bluuebunny/crossref_metadata_2025_split huggingface dataset:
The age of reason: Functional brain network development during childhood
Authors: Tooley Ursula A. , Park Anne T. , Leonard Julia A. , Boroshok Austin L. , McDermott Cassidy L. , Tisdall M. Dylan , Bassett Dani S. , Mackey Allyson P. 
Published: July 2022

AbstractHuman childhood is characterized by dramatic changes in the mind and brain. However, little is known about the large-scale intrinsic cortical network changes that occur during childhood due to methodological challenges in scanning young children. Here, we overcome this barrier by using sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 years (n = 92). At multiple spatial scales, age is positively associated with brain network segregation. At the system level, age was associated with segregation of systems involved in attention from those involved in abstract cognition, and with integration among attentional and perceptual systems. Associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, the two ends of a gradient from perceptual, externally oriented cortex to abstract, internally oriented cortex. These findings suggest that both ends of the sensory-association gradient may develop early, in contrast to the classical theories that cortical maturation proceeds from back to front, with sensory areas developing first and association areas developing last. More mature patterns of brain network architecture, controlling for age, were associated with better visuospatial reasoning abilities. Our results suggest that as cortical architecture becomes more specialized, children become more able to reason about the world and their place in it.SignificanceAnthropologists have called the transition from early to middle childhood the “age of reason”, when children across cultures become more independent. We employ cutting-edge neuroimaging acquisition and analysis approaches to investigate associations between age and functional brain architecture in childhood. Age was positively associated with segregation between cortical systems that process the external world, and those that process abstract phenomena like the past, future, and minds of others. Surprisingly, we observed pronounced development at both ends of the sensory-association gradient, challenging the theory that sensory areas develop first and association areas develop last. Our results open new directions for research into how brains reorganize to support rapid gains in cognitive and socioemotional skills as children reach the age of reason.
Variability in cognitive task performance in early adolescence is associated with stronger between-network anticorrelation and future attention problems
Authors: Chang Sarah E. , Lenartowicz Agatha , Hellemann Gerhard S. , Uddin Lucina Q. , Bearden Carrie E. 
Published: July 2022

ABSTRACTBackgroundIntra-individual variability (IIV) during cognitive task performance is a key behavioral index of attention and consistent marker of ADHD. In adults, lower IIV has been associated with anticorrelation between the default mode network (DMN) and dorsal attention network (DAN) - thought to underlie effective allocation of attention. However, whether these behavioral and neural markers of attention are (i) associated with each other and (ii) can predict future attention-related deficits has not been examined in a developmental, population-based cohort.MethodsWe examined relationships at the baseline visit between IIV on three cognitive tasks, DMN-DAN anticorrelation, and parent-reported attention problems using the Adolescent Brain and Cognitive Development Study (n=11,878 participants, aged 9-10, female=47.8%). We also investigated whether behavioral and neural markers of attention at baseline predicted attention problems, 1, 2, and 3 years later.ResultsAt baseline, greater DMN-DAN anticorrelation was associated with lower IIV across all three cognitive tasks (unstandardized β: 0.22-0.25). Older age at baseline was associated with stronger DMN-DAN anticorrelation and lower IIV (β: -0.005--0.0004). Weaker DMN-DAN anticorrelation and IIV were cross-sectionally associated with attention problems (β: 1.41-7.63). Longitudinally, lower IIV at baseline was associated with less severe attention problems, 1-3 years later, after accounting for baseline attention problems (β: 0.288-0.77).ConclusionsThe results suggest that IIV in early adolescence is associated with worsening attention problems in a representative cohort of US youth. Attention deficits in early adolescence may be important for understanding and predicting future cognitive and clinical outcomes.
Large-scale capture of hidden fluorescent labels for training generalizable markerless motion capture models
Authors: Butler Daniel J. , Keim Alexander P. , Ray Shantanu , Azim Eiman 
Published: July 2022

AbstractRecent advances in deep learning-based markerless pose estimation have dramatically improved the scale and ease with which body landmarks can be tracked in studies of animal behavior. However, pose estimation for animals in a laboratory setting still faces some specific challenges. Researchers typically need to manually generate new training data for each experimental setup and visual environment, limiting the generalizability of this approach. With each network being trained from scratch, different investigators track distinct anatomical landmarks and analyze the resulting kinematic data in idiosyncratic ways. Moreover, much of the movement data is discarded: only a few sparse landmarks are typically labeled, due to the inherent scale and accuracy limits of manual annotation. To address these issues, we developed an approach, which we term GlowTrack, for generating large training datasets that overcome the relatively modest limits of manual labeling, enabling deep learning models that generalize across experimental contexts. The key innovations are: a) an automated, high-throughput approach for generating hidden labels free of human error using fluorescent markers; b) a multi-camera, multi-light setup for generating large amounts of training data under diverse visual conditions; and c) a technique for massively parallel tracking of hundreds of landmarks simultaneously using computer vision feature matching algorithms, providing dense coverage for kinematic analysis at a resolution not currently available. These advances yield versatile deep learning models that are trained at scale, laying the foundation for standardized behavioral pipelines and more complete scrutiny of animal movements.
Grapevine leaf size influences vine canopy temperature
Authors: Migicovsky Zoë , Swift Joel F. , Helget Zachary , Klein Laura L. , Ly Anh , Maimaitiyiming Matthew , Woodhouse Karoline , Fennell Anne , Kwasniewski Misha , Miller Allison J. , Chitwood Daniel H. , Cousins Peter 
Published: July 2022

AbstractPremiseGrapevine leaves have diverse shapes and sizes. Their shape and size is known to be influenced by many factors including genetics, vine phytosanitary status, environment, leaf and vine age, and node position on the shoot. In order to determine the importance of grapevine leaf shape and size to canopy temperature, we examined the relationship in five seedling populations grown in a vineyard in California, USA.MethodsAll of the populations had one parent with compound leaves of theVitis piasezkiitype and each population had a different second parent with non-compound leaves. In previous work, we measured leaf shape and size using 21 homologous landmarks. Here, we paired these morphology data with measurements taken using an infrared thermometer to measure the temperature of the canopy. By recording time of sampling and canopy temperature, we were able to determine which vines were cooler or hotter than expected, using a linear model.ResultsWe established a relationship between leaf size and canopy temperature: vines with larger leaves were cooler than expected. In contrast, leaf shape was not strongly correlated with variation in temperature.ConclusionsUltimately, these findings indicate that vines with larger leaves may contribute to the reduction of overall vine canopy temperature, but further work is needed to determine if this is due to variation in leaf size, differences in the openness of the canopy, or other related traits.
SNVformer: An Attention-based Deep Neural Network for GWAS Data
Authors: Elmes Kieran , Benavides-Prado Diana , Tan Neşet Özkan , Nguyen Trung Bao , Sumpter Nicholas , Leask Megan , Witbrock Michael , Gavryushkin Alex 
Published: July 2022

AbstractDespite being the widely-used gold standard for linking common genetic variations to phenotypes and disease, genome-wide association studies (GWAS) suffer major limitations, partially attributable to the reliance on simple, typically linear, models of genetic effects. More elaborate methods, such as epistasis-aware models, typically struggle with the scale of GWAS data. In this paper, we build on recent advances in neural networks employing Transformer-based architectures to enable such models at a large scale. As a first step towards replacing linear GWAS with a more expressive approximation, we demonstrate prediction of gout, a painful form of inflammatory arthritis arising when monosodium urate crystals form in the joints under high serum urate conditions, from Single Nucleotide Variants (SNVs) using a scalable (long input) variant of the Transformer architecture. Furthermore, we show that sparse SNVs can be efficiently used by these Transformer-based networks without expanding them to a full genome. By appropriately encoding SNVs, we are able to achieve competitive initial performance, with an AUROC of 83% when classifying a balanced test set using genotype and demographic information. Moreover, the confidence with which the network makes its prediction is a good indication of the prediction accuracy. Our results indicate a number of opportunities for extension, enabling full genome-scale data analysis using more complex and accurate genotype-phenotype association models.
Oscillatory mechanisms of intrinsic brain networks
Authors: Luo Youjing , Meng Xianghong , Zhou Guangyu , Zhou Jiali , Deng Guangzhi , Li Man , Xu Jie , Li Yiman , Luo Yue-jia , Ai Hui , Zelano Christina Maria , Chen Fuyong , Xu Pengfei 
Published: July 2022

AbstractNeuroimaging studies of hemodynamic fluctuations have shown specific network-based organization of the brain at rest, yet the neurophysiological underpinning of these networks in human brain remain unclear. Here, we recorded resting-state activities of neuronal populations in the key regions of default mode network (DMN, posterior cingulate cortex and medial prefrontal cortex), frontoparietal network (FPN, dorsolateral prefrontal cortex and inferior parietal lobule), and salience network (SN, anterior insula and dorsal anterior cingulate cortex) from 42 human participants using intracranial electroencephalogram (iEEG). We observed stronger within-network connectivity of the DMN, FPN and SN in broadband iEEG power, stronger phase synchronization within the DMN across theta and alpha bands, and weaker phase synchronization within the FPN in delta, theta and alpha band. We also found positive power correlations in high frequency band (70-170Hz) and negative power correlations in alpha and beta band for FPN-DMN and FPN-SN. Robust negative correlations in DMN-SN were found in alpha, beta and gamma band. These findings provide intracranial electrophysiological evidence in support of the network model for intrinsic organization of human brain and shed light on the way how the brain networks communicate at rest.
An integrated model for predicting KRAS dependency
Authors: Tsai Yihsuan S. , Chareddy Yogitha S. , Price Brandon A. , Parker Joel S. , Pecot Chad V. 
Published: July 2022

AbstractBackgroundThe clinical approvals of KRAS G12C inhibitors has been a revolutionary advance in precision oncology, but response rates are often modest. To improve patient selection, we developed an integrated model to predict KRAS dependency.Methods and FindingsBy integrating molecular profiles of a large panel of cell lines from the DEMETER2 dataset, we built a binary classifier to predict a tumor’s KRAS dependency. Monte Carlo cross validation via ElasticNet within the training set was used to compare model performance and to tune parameters. The final model was then applied to the validation set. We validated the model with genetic depletion assays and an external dataset of lung cancer cells treated with a G12C inhibitor. We then applied the model to several Cancer Genome Atlas (TCGA) datasets. The final “K20” model contains 20 features, including expression of 19 genes and KRAS mutation status. In the validation cohort, K20 had an AUC of 0.94 and accurately predicted KRAS dependency in both mutant and KRAS wild-type cell lines following genetic depletion. It was also highly predictive across an external dataset of lung cancer lines treated with KRAS G12C inhibition. When applied to TCGA datasets, specific subpopulations such as the invasive subtype in colorectal cancer and copy number high pancreatic adenocarcinoma were predicted to have higher KRAS dependency.ConclusionThe K20 model has simple yet robust predictive capabilities that may provide a useful tool to select patients with KRAS mutant tumors that are most likely to respond to direct KRAS inhibitors.
A community developed conceptual model for reducing long-term health problems in children with intellectual disability in India
Authors: Nair Manisha , Hazarika Mythili , Kishore M Thomas , Sengupta Nabarun , Sheregar Ganesh , MacGregor Hayley , Wickenden Mary , Kaushik Neel Harit , Saikia Prarthana , Kelley Maureen , Shepperd Sasha 
Published: July 2022

AbstractChildren with intellectual disability (ID) have a higher risk of long-term health problems in adulthood. India has the highest prevalence of ID of any country with 1.6 million under-five children living with the condition. Despite this, compared with other children, this neglected population is excluded from mainstream disease prevention and health promotion programmes. Our objective was to develop an evidence-based conceptual framework for a needs-based inclusive intervention to reduce the risk of communicable and non-communicable diseases among children with ID in India.From April through to July 2020 we undertook community engagement and involvement activities in ten States in India using a community-based participatory approach, guided by the bio-psycho-social model. We adapted the five steps recommended for the design and evaluation of a public participation process for the health sector.Seventy stakeholders from ten States contributed to the project: 44 parents and 26 professionals who work with people with ID. We mapped the outputs from two rounds of stakeholder consultations with evidence from systematic reviews to develop a conceptual framework that underpins an approach to develop a cross-sectoral family-centred needs-based inclusive intervention to improve health outcomes for children with ID. A working theory of change (ToC) model delineates a pathway that reflected the priorities of the target population. We discussed the models during a third round of consultations to identify limitations, relevance of the concepts, structural and social barriers that could influence acceptability and adherence, success criteria, and integration with existing health system and service delivery.There are currently no health promotion programmes focusing on children with ID in India despite the population being at a higher risk of developing comorbid health problems. Therefore, an urgent next step is to test the conceptual model to determine acceptance and effectiveness within the context of socio-economic challenges faced by the children and their families in the country.
The Burden of Gallstone Disease in the United States Population
Authors: Unalp-Arida Aynur , Ruhl Constance E. 
Published: July 2022

ABSTRACTBackground and rationaleGallstone disease is one of the most common digestive disorders in the United States and leads to significant morbidity, mortality, and health care utilization. We used national survey and claims databases to expand on earlier findings and investigate current trends in the gallstone disease burden in the United States.MethodsThe National Ambulatory Medical Care Survey, National Inpatient Sample, Nationwide Emergency Department Sample, Nationwide Ambulatory Surgery Sample, Vital Statistics of the U.S., Optum Clinformatics® Data Mart, and Centers for Medicare and Medicaid Services Medicare 5% Sample databases were used to estimate claims-based prevalence, medical care including cholecystectomy, and mortality with a primary or other gallstone diagnosis. Rates were age-adjusted (for national databases) and shown per 100,000 population.ResultsGallstone disease prevalence (claims-based, 2019) was 0.72% among commercial insurance enrollees and 2.09% among Medicare beneficiaries and rose over the previous decade in both groups. Recently, in the U.S. population, gallstone disease contributed to approximately 2.2 million ambulatory care visits, 1.2 million emergency department visits, 625,000 hospital discharges, and 2,000 deaths annually. Women had higher medical care rates with a gallstone disease diagnosis, but mortality rates were higher among men. Hispanics had higher ambulatory care visit and hospital discharge rates compared with Whites, but not mortality rates. Blacks had lower ambulatory care visit and mortality rates, but similar hospital discharge rates compared with whites. During the study period, ambulatory care and emergency department visit rates with a gallstone disease diagnosis rose, while hospital discharge and mortality rates declined. Among commercial insurance enrollees, rates were higher compared with national data for ambulatory care visits and hospitalizations, but lower for emergency department visits. Cholecystectomies performed in the U.S. included 605,000 ambulatory laparoscopic, 280,000 inpatient laparoscopic, and 49,000 inpatient open procedures annually. Among commercial insurance enrollees, rates were higher compared with national data for laparoscopic proceduresConclusionThe gallstone disease burden in the United States is substantial and increasing, particularly among women, Hispanics, and older adults with laparoscopic cholecystectomy as the mainstay treatment. Current practice patterns should be monitored for better health care access.
COVID-19 vaccine hesitancy in Australian patients with solid organ cancers
Authors: Bain N. , Nguyen M. , Grech L. , Day D. , McCartney A. , Webber K. , Kwok A. , Harris S. , Chau H. , Chan B. , Nott L. , Hamad N. , Tognela A. , Underhill C. , Loe B.S. , Freeman D. , Segelov E. 
Published: July 2022

AbstractBackgroundVaccination is the cornerstone of the global public health response to the COVID-19 pandemic. Excess morbidity and mortality of COVID-19 infection is seen in people with cancer. COVID-19 vaccine hesitancy has been observed in this medically vulnerable population, although associated attitudes and beliefs remain poorly understood.Patients and MethodsAn online cross-sectional survey of people with solid organ cancers was conducted through nine health services across Australia. Demographics, cancer-related characteristics, and vaccine uptake were collected. Perceptions and beliefs regarding COVID-19 vaccination were assessed using the Oxford COVID-19 Vaccine Hesitancy Scale, the Oxford COVID-19 Vaccine Confidence and Complacency Scale, and the Disease Influenced Vaccine Acceptance Scale-6.ResultsBetween June and October 2021, 2691 people with solid organ cancers completed the survey. Median age was 62.5 years (SD=11.8; range 19-95), 40.9% were male, 71.3% lived in metropolitan areas, and 90.3% spoke English as their first language. The commonest cancer diagnoses were breast (36.6%), genitourinary (18.6%) and gastrointestinal (18.3%); 59.2% had localized disease and 56.0% were receiving anti-cancer therapy. Most participants (79.7%) had at least one COVID-19 vaccine dose. Vaccine uptake was higher in people who were older, male, metropolitan, spoke English as a first language, and had a cancer diagnosis for more than six months. Vaccine hesitancy was higher in people who were younger, female, spoke English as a non-dominant language and lived in a regional location, and lower in people with genitourinary cancer. Vaccinated respondents were more concerned about being infected with COVID-19 and less concerned about vaccine safety and efficacy.ConclusionsPeople with cancer have concerns about acquiring COVID-19, which they balance against vaccine-related concerns about the potential impact on their disease progress and/or treatment. Detailed exploration of concerns in cancer patients provides valuable insights, both for discussions with individual patients and public health messaging for this vulnerable population.
A psychometric validation of the Hospital Anxiety and Depression Scale (HADS) in community-dwelling older adults
Authors: Sivertsen Heidi Emly , Helvik Anne-Sofie , Gjøra Linda , Haugan Gørill 
Published: July 2022

AbstractObjectivesThe Hospital Anxiety and Depression scale (HADS) is commonly used to measure anxiety and depression, but the number of studies validating psychometric properties in older adults are limited. To our knowledge, no previous studies have utilized confirmative factor analyses in community-dwelling older adults, regardless of health conditions. Thus, this study aimed to examine the psychometric properties of HADS in older adults living at home in a large Norwegian city.MethodsIn total, 1190 inhabitants ≥70 (range 70 – 96) years completed the HADS inventory in the population-based Trøndelag Health Study (HUNT); termed “HUNT4 70+” in Trondheim, Norway. Confirmatory factor analyses (CFA) were performed to test the dimensionality, reliability, and construct validity.ResultsThe original two-factor-solution (Model-1) revealed only partly a good fit to the present data; however, including a cross-loading for item 6D(“I feel cheerful”) along with a correlated error term between item 2D(“I still enjoy the things I used to enjoy”) and 12D(“I look forward with enjoyment to things”), Model-3 with a two-factor solution demonstrated an acceptable/good fit. Good to acceptable measurement reliability was demonstrated, and construct validity was supported.ConclusionsThe HADS involves some items which are not reliable and valid indicators for the depression construct in this population. Especially item 6 which is problematic. To improve the reliability and validity of HADS rewording of some items is recommended.
Does the size of termite mounds affect chances of fire survival? A study of two southern African mound-building termite (Termitidae) species
Authors: de la Fontaine B. , Edwards S. 
Published: July 2022

ABSTRACTThe effect of fire on insects is an under-researched area of ecology, especially in southern Africa. This study focusing on two termite species, Trinervitermes trinervoides and Amitermes sp., aims to determine whether fire survival in termites is related to mound size. 207 termite mounds were sampled across four sites on the periphery of a semi-urban area in Makhanda, South Africa. Each sampling site consisted of a pair of plots, either recently burnt (< 1 year or ~2 years since fire) or unburnt (> 2 years since fire). Mound type, dimensions, the presence of termites and termite species were recorded. Live mounds were significantly larger than dead mounds at both burnt and unburnt plots. For at least one termite species, there was a strong relationship between survivorship and size class of mounds at burnt plots but not at unburnt plots, suggesting that mound size plays a role in fire survival.