bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wide-Angle, Monocular Head Tracking using Passive Markers
Authors: Vagvolgyi Balazs P. , Jayakumar Ravikrishnan P. , Madhav Manu S. , Knierim James J. , Cowan Noah J. 
Published: September 2021

AbstractCamera images can encode large amounts of visual information of an animal and its environment, enabling high fidelity 3D reconstruction of the animal and its environment using computer vision methods. Most systems, both markerless (e.g. deep learning based) and marker-based, require multiple cameras to track features across multiple points of view to enable such 3D reconstruction. However, such systems can be expensive and are challenging to set up in small animal research apparatuses.We present an open-source, marker-based system for tracking the head of a rodent for behavioral research that requires only a single camera with a potentially wide field of view. The system features a lightweight visual target and computer vision algorithms that together enable high-accuracy tracking of the six-degree-of-freedom position and orientation of the animal’s head. The system, which only requires a single camera positioned above the behavioral arena, robustly reconstructs the pose over a wide range of head angles (360◦ in yaw, and approximately ±120◦ in roll and pitch).Experiments with live animals demonstrate that the system can reliably identify rat head position and orientation. Evaluations using a commercial optical tracker device show that the system achieves accuracy that rivals commercial multi-camera systems.Our solution significantly improves upon existing monocular marker-based tracking methods, both in accuracy and in allowable range of motion.The proposed system enables the study of complex behaviors by providing robust, fine-scale measurements of rodent head motions in a wide range of orientations.
Characterization of Mayer wave oscillations in functional near-infrared spectroscopy using a physiologically informed model of the neural power spectra
Authors: Luke Robert , Shader Maureen J , McAlpine David 
Published: September 2021

OverviewSignificanceMayer waves are spontaneous oscillations in arterial blood pressure that can mask cortical hemodynamic responses associated with neural activity of interest.AimTo characterize the properties of oscillations in the fNIRS signal generated by Mayer waves in a large sample of fNIRS recordings. Further, we aim to determine the impact of short-channel correction for the attenuation of these unwanted signal components.ApproachMayer wave oscillation parameters were extracted from 310 fNIRS measurements using the Fitting Oscillations & One-Over-F (FOOOF) method to compute normative values. The effect of short-channel correction on Mayer wave oscillation power was quantified on 222 measurements. The practical benefit of the short-channel correction approach for reducing Mayer waves and improving response detection was also evaluated on a subgroup of 17 fNIRS measurements collected during a passive auditory speech detection experiment.ResultsMayer-wave oscillations had a mean frequency of 0.108 Hz, bandwidth of 0.04 Hz, and power of 3.5 μM2/Hz. The distribution of oscillation signal power was positively skewed, with some measurements containing large Mayer waves. Short-channel correction significantly reduced the amplitude of these undesired signals; greater attenuation was observed for measurements containing larger Mayer-wave oscillations.ConclusionsA robust method for quantifying Mayer-wave oscillations in the fNIRS signal spectrum was presented and used to provide normative parameterization. Short-channel correction is recommended as an approach for attenuating Mayer waves, particularly in participants with large oscillations.
Identification of Arhgef12 and Prkci as Genetic Modifiers of Retinal Dysplasia in the Crb1rd8 Mouse Model
Authors: Weatherly Sonia M. , Collin Gayle B. , Charette Jeremy R. , Stone Lisa , Damkham Nattaya , Hyde Lillian F. , Peterson James G. , Hicks Wanda , Carter Gregory W. , Naggert Jürgen K. , Krebs Mark P. , Nishina Patsy M. 
Published: September 2021

AbstractMutations in the apicobasal polarity gene CRB1 lead to diverse retinal diseases, such as Leber congenital amaurosis, cone-rod dystrophy, retinitis pigmentosa (with and without Coats-like vasculopathy), foveal retinoschisis, macular dystrophy, and pigmented paravenous chorioretinal atrophy. Limited correlation between disease phenotypes and CRB1 alleles, and evidence that patients sharing the same alleles often present with different disease features, suggest that genetic modifiers contribute to clinical variation. Similarly, the retinal phenotype of mice bearing the Crb1 retinal degeneration 8 (rd8) allele varies with genetic background. Here, we initiated a sensitized chemical mutagenesis screen in B6.Cg-Crb1rd8/Pjn, a strain with a mild clinical presentation, to identify genetic modifiers that cause a more severe disease phenotype. Two models from this screen, Tvrm266 and Tvrm323, exhibited increased retinal dysplasia. Genetic mapping with high-throughput exome and candidate-gene sequencing identified causative mutations in Arhgef12 and Prkci, respectively. Epistasis analysis of both strains indicated that the increased dysplastic phenotype required homozygosity of the Crb1rd8 allele. Retinal dysplastic lesions in Tvrm266 mice were smaller and caused less photoreceptor degeneration than those in Tvrm323 mice, which developed an early, large diffuse lesion phenotype. In both models at one month of age, Müller glia and microglia mislocalization at dysplastic lesions was similar to that in B6.Cg-Crb1rd8/Pjn mice, while photoreceptor cell mislocalization was more extensive. External limiting membrane disruption was comparable in Tvrm266 and B6.Cg- Crb1rd8/Pjn mice but milder in Tvrm323 mice. Immunohistological analysis of mice at postnatal day 0 indicated a normal distribution of mitotic cells in Tvrm266 and Tvrm323 mice, suggesting normal early development. Aberrant electroretinography responses were observed in both models but functional decline was significant only in Tvrm323 mice. These results identify Arhgef12 and Prkci as modifier genes that differentially shape Crb1-associated retinal disease, which may be relevant to understanding clinical variability and underlying disease mechanisms.
A climate-based model for tick life cycle: an infinite system of differential equation approach
Authors: Chenaoui Cyrine , Miled Slimane Ben , Ndongo Mamadou Sadio , Ndiaye Papa Ibrahima , Rekik Mourad , Darghouth Mohamed Aziz 
Published: September 2021

AbstractThe distribution of ticks is essentially determined by the presence of climatic conditions and ecological contexts suitable for their survival and development.We have developed a general tick biology model to study the major trends due to climate change on tick population dynamics under different climate conditions.We build a model that explicitly takes into account stage into each physiological state through a system of infinite differential equations where tick population density are structured on an infinite discrete set. We suppose that intrastage development process is temperature dependent (Arrhenius temperatures function) and that larvae hatching and adult mortality are temperature and precipitations dependent.We analysed mathematically the model and have explicit theR0of the tick population. Therefore, we performed a numerical analysis of the model under three different climate conditions (tropical, Mediterranean and subarctic climates) over the short term using climatic data from 1995 to 2005, as well as long-term simulations from 1902 to 2005.
Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic
Authors: Chow Yuen Ler , Singh Shantanu , Carpenter Anne E. , Way Gregory P. 
Published: September 2021

AbstractA variational autoencoder (VAE) is a machine learning algorithm, useful for generating a compressed and interpretable latent space. These representations have been generated from various biomedical data types and can be used to produce realistic-looking simulated data. However, standard vanilla VAEs suffer from entangled and uninformative latent spaces, which can be mitigated using other types of VAEs such as β-VAE and MMD-VAE. In this project, we evaluated the ability of VAEs to learn cell morphology characteristics derived from cell images. We trained and evaluated these three VAE variants—Vanilla VAE, β-VAE, and MMD-VAE—on cell morphology readouts and explored the generative capacity of each model to predict compound polypharmacology (the interactions of a drug with more than one target) using an approach called latent space arithmetic (LSA). To test the generalizability of the strategy, we also trained these VAEs using gene expression data of the same compound perturbations and found that gene expression provides complementary information. We found that the β-VAE and MMD-VAE disentangle morphology signals and reveal a more interpretable latent space. We reliably simulated morphology and gene expression readouts from certain compounds thereby predicting cell states perturbed with compounds of known polypharmacology. Inferring cell state for specific drug mechanisms could aid researchers in developing and identifying targeted therapeutics and categorizing off-target effects in the future.
Bakta: Rapid & standardized annotation of bacterial genomes via alignment-free sequence identification
Authors: Schwengers Oliver , Jelonek Lukas , Dieckmann Marius , Beyvers Sebastian , Blom Jochen , Goesmann Alexander 
Published: September 2021

AbstractCommand line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command line software pipelines heavily depend on taxon specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command line software tool for the robust, taxon-independent, thorough and nonetheless fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross references. Annotation results are exported in GFF3 and INSDC-compliant flat files as well as comprehensive JSON files facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references whilst providing comparable wall clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio.
Commensal Pseudomonas fluorescens protect Arabidopsis from closely-related Pseudomonas pathogens in a colonization-dependent manner
Authors: Wang Nicole R. , Melnyk Ryan A. , Wiesmann Christina L. , Hossain Sarzana S. , Chi Myoung-Hwan , Martens Kitoosepe , Haney Cara H. 
Published: September 2021

AbstractPlants form commensal associations with soil microorganisms, creating a root microbiome that provides benefits to the host including protection against pathogens. While bacteria can inhibit pathogens through production of antimicrobial compounds in vitro, it is largely unknown how microbiota contribute to pathogen protection in planta. We developed a gnotobiotic model system consisting of Arabidopsis thaliana, and an opportunistic pathogen Pseudomonas sp. N2C3, to identify mechanisms that determine the outcome of plant-pathogen-microbiome interactions in the rhizosphere. We screened 25 phylogenetically diverse Pseudomonas strains for their ability to protect against N2C3 and found that commensal strains closely related to N2C3 were more likely to protect against pathogenesis. We used a comparative genomics approach to identify unique genes in the protective strains that revealed no genes that correlate with protection, suggesting that variable regulation of components of the core Pseudomonas genome may contribute to pathogen protection. We found that commensal colonization level was highly predictive of protection and so tested deletions in genes previously shown to be required for Arabidopsis rhizosphere colonization. We identified a response regulator colR that is required for Pseudomonas protection from N2C3 and fitness in competition with N2C3 indicating that competitive exclusion may contribute to pathogen protection. We found that Pseudomonas WCS365 also protects against the agricultural pathogen Pseudomonas fuscovaginae SE-1, the causal agent of bacterial sheath brown rot of rice. This work establishes a gnotobiotic model to uncover mechanisms by which members of the microbiome can protect hosts from pathogens and informs our understanding of the use of beneficial strains for microbiome engineering in dysbiotic soil systems.
Multiplexed triage of candidate biomarkers in plasma using internal standard triggered-parallel reaction monitoring mass spectrometry
Authors: Kennedy Jacob J. , Whiteaker Jeffrey R. , Ivey Richard G. , Burian Aura , Chowdhury Shrabanti , Tsai Chia-Feng , Liu Tao , Lin ChenWei , Murillo Oscar , Lundeen Rachel , Jones Lisa A. , Gafken Philip R. , Longton Gary , Rodland Karin D. , Skates Steven , Landua John , Wang Pei , Lewis Michael T. , Paulovich Amanda G. 
Published: September 2021

AbstractDespite advances in proteomic technologies, clinical translation of plasma biomarkers remains low, partly due to a major bottleneck between the discovery of candidate biomarkers and downstream costly clinical validation studies. Due to a dearth of multiplexable assays, generally only a few candidate biomarkers are tested, and the validation success rate is accordingly low. Here, we demonstrate the capability of internal standard triggered-parallel reaction monitoring (IS-PRM) to prioritize candidate biomarkers for validation studies. A 5,176-plex assay coupling immunodepletion and fractionation with IS-PRM was developed and implemented in human plasma to quantify peptides representing 1,314 breast cancer biomarker candidates. Compared to prior approaches using data-dependent analysis, IS-PRM showed improved sensitivity (912 vs 295 proteins quantified) and precision (CV 0.1 vs 0.27) enabling rank-ordering of candidate biomarkers for validation studies. The assay greatly expands capabilities for quantification of large numbers of proteins and is well suited for prioritization of viable candidate biomarkers.
miR-34bassociates with epithelial-mesenchymal transition and regulatesBMP7, CAV1, ID2andFN1in human cervical cancer
Authors: Venkatesan Nalini , Xavier Ashley , K.J. Sindhu , Sundhram Sandhya , Sinha Himanshu , Karunagaran Devarajan 
Published: September 2021

AbstractPurposeWe aimed to identify the epithelial-mesenchymal transition and associated putative targets of themiR-34family in transcriptomic data of cervical epithelial squamous cell carcinoma (CESC) to find new therapeutic targets for better disease management.MethodsA combined computational analysis of themiR-34family; gene expression in heterogeneous primary CESCs derived from TCGA; and the integration ofmiR-34band EMT-regulated genes was performed. Four EMT-associatedmiR-34bgene targets were analysed in primary human CESC and non-cancerous cervical tissues by qRT-PCR. Effects of endogenousmiR-34bexpression and its associated gene modulations in cervical cancer cells (C33A and HeLa) were analysed using qRT-PCR, western blotting and immunofluorescence, transwell migration and invasion assays.ResultsThe results showed that themiR-34family might regulate the mTOR pathway, cell cycle (CCND2) and cell adhesion functions (FZD4). Further, we showed that a low negative correlation (r2= −0.07) betweenmiR-34b/EMĨscore and four EMT signature genes (E>MP7, CAV1, ID2, FN1) were significantly regulated bymiR-34b. Also,FN1was indicated as its putative target with the highest negative EMT score and high binding energy between MRE/3’UTR. Further, these transcriptomic signatures in CESC revealed a significant inverse correlation across the stages of primary human CESC. These genes were repressed at transcriptional and translational levels inmiR-34b-3pexpressing C33A and HeLa cells, contributing to their reduced cell migration and invasive properties.ConclusionsOur studies revealed the potential targets of themiR-34family, especiallymiR-34b, that can emerge as potential biomarkers and promising therapeutic targets in CESC disease management.
Cluster mean-field theory accurately predicts statistical properties of large-scale DNA methylation patterns
Authors: Kerr Lyndsay , Sproul Duncan , Grima Ramon 
Published: September 2021

AbstractThe accurate establishment and maintenance of DNA methylation patterns is vital for mammalian development and disruption to these processes causes human disease. Our understanding of DNA methylation mechanisms has been facilitated by mathematical modelling, particularly stochastic simulations. Mega-base scale variation in DNA methylation patterns is observed in development, cancer and ageing and the mechanisms generating these patterns are little understood. However, the computational cost of stochastic simulations prevents them from modelling such large genomic regions. Here we test the utility of three different mean-field models to predict large-scale DNA methylation patterns. By comparison to stochastic simulations, we show that a cluster mean-field model accurately predicts the statistical properties of steady-state DNA methylation patterns, including the mean and variance of methylation levels calculated across a system of CpG sites, as well as the covariance and correlation of methylation levels between neighbouring sites. We also demonstrate that a cluster mean-field model can be used within an approximate Bayesian computation framework to accurately infer model parameters from data. As mean-field models can be solved numerically in a few seconds, our work demonstrates their utility for understanding the processes underpinning large-scale DNA methylation patterns.
A systematic literature review of community disaster resilience: main and related research areas and agendas
Authors: Upadhyay Arvind , Sa-ngiamwibool Amporn 
Published: September 2021

PurposeThis study aims to characterize the main research areas of published works, identify the disciplines that associated with the works and propose research agendas for future inquiries, based on a systematic literature review that encompasses 89 research papers from 2010 to 2020.Design/methodology/approachThis review commenced with the definition of the three research questions, and subsequently three steps were followed: (1) defining criteria for research paper selection; (2) specifying the data bases and selecting the papers based on the criteria and (3) data analysis, conclusion and discussion of selected papers. The search was limited to the selection of research papers in English, focusing on “community disaster resilience” which is the subject of this review and referred to as keywords which were used for the online search for papers. All these three words must be present in the title of the selected papers.FindingsThe area “resilience management” and “disaster resilience assessment” accounted for 43% of the studies, and it indicates that research has emphasized the description of how community disaster resilience has been managed and assessed. Three disciplines relating to disaster resilience are disaster risk science, public health and environment, and it indicates that research has fostered core areas of community disaster resilience. Three key research agenda include a growing trend to describe successful efforts to avert a potentially catastrophic disaster through solution-based case studies; a paradigmatic shift and implementation of how communities could help the disaster victims recuperate from disasters.Research limitations/implicationsThis review is limited to the numbers of chosen papers, as only full papers were chosen. However, in order to establish more rigorous and inclusive results of the study, the numbers of citations of published papers to be chosen for future inquiry should be taken into account.Originality/valueThis present review originally investigated how the concept of disaster resilience has been applied at the community level and in related areas. As resilience is a multidisciplinary concept that has been investigated by several different disciplines, such as sustainability, psychology, economy and sociology, this study looked into how disciplines related to community disaster resilience to provide agenda for future inquiries. This study therefore characterized the main research areas of published works, identified the disciplines that associated with the works and proposed a research agenda for future inquiries.
Less than human: dehumanisation of people who use heroin
Authors: Sumnall Harry , Atkinson Amanda , Gage Suzanne , Hamilton Ian , Montgomery Catharine 
Published: September 2021

PurposeStigma reduction is an important public health challenge because of the large morbidity and mortality associated with some forms of substance use. Extreme stigma can lead to dehumanisation of target groups, who are ascribed with lesser humanity. The authors examined whether there was blatant and subtle dehumanisation of people who use heroin, and if these were associated with levels of support for non-discriminatory drug policy.Design/methodology/approachA cross-sectional online study using a UK convenience sample (n = 307 [75.2% female, mean age 28.6 ± 12.2 years]) was conducted. Participants completed assessments of blatant (Ascent of Humans [AoH] scale) and subtle (an emotion attribution task) dehumanisation and a bespoke measure assessing support for non-discriminatory drug policies. Other measures controlled for stigma towards people who use drugs (PWUD) and moral disgust.FindingsThere was greater blatant dehumanisation of people who used heroin compared to the general population and other potentially stigmatised reference groups, including people who use cannabis. The authors also found evidence of subtle dehumanisation, and people who used heroin were rated as being less likely to feel uniquely human emotions, less likely to feel positive emotions and more likely to feel negative emotions. Blatant dehumanisation was associated with significantly lower probability of support for non-discriminatory drug policy.Social implicationsDehumanisation may present significant challenges for stigma reduction initiatives and in fostering public support for drug policy and treatment. Denial of the humanity of this group could be used to justify discriminatory policies or relative deprioritisation of support services in funding decisions. Activities that seek to “rehumanise” PWUD, including social inclusion, and encouraging compassionate media representations that portray the lived experiences of substance use may be useful areas of future work.Originality/valueThis is the first study to investigate blatant and subtle dehumanisation of people who use heroin, and how this relates to public support for drug policy.