identified by microarray analysis. An in vivo model was established by xenotransplantation of organoids into mouse colonic mucosa.

Results
An in vitro model demonstrated that long-term inflammation induced irrecoverable changes in organoids: inflammatory response and apoptosis with oxidative stress and suppression of cell viability. This model also mimicked organoids derived from patients with UC at the gene expression and phenotype levels. Microarray analysis revealed Schlafen11 [SLFN11] was irreversibly induced by long-term inflammation. Consistently, SLFN11 was highly expressed in UC mucosa but absent in normal mucosa. The knockdown of SLFN11 [SLFN11-KD] suppressed apoptosis of intestinal epithelial cells [IECs] induced by inflammation. Moreover, SLFN11-KD improved the take rates of xenotransplantation and induced the regenerative changes of crypts observed in patients with UC in remission.

Conclusions
In vitro and in vivo UC-mimicking models were uniquely established using human colonic organoids. They revealed that SLFN11 is significant for mucosal injury in UC, and demonstrated its potential as a novel target for mucosal regeneration.
Comparative Meta-analysis Effects of Nonnative Ants (Hymenoptera: Formicidae), Ground Beetles (Coleoptera: Carabidae), and Bark and Ambrosia Beetles (Coleoptera: Curculionidae) on Native Confamilials
Authors: Hartshorn Jessica A , Coyle David R 
Published: February 2021

AbstractNonnative species often transform local communities to the detriment of native species. Much of the existing invasion ecology research focuses on the effects of a few extremely impactful species, and it is less clear how nonnative species which are not causing economic or ecological impacts alter closely related natives at risk of being displaced. Filling these knowledge gaps is critical because consequences of nonnative species are likely to vary depending on taxonomic scale, functional trait, and spatial or temporal niche. We conducted a meta-analysis to evaluate how biodiversity of native Formicidae (ants), Carabidae (ground beetles), and Scolytinae (bark and ambrosia beetles) species changes across a gradient of pressure from nonnative confamilials. We calculated Hill numbers for each group from data presented in literature and correlated native diversity metrics to proportion of nonnative species. Species richness of native ants was significantly negatively correlated with proportions of nonnative ants, whereas bark and ambrosia beetle metrics showed a nonsignificant negative correlation. Nonnative ground beetles had neutral effects on diversity of native ground beetles. Resulting contrasting patterns of invasive species effects on natives suggest complex biotic and abiotic factors driving effects of nonnative species in these groups. Our results suggest that a few extreme examples (e.g., red imported fire ants) drive most of the changes seen in native arthropod communities. To accurately assess impacts of invaders on native arthropod diversity, baseline data are needed, and community analyses must consider diverse functional traits of native taxa and improve the depth and breadth of community sampling.
The Comparative Panel File: Harmonized Household Panel Surveys from Seven Countries
Authors: Turek Konrad , Kalmijn Matthijs , Leopold Thomas 
Published: February 2021

AbstractThe Comparative Panel File (CPF) harmonizes the world’s largest and longest-running household panel surveys from seven countries: Australia (HILDA), Germany (SOEP), United Kingdom (BHPS and UKHLS), South Korea (KLIPS), Russia (RLMS), Switzerland (SHP), and the United States (PSID). The project aims to support the social science community in the analysis of comparative life course data. The CPF builds on the Cross-National Equivalent File but offers a larger range of variables, larger and more recent samples, an easier and more flexible workflow, and an open science platform for development. The CPF is not a data product but an open-source code that integrates individual and household panel data from all seven surveys into a harmonized three-level data structure. The CPF allows analysing individual trajectories, time trends, contextual effects, and country differences. The project is organized as an open science platform. The CPF version 1.0 contains 2.7 million observations from 360,000 respondents, covering the period from 1968 to 2019 and up to 40 panel waves per respondent. In this data brief, we present the background, design, and content of the CPF.
Neighbourhood characteristics and children’s oral health: a multilevel population-based cohort study
Authors: van Meijeren-van Lunteren Agatha W , Oude Groeniger Joost , Wolvius Eppo B , Kragt Lea 
Published: February 2021

Abstract

Background
To understand determinants of oral health inequalities, multilevel modelling is a useful manner to study contextual factors in relation to individual oral health. Several studies outside Europe have been performed so far, however, contextual variables used are diverse and results conflicting. Therefore, this study investigated whether neighbourhood level differences in oral health exist, and whether any of the neighbourhood characteristics used were associated with oral health.

Methods
This study is embedded in The Generation R Study, a prospective cohort study conducted in The Netherlands. In total, 5 960 6-year-old children, representing 158 neighbourhoods in the area of Rotterdam, were included. Data on individual and neighbourhood characteristics were derived from questionnaires, and via open data resources. Caries was assessed via intraoral photographs, and defined as decayed, missing and filled teeth (dmft).

Results
Differences between neighbourhoods explained 13.3% of the risk of getting severe caries, and 2% of the chance of visiting the dentist yearly. After adjustments for neighbourhood and individual characteristics, neighbourhood deprivation was significantly associated with severe dental caries (OR: 1.48, 95% CI: 1.02–2.15), and suggestive of a low odds of visiting the dentist yearly (OR: 0.81, 95% CI: 0.56–1.18).

Conclusions
Childhood caries and use of dental services differs between neighbourhoods and living in a deprived neighbourhood is associated with increased dental caries and decreased yearly use of dental services. This highlights the importance of neighbourhoods for understanding differences in children’s oral health, and for targeted policies and interventions to improve the oral health of children living in deprived neighbourhoods.
How are people with mild cognitive impairment or subjective memory complaints managed in primary care? A systematic review
Authors: Hallam Brendan , Rees Jessica , Petersen Irene , Cooper Claudia , Avgerinou Christina , Walters Kate 
Published: February 2021

Abstract

Background
Primary care is typically the first point of contact in the health care system for people raising concerns about their memory. However, there is still a lack of high-quality evidence and understanding about how primary care professionals (PCPs) currently manage people at higher risk of developing dementia.

Objectives
To systematically review management strategies provided by PCPs to reduce cognitive decline in people with mild cognitive impairment and subjective memory complaints.

Method
A systematic search for studies was conducted in December 2019 across five databases (EMBASE, Medline, PsycInfo, CINAHL and Web of Science). Methodological quality of included studies was independently assessed by two authors using the Mixed Methods Appraisal Tool.

Results
An initial 11 719 were found, 7250 were screened and 9 studies were included in the review. Most studies were self-reported behaviour surveys. For non-pharmacological strategies, the most frequent advice PCPs provided was to increase physical activity, cognitive stimulation, diet and social stimulation. For pharmacological strategies, PCPs would most frequently not prescribe any treatment. If PCPs did prescribe, the most frequent prescriptions targeted vascular risk factors to reduce the risk of further cognitive decline.

Conclusion
PCPs reported that they are much more likely to provide non-pharmacological strategies than pharmacological strategies in line with guidelines on preventing the onset of dementia. However, the quality of evidence within the included studies is low and relies on subjective self-reported behaviours. Observational research is needed to provide an accurate reflection of how people with memory problems are managed in primary care.
Bulk modulus for fluid-saturated rocks at high frequency: modification of squirt flow model proposed by Mavko & Jizba
Authors: Zhao Liming , Chen Tongjun , Mukerji Tapan , Tang Genyang 
Published: February 2021

SUMMARYThe squirt flow model, proposed by Mavko & Jizba, has been widely used in explaining the frequency-related modulus and velocity dispersion between ultrasonic and seismic measurements. In this model, the saturated bulk modulus at high frequency is obtained by taking the so-called unrelaxed frame bulk modulus into Biot's or Gassmann's formula. When using Gassmann's formula, the mineral bulk modulus is taken as matrix bulk modulus. However, the soft pores (cracks) in rocks have a weakening effect on the matrix bulk modulus. The saturated bulk modulus at high frequency calculated with mineral bulk modulus as matrix bulk modulus is higher than the real values. To overcome this shortcoming we propose a modified matrix bulk modulus based on the Betti–Rayleigh reciprocity theorem and non-interaction approximation. This modification takes the weakening effect of soft pores (cracks) into consideration and allows calculating the correct saturated bulk modulus at high frequency under different soft-pore fractions (the ratio of soft porosity to total porosity) or crack densities. We also propose an alternative expression of the modified matrix bulk modulus, which can be directly obtained from laboratory measurements. The numerical results show that the saturated bulk modulus at high frequency using the original matrix bulk modulus (i.e. mineral bulk modulus) is approximated to that using the modified one only for rocks containing a small amount of soft-pore fraction. However, as the soft-pore fraction becomes substantial, using the original bulk matrix modulus is not applicable, but the modified one is still applicable. Furthermore, the results of the modified squirt flow model show good consistency with published numerical and experimental data. The proposed modification extends the applicable range of soft-pore fraction (crack density) of the previous model, and has potential applications in media having a relatively substantial fraction of soft pores or almost only soft pores, such as granite, basalt and thermally cracked glasses.