cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
JOP812095_supplemental_material – Supplemental material for Mouse, rat, and dog bioavailability and mouse oral antidepressant efficacy of (2R,6R)-hydroxynorketamine
Creators: name: Highland, Jaclyn N
name: Morris, Patrick J
name: Zanos, Panos
name: Lovett, Jacqueline
name: Soumita Ghosh
name: Wang, Amy Q
name: Zarate, Carlos A
name: Thomas, Craig J
name: Ruin Moaddel
name: Gould, Todd D
Publisher: name: SAGE Journals
Year: 2018
Subjects: subject: 110904 Neurology and Neuromuscular Diseases
subject: FOS: Clinical medicine
subject: 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified
subject: 170199 Psychology not elsewhere classified
subject: FOS: Psychology
subject: 110319 Psychiatry (incl. Psychotherapy)

description: Supplemental material, JOP812095_supplemental_material for Mouse, rat, and dog bioavailability and mouse oral antidepressant efficacy of (2R,6R)-hydroxynorketamine by Jaclyn N Highland, Patrick J Morris, Panos Zanos, Jacqueline Lovett, Soumita Ghosh, Amy Q Wang, Carlos A Zarate, Craig J Thomas, Ruin Moaddel and Todd D Gould in Journal of Psychopharmacology
Adolescents Living With or at Risk for HIV: A Pooled Descriptive Analysis of Studies From the Adolescent Medicine Trials Network for HIV/AIDS Interventions
Creators: name: Shook-Sa, Bonnie E
name: Muessig, Kathryn E
name: Hayati Rezvan, Panteha
name: Valencia, Rachel K
name: Arnold, Elizabeth M
name: Nielsen-Saines, Karin
name: Hightow-Weidman, Lisa B
name: Comulada, W Scott
name: Amico, K Rivet
name: DeMonte, Justin
name: Slye, Nicole
name: Sanchez, Travis H
name: McCumber, Micah
name: Swendeman, Dallas
name: Nichols, Sharon L
name: Hudgens, Michael G
Publisher: name: Elsevier
Year: 2023

description: PURPOSE: This study aims to describe the cohort of Adolescent Medicine Trials Network for HIV/AIDS Interventions (ATN) research program participants and evaluate whether the ATN's recently completed 5-year cycle recruited study participants who parallel the populations most impacted by HIV in the United States. METHODS: Harmonized measures across ATN studies collected at baseline were aggregated for participants aged 13-24 years. Pooled means and proportions stratified by HIV status (at risk for or living with HIV) were calculated using unweighted averages of study-specific aggregate data. Medians were estimated using a weighted median of medians method. Public use 2019 Centers for Disease Control and Prevention surveillance data for state-level new HIV diagnoses and HIV prevalence among US youth aged 13-24 years were obtained for use as reference populations for ATN at-risk youth and youth living with HIV (YLWH), respectively. RESULTS: Data from 3,185 youth at-risk for HIV and 542 YLWH were pooled from 21 ATN study phases conducted across the United States. Among ATN studies tailored to at-risk youth, a higher proportion of participants were White and a lower proportion were Black/African American and Hispanic/Latinx compared to youth newly diagnosed with HIV in the United States in 2019. Participants in ATN studies tailored to YLWH were demographically similar to YLWH in the United States. DISCUSSION: The development of data harmonization guidelines for ATN research activities facilitated this cross-network pooled analysis. These findings suggest the ATN's YLWH are representative, but that future studies of at-risk youth should prioritize recruitment strategies to enroll more participants from African American and Hispanic/Latinx populations.
Supplementary_Material,_Table_A – Supplemental material for Human occupation strategies and related environmental-climate during the middle and late Holocene in central Pampas of Argentina
Creators: name: Messineo, Pablo G
name: Tonello, Marcela S
name: Stutz, Silvina
name: Tripaldi, Alfonsina
name: Nahuel Scheifler
name: Pal, Nélida
name: Guillermina Sánchez Vuichard
name: Navarro, Diego
Publisher: name: SAGE Journals
Year: 2018
Subjects: Geography
History

description: Supplemental material, Supplementary_Material,_Table_A for Human occupation strategies and related environmental-climate during the middle and late Holocene in central Pampas of Argentina by Pablo G Messineo, Marcela S Tonello, Silvina Stutz, Alfonsina Tripaldi, Nahuel Scheifler, Nélida Pal, Guillermina Sánchez Vuichard and Diego Navarro in The Holocene
Supplementary_Material,_Table_B – Supplemental material for Human occupation strategies and related environmental-climate during the middle and late Holocene in central Pampas of Argentina
Creators: name: Messineo, Pablo G
name: Tonello, Marcela S
name: Stutz, Silvina
name: Tripaldi, Alfonsina
name: Nahuel Scheifler
name: Pal, Nélida
name: Guillermina Sánchez Vuichard
name: Navarro, Diego
Publisher: name: SAGE Journals
Year: 2018
Subjects: Geography
History

description: Supplemental material, Supplementary_Material,_Table_B for Human occupation strategies and related environmental-climate during the middle and late Holocene in central Pampas of Argentina by Pablo G Messineo, Marcela S Tonello, Silvina Stutz, Alfonsina Tripaldi, Nahuel Scheifler, Nélida Pal, Guillermina Sánchez Vuichard and Diego Navarro in The Holocene
Adversarial learning for mono- or multi-modal registration
Creators: name: Cao, Xiaohuan
name: Shen, Dinggang
name: Yap, Pew-Thian
name: Fan, Jingfan
name: Wang, Qian
Publisher: name: Elsevier
Year: 2019

description: This paper introduces an unsupervised adversarial similarity network for image registration. Unlike existing deep learning registration methods, our approach can train a deformable registration network without the need of ground-truth deformations and specific similarity metrics. We connect a registration network and a discrimination network with a deformable transformation layer. The registration network is trained with the feedback from the discrimination network, which is designed to judge whether a pair of registered images are sufficiently similar. Using adversarial training, the registration network is trained to predict deformations that are accurate enough to fool the discrimination network. The proposed method is thus a general registration framework, which can be applied for both mono-modal and multi-modal image registration. Experiments on four brain MRI datasets and a multi-modal pelvic image dataset indicate that our method yields promising registration performance in accuracy, efficiency and generalizability compared with state-of-the-art registration methods, including those based on deep learning.
An automated framework for image classification and segmentation of fetal ultrasound images for gestational age estimation
Creators: name: Stringer, Elizabeth M
name: Vwalika, Bellington
name: Jiang, Xiaoning
name: Stamilio, David M
name: Stringer, Jeffrey S A
name: Rosenbaum, Alan J
name: Prieto, Juan C
name: Shah, Hina
name: Musonda, Patrick
name: Price, Joan T
Publisher: name: SPIE, the international society for optics and photonics
Year: 2021

description: Accurate assessment of fetal gestational age (GA) is critical to the clinical management of pregnancy. Industrialized countries rely upon obstetric ultrasound (US) to make this estimate. In low- and middle- income countries, automatic measurement of fetal structures using a low-cost obstetric US may assist in establishing GA without the need for skilled sonographers. In this report, we leverage a large database of obstetric US images acquired, stored and annotated by expert sonographers to train algorithms to classify, segment, and measure several fetal structures: biparietal diameter (BPD), head circumference (HC), crown rump length (CRL), abdominal circumference (AC), and femur length (FL). We present a technique for generating raw images suitable for model training by removing caliper and text annotation and describe a fully automated pipeline for image classification, segmentation, and structure measurement to estimate the GA. The resulting framework achieves an average accuracy of 93% in classification tasks, a mean Intersection over Union accuracy of 0.91 during segmentation tasks, and a mean measurement error of 1.89 centimeters, finally leading to a 1.4 day mean average error in the predicted GA compared to expert sonographer GA estimate using the Hadlock equation.
An Electronic Pre-Exposure Prophylaxis Initiation and Maintenance Home Care System for Nonurban Young Men Who Have Sex With Men: Protocol for a Randomized Controlled Trial
Creators: name: Brock, James B
name: Ahlschlager, Lauren
name: Hurt, Christopher B
name: Jameson, Samuel B
name: Wilde, Gretchen
name: Dominguez, Karen
name: Kelley, Colleen F
name: Bailey-Herring, Gina
name: Mena, Leandro A
name: Jenness, Samuel M
name: Siegler, Aaron J
Publisher: name: JMIR Publications
Year: 2019

description: BACKGROUND: Pre-exposure prophylaxis (PrEP) is highly efficacious for preventing HIV but has not yet been brought to scale among at-risk persons. In several clinical trials in urban areas, technology-based interventions have shown a positive impact on PrEP adherence. In rural and small-town areas in the United States, which often do not have geographically proximal access to PrEP providers, additional support may be needed. This may be particularly true for younger persons who are more likely to face multiple barriers to accessing PrEP services. Home-based care, accomplished through a tailored mobile phone app, specimen self-collection (SSC), and interactive video consultations, could increase both PrEP initiation and persistence in care. OBJECTIVE: The goal of this study is to assess the initiation and persistence in PrEP care for those randomized to a home-care intervention (electronic PrEP, ePrEP) relative to those assigned to the standard of care (control) condition. We will conduct additional assessments, including quantitative and qualitative analyses, to contextualize trial results and facilitate scale-up. METHODS: This 2-arm, randomized controlled trial will enroll young men who have sex with men (YMSM) aged between 18 and 24 years from rural areas of Georgia, Mississippi, and North Carolina. The trial will seek to recruit a diverse sample, targeting 50% participation among highly impacted groups of black or Latino men who have sex with men. Intervention participants will receive a study app that incorporates a messaging platform, a scheduling and milestone-based tracking system for PrEP care progress, electronic behavioral surveys, and interactive video consultations with a clinician. Complemented by SSC kits mailed to laboratories for standard PrEP-related monitoring, the ePrEP system will allow participants to access PrEP care without leaving their homes. YMSM randomized to the control condition will receive a listing of nearest local PrEP providers to receive standard PrEP care. Both groups will complete quarterly electronic surveys. The primary outcome, assessed at 6 and 12 months after randomization, will be the difference in the proportion of intervention versus control participants that achieve protective levels of the active metabolite of oral PrEP (tenofovir diphosphate in dried blood spots). RESULTS: Enrollment will begin in May 2019, with study completion in 2022. CONCLUSIONS: This trial will determine whether home PrEP care provided through an app-based platform is an efficacious means of expanding access to PrEP care for a diverse group of YMSM in rural and small-town areas of the United States.
Additional file 1 of ThASR3 confers salt and osmotic stress tolerances in transgenic Tamarix and Arabidopsis
Creators: name: Zhang, Yu
name: Ma, Huijun
name: Zhou, Tianchang
name: Zhu, Zhenyu
name: Zhang, Yue
name: Zhao, Xin
name: Wang, Chao
Publisher: name: figshare
Year: 2024
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Plant Biology

description: Additional file 1. Supplemental data.
An Employment Intervention Program (Work2Prevent) for Young Men Who Have Sex With Men and Transgender Youth of Color (Phase 2): Protocol for a Single-Arm Mixed Methods Pilot Test to Assess Feasibility and Acceptability
Creators: name: Reisner, Sari
name: VandeVusse, Alicia
name: McCumber, Micah
name: Sanchez, Maria
name: Loop, Matthew Shane
name: Schneider, John A
name: Rupp, Betty M
name: Hill, Brandon J
name: Renshaw, Laura
name: Kuhns, Lisa M
name: Motley, Darnell N
name: Rosentel, Kris
name: Garofalo, Robert
name: Kipke, Michele D
name: Goolsby, Rachel West
Publisher: name: JMIR Publications
Year: 2020

description: BACKGROUND: Young cisgender men who have sex with men (YMSM), young transgender women (YTW), and gender nonconforming (GNC) youth of color face substantial economic and health disparities. In particular, HIV risk and infection among these groups remains a significant public health issue. In 2017, 17% of all new HIV diagnoses were attributed to male-to-male sexual contact among adolescents and young adults aged 13 to 24 years. However, such disparities cannot be attributed to individual-level factors alone but rather are situated within larger social and structural contexts that marginalize and predispose YMSM, YTW, and GNC youth of color to increased HIV exposure. Addressing social and structural risk factors requires intervention on distal drivers of HIV risk, including employment and economic stability. The Work2Prevent (W2P) study aims to target economic stability through job readiness and employment as a structural-level intervention for preventing adolescent and young adult HIV among black and Latinx YMSM, YTW, and GNC youth. This study seeks to assess intervention feasibility and acceptability in the target populations and determine preliminary efficacy of the intervention to increase employment and reduce sexual risk behaviors. OBJECTIVE: The goal of the research is to pilot-test a tailored, theoretically informed employment intervention program among YMSM, YTW, and GNC youth of color. This intervention was adapted from Increased Individual Income and Independence, an existing evidence-based employment program for HIV-positive adults during phase 1 of the W2P study. METHODS: The employment intervention will be pilot-tested among vulnerable YMSM, YTW, and GNC youth of color in a single-arm pre-post trial to assess feasibility, acceptability, and preliminary estimates of efficacy. RESULTS: Research activities began in March 2018 and were completed in November 2019. Overall, 5 participants were enrolled in the pretest and 51 participants were enrolled in the pilot. CONCLUSIONS: Interventions that address the social and structural drivers of HIV exposure and infection are sorely needed in order to successfully bend the curve in the adolescent and young adult HIV epidemic. Employment as prevention has the potential to be a scalable intervention that can be deployed among this group.
An Exploratory Case-Control Study on the Associations of Bacterially-Derived Vitamin K Forms with the Intestinal Microbiome and Obesity-Related Osteoarthritis
Creators: name: Azcarate-Peril, M Andrea
name: Shea, M Kyla
name: Liu, Minying
name: Loeser, Richard F
name: Matuszek, Gregory
Publisher: name: Elsevier
Year: 2023

description: Background: Evidence suggests that natural metabolites produced by intestinal microorganisms may have beneficial or harmful effects on osteoarthritis (OA). This could include menaquinones, which are bacterially-synthesized, biologically-active vitamin K forms abundant in the intestinal microbiome. Objectives: The overall goal of this study was to evaluate the association of intestinally-derived menaquinones with obesity-related OA. Methods: This case-control study used data and biospecimens derived from a subgroup of Johnston County Osteoarthritis Study participants. Fecal menaquinone concentrations and microbial composition were determined in 52 obese participants with hand and knee OA and 42 age- and sex-matched obese participants without OA. The inter-relationships among fecal menaquinones were evaluated using principal component analysis. The differences in alpha and beta diversities and microbial composition across menaquinone clusters were evaluated using ANOVA. Results: The samples were clustered into the following 3 groups: cluster 1 characterized by higher fecal menaquinone-9 and -10 concentrations, cluster 2 characterized by lower overall menaquinone concentrations, and cluster 3 characterized by higher menaquinone-12 and -13 concentrations. Overall, fecal menaquinone clusters did not differ between participants with or without OA (P = 0.707). Microbial diversity did not differ across the fecal menaquinone clusters (all F-test P > 0.12). However, the relative abundance of bacterial taxa differed among clusters, with higher abundance of Coprococcus, Prevotella, and Eggerthella in cluster 2 than in cluster 1; higher abundance of Oscillospira, Dorea, Eubacterium, and Bacteroides in cluster 3 than in cluster 1; and higher abundance of Prevotella, Sutterella, and Dorea in cluster 3 than in cluster 2 (all P < 0.001). Conclusion: Menaquinones were variable and abundant in the human gut, but the fecal menaquinone clusters did not differ with OA status. Although the relative abundance of specific bacterial taxa differed among fecal menaquinone clusters, the relevance of these differences with respect to vitamin K status and human health is uncertain.
Dynamic Brain Function Tracking During Cognitive Tasks in Extreme Environments Using fNIRS
Creators: name: Bu, Lingguo
name: Zou, Tan
name: Zhang, Yulin
name: Qu, Jing
name: Lu, Zhengyi
name: Zhang, Yuqian
name: Li, Si
name: Wang, Xin
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Space Science
subject: Medicine
subject: Neuroscience
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Mental Health

description: In special environments such as isolated, confined, and extreme (ICE) spaces, optimizing the human-computer interaction (HCI) experience and accurately assessing the cognitive state of users is important. In this study, portable functional near-infrared spectroscopy (fNIRS) was used to monitor the changes in users’ brain activities while they performed three cognitive tasks: Stroop, Vigilance, and Reverse. The study aimed to evaluate the effects of different tasks on users’ cognitive load and provide a basis for the design optimization of HCI systems in special environments. The results demonstrate that regional brain activation shows the greatest feature importance between resting and task states, reflecting the users’ cognitive processing, while functional connectivity networks show higher stability across tasks and play a key role in state recognition. This discovery lays the groundwork for developing intelligent systems capable of real-time sensing and optimizing interactions, guiding the optimization of HCI systems in special environments.
Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis
Creators: name: Liu, Mingxia
name: Yap, Pew-Thian
name: Zhang, Jun
name: Nie, Dong
name: Shen, Dinggang
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2018

description: Most automated techniques for brain disease diagnosis utilize hand-crafted (e.g., voxel-based or region-based) biomarkers from structural magnetic resonance (MR) images as feature representations. However, these hand-crafted features are usually high-dimensional or require regions-of-interest defined by experts. Also, because of possibly heterogeneous property between the hand-crafted features and the subsequent model, existing methods may lead to sub-optimal performances in brain disease diagnosis. In this paper, we propose a landmark-based deep feature learning (LDFL) framework to automatically extract patch-based representation from MRI for automatic diagnosis of Alzheimer's disease. We first identify discriminative anatomical landmarks from MR images in a data-driven manner, and then propose a convolutional neural network for patch-based deep feature learning. We have evaluated the proposed method on subjects from three public datasets, including the Alzheimer's disease neuroimaging initiative (ADNI-1), ADNI-2, and the minimal interval resonance imaging in alzheimer's disease (MIRIAD) dataset. Experimental results of both tasks of brain disease classification and MR image retrieval demonstrate that the proposed LDFL method improves the performance of disease classification and MR image retrieval.
Appendix – Supplemental material for Answering Questions About Race: How Racial and Ethnic Identities Influence Survey Response
Creators: name: Abrajano, Marisa
name: R. Michael Alvarez
Publisher: name: SAGE Journals
Year: 2018
Subjects: subject: 160607 International Relations
subject: FOS: Political science

description: Supplemental material, Appendix for Answering Questions About Race: How Racial and Ethnic Identities Influence Survey Response by Marisa Abrajano and R. Michael Alvarez in American Politics Research
Anxiety and Depression Correlates at Age 10 in Children Born Extremely Preterm
Creators: name: Douglass, Laurie M
name: Santos, Hudson P
name: Dvir, Yael
name: Frazier, Jean A
name: Moore, Phoebe S
name: Mokrova, Irina
name: O'Shea, T Michael
name: Kuban, Karl C K
name: Joseph, Robert M
name: Hooper, Stephen R
Publisher: name: Oxford University Press (OUP)
Year: 2021

description: Objective:Anxiety and depression rates are known to be elevated in prematurely-born children and adolescents. This prospective study examines demographic, academic, and physical health correlates of anxiety and depression symptoms in a sample of 10-year-old children who were born extremely preterm. Methods:Participants were 889 (51.2% male; 62.3% White) children who were born <28weeks gestation. Child and family demographic data were collected at birth. When the children were 10, parents (n=871) and teachers (n=640) rated the level of anxiety and depression in children through the Child Symptom Inventory-4. Child academic functioning was assessed via the Wechsler Individual Achievement Test-III. Parents completed questionnaires about child academic functioning and physical health issues. Data analyses were conducted with multivariate linear modeling. Results:Level of prematurity was significantly related to both parent and teacher reports of anxiety. Public health insurance and individualized education program (IEP) status were associated with both parent and teacher reports of depression. Hispanic ethnicity, public insurance, IEP status, and asthma were significantly associated with both parent-reported anxiety and depression. Gross motor impairment was associated with parent-reported anxiety and teacher-reported depression. Child obesity was associated with teacher reports of anxiety, while male sex was significantly related to teacher reports of depression. Conclusion:This pattern of findings may suggest hypotheses for future research on models of the development and persistence of anxiety and depression within this particularly vulnerable group of children.
Are Extremely Low Gestational Age Newborns Born to Obese Women at Increased Risk of Cerebral Palsy at 2 Years?
Creators: name: van der Burg, Jelske W.
name: Leviton, Alan
name: Dammann, Olaf
name: Paneth, Nigel
name: Allred, Elizabeth N.
name: Kuban, Karl
name: O'Shea, T. Michael
Publisher: name: SAGE Publications
Year: 2018

description: The authors hypothesized that the risk of cerebral palsy at 2 years in children born extremely preterm to overweight and obese women is increased relative to the risk among children born to neither overweight nor obese women. In a multicenter prospective cohort study, the authors created multinomial logistic regression models of the risk of diparetic, quadriparetic, and hemiparetic cerebral palsy that included the prepregnancy body mass index of mothers of 1014 children born extremely preterm, cerebral palsy diagnoses of children at 2 years, as well as information about potential confounders. Overweight and obese women were not at increased risk of giving birth to a child who had cerebral palsy. The risk ratios associated with overweight varied between 1.1 for quadriparesis (95% CI = 0.5, 2.1) to 2.0 for hemiparesis (95% CI = 0.4, 9.8). The risk ratios associated with obesity varied between 0.7 for diparesis (95% CI = 0.2, 2.5) to 2.5 for hemiparesis (95% CI = 0.4, 13).
Assessing the Robustness of Cluster Solutions Obtained From Sparse Count Matrices
Creators: name: Gates, Kathleen M.
name: Arizmendi, Cara
name: Henry, Teague R.
name: Fisher, Zachary F.
name: Duffy, Kelly A.
name: Mucha, Peter J.
Publisher: name: American Psychological Association (APA)
Year: 2019

description: Psychological researchers often seek to obtain cluster solutions from sparse count matrices (e.g., social networks; counts of symptoms that are in common for 2 given individuals; structural brain imaging). Increasingly, community detection methods are being used to subset the data in a data-driven manner. While many of these approaches perform well in simulation studies and thus offer some improvement upon traditional clustering approaches, there is no readily available approach for evaluating the robustness of these solutions in empirical data. Researchers have no way of knowing if their results are due to noise. We describe here 2 approaches novel to the field of psychology that enable evaluation of cluster solution robustness. This tutorial also explains the use of an associated R package, perturbR, which provides researchers with the ability to use the methods described herein. In the first approach, the cluster assignment from the original matrix is compared against cluster assignments obtained by randomly perturbing the edges in the matrix. Stable cluster solutions should not demonstrate large changes in the presence of small perturbations. For the second approach, Monte Carlo simulations of random matrices that have the same properties as the original matrix are generated. The distribution of quality scores ("modularity") obtained from the cluster solutions from these matrices are then compared with the score obtained from the original matrix results. From this, one can assess if the results are better than what would be expected by chance. perturbR automates these 2 methods, providing an easy-to-use resource for psychological researchers. We demonstrate the utility of this package using benchmark simulated data generated from a previous study and then apply the methods to publicly available empirical data obtained from social networks and structural neuroimaging.
DESIGN OF A FIELD-PROGRAMMABLE GATE ARRAY PLATFORM FOR ANIMAL VOCALIZATION CLASSIFICATION UTILIZING A CONVOLUTIONAL NEURAL NETWORK
Creators: name: Wacyk, Nicolas George
Publisher: name: Purdue University Graduate School
Year: 2025
Subjects: classificationCode: 400902
subject: Digital electronic devices
classificationCode: 400904
subject: Electronic device and system performance evaluation, testing and simulation
classificationCode: 400906
subject: Electronic sensors
classificationCode: 400802
subject: Electrical circuits and systems
classificationCode: 461104
subject: Neural networks
classificationCode: 461199
subject: Machine learning not elsewhere classified
classificationCode: 300306
subject: Animal welfare

description: Studies such as Manteuffel et al., (2004) and Laurjis et al., (2021) have established links between animal vocalizations and their wellbeing, including emotional states and respiratory illness. Zhao et al., (2016) have proven Field-Programmable Gate Arrays (FPGAs) to have a higher computational speed than CPU based system (four times faster), and a greater energy efficiency than GPU based systems (7.5 times reduction in power consumption) for Convolutional Neural Network (CNN) applications. The purpose of this study is to investigate the ability to implement an animal vocalization classification CNN on a custom wearable, low power (up to 123 mW), FPGA system. Specifically, this study focuses on the design of the custom hardware, and the identification of vocalizations originating from animals with respiratory illness. The CNN was trained on a dataset of one-second-long recordings of healthy and sick chickens, with the goal of detecting vocalizations from sick chickens. The performance of the vocalization CNN was evaluated on both CPU based and FPGA based systems. The testing accuracy of the CNN on a CPU system was 92.4%. The accuracy on a commercially available FPGA system was 84.2%, with a recall of 96.7% and a precision of 78.7%. The custom FPGA board was unable to successfully detect any vocalizations. The power consumption of the FPGA based systems were significantly reduced from the CPU based system; ~8mW for the FPGA systems, compared to ~95W for the CPU system (Intel, 2018).
Association of Foot Symptoms With Decreased Time to All-Cause Mortality: The Johnston County Osteoarthritis Project
Creators: name: Alvarez, Carolina
name: Harmon, Skylar
name: Golightly, Yvonne M.
name: Callahan, Leigh F.
name: Nelson, Amanda E.
name: Hannan, Marian T.
name: Gates, Lucy S.
name: Bowen, Catherine J.
name: Menz, Hylton B.
Publisher: name: Wiley
Year: 2023

description: OBJECTIVE: Adults with foot symptoms (ie, pain, aching, or stiffness) may be at increased risk of reduced time to all-cause mortality. The purpose of this study was to evaluate whether foot symptoms are independently associated with all-cause mortality in older adults. METHODS: We analyzed longitudinal data from 2613 participants from the Johnston County Osteoarthritis Project, a longitudinal population-based cohort of adults 45years of age and older. Participants completed questionnaires at baseline to determine presence of foot symptoms and covariable status. Baseline walking speed was measured via an 8-foot walk test. To examine the association of foot symptoms with time to mortality, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox regression models, adjusted for potential confounders. RESULTS: We observed 813 deaths over 4 to 14.5years of follow-up. At baseline, 37% of participants had foot symptoms, mean age was 63years, mean body mass index was approximately 31 kg/m2 , 65% were women, and 33% were Black. Moderate to severe foot symptoms were associated with reduced time to mortality after adjustment for demographics, comorbidities, physical activity, and knee and hip symptoms (HR = 1.30, 95% CI 1.09-1.54). Importantly, this association was not modified by walking speed or diabetes. CONCLUSION: Individuals with foot symptoms had an increased hazard of all-cause mortality compared with those with no foot symptoms. These effects were independent of key confounders and were not moderated by walking speed. Effective interventions to identify and manage at least moderate foot symptoms may reduce the risk of decreased time to mortality.
Supplemental material for Beta regression in the presence of outliers – A wieldy Bayesian solution
Creators: name: Niekerk, Janet Van
name: Andriette Bekker
name: Arashi, Mohammad
Publisher: name: SAGE Journals
Year: 2018
Subjects: subject: 111708 Health and Community Services
subject: FOS: Health sciences
subject: 111099 Nursing not elsewhere classified
subject: 160807 Sociological Methodology and Research Methods
subject: FOS: Sociology

description: Supplementary Material for Beta regression in the presence of outliers – A wieldy Bayesian solution by Janet van Niekerk, Andriette Bekker and Mohammad Arashi in Statistical Methods in Medical Research
Association of Increased Serum Lipopolysaccharide, But Not Microbial Dysbiosis, With Obesity-Related Osteoarthritis
Creators: name: Jordan, Joanne M.
name: Renner, Jordan B.
name: Sumner, Susan J.
name: Loeser, Richard F.
name: Kelley, Kathryn
name: Nelson, Amanda E.
name: Arbeeva, Liubov
name: Ulici, Veronica
name: Longobardi, Lara
name: Azcarate-Peril, M. Andrea
name: Sun, Shan
name: Fodor, Anthony A.
name: Stewart, Delisha A.
name: Cui, Yang
name: Carroll, Ian M.
name: Sartor, R. Balfour
Publisher: name: Wiley
Year: 2022

description: OBJECTIVE: To test the hypothesis that an altered gut microbiota (dysbiosis) plays a role in obesity-associated osteoarthritis (OA). METHODS: Stool and blood samples were collected from 92 participants with a body mass index (BMI) ≥30 kg/m2 , recruited from the Johnston County Osteoarthritis Project. OA patients (n=50) had hand and knee OA (Kellgren/Lawrence [K/L] grade≥2 or arthroplasty). Controls (n=42) had no hand OA and a K/L grade of 0-1 for the knees. Compositional analysis of stool samples was carried out by 16S ribosomal RNA amplicon sequencing. Alpha- and beta-diversity and differences in taxa relative abundances were determined. Blood samples were used for multiplex cytokine analysis and measures of lipopolysaccharide (LPS) and LPS binding protein. Germ-free mice were gavaged with patient- or control-pooled fecal samples and fed a 40% fat, high-sucrose diet for 40weeks. Knee OA was evaluated histologically. RESULTS: On average, OA patients were slightly older than the controls, consisted of more women, and had a higher mean BMI, higher mean Western Ontario and McMaster Universities Osteoarthritis Index pain score, and higher mean K/L grade. There were no significant differences in alpha or beta-diversity or genus level composition between patients and controls. Patients had higher plasma levels of osteopontin (P=0.01) and serum LPS (P<0.0001) compared to controls. Mice transplanted with patient or control microbiota exhibited a significant difference in alpha diversity (P=0.02) and beta diversity, but no differences in OA severity were observed. CONCLUSION: The lack of differences in the gut microbiota, but increased serum LPS levels, suggest the possibility that increased intestinal permeability allowing for greater absorption of LPS, rather than a dysbiotic microbiota, may contribute to the development of OA associated with obesity.
Associations between the chemokine biomarker CCL2 and knee osteoarthritis outcomes: the Johnston County Osteoarthritis Project
Creators: name: Shi, X.A.
name: Renner, J.B.
name: Schwartz, T.A.
name: Longobardi, L.
name: Barrow, D.A.
name: Nelson, A.E.
name: Jordan, J.M.
name: Kraus, V.B.
name: Spagnoli, A.
Publisher: name: Elsevier
Year: 2018

description: OBJECTIVE: Our study analyzes the association between chemokine-ligand-2 (CCL2) serum concentrations at baseline and knee radiographic osteoarthritis (OA) (knee-rOA), knee-rOA progression, individual radiographic features and knee symptomatic OA at 5-year follow-up. DESIGN: OA outcomes were analyzed in a community-based cohort including a baseline enrollment and a 5-year follow-up. Baseline CCL2 serum concentrations were assessed by multiplex assay and associated with presence or progression of individual radiographic features at 5-year follow-up. Separate multiple logistic regression models were used to examine adjusted associations between baseline CCL2 and each of the knee OA variables at follow-up. CCL2 at baseline was modeled as an explanatory variable, whereas each of the knee OA variables at follow-up served as the response variables. Models were adjusted for age, BMI, race, and sex. Trend tests were conducted to assess any linear effect on outcomes across CCL2 tertiles. RESULTS: Participants (n = 168) had a median age of 57-years and median BMI of 29 kg/m2. About 63% of all participants were women, and 58% Caucasian (42% African American). In adjusted logistic models, continuous log-CCL2 was significantly associated with knee-rOA. For each unit increase in log CCL2, the odds of having knee-rOA at follow-up was increased by 72%. CCL2 tertiles showed significant linear associations with presence and progression of knee-rOA and medial joint space narrowing (JSN), but not with presence or progression of osteophytes, bone sclerosis, knee symptoms, or symptomatic knee-rOA. CONCLUSIONS: Serum CCL2 may help to elucidate some mechanisms of joint destruction and identify individuals with higher odds of structural knee changes.
Attention-Guided Hybrid Network for Dementia Diagnosis With Structural MR Images
Creators: name: Liu, Mingxia
name: Pan, Yongsheng
name: Shen, Dinggang
name: Lian, Chunfeng
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2022

description: Deep-learning methods (especially convolutional neural networks) using structural magnetic resonance imaging (sMRI) data have been successfully applied to computer-aided diagnosis (CAD) of Alzheimer's disease (AD) and its prodromal stage [i.e., mild cognitive impairment (MCI)]. As it is practically challenging to capture local and subtle disease-associated abnormalities directly from the whole-brain sMRI, most of those deep-learning approaches empirically preselect disease-associated sMRI brain regions for model construction. Considering that such isolated selection of potentially informative brain locations might be suboptimal, very few methods have been proposed to perform disease-associated discriminative region localization and disease diagnosis in a unified deep-learning framework. However, those methods based on task-oriented discriminative localization still suffer from two common limitations, that is: 1) identified brain locations are strictly consistent across all subjects, which ignores the unique anatomical characteristics of each brain and 2) only limited local regions/patches are used for model training, which does not fully utilize the global structural information provided by the whole-brain sMRI. In this article, we propose an attention-guided deep-learning framework to extract multilevel discriminative sMRI features for dementia diagnosis. Specifically, we first design a backbone fully convolutional network to automatically localize the discriminative brain regions in a weakly supervised manner. Using the identified disease-related regions as spatial attention guidance, we further develop a hybrid network to jointly learn and fuse multilevel sMRI features for CAD model construction. Our proposed method was evaluated on three public datasets (i.e., ADNI-1, ADNI-2, and AIBL), showing superior performance compared with several state-of-the-art methods in both tasks of AD diagnosis and MCI conversion prediction.
Supplementary_table_1_xyz10787872bd34a – Supplemental material for Climate and Soil Properties Influence Species Diversity of Soil Bacillus Community in India
Creators: name: Girish R Nair
name: Raja, Suresh SS
Publisher: name: SAGE Journals
Year: 2018
Subjects: subject: 69999 Biological Sciences not elsewhere classified
subject: FOS: Biological sciences

description: Supplemental material, Supplementary_table_1_xyz10787872bd34a for Climate and Soil Properties Influence Species Diversity of Soil Bacillus Community in India by Girish R Nair and Suresh SS Raja in Microbiology Insights
Supplemental Material, DS_10.11770706743718809347 - Access and Health System Impact of an Early Intervention Treatment Program for Emerging Adults with Mood and Anxiety Disorders
Creators: name: Anderson, Kelly K.
name: John-Baptiste, Ava
name: MacDougall, Arlene G.
name: Li, Lihua
name: Kurdyak, Paul
name: Osuch, Elizabeth A.
Publisher: name: SAGE Journals
Year: 2018
Subjects: Psychology not elsewhere classified
Psychiatry (incl. Psychotherapy)

description: Supplemental Material, DS_10.11770706743718809347 for Access and Health System Impact of an Early Intervention Treatment Program for Emerging Adults with Mood and Anxiety Disorders by Kelly K. Anderson, Ava John-Baptiste, Arlene G. MacDougall, Lihua Li, Paul Kurdyak, and Elizabeth A. Osuch in The Canadian Journal of Psychiatry
A low-latency feedback system for the control of horizontal betatron oscillations
Creators: name: Scomparin, Luca
name: Blomley, Edmund
name: Bründermann, Erik
name: Caselle, Michele
name: Kopmann, Andreas
name: Mueller, Anke-Susanne
name: Santamaria Garcia, Andrea
name: Steinmann, Johannes
name: Weber, Marc
name: Assmann, Ralph
name: McIntosh, Peter
name: Fabris, Alessandro
name: Bisoffi, Giovanni
name: Andrian, Ivan
name: Vinicola, Giulia
Publisher: name: JACoW Publishing
Year: 2023
Subjects: Accelerator Physics
mc6-beam-instrumentation-controls-feedback-and-operational-aspects - MC6: Beam Instrumentation
Controls
Feedback and Operational Aspects
mc6-a27-machine-learning-and-digital-twin-modelling - MC6.A27: Machine Learning and Digital Twin Modelling

description: Reinforcement learning (RL) algorithms are investigated at KIT as an option to control the beam dynamics at storage rings.
These methods require specialized hardware to satisfy throughput and latency constraints dictated by the timescale of the relevant phenomena.

The KINGFISHER platform, based on the novel Xilinx Versal Adaptive Compute and Acceleration Platform, is an ideal candidate to deploy RL-on-a-chip thanks to its ability to execute computationally intensive and low latency feedback loops in the order of tens of microseconds. 
In this publication, we will present the integration of the KINGFISHER system at the Karlsruhe Research Accelerator (KARA), as a proof-of-principle turn-by-turn control feedback loop, to control induced transversal oscillations of an electron beam.
Whitney_et_al_Supplementary_figures_R1 – Supplemental material for Constraining pollen-based estimates of forest cover in the Amazon: A simulation approach
Creators: name: Whitney, Bronwen S
name: T Luke Smallman
name: Mitchard, Edward TA
name: Carson, John F
name: Mayle, Francis E
name: M Jane Bunting
Publisher: name: SAGE Journals
Year: 2018
Subjects: Geography
History

description: Supplemental material, Whitney_et_al_Supplementary_figures_R1 for Constraining pollen-based estimates of forest cover in the Amazon: A simulation approach by Bronwen S Whitney, T Luke Smallman, Edward TA Mitchard, John F Carson, Francis E Mayle and M Jane Bunting in The Holocene
Autophagy regulates the localization and degradation of p16INK4a
Creators: name: Redick, Margaret A.
name: Purvis, Jeremy E.
name: Coryell, Philip R.
name: Sisk, Samuel R.
name: Goraya, Supreet K.
name: Griffin, Katherine A.
Publisher: name: Wiley
Year: 2020

description: The tumor suppressor protein p16INK4a (p16) is a well-established hallmark of aging that induces cellular senescence in response to stress. Previous studies have focused primarily on p16 regulation at the transcriptional level; comparatively little is known about the protein's intracellular localization and degradation. The autophagy-lysosomal pathway has been implicated in the subcellular trafficking and turnover of various stress-response proteins and has also been shown to attenuate age-related pathologies, but it is unclear whether p16 is involved in this pathway. Here, we investigate the role of autophagy, vesicular trafficking, and lysosomal degradation on p16 expression and localization in human epithelial cells. Time-lapse fluorescence microscopy using an endogenous p16-mCherry reporter revealed that serum starvation, etoposide, and hydrogen peroxide stimulate autophagy and drive p16 recruitment to acidic cytoplasmic vesicles within 4 hr. Blocking lysosomal proteases with leupeptin and ammonium chloride resulted in the accumulation of p16 within lysosomes and increased total p16 levels suggesting that p16 is degraded by this pathway. Furthermore, autophagy blockers chloroquine and bafilomycin A1 caused p16 aggregation within stalled vesicles containing autophagosome marker LC3. Increase of p16 within these vesicles coincided with the accumulation of LC3-II. Knockdown of autophagosome chaperone p62 attenuated the formation of p16 aggregates in lysosomes, suggesting that p16 is targeted to these vesicles by p62. Taken together, these results implicate the autophagy pathway as a novel regulator of p16 degradation and localization, which could play a role in the etiology of cancer and age-related diseases.
Biomarkers reflect differences in osteoarthritis phenotypes of the lumbar spine: the Johnston County Osteoarthritis Project
Creators: name: Nelson, A.E.
name: Renner, J.B.
name: Jordan, J.M.
name: Goode, A.P.
name: Kraus, V.B.
Publisher: name: Elsevier
Year: 2017

description: OBJECTIVE: To determine differences in biomarker levels between radiographic phenotypes of facet joint osteoarthritis (FOA) only, spine OA only ((disc space narrowing (DSN) and vertebral osteophytes (OST)) or the combination of FOA and spine OA. DESIGN: A cross-sectional analysis of data from 555 participants in the Johnston County Osteoarthritis Project was performed. Lumbar spine levels were graded by severity (OST and DSN) and presence (FOA) of degeneration. Biomarkers included hyaluronan (HA) and type II collagen (CTX-II). Adjusted risk ratios (aRRR) were estimated using multinomial regression, with adjustment for age, race, sex, body mass index (BMI), and radiographic OA (knee, hip, hand). Interactions were tested between sex, race and low back symptoms. RESULTS: FOA only was present in 22.4%, 14.5% had spine OA only, and 34.6% had the combination of FOA and spine OA. Compared to the reference group of neither FOA or spine OA, a one unit higher ln HA level was associated with 31% higher relative risk ratio (RRR = 1.31 (95% 1.03, 1.67)) of having FOA only, while, a one unit higher lnuCTX-II level was associated with 84% higher relative risk ratio (RRR = 1.84 (95% CI 1.19, 2.84)) of having spine OA only. No significant interactions were identified. CONCLUSION: Interestingly, OA affecting the synovial facet joint was associated with a marker of inflammation (HA). Spine OA, affecting intervertebral discs that contain collagen type II, was associated with a marker reflecting collagen type II degradation (CTX-II). These findings suggest that biomarkers may reflect the different pathophysiologic processes of lumbar spine OA phenotypes.
Additional file 2 of Pediatric high-grade glioma MYCN is frequently associated with Li-Fraumeni syndrome
Creators: name: Guerrini-Rousseau, Léa
name: Tauziède-Espariat, Arnault
name: Castel, David
name: Rouleau, Etienne
name: Sievers, Philipp
name: Saffroy, Raphaël
name: Beccaria, Kévin
name: Blauwblomme, Thomas
name: Hasty, Lauren
name: Bourdeaut, Franck
name: Grill, Jacques
name: Varlet, Pascale
name: Debily, Marie-Anne
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Marine Biology
subject: Cancer
subject: Plant Biology
subject: Virology

description: Additional file 2. Methods used in this series.
Bone Mineral Density and the Risk of Hip and Knee Osteoarthritis: The Johnston County Osteoarthritis Project
Creators: name: Jordan, Joanne M.
name: Hootman, Jennifer M.
name: Renner, Jordan B.
name: Helmick, Charles G.
name: Murphy, Louise B.
name: Barbour, Kamil E.
Publisher: name: Wiley
Year: 2017

description: OBJECTIVE: To address knowledge gaps regarding the relationship between bone mineral density (BMD) and incident hip or knee osteoarthritis (OA); specifically, lack of information regarding hip OA or symptomatic outcomes. METHODS: Using data (n = 1,474) from the Johnston County Osteoarthritis Project's first (1999-2004) and second (2005-2010) followup of participants ages ≥45 years, we examined the association between total hip BMD and both hip and knee OA. Total hip BMD was measured using dual x-ray absorptiometry, and participants were classified into sex-specific quartiles (low, intermediate low, intermediate high, and high). Radiographic OA (ROA) was defined as development of Kellgren/Lawrence grade ≥2. Symptomatic ROA (sROA) was defined as onset of both ROA and symptoms. Weibull regression modeling was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs). RESULTS: Median followup time was 6.5 years (range 4.0-10.2 years). In multivariate models, and compared with participants with low BMD, those with intermediate high and high BMD were less likely to develop hip sROA (HR 0.52 [95% CI 0.31-0.86] and 0.56 [95% CI 0.31-0.86], respectively; P = 0.024 for trend); high BMD was not associated (HR 0.69 [95% CI 0.45-1.06]) with risk of hip ROA. Compared with participants with low BMD, those with intermediate low and intermediate high total hip BMD were more likely to develop knee sROA (HR 2.15 [95% CI 1.40-3.30] and 1.65 [95% CI 1.02-2.67], respectively; P = 0.325 for trend); similar associations were seen with knee ROA. CONCLUSION: Our findings suggest that higher BMD may reduce the risk of hip sROA, while intermediate levels may increase the risk of both knee sROA and ROA.