bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real world validation of activity recognition algorithm and development of novel behavioral biomarkers of falls in aged control and movement disorder patients
Authors: Nouriani Ali , Jonason Alec , Sabal Luke , Hanson Jacob , Jean James , Lisko Thomas , Reid Emma , Moua Yeng , Rozeboom Shane , Neverman Kaiser , Stowe Casey , Rajamani Rajesh , McGovern Robert A. 
Published: November 2022

AbstractThe use of wearable sensors in movement disorder patients such as Parkinson’s disease (PD) and normal pressure hydrocephalus (NPH) is becoming more widespread, but most studies are limited to characterizing general aspects of mobility using smartphones. There is a need to accurately identify specific activities at home in order to properly evaluate gait and balance at home, where most falls occur.We developed an activity recognition algorithm to classify multiple daily living activities including high fall risk activities such as sit to stand transfers, turns and near-falls using data from 5 inertial sensors placed on the chest, upper-legs and lower-legs of the subjects. The algorithm is then verified with ground truth by collecting video footage of our patients wearing the sensors at home.Our activity recognition algorithm showed >95% sensitivity in detection of activities. Extracted features from our home monitoring system showed significantly better correlation (∼69%) with prospectively measured fall frequency of our subjects compared to the standard clinical tests (∼30%) or other quantitative gait metrics used in past studies when attempting to predict future falls over one year of prospective follow-up.Although detecting near-falls at home is difficult, our proposed model suggests that near-fall frequency is the most predictive criterion in fall detection through correlation analysis and fitting regression models.
Prevalence and causes of blindness and visual impairment in Sudur paschim Province of Nepal
Authors: Pant Suresh Raj , Bhatta Ramesh Chandra , Bhatta Subash , Sapkota YuddhaDhoj 
Published: November 2022

AbstractAimTo determine the prevalence and causes of blindness and visual impairment among aged 50 years and older population in Sudurpaschim Province of Nepal.MethodsA cross sectional study, among population aged 50 years and older using a random multistage cluster sampling procedure. Eligible study participants were enrolled by door-to-door enumeration. Survey team lead by an Ophthalmologist assessed visual acuity, examination of eye and data collection was carried out on tablets installed with mRAAB 7 software.ResultsThe survey examined 4573 out of 4615 subjects enumerated, with a response rate 99.1%. Out of 4573 subjects, 1995 (43.63%) were male and 2578 (56.37%) were female. Among the examined, 2214 (48.4%) were between 50-59 years. The age- and sex-adjusted prevalence of blindness was 0.6% (95% CI 0.3 – 0.87).The age- and sex-adjusted prevalence of severe visual impairment, moderate visual impairment, and early visual impairment were 1.0% (95% CI 0.6 – 1.3), 5.3% (95% CI 4.5 – 6.2) and 7.0% (95% CI 6.0 – 8.0) respectively. The main causes of bilateral blindness were untreated cataract (36.4%), non-trachomatous corneal opacity (24.2%), glaucoma (21.2%), globe or central nervous system abnormalities (9.1%), age related macular degeneration (6.1%) and other posterior segment diseases (3.0%).ConclusionPrevalence of blindness was reduced in the province in comparison to the previous survey. Cataract remains the major cause of blindness, severe visual impairment, and moderate visual impairment followed by corneal opacities and glaucoma. The study suggests more attention to be given for cataract, corneal blindness and glaucoma in future interventions to eliminate blindness.
Variation in price of cardiovascular and diabetes medicine in Indonesia, and relationship with quality: a mixed methods study in East Java
Authors: Pisani Elizabeth , Dewi Aksari , Palagyi Anna , Praveen Devarsety , Pratita Ihsan Bachtiar Rifai , Hariadini Ayuk Lawuningtyas , Lyrawati Diana , Sujarwoto  , Maharani Asri , Tampubolon Gindo , Patel Anushka 
Published: November 2022

AbstractLower-middle income Indonesia, the world’s fourth most populous country, has struggled to contain costs in its mandatory, single-payer public health insurance system since the system’s inception in 2014. Public procurement policies radically reduced prices of most medicines in public facilities and the wider market. However, professional associations and the press have questioned the quality of these low-cost, unbranded generic medicines.We collected 204 samples of 4 cardiovascular and 1 antidiabetic medicine from health facilities and retail outlets in East Java. We collected amlodipine, captopril, furosemide, simvastatin and glibenclamide, sampling to reflect patients’ likelihood of exposure to specific brands and outlets. We recorded sales prices and maximum retail prices, and tested medicines for dissolution and percent of labelled content, using high-performance liquid chromatography. We conducted in-depth interviews with supply chain actors.All samples, including those provided free in public facilities, met quality specifications.Most manufacturers make both branded and unbranded medicines. Retail prices varied widely. The median ratio of price to the lowest price for an equivalent product was 5.1, and a few brands sold for over 100 times the minimum price. Prices also varied between outlets for identical products, as retail pharmacies set prices to maximize profit. Since very low-cost medicines were universally available and of good quality, we believe richer patients who chose to buy branded products effectively protected medicine quality for poorer patients in Indonesia, because manufacturers cross-subsidize between branded and unbranded versions of the same medicine.
Impact of a multimodal hand hygiene improvement intervention in a 1000-bed hospital in Thailand: a stepped wedge cluster randomized controlled trial
Authors: Hongsuwan Maliwan , Srisamang Pramot , Nuntalohit Somboon , Luangasanatip Nantasit , Lim Cherry , Day Nicholas P. , Limmathurotsakul Direk , Cooper Ben S. 
Published: November 2022

AbstractBackgroundGood hand hygiene compliance amongst healthcare workers is critical for patient safety and plays a central role in preventing healthcare-associated infections. The World Health Organization (WHO) recommends a multimodal strategy to improve healthcare worker hand hygiene. We aimed to evaluate the effectiveness of this strategy in a middle-income country using a stepped-wedge cluster randomized trial.MethodsThe trial was conducted between 2013 and 2015 in 58 wards in a 1000-bed hospital in Thailand. The intervention was adapted from the WHO’s Hand Hygiene Improvement Strategy and implemented by the hospital’s infection control team. The primary outcome was observed hand hygiene compliance among healthcare workers in the study wards. This study was registered atClinicalTrials.gov(NCT01933087).FindingsDuring 4,230 observation sessions, 54,073 hand hygiene opportunities were identified. Hand hygiene compliance increased from 10.0% (2,660/26,482) to 11.0% (3,048/27,591) after the intervention (odds ratio [OR] 1.12; 95% CI: 1.01-1.24). Among the five moments for hand hygiene, the greatest improvement in compliance was observed in hand hygiene before patient contact (OR 1.52; 95% CI: 1.21, 1.91).InterpretationWhile hand hygiene compliance improved slightly, the intervention failed to achieve the substantial improvements that were needed. There is a need for new strategies to ensure that all hospitals in low and middle-income countries can achieve and maintain acceptable levels of hand hygiene.FundingOak Foundation, MRC
Using DEPendency of association on the number of Top Hits (DEPTH) as a complementary tool to identify novel risk loci in colorectal cancer
Authors: Lai John , Wong Chi , Schmidt Daniel F. , Kapuscinski Miroslaw , Alpen Karen , MacInnis Robert J. , Buchanan Daniel D. , Win Aung K. , Figueiredo Jane , Chan Andrew T. , Harrison Tabitha A. , Hoffmeister Michael , White Emily , Marchand Loic Le , Peters Ulrike , Hopper John L. , Makalic Enes , Jenkins Mark A. 
Published: November 2022

AbstractBackgroundDEPendency of association on the number of Top Hits (DEPTH) is an approach to identify candidate risk regions by considering the risk signals from over-lapping groups of sequential variants across the genome.MethodsWe conducted a DEPTH analysis using a sliding window of 200 SNPs to colorectal cancer (CRC) data from the Colon Cancer Family Registry (CCFR) (5,735 cases and 3,688 controls), and GECCO (8,865 cases and 10,285 controls) studies. A DEPTH score >1 was used to identify risk regions common to both studies. We compared DEPTH results against those from conventional GWAS analyses of these two studies as well as against 132 published risk regions.ResultsInitial DEPTH analysis revealed 2,622 (CCFR) and 3,686 (GECCO) risk regions, of which 569 were common to both studies. Bootstrapping revealed 40 and 49 likely risk regions in the CCFR and GECCO data sets, respectively. Notably, DEPTH identified at least 82 likely risk regions that would not be detected using conventional GWAS methods, nor had they been identified in previous CRC GWASs. We found four reproducible risk regions (2q22.2, 2q33.1, 6p21.32, 13q14.3), with the HLA locus at 6p21 having the highest DEPTH score. The strongest associated SNPs were rs762216297, rs149490268, rs114741460, and rs199707618 for the CCFR data, and rs9270761 for the GECCO data.ConclusionDEPTH can identify novel likely risk regions for CRC not identified using conventional analyses of much larger datasets.ImpactDEPTH has potential as a powerful complementary tool to conventional GWAS analyses for identifying risk regions within the genome.
Transmission prevention behaviors in US households with SARS-CoV-2 cases in 2020
Authors: Rubinstein Rebecca , Mei Wenwen , Cassidy Caitlin A. , Streeter Gabrielle , Basham Christopher , Cerami Carla , Lin Feng-Chang , Lin Jessica T. , Mollan Katie R. 
Published: November 2022

ABSTRACTBackgroundSARS-CoV-2 transmission frequently occurs within households, yet few studies describe which household contacts and household units are most likely to engage in transmission-interrupting behaviors.MethodsWe analyzed a COVID-19 prospective household transmission cohort in North Carolina (April-Oct 2020) to quantify changes in physical distancing behaviors among household contacts over 14 days. We evaluated which household contacts were most likely to ever mask at home and to ever share a bedroom with the index case between Days 7-14.ResultsIn the presence of a household COVID-19 infection, 24% of household contacts reported ever masking at home during the week before study entry. Masking in the home between Days 7-14 was reported by 26% of household contacts, and was more likely for participants who observed their household index case wearing a mask. Participants of color and participants in high-density households were more likely to mask at home. After adjusting for race/ethnicity, living density was not as clearly associated with masking. Symptomatic household contacts were more likely to share a bedroom with the index case. Working individuals and those with comorbidities avoided sharing a bedroom with the index case.ConclusionIn-home masking during household exposure to COVID-19 was infrequent in 2020. In light of ongoing transmission of SARS-CoV-2, these findings underscore a need for health campaigns to increase the feasibility and social desirability of in-home masking among exposed household members. Joint messaging on social responsibility and prevention of breakthrough infections, reinfections, and long COVID-19 may help motivate transmission-interruption behaviors.
Instantly adhesive and ultra-elastic patches for dynamic organ and wound repair
Authors: Chansoria Parth , Bonacquisti Emily , Heavey Mairead , Le Lina , Maruthamuthu Murali Kannan , Blackwell John , Jasiewicz Natalie , Sellers Rani S. , Maile Robert , Wallet Shannon , Egan Thomas , Nguyen Juliane 
Published: November 2022

AbstractBioadhesive materials and patches are promising alternatives to surgical sutures and staples. However, many existing bioadhesives do not meet the functional requirements of current surgical procedures and interventions. Here we present a translational patch material that exhibits: (1) instant adhesion to wet tissues (2.5-fold stronger than Tisseel, an FDA-approved fibrin glue), (2) ultra-stretchability (stretching to >300% its original length without losing elasticity), (3) compatibility with rapid photo-projection (<2 min fabrication time/patch), and (4) ability to deliver therapeutics. Using our established procedures for thein silicodesign and optimization of anisotropic-auxetic patches, we create next generation patches for instant attachment to wet and dry tissues while conforming to a broad range of organ mechanicsex vivoandin vivo. Patches coated with exosomes demonstrate robust wound healing capabilityin vivowithout inducing a foreign body response and without the need for patch removal that can cause pain and bleeding. We further demonstrate a new single material-based, void-filling auxetic patch designed for the treatment of lung puncture wounds.TeaserWe demonstrate a sticky and highly elastic patch with conforming designs for dynamic organ repair.
A deep learning network for parallel self-denoising and segmentation in visible light optical coherence tomography of human retina
Authors: Ye Tianyi , Wang Jingyu , Yi Ji 
Published: November 2022

AbstractVisible light optical coherence tomography (VIS-OCT) of human retina is an emerging imaging modality that uses shorter wavelength in visible light range than conventional near infrared (NIR) light. It provides one-micron level axial resolution to better separate stratified retinal layers, as well as microvascular oximetry. However, due to the practical limitation of laser safety and comfort, the permissible illumination power is much lower than NIR OCT which can be challenging to obtain high quality VIS-OCT images and subsequent image analysis. Therefore, improving VIS-OCT image quality by denoising is an essential step in the overall workflow in VIS-OCT clinical applications. In this paper, we provide the first VIS-OCT retinal image dataset from normal eyes, including retinal layer annotation and “noisy-clean” image pairs. We propose an efficient co-learning deep learning framework for parallel self-denoising and segmentation simultaneously. Both tasks synergize within the same network and improve each other’s performance. The significant improvement of segmentation (2% higher Dice coefficient compared to segmentation-only process) for ganglion cell layer (GCL), inner plexiform layer (IPL) and inner nuclear layer (INL) is observed when available annotation drops to 25%, suggesting an annotation-efficient training. We also showed that the denoising model trained on our dataset generalizes well for a different scanning protocol.
Expected Costs of Mental Efforts are Updated When People Exert Effort, not by Prospective Information
Authors: Nagase Asako Mitsuto , Westbrook Andrew , Onoda Keiichi , Morita Kenji , Kawagoe Toshikazu , Yamaguchi Shuhei , Akaishi Rei , Hanajima Ritsuko 
Published: November 2022

SummaryTo understand human behaviour, it is crucial to reveal the mechanisms by which we learn and decide about effort costs and benefits in an uncertain world. Whereas the mechanisms for reward learning are well-understood, the mechanisms for effort cost learning, and especially mental effort, remain elusive. Initially, we hypothesized that cost learning follows temporal-difference learning such that brains update expected costs when informed about upcoming effort levels. However, fMRI data revealed neural correlates of a cost-prediction error of mental effort during task execution and not in response to an effort cue about upcoming effort demands. These results imply that expected costs are updated during actual effort exertion, implying that the adaptive learning of mental effort cost does not follow traditional temporal-difference learning. This study contributes to the understanding of the neural mechanism underlying unwillingness to work, suggesting that humans learn mental effort costs only when they experience effort exertion.
Magnetic Bead Based Proximity Extension Assay for Sensitive Protein and Extracellular Vesicles Detection
Authors: Muthelo Phathutshedzo , Ebai Tonge , Doulabi Ehsan Manouchehri , Al-Amin Rasel A. , Wu Yajun , Kamali-Moghaddam Masood , Landegren Ulf 
Published: November 2022

AbstractDuring the early stages of disease development, protein biomarkers can leak into the blood creating opportunities for early diagnosis of disease with minimally invasive sampling. These proteins biomarkers however are often masked by the presence of more abundant functional blood proteins, making specific detection a challenge with most current immunoassays. We we report on the development of a magnetic bead based solid-phase PEA (SP-PEA) for sensitive detection of proteins in plasma and serum samples. Antibody functionalized magnetic beads are used to capture the target of interest. Following capture, non-specifically bound proteins are washed off before PEA probes are added for detection of the bound proteins. Compared to hoogenous PEA, SP-PEA admits the use of larger sample volumes to increase available target molecules, higher concentration of detection reagents for more efficient formation of detection complexes and washes for removal of nonspecific background. We compared SP-PEA to solution phase PEA for the detection of cytokines: interlukin-6, interlukin-2, interlukin-4, interlukin-10 and Tumor Necrosis Factor-alpha, and we demonstrated an increased sensitivity by 15 to 60 fold in buffer and chicken serum. We further expanded SP-PEA to detect extracellular vesicles (EVs) through combinations of proteins on the surface of specific EV populations.
Rat superior colliculus encodes the transition between static and dynamic vision modes
Authors: Gil Rita , Valente Mafalda , Shemesh Noam 
Published: November 2022

AbstractWhen visual stimuli are presented at a sufficiently high temporal frequency, visual perception shifts from the static to dynamic vision mode, thereby facilitating a continuity illusion which is key for correctly identifying continuous and moving objects and placing them in the context of the surrounding environment. However, how this continuity illusion is encoded along the entire visual pathway remains poorly understood, with disparate Flicker Fusion Frequency (FFF) thresholds measured at retinal, cortical, and behavioural levels. Here, we hypothesized that these disparities may suggest that other brain areas may be involved in encoding the shift from static to dynamic vision modes. We employ a comprehensive approach encompassing behavioural measurements, whole brain activation mapping with high fidelity functional MRI (fMRI), and local electrophysiological validation for studying the mechanisms underlying the shift from static to dynamic vision modes in the rat. Our behavioural measurements reported an FFF threshold proxy of 18±2 Hz. At the network level, functional MRI revealed that the superior colliculus (SC) exhibits marked signal transitions from positive to negative fMRI signal regimes at the behaviourally measured FFF threshold surrogates, with a strong linear correlation between fMRI signal and behaviour, while thalamic and cortical visual areas displayed a significantly poorer correlation with the behaviour. fMRI-driven neurometric curves approximated the behavioural psychometric curve in SC but not in the other visual areas. Electrophysiological recordings in SC suggested that these fMRI signals transitions arise from strong neural activation/suppression at low/high frequency regimes, respectively, and that a transition between these regimes occurs around the measured FFF threshold proxies. Lesions in V1 further reinforced that these transitions originate in SC. Combined, our data suggests a critical role for SC in encoding temporal frequency discriminations, in particular the shifts from the static to the dynamic vision modes.
Association Rule Mining of the Human Gut Microbiome
Authors: Zhang Yiyan , Ke Shanlin , Wang Xu-Wen , Liu Yang-Yu 
Published: November 2022

AbstractThe human gut carries a vast and diverse microbial community that is essential for human health. Understanding the structure of this complex community requires quantitative approaches. Traditional co-occurrence and correlation analyses typically focus on pair-wise relationships and ignore higher-order relationships. Association rule mining (ARM) is a well-developed technique in data mining and has been applied to human microbiome data to identify higher-order relationships. Yet, existing attempts suffer from small sample sizes and low taxonomic resolution. Here we leverage the curatedMetagenomic Database (CMD) to resolve those issues. We first infer association rules from gut microbiome samples of a large cohort of healthy individuals (n=2,815) in CMD. Then we compare those rules with that inferred from samples of individuals with different diseases: Inflammatory Bowel Disease (IBD, n=768), Colorectal cancer (CRC, n=368), Impaired Glucose Tolerance (IGT, n=199), and Type 2 Diabetes (T2D, n=164). Finally, we demonstrate that using ARM as a feature selection tool can improve the performance of microbiome-based disease classification. Together, this study provides a comprehensive study of higher-order microbial relationships in the human gut microbiome and highlights the importance of incorporating association rules in microbiome-based disease classification.
To disperse or compete? Coevolution of traits leads to a limited number of reproductive strategies
Authors: Planas-Sitjà Isaac , Monnin Thibaud , Loeuille Nicolas , Cronin Adam L 
Published: November 2022

AbstractReproductive strategies are defined by a combination of behavioural, morphological, and life-history traits. Reproductive investment and offspring propagule size are two key traits defining reproductive strategies. While a substantial amount of work has been devoted to understanding the independent fitness effects of each of these traits, it remains unclear how coevolution between them ultimately affects the evolution of reproductive strategies, and how this might influence the relationship between dispersal and environmental factors. In this study we explore how the evolution of reproductive strategies defined by these two coevolving traits is influenced by resource availability and spatial structuring of the environment using a simulation model. We find three possible equilibrium strategies across all scenarios: a competitor strategy with high reproductive investment (producing large propagules which disperse short distances), and two coloniser strategies differing in reproductive investment (both producing small propagules which disperse long distances). The possible equilibrium strategies for each scenario depended on starting conditions, spatial structure and resource availability. Evolutionary transitions between these equilibrium strategies were more likely in heterogeneous than homogeneous landscapes and at higher resource levels. Transition from coloniser strategy to competitor strategy was usually a two-step process, with changes in propagule size following initial evolution in investment. This highlights how the interaction between the two trait axes affects the evolution of reproductive strategies, particularly where fitness valleys preclude the simultaneous evolution of traits. Our results highlight the need to incorporate trait coevolution into evolutionary models to help develop a more integrative understanding of the structure of natural populations and how the interaction between traits constrains or hinders evolutionary processes.