bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wheat cells show positional responses to invasive Zymoseptoria tritici
Authors: Valente Francesco , Mansfield Jessica , Herring Daniel , Romana Giuseppe , Rodrigues Cecilia , Metz Jeremy , Craze Melanie , Bowden Sarah , Greenland Andy , Moger Julian , Haynes Ken , Richards David M. , Wallington Emma , Deeks Michael J. 
Published: July 2022

SummaryThe stomatal complex of grasses consists of two guard cells and two adjacent subsidiary cells that cooperate during stomatal closure. Zymoseptoria tritici, the main causal agent of Septoria tritici blotch in wheat, enters the host via stomata. Here we test the hypothesis that the stomatal complex shows focused sub-cellular responses to invading Z. tritici hyphae.We have combined live-cell transmission light microscopy, immunofluorescence and CRS microscopy to identify cell wall modifications triggered by hyphal invasion. Furthermore, we have used confocal fluorescence microscopy and automated quantitative image analysis to assess whether host cells respond to hyphae through spatial redistribution of organelles.We find that subsidiary cells construct papillae that are accurately aligned with hyphal position even when hyphae are occluded by guard cells. These are distinct from those induced by powdery mildew, with callose restricted to a crust that surrounds content with a high-amplitude Raman signal in the CH-band. Peroxisome populations in subsidiary cells show distributions with modes weakly correlated with hyphal position but do not differ significantly between compatible and incompatible interactions.Our data suggest local changes to cell wall architecture and focal accumulation of organelles in subsidiary cells could play roles in crop defence during host leaf penetration by Z. tritici. Molecular strategies to amplify these responses may provide novel routes for crop protection.
Cryptochrome Stabilization Ameliorates Chronic Pain
Authors: Wei L. , Wu Y. , Zirpel F. , Flower G. , Vierbergen J. V , Wieser V. , Peirson S. , Sleven H. , Pokhilko A. , Cader M. Z. 
Published: July 2022

AbstractPhysiological and pathological pain exhibits striking diurnal variation, but the underlying mechanisms are largely unknown. We now describe an independent molecular clock in peripheral sensory neurons and satellite glial cells of sensory ganglia. We show that it is the sensory neuron transcription-translation feedback loops (TTFLs) that are responsible for diurnal pain behaviors. This clock regulates diurnal neurophysiological responses to a range of ligands, as well as synaptic activities of primary nociceptors. Furthermore, we find that loss of Cry1 and Cry2, the repressive arm of the core TTFLs, intensifies pain responses associated with increased voltage-gated sodium channel currents. Conversely, stabilization of CRY1 and CRY2 using the small molecule KL001, reduces pain sensitivity. Our results highlight novel opportunities to address chronic pain by directly harnessing circadian mechanisms.One-Sentence SummaryA peripheral pain clock governs daily pain fluctuations, which can be harnessed for treating pain disorders.
In vitroandin silicoanalysis proving DPP4 inhibition and diabetes associated gene network modulation by a polyherbal formulation –Nisakathakadi Kashaya
Authors: Thottappillil Anjana , Sahoo Sthitaprajna , Chakraborty Abhijnan , Kouser Sania , Ravi R. Vidhya , Garawadmath Soumya , Banvi Pranav Girish , Kukkupuni Subrahmanya Kumar , Mohan S Suma , Vishnuprasad Chethala N 
Published: July 2022

AbstractFrontiers of disease biology started recognizing the importance of systems and network medicine approach for managing chronic disease like diabetes. Dipeptidyl-peptidase IV (DPP4) inhibitors are one such class of anti-diabetic drugs recognized for their systemic biological actions. Polyherbal preparations likeAyurvedaformulations are ideal for identifying novel DPP4 inhibitors having greater efficacy and safety profile. Additionally, expanding the research on the multitargeted mode of action of these polyherbal formulations can render novel insights into the complex biology of disease manifestations. The current study aims at identifying DPP4 inhibitory potential of a clinically established Ayurveda anti-diabetic formulationNisakathakadi Kashaya(NK) usingin vitroandin silicomethods as well as the modulation of diabetes associated gene network by NK. a. Standard enzyme inhibition assay was used to study the DPP4 inhibitory potential of NK, followed by bioinformatics and computational biology tools for identifying the potential bioactives and their molecular interactions involved in DPP4 inhibition. STITCH, CHEMBL and BindingDB databases were used for target mapping and depicting the multi-targeted network pharmacology interaction of NK and the formulation. EnrichR was used to depict a sub-network of diabetes proteins and their relationship with diabetes associated comorbidities. NK demonstrated a dose dependent DPP4 inhibition with an IC50of 2.06 μg GAE/mL. Molecular docking identified three compounds namely Terchebin, Locaracemoside B and 1,2,4,6 Tetra o Galloyl Beta D Glucose showing stable interactions with DPP4 similar to the standard drug Vildagliptin. The network pharmacology analysis of NK identified a number of targets like TNFα, TGFβ1, SOD1, SOD2, AKT1, DPP4 and GLP1R in its protein-protein interaction network which are vital to diabetic progression and complications. The present work demonstrated that the polyherbal formulation NK has DPP4 inhibition potential and modulates a large number of diabetes related proteins and pathways. The approach adopted in the current study by combiningin vitroandin silicomethods allowed us to understand the mechanism of DPP4 inhibition by the formulation and also the possible pharmacological networking through which the formulation exert its systemic effect in diabetes management.
Effects of environmental manipulations on cocaine-vs-social choice in male and female rats
Authors: Marcus Madison M. , Negus S. Stevens , Banks Matthew L. 
Published: July 2022

AbstractCocaine use disorder occurs in an environment where cocaine and other nondrug commodities are concurrently available. Preclinical drug-vs-nondrug choice procedures are one simplified method of modeling this complex clinical environment. The present study established a discrete-trial progressive-ratio (PR) cocaine-vs-social interaction choice procedure in male and female rats and determined sensitivity of choice behavior to manipulations of reinforcer magnitude and non-contingent “sample” reinforcer presentation. Rats could make up to nine discrete choices between an intravenous cocaine infusion (0.1 – 1.0 mg/kg/inf) and social interaction with a same-sex social “Partner” rat. Cocaine infusions were available under a PR schedule of reinforcement, and social interaction was available under a fixed-ratio (FR) 3 schedule. Social interaction was chosen over no or small cocaine doses (saline, 0.01 mg/kg/inf) and behavior was reallocated away from social and towards cocaine at larger cocaine doses (1.0 mg/kg/inf). Manipulating social interaction time as one method to alter social reinforcer magnitude did not significantly alter cocaine-vs-social choice. Removing the non-contingent reinforcer presentations before the discrete choice trials also failed to affect cocaine-vs-social choice, suggesting the time interval was sufficient to minimize any potential influence of the non-contingent cocaine infusions on subsequent choice behavior. Overall, the present results were consistent with previous drug-vs-social choice studies and extend our knowledge of environmental factors impacting drug-vs-social choice. Future studies determining the pharmacological sensitivity of cocaine-vs-social choice will be important in expanding the preclinical utility of these procedures for candidate medication drug development.
A community driven GWAS summary statistics standard
Authors: Hayhurst James , Buniello Annalisa , Harris Laura , Mosaku Abayomi , Chang Christopher , Gignoux Christopher R. , Hatzikotoulas Konstantinos , Karim Mohd Anisul , Lambert Samuel A. , Lyon Matt , McMahon Aoife , Okada Yukinori , Pirastu Nicola , Rayner N. William , Schwartzentruber Jeremy , Vaughan Robert , Verma Shefali , Wilder Steven P. , Cunningham Fiona , Hindorff Lucia , Wiley Ken , Parkinson Helen , Barroso Inês 
Published: July 2022

AbstractSummary statistics from genome-wide association studies (GWAS) represent a huge potential for research. A challenge for researchers in this field is the access and sharing of summary statistics data due to a lack of standards for the data content and file format. For this reason, the GWAS Catalog hosted a series of meetings in 2021 with summary statistics stakeholders to guide the development of a standard format. The key requirements from the stakeholders were for a standard that contained key data elements to be able to support a wide range of data analyses, required low bioinformatics skills for file access and generation, to have easily accessible metadata, and unambiguous and interoperable data. Here, we define the specifications for the first version of the GWAS-SSF format, which was developed to meet the requirements discussed with the community. GWAS-SSF consists of a tab-separated data file with well-defined fields and an accompanying metadata file.
Rarity: Discovering rare cell populations from single-cell imaging data
Authors: Märtens Kaspar , Bortolomeazzi Michele , Montorsi Lucia , Spencer Jo , Ciccarelli Francesca , Yau Christopher 
Published: July 2022

AbstractBackgroundCell type identification plays an important role in the analysis and interpretation of single-cell data and can be carried out via supervised or unsupervised clustering approaches. Supervised methods are best suited where we can list all cell types and their respective marker genes a priori. While unsupervised clustering algorithms look for groups of cells with similar expression properties. This property permits the identification of both known and unknown cell populations, making unsupervised methods suitable for discovery.. Success is dependent on the relative strength of the expression signature of each group as well as the number of cells. Rare cell types therefore present a particular challenge that are magnified when they are defined by differentially expressing a small number of genes. Typical unsupervised approaches fail to identify such rare subpopulations, and these cells tend to be absorbed into more prevalent cell types.ResultsIn order to balance these competing demands, we have developed a novel statistical framework for unsupervised clustering, named Rarity, that enables the discovery process for rare cell types to be more robust, consistent and interpretable. We achieve this by devising a novel clustering method based on a Bayesian latent variable model in which we assign cells to inferred latent binary on/off expression profiles. This lets us achieve increased sensitivity to rare cell populations while also allowing us to control and interpret potential false positive discoveries.ConclusionsWe systematically study the challenges associated with rare cell type identification and demonstrate the utility of Rarity on various IMC data sets.
Role of Serum Soluble Interleukin-2 Receptor Level in the Diagnosis of Sarcoidosis: A Systematic Review and Meta-Analysis
Authors: Gupta Samiksha , Parmar Miloni , Padappayil Rana Prathap , Bansal Agam , Daouk Salim 
Published: July 2022

AbstractIntroductionSerum Soluble Interleukin-2 Receptor (sIL-2R) levels are used clinically as a disease activity marker for systemic sarcoidosis. Studies have investigated the diagnostic role of serum soluble interleukin-2 receptor (sIL-2R) level for sarcoidosis relative to biopsy. We performed a systematic review and meta-analysis of studies evaluating the diagnostic utility of sIL-2R.MethodsWe carried out an electronic search in Medline, Embase, Google Scholar, and Cochrane databases using keyword and Medical Subject Heading (MeSH) terms: sarcoidosis and sIL-2R. Studies evaluating the sIL-2R levels as a diagnostic tool in clinically diagnosed or biopsy-proven sarcoidosis patients compared to control groups with non-sarcoidosis patients were included. Forest plots were constructed using a random effect model depicting pooled sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy.ResultsWe selected ten studies comprising 1477 patients, with 592 in the sarcoidosis group and 885 in the non-sarcoidosis group. Pooled sensitivity and specificity of sIL-2R levels were 0.88 (95% CI: 0.75-0.95) and 0.87 (95% CI 0.73-0.94) respectively. Pooled negative predictive value and positive predictive value were 0.91 (95% CI 0.77-0.97) and 0.85 (95% CI 0.59-0.96) respectively with diagnostic accuracy of 0.86 (95% CI 0.71-0.93).ConclusionIn addition to its utility as a marker of sarcoidosis disease activity, sIL-2R has high diagnostic accuracy. Despite the limitations of the heterogenous sarcoidosis population and different sIL-2R cutoffs, our results suggest that sIL-2R is an important biomarker that can be used to confirm sarcoidosis diagnosis in unconfirmed or unclear cases.
A taxonomic synopsis of unifoliolate continental AfricanVepris(Rutaceae) with three new threatened forest tree species from Kenya and Tanzania
Authors: Cheek Martin , Luke W.R. Quentin 
Published: July 2022

SummaryDescriptions and illustrations are presented for three new species to science,Vepris udzungwaCheek, V. lukeiCheek (both Udzungwa Mts, Tanzania) andV. robertsoniaeCheek & Q. Luke (SE Kenyan kaya forests) in the context of a synoptic taxonomic revision, with an identification key to all the known unifoliolate taxa ofVeprisin continental Africa. The remaining species are given skeletal taxonomic treatments (lacking descriptions). One widespread species in montane eastern Africa is renamed asVepris simplexCheek because its previous name,Vepris simplicifolia(Engl.)Mziray is predated byVepris simplicifoliaEndl. (basionym ofSarcomelicope simplicifolia(Endl.)T.G. Hartley, a widespread species of Australia, Lord Howe and Norfolk Islands, and of New Caledonia).Conservation assessments are presented for all species, or provisional conservation assessments are presented. Of the 13 taxa, 11 are considered threatened, of which six are VU, two EN and three CR, of which two are possibly extinct globally in the Uluguru Mts of Tanzania although not yet Red Listed on iucnredlist.org.
Discovering Patterns in Bipartite Networks
Authors: Costa Luciano da Fontoura 
Published: July 2022

AbstractBipartite networks constitute an especially important type of network that can be widely applied to model and study several intricate systems in many scientific areas, being also theoretically related to several network models and concepts. However, given a bipartite network the identification of specific recurrent patterns of interest often represents a substantial challenge. In the present work, we apply the coincidence methodology for translating data into networks as a means for automatically identifying repeating interconnection patterns in given bipartite networks. The important issue of normalization of the links strength is also addressed. Though the method is illustrated with respect to foodweb networks, its application is general and encompasses many other subjects and areas.
A geometric deep learning framework for drug repositioning over heterogeneous information networks
Authors: Zhao Bo-Wei , Su Xiaorui , Hu Peng-Wei , Ma Yu-Peng , Zhou Xi , Hu Lun 
Published: July 2022

AbstractThe effectiveness of computational drug repositioning techniques has been further improved due to the development of artificial intelligence technology. However, most of the existing approaches fall short of taking into account the non-Euclidean nature of biomedical data. To overcome this problem, we propose a geometric deep learning (GDL) framework, namely DDAGDL, to predict drug-disease associations (DDAs) on heterogeneous information networks (HINs). DDAGDL can take advantage of complicated biological information to learn the feature representations of drugs and diseases by ingeniously projecting drugs and diseases including geometric prior knowledge of network structure in a non-Euclidean domain onto a latent feature space. Experimental results show that DDAGDL is able to identify high-quality candidates for Alzheimer’s disease (AD) and Breast neoplasms (BN) that have already been reported by previously published studies, and some of them are not even identified by comparing models.
Snake Herders: Novel anti-predator behavior by black-tailed prairie dogs in response to prairie rattlesnakes
Authors: Verdolin J.L. , Bledsoe Ellen K. 
Published: July 2022

AbstractWe describe a case of a unique antipredator behavior sequence in response to rattlesnakes observed in a population of black-tailed prairie dogs in Fort Collins, Colorado. An analysis of 5 independent opportunistic video recordings of 6 identifiable individuals revealed individuals across multiple social groups within the population engaged in novel behavioral responses to prairie rattlesnakes. Using Markov-chain analysis we found that prairie dogs engaged in non-random behavioral transitions and that specific pairs of behaviors were contributing to this pattern. We also observed that prairie dogs in this population engaged in novel responses to prairie rattlesnakes, including ‘escorting’ behavior, where a prairie dog would walk alongside the snake.
Dietary vitamin D intake and sun exposure are not associated with type 1 diabetic schoolchildren and adolescents: a first report in Algerian Sahara
Authors: Brikhou Slimane , Nouari Wafa , Bouazza Sofiane , Mezouar Chahrazed El , Benzian Zakaria , Talha Kheira , Aribi Mourad 
Published: July 2022

AbstractBackgroundA great number of children and adolescents worldwide suffer from physiological Vitamin D (VD) deficiency, which has been associated to the sun exposure and, consequently, to the risk of the development of various autoimmune diseases, including type 1 diabetes (T1D). However, the association of the disease with VD intake and sun exposure have yet to be explored.Materials and methodsWe conducted a food frequency questionnaire and 24-hour recall food survey, using “Ciqual table 2016” in 335 type 1 diabetic and age- and gender-matched healthy Algerian school children and teenager pupils from sunny Saharan and relatively less sunny Northern regions, aged between 5 and 19 years old.ResultsBoth dietary VD intake and VD levels were similar in T1D patients when comparing between North and South regions (for the two comparisons, p > 0.05). Neither sun exposure, nor VD intake was associated with the disease (respectively, relative risk [RR] = 1.050, p = 0.680; RR = 1.082, p = 1.000. For Cochran and Mantel-Haenszel analysis; RR = 0.841, p = 0.862). VD intake showed a significant difference between diabetics and non-diabetics in sunny region (p = 0.022). Additionally, significant differences were highlighted between normal and T1D schoolboys (p = 0.038), and when comparing the two groups according to the dry areas (p = 0.016). Moreover, in contrast with the levels of circulating VD, which is decreased in T1D patients than in healthy controls, those of VD intake was significantly higher (p < 0.05), especially in male patients and in those with balanced diet, poor protein or carbohydrate consumption, a particular food intolerance, and a regular meal (p < 0.05), as well as in patients with a moderate or low consumption of cooked meals or steamed food (p < 0.01). Conversely, VD intake was markedly lower in type 1 diabetics than in controls regarding dry sunny region, including Adrar area, as well as in low fatty foods and eggs consumption (p < 0.05 for all comparisons). Nevertheless, relative risk of sun exposure and dietary vitamin D intake according to the WHO standard showed no significant association with T1D (common Mantel-Haenszel estimation, RR = 0.841, 95% CI 0.118-5.973, p > 0.05).ConclusionsT1D seems to be not associated with VD intake and sun exposure in the Algerian Sahara region. Therefore, the consumption of VD in T1D patients from the Algerian Sahara would suspect that its association with the disease would be related to its synthesis alteration.
Mental disorders and adherence to antiretroviral treatment in health facilities in Mozambique
Authors: Mandlate Flavio M. , Greene M. Claire , Pereira Luis F. , Gouveia Maria Lidia , Mari Jair Jesus , Cournos Francine , Duarte Cristiane S. , Oquendo Maria A. , Feijó Mello Marcelo , Wainberg Milton L. 
Published: July 2022

AbstractIntroductionLess adherence to antiretroviral treatment (ART) has been found among people suffering from HIV (PWH) with comorbid mental disorders like depression and alcohol use in Mozambique, a Sub-Saharan African country. However, less is explored with regards to other mental disorders.MethodsThis study assessed the association of multiple mental disorders and adherence to ART based on the data from primary/tertiary health care facilities in Maputo and Nampula, Mozambique. We administered a sociodemographic questionnaire, Mini International Neuropsychiatric Interview (MINI) Plus 4.0.0 adapted for use in Mozambique to assess mental conditions, and a 3-item self-report to measure ART adherence.ResultsOut of 1469 participants, 409 were HIV positive (self-report), with an average age of 36.7 years (SD=9.8), and 30.4% were male. The most common mental disorders were major depressive disorder (27.34%) followed by psychosis (22.03%), suicidal ideation/behavior (15.44%), and alcohol-use disorder (8.35%). Higher levels of non-adherence to ART [(Mean Difference=1.19, 95% CI: 1.04, 1.37)] and the likelihood of missing at least one dose in the last 30 days (OR=3.06, 95% CI: 2.00, 4.67) were found in participants with any mental disorder compared to those without a mental disorder. The highest levels of non-adherence were observed among those with drug use disorders and panic disorder.ConclusionsIn Mozambique, PWH with any co-occurring mental conditions had a lower probability of ART adherence. Integrating comprehensive mental health assessment and treatment and ART adherence interventions tailored to PWH with co-occurring mental disorders is necessary to attain optimal ART adherence and reach the UNAIDS ART target.
A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq
Authors: Ye Wenbin , Lian Qiwei , Ye Congting , Wu Xiaohui 
Published: July 2022

AbstractAlternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA-seq data, and single-cell RNA-seq (scRNA-seq) data. Particularly, we examined several representative tools using RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques and provided our perspective on how computational methodologies might evolve in the future for non-3’ UTR, tissue-specific, cross-species, and single-cell pA prediction.