bluuebunny/crossref_metadata_2025_split huggingface dataset:
High throughput method for simultaneous screening of membrane permeability and toxicity for discovery of new cryoprotective agents
Authors: Ahmadkhani Nima , Benson James D. , Eroglu Ali , Higgins Adam Z. 
Published: July 2024

AbstractVitrification is the most promising method for cryopreservation of complex structures such as organs and tissue constructs. However, this method requires multimolar concentrations of cell-permeant cryoprotective agents (CPAs), which can be toxic at such elevated levels. The selection of CPAs for organ vitrification has been limited to a few chemicals; however, there are numerous chemicals with properties similar to commonly used CPAs. In this study, we developed a high-throughput method that significantly increases the speed of cell membrane permeability measurement, enabling ~100 times faster permeability measurement than previous methods. The method also allows assessment of CPA toxicity using the same 96-well plate. We tested five commonly used CPAs and 22 less common ones at both 4 °C and room temperature, with 23 of them passing the screening process based on their favorable toxicity and permeability properties. Considering its advantages such as high throughput measurement of membrane permeability along with simultaneous toxicity assessment, the presented method holds promise as an effective initial screening tool to identify new CPAs for cryopreservation.SignificanceCryoprotective agent (CPA) toxicity is the most limiting factor impeding cryopreservation of critically needed tissues and organs for transplantation and medical research. This limitation is in part due to the challenge of rapidly screening compounds to identify candidate molecules that are highly membrane permeable and non-toxic at high concentrations. Such a combination would facilitate rapid CPA permeation throughout the sample, enabling ice-free cryopreservation with minimal toxicity. This study presents a method for rapidly assessing the cell membrane permeability and toxicity of candidate CPAs, identifies several novel high-permeability low-toxicity CPAs for further testing, and lays the groundwork for additional high throughput screening to discover novel CPAs with the potential to improve cryopreservation of complex tissues and organs.
Polygenic proxies of age-related plasma protein levels reveal TIMP2 role in cognitive performance
Authors: Anastasi Federica , Genius Patricia , Rodriguez-Fernandez Blanca , Yang Chengran , Gorijala Priyanka , Timsina Jigyasha , Hernández-Villamizar Felipe , Lorenzini Luigi , del Campo Marta , Sánchez-Benavides Gonzalo , Minguillon Carolina , Navarro Arcadi , Cruchaga Carlos , Suárez-Calvet Marc , Vilor-Tejedor Natalia 
Published: July 2024

AbstractSeveral studies have identified blood proteins that influence brain aging performance in mice, yet translating these findings to humans remains challenging. Here we found that higher predicted plasma levels of Tissue Inhibitor of Metalloproteinases 2 (TIMP2) were significantly associated with improved global cognition and memory performance in humans. We first identified 12 proteins with aging or rejuvenating effects on murine brains through a systematic review. Using protein quantitative trait loci data for these proteins, we computed polygenic scores as proxies for plasma protein levels and validated their prediction accuracy in two independent cohorts. Association models between genetic proxies and cognitive performance highlighted the significance of TIMP2, also when the models were stratified by sex,APOE-ε4, and Aβ42 status. This finding aligns with TIMP2’s brain-rejuvenating role in murine models, suggesting it as a promising therapeutic target for brain aging and age-related brain diseases in humans.
Association of home and neighbourhood conditions with anxiety and depression symptoms during the COVID-19 lockdown: Findings from the ALSPAC study
Authors: Pinkney Connor , Kirkbride James B. , Boyd Andrew , Zammit Stanley , Newbury Joanne B. 
Published: July 2024

AbstractBackgroundThe first COVID-19 lockdown in the UK was initially hailed as a great leveller. However, given that people were restricted to their homes and immediate neighbourhoods, there were stark inequalities in how different people experienced lockdown. Nevertheless, evidence on the associations of home and neighbourhood conditions in mental health during lockdown is sparce.MethodsUsing data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a UK population-based cohort, we examined associations of home and neighbourhood conditions with anxiety and depression symptoms at two points during the first UK lockdown in 2020 (23/03/20-15/06/20). Questionnaires were sent to the ALSPAC cohort at two timepoints (T1: April; T2: May/June), including validated measures of mental health, and questions about current home conditions and behaviours, including access to nature, garden access, house type, and household composition. Neighbourhood conditions were obtained via a novel linkage, and included neighbourhood deprivation, population density, social fragmentation, and greenspace. Main associations were examined using linear regression. Potential confounders were identified using a directed acyclic graph and included ethnicity, family psychiatric history, maternal social class, financial difficulties before lockdown, and previous anxiety and depression at age 18.FindingsAt T1, reduced access to nature (B=1.06, 95% CI=0.68-1.45, p<0.001) and neighbourhood deprivation (B=0.25, 95% CI=0.02-0.48) were associated with anxiety. Furthermore, reduced access to nature (B=0.99, 95% CI=0.57-1.40, p<0.001), no garden access (B=0.62, 95% CI=0.04-1.20, p=0.037), living alone (B=1.53, 95% CI=0.63-2.43, p=0.001), and neighbourhood deprivation (B=0.27, 95% CI=0.02-0.52, p=0.033) were associated with depression. Associations were similar, but often weaker, at T2. For example, there was strong evidence of associations only for access nature with anxiety (B=0.74, 95% CI=0.25-1.23, p=0.004); and for access to nature (B=1.06, 95% CI=0.50-1.61, p=0.001) and living alone (B=1.19, 95% CI=0.25-2.13, p=0.013) with depression.InterpretationDisadvantaged home and neighbourhood conditions, especially reduced access to nature and neighbourhood deprivation, were associated with more anxiety and depression symptoms during the first UK lockdown. In the case of future pandemics, mitigation efforts should be tailored to reduce the burden on mental health for those most vulnerable. However, the causality of these observational findings is uncertain.
Trends in hospitalisations for lower respiratory tract infection after the COVID-19 pandemic in adults with chronic respiratory disease
Authors: Sabaté-Elabbadi Alexandre , Brolon Lucie , Brun-Buisson Christian , Guillemot Didier , Fartoukh Muriel , Watier Laurence 
Published: July 2024

ABSTRACTIntroductionCOVID-19 pandemic has modified the epidemiology of lower respiratory tract infections (LRTI), particularly in patients presenting a chronic respiratory disease (CRD). LRTI incidence substantially decreased at the start of the COVID-19 pandemic. However, studies focusing on the post-pandemic period are missing. We aimed to evaluate the impact of the pandemic and post-pandemic periods on hospital admissions for LRTI, with a focus on patients with CRD.MethodsFrom July 2013 to June 2023, monthly numbers of adult hospitalisations for LRTI (excluding SARS-CoV-2) were extracted from the anonymized French National Hospital Discharge Database. They were modelled by regressions with autocorrelated errors. Three periods were defined: (1) early pandemic and successive lockdowns (April 2020 to May 2021); (2) gradual lifting of restrictions and widespread SARS-CoV-2 vaccination (June 2021 to June 2022); (3) withdrawal of restriction measures (July 2022 to July 2023). Analyses were computed for the entire series, by gender, age, severity, and pre-existing CRDResultsBefore the pandemic, LRTI hospitalisations showed a winter seasonal pattern with a rising trend. Pre-pandemic incidence was 96 (90.5 to 101.5) per 100,000 population. Compared with the pre-pandemic period, seasonality was no longer present and significant reductions were estimated in the first two periods: −43.64% (−50.11 to −37.17) and −32.97% (−39.88 to −26.05), respectively. A rebound with a positive trend and a seasonal pattern was observed in period 3. Similar results were observed for CRD patients with no significant difference with pre-pandemic levels in the last period (−9.21%; −20.9% to 1.67%), albeit with differential changes according to the type of CRD.ConclusionsCOVID-19 pandemic containment measures contributed to significant changes in LRTI incidence, with a rapid increase and return to a seasonal pattern after their gradual lifting, particularly in patients with CRD.
Stress and Sleep Duration in Immune and Neuroendocrine Patterning. An Analytical Triangulation in ELSA
Authors: Hamilton Odessa S. , Steptoe Andrew 
Published: July 2024

AbstractBackground. Proinflammatory and neuroendocrine mediators are implicated in disease aetiopathogenesis. Stress increases concentrations of immune-neuroendocrine biomarkers through a complex network of brain-body signalling pathways. Suboptimal sleep further modulates these processes by altering major effector systems that sensitise the brain to stress. Given the ubiquitous, impactful nature of material deprivation, we tested for a synergistic association of financial stress and suboptimal sleep with these molecular processes.Methods. With data drawn from the English Longitudinal Study of Ageing (ELSA), associations were tested on 4,940 participants (∼66±9.4 years) across four-years (2008-2012). Through analytical triangulation, we tested whether financial stress (>60% insufficient resources) and suboptimal sleep (≤5/≥9 hours) were independently and interactively associated with immune-neuroendocrine profiles, derived from a latent profile analysis (LPA) of C-reactive protein, fibrinogen, white blood cell counts, hair cortisol, and insulin-like growth factor-1.Results. A three-class LPA model offered the greatest parsimony. After adjustment for genetic predisposition, sociodemographics, lifestyle, and health, financial stress was associated with short-sleep cross-sectionally (RRR=1.45; 95%CI=1.18-1.79;p<0.001) and longitudinally (RRR=1.31; 95%CI=1.02-1.68;p=0.035), and it increased risk of belonging to thehigh-riskbiomarker profile by 42% (95%CI=1.12-1.80;p=0.004). Suboptimal sleep was not related to future risk ofhigh-riskprofile membership, nor did it moderate financial stress-biomarker profile associations.Discussion. Results advance psychoneuroimmunological knowledge by revealing how immune-neuroendocrine markers cluster in older cohorts and respond to financial stress over time. Financial stress associations with short-sleep are supported. The null role of suboptimal sleep, as exposure and mediator, in profile membership, provides valuable insight into the dynamic role of sleep in immune-neuroendocrine processes.
Purging of highly deleterious alleles through an extreme bottleneck
Authors: Stuart Oliver P. , Cleave Rohan , Pearce Kate , Magrath Michael J.L. , Mikheyev Alexander S. 
Published: July 2024

AbstractTransitions to captivity often produce population bottlenecks. On one hand, bottlenecks increase inbreeding and decrease effective population size, thus increasing extinction risk. On the other, elevated homozygosity associated with extreme bottlenecks may purge deleterious alleles. Previous studies of purging in captive breeding programs have focused on phenotypic measurements and may be confounded with environmental effects. We test the ability of natural selection to purge deleterious alleles following an extreme population bottleneck by analysing patterns of genetic diversity in wild and captive-bred populations of the Lord Howe Island stick insect (Dryococelus australis).Dryococelus australishas been bred in captivity for two decades, having passed through an extreme bottleneck – only two mating pairs with few new additions since then. The magnitude of the bottleneck, together with the fact that each female lays hundreds of eggs most of which are not recruited, set up nearly ideal conditions for the purging of deleterious alleles. As expected, captive-bred individuals had a greater number of long runs-of-homozygosity compared to wild individuals, implying strong inbreeding in captivity which would facilitate purging in the homozygous regions. Stop-codon and frameshift alleles were preferentially depleted in captivity compared to other alleles, in coding and non-coding regions. The more deleterious an allele was predicted to be, the more likely it was found outside of runs-of-homozygosity, implying that inbreeding events facilitate the expression and thus removal of deleterious alleles, even after such an extreme bottleneck and under the benign conditions of captivity. These data show that extreme inbreeding has likely decreased the deleterious mutation load of the stick insects, though loss of genetic diversity may make future adaptation more difficult.
Towards Wearable Electromyography for Personalized Musculoskeletal Trunk Models using an Inverse Synergy-based Approach
Authors: Rook Jan Willem A. , Sartori Massimo , Refai Mohamed Irfan 
Published: July 2024

AbstractElectromyography (EMG)-driven musculoskeletal models (EMS) of the trunk are used for estimating lumbosacral joint moments and compressive loads during lifting tasks. These models provide personalized estimates of the parameters using information from many sensors. However, to advance technology from labs to workplaces, there is a need for sensor reduction to improve wearability and applicability. Therefore we introduce an EMG sensor reduction approach based on inverse synergy extrapolation, to reconstruct unmeasured EMG signals for different box-lifting techniques. 12 participants performed an array of tasks (squat, stoop, unilateral twist and bilateral twist) with different weights (0 kg, 7.5 kg and 15 kg). We found that two synergies were sufficient to explain the different lifting tasks (median variance accounted for of 0.91). Building upon this, we used two sensors at optimal subject-specific muscle locations to reconstruct the EMG of four unmeasured channels. Evaluation of the reconstructed and reference EMG showed median coefficients of determination (R2) between 0.70 and 0.86, with median root mean squared errors (RMSE) ranging from 0.02 to 0.04 relative to maximal voluntary contraction. This indicates that our proposed method shows promise for sensor reduction for driving a trunk EMS for ambulatory biomechanical risk assessment in occupational settings and exoskeleton control.
Characterization of three resistance-breaking isolates of sugarcane mosaic virus from Rwanda and implications for maize lethal necrosis
Authors: Wilson Jennifer R. , Willie Kristin J. , Stewart Lucy R. , Redinbaugh Margaret G. , Ohlson Erik W. 
Published: July 2024

AbstractMaize lethal necrosis (MLN) is a devastating disease of maize caused by synergy between two viruses: maize chlorotic mottle virus (MCMV) and a potyvirus, most often sugarcane mosaic virus (SCMV). Throughout the 2010s, severe MLN outbreaks occurred in sub-Saharan East Africa including Kenya, Rwanda, and Ethiopia. In this study, we assessed the virulence of SCMV isolates collected from Rwanda by screening a panel of maize near isogenic lines containing different combinations of major potyvirus resistance loci. We discovered that the three Rwandan SCMV isolates tested could overcome all three potyvirus resistance loci even when used in combination, including one isolate that could asymptomatically infect all resistant lines tested. To understand how SCMV virulence may contribute to MLN, each of the three isolates were co-inoculated with MCMV on a panel of SCMV and MCMV resistant maize lines. No significant differences in MLN severity were observed for the Rwandan isolates compared to the reference SCMV isolates, indicating that increased virulence in SCMV single infection does not necessarily correlate with increased MLN severity in co-infection with MCMV. For all SCMV isolates tested, at least two potyvirus resistance loci were needed to reduce MLN severity, and maize lines with a combination of SCMV and MCMV resistance were most effective. Surprisingly, in some cases co-infection with MCMV facilitated SCMV infection of potyvirus resistant lines that SCMV could not infect alone. These results underscore the challenges of developing durable MLN resistance and highlight the importance of incorporating strong, multigenic potyvirus resistance into MLN resistance breeding programs.
Methodological approaches to derive the heartbeat evoked potential: past practices and future recommendations
Authors: Virjee Rania-Iman , Kandasamy Rohan , Garfinkel Sarah N , Carmichael David , Yogarajah Mahinda 
Published: July 2024

AbstractThe heartbeat-evoked potential (HEP), a cortical response time-locked to each heartbeat, is suggested as an implicit electrophysiological marker reflecting the cortical processing of heartbeats, and more broadly interoceptive processing. An increasing number of studies suggest that HEP may be a meaningful clinical measure. However, on the scalp, HEP are low amplitude signals that are mixed with direct cardiac field artefacts. Therefore, signal processing pipelines that separate the cortical HEP from cardiac field artefacts are required. With a view to establishing optimal and standardised HEP pipelines, this review aims to evaluate the current approaches to this analysis used within the literature, address gaps and inconsistencies in HEP pipelines, and highlight the impact of crucial parameter choices. To do this, a scoping review investigated current HEP processing methods and parameters used in EEG and MEG studies. Testing these processing methods on Temple University’s normal scalp EEG data (Obeid and Picone, 2016), the effect of different methods/parameters (e.g. HEP window, electrodes, filters, independent component analysis (ICA) and artefact subspace reconstruction (ASR)) on HEP extraction was explored.EEG studies (N=101) demonstrated greater parameter variability and heterogeneity than MEG studies (N=10), although significantly more studies used EEG. ICA without cardiac field artefact and ASR at threshold 20 exhibit similar results for artefact removal. Statistical analysis revealed that the RR interval, the start and end of the HEP window and the start of the baseline correction window significantly affect HEP values in pre-frontal, frontal and centrotemporal electrodes.Publications should report critical values for reliable HEP extraction, emphasising the need for standardised methods to enhance study comparison and reproducibility and establish a gold standard in the field.
Synthetic dysmobility screening reveals a phosphorylation-independent facet of the SLK-Ezrin-F-actin signaling cascade
Authors: Lin Hsuan-Chao , Lin Yun-Yu , Wei Ling-Ying , Zhang Jia-Ming , Tsai Pei-Ju , Lin Yu-Chiao , Chia Jean-San , Tsai Feng-Chiao 
Published: July 2024

AbstractThis study investigates the role of Ste20-like kinase (SLK) in cytoskeletal dynamics, focusing on its interaction with Ezrin and actin remodeling, independent of phosphorylation processes. We utilized HaCaT to explore the effects of SLK and Ezrin knockdown, as well as the application of specific inhibitors on the organization of actin structures. Our findings reveal that both SLK and Ezrin significantly influence the architecture of actin cytoskeletons with differential impacts observed between protein knockdown and dephosphorylation events. Additionally, our results suggest novel, phosphorylation-independent pathways through which Ezrin modulates actin dynamics, potentially indicating alternative, non-enzymatic roles for Ezrin in cytoskeletal integrity.
TwinEco: A Unified Framework for Dynamic Data-Driven Digital Twins in Ecology
Authors: Khan Taimur , de Koning Koen , Endresen Dag , Chala Desalegn , Kusch Erik 
Published: July 2024

1.AbstractA Digital Twin (DT) is a virtual replica of a physical object or process that is continuously updated at a certain frequency and can steer change on the physical system, enabling a seamless integration of observation, understanding, and action. Although initially applied primarily in industry, DT is emerging as a powerful tool in ecology, offering new possibilities for dynamic simulations of change in the biosphere. However, since DTs are relatively new in this field, there is currently no standard framework to guide their conceptualisation and development. Thus, DTs in ecological applications are already experiencing fragmentation in software concepts and design philosophies, leading to incompatibilities across DT implementations. This fragmentation risks undermining the progress and potential of the DT concept in ecology. A unifying framework, such as TwinEco, can address these discrepancies and establish a cohesive foundation for the effective adoption and integration of DTs across ecological domains. TwinEco is a modular framework designed to aid and harmonise ecologists’ efforts to build DTs. In doing so, TwinEco focuses on three major design goals:Modularity, flexibility, and interoperability of DTs facilitated through distinct “components” nested within DT “layers”.Dynamic modeling of ecological processes and states that evolve over time.Linking ecological modelling to downstream actions or decisions made on the ecological object or process of study.TwinEco’s architecture builds upon the feedback loops and state management strategies introduced in the Dynamic Data-Driven Application Systems (DDDAS) paradigm, which has already inspired many DTs across scientific domains. We also discuss the usefulness and ease-of-use of TwinEco by demonstrating its applicability to computational case studies and suggesting future recommendations to the community of data infrastructure builders and modellers in regards to open considerations. By introducing a shared terminology and emphasising model-data fusion, TwinEco highlights the importance of a unified framework to avoid fragmentation in the burgeoning field of ecological digital twinning.
Does Sex-Differential Gene Expression Drive Sex-Differential Selection in Humans?
Authors: Ming Matthew J. , Cheng Changde , Kirkpatrick Mark , Harpak Arbel 
Published: July 2024

AbstractSex differences in human transcriptomes have been argued to drive sex-differential natural selection (SDS). Here, we show that previous evidence supporting this hypothesis has been largely unfounded. We develop a new method to test for a genome-wide relationship between sex differences in expression and selection on expression-influencing alleles (eQTLs). We apply it across 39 human tissues and find no evidence for a general relationship. We offer possible explanations for the lack of evidence, including that it is due in part to eQTL ascertainment bias towards sites under weak selection. We conclude that the drivers of ongoing SDS in humans remain to be identified.