bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognition as a mediator for gait and balance impairments in GBA-related Parkinson’s disease
Authors: Morris Rosie , Martini Douglas N. , Ramsey Katrina , Kelly Valerie E. , Smulders Katrijn , Hiller Amie , Chung Kathryn A. , Hu Shu-Ching , Zabetian Cyrus P. , Poston Kathleen L. , Mata Ignacio F. , Edwards Karen L. , Lapidus Jodi , Cholerton Brenna , Montine Thomas J. , Quinn Joseph F. , Horak Fay 
Published: June 2022

AbstractThe extent to which the heterogeneity of gait and balance problems in PD may be explained by genetic variation is unknown. Variants in the glucocerebrosidase (GBA) gene are the strongest known genetic risk factor for PD and are associated with greater motor and cognitive severity. However, the impact of GBA variants on comprehensive measures of gait and balance and their relationship to cognition remains unknown. We aimed to determine differences in gait and balance impairments in those with and without GBA variants (mutation carriers and E326K polymorphism) and explore direct and indirect effects of GBA status on gait, balance, and cognition. 332 participants, 43 of whom had GBA variants, were recruited. Participants completed a comprehensive, objective assessment of gait and standing balance using body-worn inertial sensors. Group differences in gait and balance between PD with and without GBA variants were assessed with linear regression, adjusting for age, gender, clinical testing site, disease duration, and apolipoprotein E (APOE) ɛ4 status. Structural equation modeling (SEM) explored direct relationships between GBA status and gait and balance and indirect relationships between GBA status and gait and balance via cognition. The GBA variant group had more impaired gait (pace and variability) and balance (sway area/jerk and sway velocity), than the non-GBA variant group. SEM demonstrated cognition as a mediator of GBA status on gait and balance. The close relationships among GBA, gait/balance, and cognition suggest potential for novel therapeutics to target the GBA pathway and/or cognition to improve mobility in PD GBA variants.
Photocaged 5′ cap analogues for optical control of mRNA translation in cells
Authors: Klöcker Nils , Weissenboeck Florian P. , van Dülmen Melissa , Špaček Petr , Hüwel Sabine , Rentmeister Andrea 
Published: June 2022

AbstractThe translation of messenger RNA (mRNA) is a fundamental process in gene expression, and control of translation is important to regulate protein synthesis in cells. The primary hallmark of eukaryotic mRNAs is their 5′ cap, whose molecular contacts to the eukaryotic translation initiation factor eIF4E govern the initiation of translation. Here we report 5′ cap analogues with photo-cleavable groups (FlashCaps) that prohibit binding to eIF4E and resist cleavage by decapping enzymes. These compounds are compatible with the general and efficient production of mRNAs by in vitro transcription. In FlashCap-mRNAs, the single photocaging group abrogates translation in vitro and in mammalian cells without increasing immunogenicity. Irradiation restores the native cap, triggering efficient translation. FlashCaps overcome the problem of remaining sequence or structure changes in mRNA after irradiation that limited previous designs. Together, these results demonstrate that FlashCaps offer a route to regulate the expression of any given mRNA and to dose mRNA therapeutics with spatio-temporal control.
Genome-wide mapping of somatic mutation rates uncovers drivers of cancer
Authors: Sherman Maxwell A. , Yaari Adam U. , Priebe Oliver , Dietlein Felix , Loh Po-Ru , Berger Bonnie 
Published: June 2022

AbstractIdentification of cancer driver mutations that confer a proliferative advantage is central to understanding cancer; however, searches have often been limited to protein-coding sequences and specific non-coding elements (for example, promoters) because of the challenge of modeling the highly variable somatic mutation rates observed across tumor genomes. Here we present Dig, a method to search for driver elements and mutations anywhere in the genome. We use deep neural networks to map cancer-specific mutation rates genome-wide at kilobase-scale resolution. These estimates are then refined to search for evidence of driver mutations under positive selection throughout the genome by comparing observed to expected mutation counts. We mapped mutation rates for 37 cancer types and applied these maps to identify putative drivers within intronic cryptic splice regions, 5′ untranslated regions and infrequently mutated genes. Our high-resolution mutation rate maps, available for web-based exploration, are a resource to enable driver discovery genome-wide.
Rapid biosensor development using plant hormone receptors as reprogrammable scaffolds
Authors: Beltrán Jesús , Steiner Paul J. , Bedewitz Matthew , Wei Shuang , Peterson Francis C. , Li Zongbo , Hughes Brigid E. , Hartley Zachary , Robertson Nicholas R. , Medina-Cucurella Angélica V. , Baumer Zachary T. , Leonard Alison C. , Park Sang-Youl , Volkman Brian F. , Nusinow Dmitri A. , Zhong Wenwan , Wheeldon Ian , Cutler Sean R. , Whitehead Timothy A. 
Published: June 2022

AbstractA general method to generate biosensors for user-defined molecules could provide detection tools for a wide range of biological applications. Here, we describe an approach for the rapid engineering of biosensors using PYR1 (Pyrabactin Resistance 1), a plant abscisic acid (ABA) receptor with a malleable ligand-binding pocket and a requirement for ligand-induced heterodimerization, which facilitates the construction of sense–response functions. We applied this platform to evolve 21 sensors with nanomolar to micromolar sensitivities for a range of small molecules, including structurally diverse natural and synthetic cannabinoids and several organophosphates. X-ray crystallography analysis revealed the mechanistic basis for new ligand recognition by an evolved cannabinoid receptor. We demonstrate that PYR1-derived receptors are readily ported to various ligand-responsive outputs, including enzyme-linked immunosorbent assay (ELISA)-like assays, luminescence by protein-fragment complementation and transcriptional circuits, all with picomolar to nanomolar sensitivity. PYR1 provides a scaffold for rapidly evolving new biosensors for diverse sense–response applications.
Drivers of adaptive evolution during chronic SARS-CoV-2 infections
Authors: Harari Sheri , Tahor Maayan , Rutsinsky Natalie , Meijer Suzy , Miller Danielle , Henig Oryan , Halutz Ora , Levytskyi Katia , Ben-Ami Ronen , Adler Amos , Paran Yael , Stern Adi 
Published: June 2022

AbstractIn some immunocompromised patients with chronic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, considerable adaptive evolution occurs. Some substitutions found in chronic infections are lineage-defining mutations in variants of concern (VOCs), which has led to the hypothesis that VOCs emerged from chronic infections. In this study, we searched for drivers of VOC-like emergence by consolidating sequencing results from a set of 27 chronic infections. Most substitutions in this set reflected lineage-defining VOC mutations; however, a subset of mutations associated with successful global transmission was absent from chronic infections. We further tested the ability to associate antibody evasion mutations with patient-specific and virus-specific features and found that viral rebound is strongly correlated with the emergence of antibody evasion. We found evidence for dynamic polymorphic viral populations in most patients, suggesting that a compromised immune system selects for antibody evasion in particular niches in a patient’s body. We suggest that a tradeoff exists between antibody evasion and transmissibility and that extensive monitoring of chronic infections is necessary to further understanding of VOC emergence.
Compilation of parasitic immunogenic proteins from 30 years of published research using machine learning and natural language processing
Authors: Goodswen Stephen J. , Kennedy Paul J. , Ellis John T. 
Published: June 2022

AbstractThe World Health Organisation reported in 2020 that six of the top 10 sources of death in low-income countries are parasites. Parasites are microorganisms in a relationship with a larger organism, the host. They acquire all benefits at the host’s expense. A disease develops if the parasitic infection disrupts normal functioning of the host. This disruption can range from mild to severe, including death. Humans and livestock continue to be challenged by established and emerging infectious disease threats. Vaccination is the most efficient tool for preventing current and future threats. Immunogenic proteins sourced from the disease-causing parasite are worthwhile vaccine components (subunits) due to reliable safety and manufacturing capacity. Publications with ‘subunit vaccine’ in their title have accumulated to thousands over the last three decades. However, there are possibly thousands more reporting immunogenicity results without mentioning ‘subunit’ and/or ‘vaccine’. The exact number is unclear given the non-standardised keywords in publications. The study aim is to identify parasite proteins that induce a protective response in an animal model as reported in the scientific literature within the last 30 years using machine learning and natural language processing. Source code to fulfil this aim and the vaccine candidate list obtained is made available.
Dimensionality reduction of independent influence factors in the objective evaluation of quality of experience
Authors: Skaka-Čekić Fatima , Baraković Husić Jasmina , Odžak Almasa , Hadžialić Mesud , Huremović Adnan , Šehić Kenan 
Published: June 2022

AbstractBig Data analytics and Artificial Intelligence (AI) technologies have become the focus of recent research due to the large amount of data. Dimensionality reduction techniques are recognized as an important step in these analyses. The multidimensional nature of Quality of Experience (QoE) is based on a set of Influence Factors (IFs) whose dimensionality is preferable to be higher due to better QoE prediction. As a consequence, dimensionality issues occur in QoE prediction models. This paper gives an overview of the used dimensionality reduction technique in QoE modeling and proposes modification and use of Active Subspaces Method (ASM) for dimensionality reduction. Proposed modified ASM (mASM) uses variance/standard deviation as a measure of function variability. A straightforward benefit of proposed modification is the possibility of its application in cases when discrete or categorical IFs are included. Application of modified ASM is not restricted to QoE modeling only. Obtained results show that QoE function is mostly flat for small variations of input IFs which is an additional motive to propose a modification of the standard version of ASM. This study proposes several metrics that can be used to compare different dimensionality reduction approaches. We prove that the percentage of function variability described by an appropriate linear combination(s) of input IFs is always greater or equal to the percentage that corresponds to the selection of input IF(s) when the reduction degree is the same. Thus, the proposed method and metrics are useful when optimizing the number of IFs for QoE prediction and a better understanding of IFs space in terms of QoE.
Personality, self-esteem, familiarity, and mental health stigmatization: a cross-sectional vignette-based study
Authors: Steiger Sahar , Sowislo Julia F. , Moeller Julian , Lieb Roselind , Lang Undine E. , Huber Christian G. 
Published: June 2022

AbstractThere has been little research exploring the relationship between personality traits, self-esteem, and stigmatizing attitudes toward those with mental disorders. Furthermore, the mechanisms through which the beholder’s personality influence mental illness stigma have not been tested. The aim of this study is to examine the relationship between Big Five personality traits, self-esteem, familiarity, being a healthcare professional, and stigmatization. Moreover, this study aims to explore the mediating effect of perceived dangerousness on the relationship between personality traits and desire for social distance. We conducted a vignette-based representative population survey (N = 2207) in the canton of Basel-Stadt, Switzerland. Multiple regression analyses were employed to examine the associations between personality traits, self-esteem, familiarity, and being a healthcare professional with the desire for social distance and perceived dangerousness. The mediation analyses were performed using the PROCESS macro by Hayes. Analyses showed associations between personality traits and stigmatization towards mental illness. Those who scored higher on openness to experience (β = − 0.13, p < 0.001), (β = − 0.14, p < 0.001), and those who scored higher on agreeableness (β = − 0.15, p < 0.001), (β = − 0.12, p < 0.001) showed a lower desire for social distance and lower perceived dangerousness, respectively. Neuroticism (β = − 0.06, p = 0.012) was inversely associated with perceived dangerousness. Additionally, high self-esteem was associated with increased stigmatization. Personal contact or familiarity with people having mental disorders was associated with decreased stigmatization. Contrarily, healthcare professionals showed higher perceived dangerousness (β = 0.04, p = 0.040). Finally, perceived dangerousness partially mediated the association between openness to experience (indirect effect = − .57, 95% CI [− .71, − 0.43]) as well as agreeableness (indirect effect = − 0.57, 95% CI [− 0.74, − 0.39]) and desire for social distance. Although the explained variance in all analyses is < 10%, the current findings highlight the role of personality traits and self-esteem in areas of stigma. Therefore, future stigma research and anti-stigma campaigns should take individual differences into consideration. Moreover, the current study suggests that perceived dangerousness mediates the relationship between personality traits and desire for social distance. Further studies are needed to explore the underlying mechanisms of such relationship. Finally, our results once more underline the necessity of increasing familiarity with mentally ill people and of improving the attitude of healthcare professionals towards persons with mental disorders.
Hair cortisol in polycystic ovary syndrome
Authors: Gonzalez D. , Maidana P. , Ibar C. , Jamardo J. , Jacobsen D. , Fritzler A. , Fortuna F. , Fernandez G. , Lamas-Majek E. , Mallea-Gil S. , Ballarino C. , Onetto C. , Lopez M. , Mesch Viviana , Fabre B. 
Published: June 2022

AbstractThe aim of the study was to evaluate adrenal axis hyperactivation measuring hair cortisol levels, and its influence on the relationship among metabolic parameters, inflammation markers and androgens in adult women with PCOS. 44 women (18–34 years) with PCOS diagnosis and a control group of 49 healthy women (19–35 years) were included. In both gropus body mass index (BMI) was calculated and waist circumference (WC) was measured. Hair cortisol, total serum testosterone (TT), serum cortisol, 25 OH vitamin D (25OHD), insulin, high sensitivity C-reactive protein (hsCRP), triglycerides (TG), HDL cholesterol (HDL), glucose and leptin were measured. Bioavailable testosterone (bioT) was calculated. Hair cortisol concentration was higher and significantly different in PCOS patients compared to the control group (130 vs 63 pg/mg of hair, p < 0.001). Subsequently, patients with PCOS were divided into two groups according to hair cortisol levels: group 1 with normal hair cortisol concentration and group 2 with levels above the upper limit of the reference values (128 pg/mg of hair). In group 2, TT significantly correlated with 25OHD, hsCRP, TG/HDL index, BMI, WC, insulin and HOMA (p < 0.05); bioT correlated with hsCRP and leptin (p < 0.05). Finally, 25OHD was inversely correlated with leptin and with TG/HDL index (p < 0.05). High hair cortisol concentration in patients with PCOS confirmed hyperactivation of the HPA axis. The associations observed were only found in patients with PCOS with high hair cortisol levels (> 128 pg/mg of hair), showing a possible effect of HPA axis in these associations.
Effect of dietary soybean oil inclusion on liver-related transcription factors in a pig model for metabolic diseases
Authors: Fanalli Simara Larissa , da Silva Bruna Pereira Martins , Gomes Julia Dezen , Ciconello Fernanda Nery , de Almeida Vivian Vezzoni , Freitas Felipe André Oliveira , Moreira Gabriel Costa Monteiro , Silva-Vignato Bárbara , Afonso Juliana , Reecy James , Koltes James , Koltes Dawn , Regitano Luciana Correia Almeida , de Carvalho Baileiro Júlio Cesar , Freitas Luciana , Coutinho Luiz Lehmann , Fukumasu Heidge , de Alencar Severino Matias , Luchiari Filho Albino , Cesar Aline Silva Mello 
Published: June 2022

AbstractDietary fatty acids (FA) are components of the lipids, which contribute to membrane structure, energy input, and biological functions related to cellular signaling and transcriptome regulation. However, the consumers still associate dietary FA with fat deposition and increased occurrence of metabolic diseases such as obesity and atherosclerosis. Previous studies already demonstrated that some fatty acids are linked with inflammatory response, preventing metabolic diseases. To better understand the role of dietary FA on metabolic diseases, for the first time, a study to identify key transcription factors (TF) involved in lipid metabolism and inflammatory response by transcriptome analysis from liver samples of animal models was performed. The key TF were identified by functional enrichment analysis from the list of differentially expressed genes identified in liver samples between 35 pigs fed with 1.5% or 3.0% soybean oil. The functional enrichment analysis detected TF linked to lipid homeostasis and inflammatory response, such asRXRA,EGFR, andSREBP2precursor. These findings demonstrated that key TF related to lipid metabolism could be modulated by dietary inclusion of soybean oil. It could contribute to nutrigenomics research field that aims to elucidate dietary interventions in animal and human health, as well as to drive food technology and science.
COVID-19 conspiracy ideation is associated with the delusion proneness trait and resistance to update of beliefs
Authors: Acar K. , Horntvedt O. , Cabrera A. , Olsson A. , Ingvar M. , Lebedev A. V. , Petrovic P. 
Published: June 2022

AbstractThe rapid spread of conspiracy ideas associated with the recent COVID-19 pandemic represents a major threat to the ongoing and coming vaccination programs. Yet, the cognitive factors underlying the pandemic-related conspiracy beliefs are not well described. We hypothesized that such cognitive style is driven by delusion proneness, a trait phenotype associated with formation of delusion-like beliefs that exists on a continuum in the normal population. To probe this hypothesis, we developed a COVID-19 conspiracy questionnaire (CCQ) and assessed 577 subjects online. Their responses clustered into three factors that included Conspiracy, Distrust and Fear/Action as identified using principal component analysis. We then showed that CCQ (in particular the Conspiracy and Distrust factors) related both to general delusion proneness assessed with Peter’s Delusion Inventory (PDI) as well as resistance to belief update using a Bias Against Disconfirmatory Evidence (BADE) task. Further, linear regression and pathway analyses suggested a specific contribution of BADE to CCQ not directly explained by PDI. Importantly, the main results remained significant when using a truncated version of the PDI where questions on paranoia were removed (in order to avoid circular evidence), and when adjusting for ADHD- and autistic traits (that are known to be substantially related to delusion proneness). Altogether, our results strongly suggest that pandemic-related conspiracy ideation is associated with delusion proneness trait phenotype.
Highly sensitive and non-disruptive detection of residual undifferentiated cells by measuring miRNAs in culture supernatant
Authors: Masumoto Kanako , Aihara Yuki , Miyagawa Kuroishi Mao , Maeda Natsuki , Sakai Yumiko , Oka Yuma , Takahashi Yusuke , Oda Kenta , Yanagida Masatoshi 
Published: June 2022

AbstractThe clinical usage of induced pluripotent stem cell (iPSC)-derived regenerative medicine products is limited by the possibility of residual undifferentiated cells forming tumours after transplantation. Most of the existing quality control tests involve crushing of cells. As a result, the cells to be transplanted cannot be directly tested, thereby increasing the cost of transplantation. Therefore, we tested a highly sensitive and non-disruptive quality-testing method that involves measuring microRNAs (miRNAs) in culture supernatants released by cells. By measuring miR-302b in the culture supernatant, residual iPSCs were detected with higher sensitivity than by measuring LIN28 (Lin-28 Homolog A) in the cells. To use this method, we also monitored the progression of differentiation. Our novel highly sensitive and non-disruptive method for detecting residual undifferentiated cells will contribute to reducing the manufacturing cost of iPSC-derived products and improving the safety of transplantation.
The relative abundances of yeasts attractive to Drosophila suzukii differ between fruit types and are greatest on raspberries
Authors: Jones Rory , Fountain Michelle T. , Andreani Nadia A. , Günther Catrin S. , Goddard Matthew R. 
Published: June 2022

AbstractFungal metabolic volatiles attract Drosophila suzukii which oviposits in ripening fruits, but there are few data describing the fungal microbiomes of commercial fruits susceptible to this insect pest. We tested the hypothesis that fruit type and ripening stage have a significant effect on fruit surface fungal communities using DNA metabarcoding approaches and found strong support for differences in all three fungal community biodiversity metrics analysed (numbers, types, and abundances of taxa). There was an average fivefold greater difference in fungal communities between sites with different fruit types (strawberry, cherry, raspberry, and blueberry) than across fruit developmental stages, demonstrating site and/or fruit type is the greater factor defining fungal community assemblage. The addition of a fungal internal standard (Plectosphaerella cucumerina) showed cherry had relatively static fungal populations across ripening. Raspberry had a greater prevalence of Saccharomycetales yeasts attractive to D. suzukii, including Hanseniaspora uvarum, which aligns with reports that raspberry is among the fruits with greatest susceptibility and attraction to D. suzukii. Greater knowledge of how yeast communities change during fruit maturation and between species or sites may be valuable for developing methods to manipulate fruit microbiomes for use in integrated pest management strategies to control D. suzukii.