bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of Adenopathy at Chest Computed Tomography After Vaccination for Severe Acute Respiratory Syndrome Coronavirus 2
Authors: McGuinness Georgeann , Alpert Jeffrey B. , Brusca-Augello Geraldine , Azour Lea , Ko Jane P. , Tamizuddin Farah , Gozansky Elliott K. , Moore William H. 
Published: December 2022

Objective
This study aimed to determine the prevalence of axillary and subpectoral (SP) lymph nodes after ipsilateral COVID-19 vaccine administration on chest computed tomography (CT).

Methods
Subjects with chest CTs between 2 and 25 days after a first or second vaccine dose, December 15, 2020, to February 12, 2021, were included. Orthogonal measures of the largest axillary and SP nodes were recorded by 2 readers blinded to vaccine administration and clinical details. A mean nodal diameter discrepancy of ≥6 mm between contralateral stations was considered positive for asymmetry. Correlation with the side of vaccination, using a Spearman rank correlation, was performed on the full cohort and after excluding patients with diseases associated with adenopathy.

Results
Of the 138 subjects (81 women, 57 men; mean [SD] age, 74.4 ± 11.7 years), 48 (35%) had asymmetrically enlarged axillary and/or SP lymph nodes, 42 (30%) had ipsilateral, and 6 (4%) had contralateral to vaccination (P = 0.003). Exclusion of 29 subjects with conditions associated with adenopathy showed almost identical correlation, with asymmetric nodes in 32 of 109 (29%) ipsilateral and in 5 of 109 (5%) contralateral to vaccination (P = 0.002).

Conclusions
Axillary and/or SP lymph nodes ipsilateral to vaccine administration represents a clinical conundrum. Asymmetric nodes were detected at CT in 30% of subjects overall and 29% of subjects without conditions associated with adenopathy, approximately double the prevalence rate reported to the Centers for Disease Control and Prevention by vaccine manufacturers. When interpreting examinations correlation with vaccine administration timing and site is important for pragmatic management.
Learning
from
others is good,
with
others is better: the role of social interaction in human acquisition of new knowledge
Authors: De Felice Sara , Hamilton Antonia F. de C. , Ponari Marta , Vigliocco Gabriella 
Published: December 2022

Learning in humans is highly embedded in social interaction: since the very early stages of our lives, we form memories and acquire knowledge about the world from and with others. Yet, within cognitive science and neuroscience, human learning is mainly studied in isolation. The focus of past research in learning has been either exclusively on the learner or (less often) on the teacher, with the primary aim of determining developmental trajectories and/or effective teaching techniques. In fact, social interaction has rarely been explicitly taken as a variable of interest, despite being the medium through which learning occurs, especially in development, but also in adulthood. Here, we review behavioural and neuroimaging research on social human learning, specifically focusing on cognitive models of how we acquire semantic knowledge from and with others, and include both developmental as well as adult work. We then identify potential cognitive mechanisms that support social learning, and their neural correlates. The aim is to outline key new directions for experiments investigating how knowledge is acquired in its ecological niche, i.e. socially, within the framework of the two-person neuroscience approach.
This article is part of the theme issue ‘Concepts in interaction: social engagement and inner experiences’.
Multi-dimensional sensorimotor grounding of concrete and abstract categories
Authors: Banks Briony , Connell Louise 
Published: December 2022

Semantic categories, and the concepts belonging to them, have commonly been defined by their relative concreteness, that is, their reliance on perception. However, sensorimotor grounding must be regarded as going beyond the basic five senses and incorporate a multi-dimensional variety of perceptual and action experience. We present a series of exploratory analyses examining the sensorimotor grounding of participant-produced member concepts for 117 categories, spanning concrete (e.g.animalandfurniture) and highly abstract (e.g.unit of timeandscience) categories. We found that both concrete and abstract categories are strongly grounded in multi-dimensional sensorimotor experience. Both domains were dominated by vision and, to a lesser extent, head movements, but concrete categories were more grounded in touch and hand–arm action, while abstract categories were more grounded in hearing and interoception. Importantly, this pattern of grounding was not uniform, and subdomains of concrete (e.g. ingestibles, animates, natural categories and artefacts) and abstract (e.g. internal, social and non-social) categories were grounded in different profiles of sensorimotor experience. Overall, these findings suggest that the distinction between abstract and concrete categories is not as clearcut as ontological assumptions might suggest, and that the strength and diversity of sensorimotor grounding in abstract categories must not be underestimated.This article is part of the theme issue ‘Concepts in interaction: social engagement and inner experiences’.
Influence of language on perception and concept formation in a brain-constrained deep neural network model
Authors: Henningsen-Schomers Malte R. , Garagnani Max , Pulvermüller Friedemann 
Published: December 2022

A neurobiologically constrained model of semantic learning in the human brain was used to simulate the acquisition of concrete and abstract concepts, either with or without verbal labels. Concept acquisition and semantic learning were simulated using Hebbian learning mechanisms. We measured the network's category learning performance, defined as the extent to which it successfully (i) grouped partly overlapping perceptual instances into a single (abstract or concrete) conceptual representation, while (ii) still distinguishing representations for distinct concepts. Co-presence of linguistic labels with perceptual instances of a given concept generally improved the network's learning of categories, with a significantly larger beneficial effect for abstract than concrete concepts. These results offer a neurobiological explanation for causal effects of language structure on concept formation and on perceptuo-motor processing of instances of these concepts: supplying a verbal label during concept acquisition improves the cortical mechanisms by which experiences with objects and actions along with the learning of words lead to the formation of neuronal ensembles for specific concepts and meanings. Furthermore, the present results make a novel prediction, namely, that such ‘Whorfian’ effects should be modulated by the concreteness/abstractness of the semantic categories being acquired, with language labels supporting the learning of abstract concepts more than that of concrete ones.
This article is part of the theme issue ‘Concepts in interaction: social engagement and inner experiences’.
Rethinking the role of language in embodied cognition
Authors: Dove Guy O. 
Published: December 2022

There has been a lot of recent interest in the way that language might enhance embodied cognition. This interest is driven in large part by a growing body of evidence implicating the language system in various aspects of semantic memory—including, but not limited to, its apparent contribution to abstract concepts. In this essay, I develop and defend a novel account of the cognitive role played by language in our concepts. This account relies on the embodied nature of the language system itself, diverges in significant ways from traditional accounts, and is part of a flexible, multimodal and multilevel view of our conceptual system.This article is part of the theme issue ‘Concepts in interaction: social engagement and inner experiences’.
A machine learning-based phenotype for long COVID in children: an EHR-based study from the RECOVER program
Authors: Lorman Vitaly , Razzaghi Hanieh , Song Xing , Morse Keith , Utidjian Levon , Allen Andrea J. , Rao Suchitra , Rogerson Colin , Bennett Tellen D. , Morizono Hiroki , Eckrich Daniel , Jhaveri Ravi , Huang Yungui , Ranade Daksha , Pajor Nathan , Lee Grace M. , Forrest Christopher B. , Bailey L. Charles 
Published: December 2022

AbstractBackgroundAs clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data.Methods and FindingsIn this study, we developed and validated a machine learning algorithm to classify which patients have PASC (distinguishing between Multisystem Inflammatory Syndrome in Children (MIS-C) and non-MIS-C variants) from a cohort of patients with positive SARS-CoV-2 test results in pediatric health systems within the PEDSnet EHR network. Patient features included in the model were selected from conditions, procedures, performance of diagnostic testing, and medications using a tree-based scan statistic approach. We used an XGboost model, with hyperparameters selected through cross-validated grid search, and model performance was assessed using 5-fold cross-validation. Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values.ConclusionsThe model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. Using appropriate threshold settings, the model can be used to identify PASC patients in health systems data at higher precision for inclusion in studies or at higher recall in screening for clinical trials, especially in settings where PASC diagnosis codes are used less frequently or less reliably. Analysis of how specific features contribute to the classification process may assist in gaining a better understanding of features that are associated with PASC diagnoses.Funding SourceThis research was funded by the National Institutes of Health (NIH) Agreement OT2HL161847-01 as part of the Researching COVID to Enhance Recovery (RECOVER) program of research.DisclaimerThe content is solely the responsibility of the authors and does not necessarily represent the official views of the RECOVER Program, the NIH or other funders.
Comparative effectiveness of four COVID-19 vaccines, BNT162b2 mRNA, mRNA-1273, ChAdOx1 nCov-19 and NVX-CoV2373 against SARS-CoV-2 B.1.1.529 (Omicron) infection
Authors: Liu Bette , Stepien Sandrine , Qian Jiahui , Gidding Heather , Nicolopoulos Katrina , Amin Janaki , Cheng Allen , Macartney Kristine 
Published: December 2022

AbstractThere is limited data directly comparing the effectiveness of COVID-19 vaccines. We compared rates of SARS-CoV-2 Omicron BA.1/2 infection in Australian adults during March to May 2022 who had received one of four COVID-19 vaccines in the last 14-63 days as either a primary course or a booster dose. As a primary course, compared to recipients of BNT162b2 mRNA vaccine, adjusted hazard ratios for SARS-CoV-2 infection were 1.03 (95%CI 0.82-1.30), 1.19 (0.95-1.49), 1.70 (1.46-1.97) for respectively mRNA-1273, ChAdOx-1 nCov-19 and NVX-CoV2373. For booster dose, respective adjusted hazard ratios compared to BNT162b2 mRNA vaccine were 1.02 (95%CI 1.00-1.04), 1.20 (1.10-1.32), 1.39 (1.20-1.60). Our findings suggest relatively higher effectiveness of ancestral strain mRNA vaccines against SARS-CoV-2 Omicron infection than viral vector and protein subunit vaccines, but further studies are required due to small numbers of recipients of ChAdOx-1 nCov-19 and NVX-CoV2373.
Unequal Recovery in Colorectal Cancer Screening Following the COVID-19 Pandemic: A Comparative Microsimulation Analysis
Authors: de Lima Pedro Nascimento , van den Puttelaar Rosita , Hahn Anne I. , Harlass Matthias , Collier Nicholson , Ozik Jonathan , Zauber Ann G. , Lansdorp-Vogelaar Iris , Rutter Carolyn M. 
Published: December 2022

AbstractThe aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in access to colorectal cancer (CRC) screening due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term colorectal cancer (CRC) outcomes was measured by the number of Life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in colorectal cancer outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.
COMPARATIVE STUDY ON THE PREVALENCE OF MALNUTRITION AMONG PUBLIC PRIMARY SCHOOL PUPILS IN RURAL AND URBAN COMMUNITIES IN WARRI SOUTH
Authors: Emeagi Chinwendu Sandra , Apugo Uchechukwu Ifeanyichukwu 
Published: December 2022

AbstractBackgroundMalnutrition among primary school-age children has continued to pose a major public health issue, especially in developing countries. Nigeria is ranked amongst the top ten countries with the highest prevalence of undernutrition in children while about 2,300 children die daily in Nigeria as a result of malnutrition.AimTo determine and compare the prevalence of malnutrition among public school pupils in rural and urban communities in Warri South LGA.Materials and MethodThis school-based comparative cross-sectional study made use of a bio-data form that collected socio-demographic details and anthropometric measurements of the pupils. The nutritional status of the pupils was obtained using WHO AnthroPlus software, while the resulting data were analysed and presented accordingly.ResultsA total of 330 pupils (165 each from urban and rural public primary schools) were recruited, out of which more of the pupils in urban areas were younger, had parents who were better educated and employed while those from rural areas had higher family sizes. However, there was no difference in the sex and type of family of the pupils. The prevalence of malnutrition was reported as 36.7% with the prevalent form of malnutrition discovered as underweight (35.0%), followed by stunting (13.9%), overweight/obese (8.5%), and wasting (7.2%). Wasting, stunting, and overweight were higher among urban pupils, while the rate of underweight was higher among rural children.ConclusionThis high prevalence of undernutrition among urban pupils could be attributed to poor nutrition arising from a myriad of interrelated circumstances such as poor feeding, eating practices, and recurrent infection. Hence, the need for improved sensitisation of mothers concerning correct childhood feeding and provision of balanced nutrition.
No patient is the same; lessons learned from antibody repertoire profiling in hospitalized severe COVID-19 patients
Authors: Bondt Albert , Hoek Max , Dingess Kelly , Tamara Sem , de Graaf Bastiaan , Peng Weiwei , den Boer Maurits A. , Damen Mirjam , Zwart Ceri , Barendregt Arjan , van Rijswijck Danique M.H. , Grobben Marloes , Tejjani Khadija , van Rijswijk Jacqueline , Völlmy Franziska , Snijder Joost , Fortini Francesca , Papi Alberto , Volta Carlo Alberto , Campo Gianluca , Contoli Marco , van Gils Marit J. , Spadaro Savino , Rizzo Paola , Heck Albert J.R. 
Published: December 2022

AbstractHere, by using mass spectrometry-based methods IgG1 and IgA1 clonal repertoires were monitored quantitatively and longitudinally in more than 50 individual serum samples obtained from 17 COVID-19 patients admitted to intensive care units because of acute respiratory distress syndrome. These serological clonal profiles were used to examine how each patient reacted to a severe SARS-CoV-2 infection. All 17 donors revealed unique polyclonal repertoires and changes after infection. Substantial changes over time in the IgG1 and/or IgA1 clonal repertoires were observed in individual patients, with several new clones appearing following the infection, in a few cases leading to a few very high abundant IgG1 and/or IgA1 clones dominating the repertoire. Several of these clones werede novosequenced through combinations of top-down, middle-down and bottom-up proteomics approaches. This revealed several sequence features in line with sequences deposited in the SARS-CoV-specific database of antibodies. In other patients, the serological Ig profiles revealed the treatment with tocilizumab, as after treatment, this IgG1-mAb dominated the serological IgG1 repertoire. Tocilizumab clearance could be monitored and a half-life of approximately 6 days was established in these patients. Overall, our longitudinal monitoring of IgG1 and IgA1 repertoires of individual donors reveals that antibody responses are highly personalized traits of each patient, affected by the disease and the chosen clinical treatment. The impact of these observations argues for a more personalized and longitudinal approach in patients’ diagnostics, both in serum proteomics as well as in monitoring immune responses.
Continuous Patient State Attention Models
Authors: Chauhan Vinod K. , Thakur Anshul , O’Donoghue Odhran , Rohanian Omid , Clifton David A. 
Published: December 2022

AbstractIrregular time-series (ITS) are prevalent in the electronic health records (EHR) as the data is recorded in EHR system as per the clinical guidelines/requirements but not for research and also depends on the patient health status. ITS present challenges in training of machine learning algorithms, which are mostly built on assumption of coherent fixed dimensional feature space. In this paper, we propose a computationally efficient variant of the transformer based on the idea of cross-attention, called Perceiver, for time-series in healthcare. We further develop continuous patient state attention models, using the Perceiver and the transformer to deal with ITS in EHR. The continuous patient state models utilise neural ordinary differential equations to learn the patient health dynamics, i.e., patient health trajectory from the observed irregular time-steps, which enables them to sample any number of time-steps at any time. The performance of the proposed models is evaluated on in-hospital-mortality prediction task on Physionet-2012 challenge and MIMIC-III datasets. The Perceiver model significantly outperforms the baselines and reduces the computational complexity, as compared with the transformer model, without significant loss of performance. The carefully designed experiments to study irregularity in healthcare also show that the continuous patient state models outperform the baselines. The code is publicly released and verified athttps://codeocean.com/capsule/4587224.
The deacetylase dependent and independent role of HDAC3 in cardiomyopathy
Authors: Ren Jieyu , Zeng Qun , Wu Hongmei , Liu Xuewen , Guida Maria Clara , Huang Wen , Zhai Yiyuan , Li Junjie , Ocorr Karen , Bodmer Rolf , Tang Min 
Published: December 2022

BackgroundCardiomyopathy is a common disease of cardiac muscle that negatively affects cardiac function. HDAC3 commonly functions as co-repressor by removing acetyl moieties from histone tails. However, a deacetylase-independent role of HDAC3 has also been described. Cardiac deletion of HDAC3 causes reduced cardiac contractility accompanied by lipid accumulation. The molecular function of HDAC3 in cardiomyopathy remains unknown. We have used the powerful genetic tools inDrosophilato investigate the enzymatic and non-enzymatic roles of HDAC3 in cardiomyopathy.Methods and ResultsUsing theDrosophilaheart model, we showed that cardiac-specific HDAC3 knockdown leads to prolonged systoles and reduced cardiac contractility. Immunohistochemistry revealed structural abnormalities characterized by myofiber disruption in HDAC3 knock down hearts. Cardiac-specific HDAC3 knockdown showed increased levels of whole body triglycerides and increased fibrosis. The introduction of deacetylase-dead HDAC3 mutant in HDAC3 KD background showed comparable results with wild type HDAC3 in aspects of contractility and Pericardin deposition. However, deacetylase-dead HDAC3 mutants failed to improve triglyceride accumulation.ConclusionsOur data indicate that HDAC3 plays a deacetylase-independent role in maintaining cardiac contractility and preventing Pericardin deposition as well as a deacetylase-dependent role to maintain triglyceride homestasis.
Optical Genome Mapping for detecting Homologous Recombination Deficiency (HRD) in human breast and ovarian cancers
Authors: Vanhuele Sandra , Kirova Youlia , Hamy-Petit Anne-Sophie , Rapinat Audrey , Gentien David , Callens Céline , Villy Marie-Charlotte , Reyal Fabien , Vincent-Salomon Anne , Eeckhoutte Alexandre , Rodrigues Manuel , Stern Marc-Henri , Popova Tatiana 
Published: December 2022

AbstractHomologous recombination deficiency (HRD) leads to genomic instability that marks HRD tumor genome with a specific genomic scar. Present in many cancers, HRD is important to be detected as it is associated with a hyper-sensitivity to some classes of drugs, in particular the PARP inhibitors. Here, we investigated the use of structural variants (SVs) detected by the Optical Genome Mapping (OGM) technology as biomarkers to identify HRD tumors. We analyzed SVs data obtained by OGM from 37 samples of triple-negative breast cancer or high grade ovarian cancer with the known HRD status. We found that HRD cases were enriched with duplications and reciprocal translocations, while nonHRD cases were enriched with inversions. The number of translocations, defined as inter-chromosomal or intra-chromosomal rearrangements of more 5Mb were similar in HRD and nonHRD cases. We defined isolated translocations as the subset of translocations having no other translocation within 2 megabase zone around both junctions, and demonstrated that the number of isolated translocations perfectly discriminated HRD and nonHRD cases in the training series. Validation series consisting from 26 cases showed 20% false positive and zero false negative error rate, which proved isolated translocations to be 100% sensitive and 80% specific SV marker of HRD.Our results demonstrate that the OGM technology is an affordable way of getting an insight of the structural variants present in solid tumors, even with low tumoral cellularity. It represents a promising technology for HRD diagnosis, where a single marker already gives 80% correct recognition.