bluuebunny/crossref_metadata_2025_split huggingface dataset:
A generalized framework to identify SARS-CoV-2 broadly neutralizing antibodies
Authors: Jian Fanchong , Wec Anna Z. , Feng Leilei , Yu Yuanling , Wang Lei , Wang Peng , Yu Lingling , Wang Jing , Hou Jacob , Berrueta Daniela Montes , Lee Diana , Speidel Tessa , Ma LingZhi , Kim Thu , Yisimayi Ayijiang , Song Weiliang , Wang Jing , Liu Lu , Yang Sijie , Niu Xiao , Xiao Tianhe , An Ran , Wang Yao , Shao Fei , Wang Youchun , Henry Carole , Pecetta Simone , Wang Xiangxi , Walker Laura M. , Cao Yunlong 
Published: April 2024

AbstractMonoclonal antibodies (mAbs) targeting the SARS-CoV-2 receptor-binding domain (RBD) showed high efficacy in the prevention and treatment of COVID-19. However, the rapid evolution of SARS-CoV-2 has rendered all clinically authorized mAbs ineffective and continues to stymie the development of next-generation mAbs. Consequently, the ability to identify broadly neutralizing antibodies (bnAbs) that neutralize both current and future variants is critical for successful antibody therapeutic development, especially for newly emerged viruses when no knowledge about immune evasive variants is available. Here, we have developed a strategy to specifically select for potent bnAbs with activity against both existing and prospective SARS-CoV-2 variants based on accurate viral evolution prediction informed by deep mutational scanning (DMS). By adopting this methodology, we increased the probability of identifying XBB.1.5-effective SARS-CoV-2 bnAbs from ∼1% to 40% if we were at the early stage of the pandemic, as revealed by a retrospective analysis of >1,000 SARS-CoV-2 wildtype (WT)-elicited mAbs. From this collection, we identified a bnAb, designated BD55-1205, that exhibited exceptional activity against historical, contemporary, and predicted future variants. Structural analyses revealed extensive polar interactions between BD55-1205 and XBB.1.5 receptor-binding motif (RBM), especially with backbone atoms, explaining its unusually broad reactivity. Importantly, mRNA-based delivery of BD55-1205 IgG to human FcRn-expressing transgenic mice resulted in high serum neutralizing titers against selected XBB and BA.2.86 subvariants. Together, the ability to identify bnAbs via accurate viral evolution prediction, coupled with the speed and flexibility of mRNA delivery technology, provides a generalized framework for the rapid development of next-generation antibody-based countermeasures against SARS-CoV-2 and potentially other highly variable pathogens with pandemic potential.
Assessing visual performance during intense luminance changes in virtual reality
Authors: Domdei Niklas , Sauer Yannick , Hecox Brian , Neugebauer Alexander , Wahl Siegfried 
Published: April 2024

SummaryDuring indoor-outdoor transitions humans encounter luminance changes beyond the functional range of the photoreceptors, leaving the individual at risk of overlooking harmful low-contrast objects until adaptation processes re-enable optimal vision. To study human visual performance during intense luminance changes, we propose a virtual reality based testbed. After linearization of the headset’s luminance output, detection times were recorded for ten participants. The small (FWHM = 0.6 degree) low-contrast stimuli appeared randomly in one of four corners (±10 degree) after luminance changes of three magnitudes within 1 or 3 seconds. Significantly decreased detection times were observed for the conditions with simulated self-tinting lenses compared to lenses with fixed transmission rates after luminance decreases. In cases of luminance increases all detection times were similar. In conclusion, the proposed virtual reality testbed allows for studying vision during or after steep luminance changes and helps to design technical aids like self-tinting lenses.HighlightsThe HTC Vive headset provides a practicable luminance range of 3 magnitudes, allowing the simulation of indoor-outdoor transitions.Visual performance after steep luminance decreases was significantly better with simulated self-tinting spectacles reducing the encountered luminance step.Different transmission rates of the simulated lenses did not affect the detection times for small low-contrast stimuli after luminance increases.
Moving towards precision TMS? Evaluating individual differences and reproducibility of personalized stimulation targets in UK Biobank
Authors: Zhao Ying , Zhao Yi-Jie , Cui Hailun , Bethlehem Richard A.I. , Voon Valerie 
Published: April 2024

AbstractObjectivePersonalized transcranial magnetic stimulation (TMS) targeting, guided by functional connectivity (FC), shows potential in treating depression. The present study aims to map individual FC peak location using UK Biobank, to evaluate individual differences and reproducibility of FC-based targets.MethodsWe analyzed UK Biobank resting-state fMRI (rfMRI) of 35,423 participants, identifying individual FC peak locations on the dorsolateral prefrontal cortex (DLPFC) that functionally connected to the subcallosal cingulate, amygdala, and ventromedial prefrontal cortex, respectively. Euclidean distance between each participant’s individual peak and group-average peak was calculated. With follow-up rfMRI of 1341 participants, within-subject FC peak location changes were calculated. We also compared common TMS targets and random locations for their median distance to individual peaks in a permutation test.ResultsSeed-based FC analyses revealed large differences in the individual FC peak location on DLPFC: the mean distance from the individual peaks to group-average peak ranged from 14.24 to 29.92mm; 70% to 94% of participants were >10mm away from the group-average peak and potentially located outside of the TMS effective area with common TMS coils. Similar variability was observed in within-subject peak locations across two fMRI assessments. Common TMS targets and the group-average FC peak showed no significant difference in median distances to individual FC peaks when compared to random locations.ConclusionsFC peak location shows wide inter- and intra-individual variability. We emphasize a role for individualized TMS neuronavigation targeting but emphasize the need for more reliable biomarker studies.
Proteolytic processing of both RXLR and EER motifs in oomycete effectors
Authors: Xu Lin , Wang Shumei , Wang Wei , Wang Haixia , Welsh Lydia , Boevink Petra C , Whisson Stephen C , Birch Paul RJ 
Published: April 2024

AbstractArg-any amino acid-Leu-Arg (RXLR) effectors are central oomycete virulence factors that target diverse host proteins and processes to suppress plant immunity. Relatively little is known about how they are processed post-translationally before delivery into host cells. Proteolytic cleavage at the RXLR motif was observed to occur prior to secretion in allPhytophthora infestanseffectors tested, suggesting it is a general rule, and was observed to occur between the leucine and the second arginine. There was no cleavage of a naturally occurring second RXLR motif in a structured region of Pi21388/AvrBlb1, or one introduced at a similar position in effector Pi04314, in keeping with the motif being positionally constrained, potentially to disordered regions closely following the signal peptide. Remarkably, independent proteolytic cleavage of the Glu-Glu-Arg (EER) motif, often found immediately downstream of the RXLR, was also observed in diverse effectors, occurring immediately after the arginine. Expression of full-length effectors in host plantNicotiana benthamianarevealed that, although secreted, they were poorly processed, suggesting that RXLR and EER cleavage does not occur in all eukaryotic cells. Our observations indicate that, whether possessing both RXLR and EER, or either motif alone, these effectors are likely proteolytically processed prior to secretion in all cases.
Phytochemical studies and Antimicrobial Activity on the leaves ofAntigonon leptopusandEcbolium viridae
Authors: Rudhra S , Venkatesan A. 
Published: April 2024

AbstractThe aim of the present study is to investigate the in vitro Antibacterial activity ofAntigonon leptopusandEcbolium viridaemethanol, ethanol, acetone leaf extracts for against selected bacterial strains respectively. Preliminary phytochemical screening of the leaf crude extract revealed the presence of alkaloids, flavonoids, phenols, taninns, carbohydrates, saponins. The evaluation of leaf powder was supported by physico-chemical analysis. The antibacterial activities of leaf ofE.virideandAntigonon leptopusin successive different solvent were tested against gram +ve (Staphylococcus aureus, Streptococcus pyogenes) and gram −ve (Escherichia coli, Pseudomonas aeruginosa) Antibacterial activity of those crude extracts are determined by using agar well diffusion method and the zone of inhibition of microorganisms was measured in mm. Amphicillin is used as a positive control respectively.
Default mode network tau predicts future clinical decline in atypical early Alzheimer’s disease
Authors: Katsumi Yuta , Howe Inola A. , Eckbo Ryan , Wong Bonnie , Quimby Megan , Hochberg Daisy , McGinnis Scott M. , Putcha Deepti , Wolk David A. , Touroutoglou Alexandra , Dickerson Bradford C. 
Published: April 2024

AbstractIdentifying individuals with early stage Alzheimer’s disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years). All patients underwent structural magnetic resonance imaging (MRI), tau (18F-Flortaucipir) PET, and amyloid (either18F-Florbetaben or11C-Pittsburgh Compound B) PET scans at baseline. Each patient’s longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Our sample of early atypical AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year:t(47) = 6.56,p< .001,d= 0.95. These AD patients showed prominent baseline tau burden in posterior cortical regions including the major nodes of the default mode network, including the angular gyrus, posterior cingulate cortex/precuneus, and lateral temporal cortex. Greater baseline tau in the broader default mode network predicted faster clinical decline. Tau in the default mode network was the strongest predictor of clinical decline, outperforming baseline clinical impairment, tau in other functional networks, and the magnitude of cortical atrophy and amyloid burden in the default mode network. Overall, these findings point to the contribution of baseline tau burden within the default mode network of the cerebral cortex to predicting the magnitude of clinical decline in a sample of atypical early AD patients one year later. This simple measure based on a tau PET scan could aid the development of a personalized prognostic, monitoring, and treatment plan tailored to each individual patient, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient’s tau burden while still early in the disease course.
Optimization of Multi-Ancestry Polygenic Risk Score Disease Prediction Models
Authors: Lerga-Jaso Jon , Terpolovsky Andrew , Novković Biljana , Osama Alex , Manson Charlie , Bohn Sandra , De Marino Adriano , Kunitomi Mark , Yazdi Puya G. 
Published: April 2024

AbstractBackgroundPolygenic risk scores (PRS) have ushered in a new era in genetic epidemiology, offering insights into individual predispositions to a wide range of diseases. However, despite recent marked enhancements in their predictive power, there are still challenges that need to be overcome before PRS-based models can be broadly applied in the clinic, including sufficient accuracy, easy interpretability and portability across diverse populations.MethodsLeveraging trans-ancestry genome-wide association study (GWAS) meta-analysis, we generated novel, diverse summary statistics for 30 medically-related traits which were used to benchmark the performance of six existing PRS algorithms using UK biobank. Observing that SBayesRC had the best overall performance but recognizing strengths in each method, we developed an ensemble PRS model using logistic regression to combine outputs from top-performing algorithms. This ensemble model was validated on the diverse eMERGE and PAGE MEC cohorts, and the performance was compared against current state-of-the-art PRS models. To enhance predictive accuracy for clinical application, we incorporated easily-accessible clinical characteristics such as age, gender, ancestry and risk factors, creating disease prediction models intended as prospective diagnostic tests, with easily interpretable positive or negative outcomes.ResultsPredictive performance of PRS models improved with trans-ancestry GWAS meta-analysis and was further enhanced by the ensemble model, which surpassed state-of-art PRS models. When applied to external cohorts, performance drops were minimal, indicating good calibration. After adding clinical characteristics, 12 out of 30 models surpassed 80% AUC. Further, 25 traits exceeded the diagnostic odds ratio (DOR) of 5 and 19 traits exceeded DOR of 10 for all ancestry groups, indicating high predictive value. The highest DOR in a population with a sufficient number of cases was 66.2 for Alzheimer’s disease in Europeans. Our PRS model for coronary artery disease identified 55-80 times more true coronary events than rare pathogenic variant models, reinforcing its clinical potential. The polygenic component modulated the effect of high-risk rare variants, stressing the need to consider all genetic components in clinical settings.ConclusionsNewly developed PRS-based disease prediction models have sufficient accuracy and portability to warrant consideration of being used in the clinic.
Media-driven adaptive behavior in pandemic modeling and data analysis
Authors: Yu Zhiyuan , Gurarie David , Huang Qimin 
Published: April 2024

1AbstractHuman behavior and public attitudes towards preventive control measures, such as personal protection, screening, isolation, and vaccine acceptance, play a crucial role in shaping the course of a pandemic. These attitudes and behaviors are often influenced by various information sources, most prominently by social media platforms.The primary information usually comes from government bodies, e.g. CDC, responsible for public health mandates. However, social media can amplify, modify, or distort this information in numerous ways. The dual nature of social media can either raise awareness and encourage protective behaviors and reduce transmission, or have the opposite effect by spreading misinformation and fostering non-compliance.To analyze the interplay between these components, we have developed a coupled SIR-type dynamical model that integrates three essential components: (i) disease spread, as reported by official sources; (ii) the response of social media to this information; and (iii) the subsequent modification of human behavior, which directly impacts the spread of disease.To calibrate and validate our model, we utilized available data sources on the Covid-19 pandemic from a one-year period (2021-2022) in the United States, as well as data on social media responses, particularly tweets. By analyzing the data and conducting model simulations, we have identified significant inputs and parameters, such as initial compliance levels and behavioral transition rates. These factors enable a quantitative assessment of their contributions to disease outcomes, including cumulative outbreak size and its dynamic trajectory.This modeling approach gives some valuable insights into the relationship between public attitudes, information dissemination, and their impact on the progression of the pandemic. By understanding these dynamics, we can inform policy decisions, public health campaigns, and interventions to effectively combat the spread of Covid-like pathogens and future pandemics.
Sociodemographic and geographic variation in mortality attributable to air pollution in the United States
Authors: Geldsetzer Pascal , Fridljand Daniel , Kiang Mathew V. , Bendavid Eran , Heft-Neal Sam , Burke Marshall , Thieme Alexander H. , Benmarhnia Tarik 
Published: April 2024

AbstractThere are large differences in premature mortality in the USA by racial/ethnic, education, rurality, and social vulnerability index groups. Using existing concentration-response functions, particulate matter (PM2.5) air pollution, population estimates at the tract level, and county-level mortality data, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in mortality attributable to PM2.5were consistently more pronounced between racial/ethnic groups than by education, rurality, or social vulnerability index, with the Black American population having by far the highest proportion of deaths attributable to PM2.5in all years from 1990 to 2016. Over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic White population was attributable to PM2.5in the years 2000 to 2011.
Validation of an in vitro diagnostic test for endometriosis: impact of confounding medical conditions and lesion location
Authors: Daoud Elza , Archer David F. , Herranz-Blanco Bárbara 
Published: April 2024

AbstractWith the aim to shorten the time for diagnosis and accelerate access to correct management, a non-invasive diagnostic test for endometriosis was developed and validated. The IVD test combines an ELISA test kit to quantify CA125 and BDNF concentrations in serum and a data treatment algorithm hosted in medical software processing results from the ELISA test and responses to six clinical variables. Serum samples and clinical variables extracted from psychometric questionnaires from 77 patients were collected from the Oxford Endometriosis CaRe Centre biobank (UK). Case/control classification was performed based on laparoscopy and histological verification of the excised lesions. Biomarkers serum concentrations and clinical variables were introduced to the software, which generates the qualitative diagnostic result (“positive” or “negative”). This test allowed the detection of 32% of cases with superficial endometriosis, which is an added value given the limited efficacy of existing imaging techniques. Even in the presence of various confounding medical conditions, the test maintained a specificity of 100%, supporting its suitability for use in patients with underlying medical conditions.
Study protocol for the Multimodal Approach to Preventing Suicide in Schools (MAPSS) project: A regionally based feasibility trial of an integrated response to suicide risk among UK secondary school pupils
Authors: Ashworth Emma , McCarthy Molly , Wynne Sio , Robinson Jo , McKay Samuel , Lane Steven , Richardson Gerry , Boardman Neil , Henderson Kate , Crosbie Vivienne , Humphrey Neil , York Sian , Michail Maria , Hart Damian , Clacy David , Jalota Mani , Saini Pooja 
Published: April 2024

AbstractBackgroundSuicide is the leading cause of death of children and young people under 35 in the UK, and suicide rates are rising in this age group. Schools are considered an appropriate and logical setting for youth suicide prevention activities, with universal, selective, and indicated approaches all demonstrating efficacy. Given that international best practice recommends suicide prevention programmes combine these approaches, and that to date this has not been done in school settings in the UK, this study aims to evaluate the feasibility of delivering a suicide prevention programme incorporating universal, selective, and indicated components in UK schools.MethodsThis study is a feasibility cluster-randomised controlled trial (RCT) of an adapted version of the Multimodal Approach to Preventing Suicide in Schools (MAPSS) programme. The programme, initially developed in Australia, involves delivering universal psychoeducation to all pupils, screening them for suicide risk, and delivering Internet-based Cognitive Behavioural Therapy (Reframe IT-UK) to those students identified as being at high-risk for suicide. The programme will be trialled in six secondary schools in Northwest England and will target Year 10 students (14- and 15-year-olds). The primary aims are to assess: 1) the acceptability and safety of delivering MAPSS in a school setting in the UK; 2) the social validity of the MAPSS programme; and 3) the feasibility of delivering a large-scale, appropriately powered, cluster-RCT and economic evaluation of this intervention in the future. Secondary aims are to assess changes over time in mental health and wellbeing outcomes.DiscussionThis study is the first to evaluate a suicide prevention programme comprising universal, selective, and indicated components in UK schools. If the programme is found to be feasible, it could be more widely tested in schools and may ultimately lead to reduced rates of suicide and suicidal behaviour in young people.
A standardised, high-throughput approach to diagnostic group testing method validation
Authors: Unruh Leonhardt A. H. , Crone Michael A. , Freemont Paul S. , Chindelevitch Leonid 
Published: April 2024

1AbstractBackgroundGroup testing, combining the samples of multiple patients into a single pool to be tested for infection, is an approach to increase throughput in clinical diagnostic and population testing by reducing the number of tests required. In order to further increase the throughput and accuracy of these approaches, mathematicians regularly devise novel combinatorial methods. However, although these novel methods are easily validated in silico, they are often never implemented in diagnostic laboratories because of the lack of clear and standardised pathways to clinical validation.MethodsWe develop a standardised analytical workflow that makes use of high-throughput automation and virus-like particle standards to validate theoretical group testing approaches. We then utilise specially developed virus-like particles for SARS-CoV-2, Influenza A, Influenza B, and Respiratory Syncytial Virus (RSV) to develop and validate a novel multiplex group testing approach based on simulated annealing and Bayesian optimization. Our approach improves the inference of positive samples in group testing, leveraging the quantitative nature of RT-qPCR test results.ResultsOur results show a higher positive predictive value of our novel approach for the inference of positive samples compared to the standard approach using binary test outcomes. In large-scale surveillance testing our method can greatly reduce the number of false positive identifications. Our in vitro findings show the viability of group testing for multiplexed testing of respiratory infections and demonstrate the potential of a novel inference method. Both innovations increase the number of people that can be tested with the available resources, which is particularly important in low-resource settings.