bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wearable technology to capture arm use of stroke survivors in home and community settings: feasibility and early insights on motor performance
Authors: Demers Marika , Bishop Lauri , Cain Amelia , Saba Joseph , Rowe Justin , Zondervan Daniel , Winstein Carolee 
Published: January 2023

AbstractObjectiveTo establish short-term feasibility and usability of wrist-worn wearable sensors to capture arm/hand activity of stroke survivors and to explorethe association betweenfactors related to use of the paretic arm/hand.Methods30 chronic stroke survivors were monitored with wrist-worn wearable sensors during 12h/day for a 7-day period. Participants also completed standardized assessments to capture stroke severity, arm motor impairments, self-perceived arm use and self-efficacy. Usability of the wearable sensors was assessed using the adapted System Usability Scale and an exit interview. Associations between motor performance and capacity (arm/hand impairments and activity limitations) were assessed using Spearman’s correlations.ResultsMinimal technical issues or lack of adherence to the wearing schedule occurred, with 87.6% of days procuring valid data from both sensors. Average sensor wear time was 12.6 (standard deviation: 0.2) h/day. Three participants experienced discomfort with one of the wristbands and three other participants had unrelated adverse events. There were positive self-reported usability scores (mean: 85.4/100) and high user satisfaction. Significant correlations were observed for measures of motor capacity and self-efficacy with paretic arm use in the home and the community (Spearman’s correlation ρs: 0.44-0.71).ConclusionsThis work demonstrates the feasibility and usability of a consumer-grade wearable sensor to capture paretic arm activity outside the laboratory. It provides early insight into stroke survivors’ everyday arm use and related factors such as motor capacity and self-efficacy.ImpactThe integration of wearable technologies into clinical practice offers new possibilities to complement in-person clinical assessments and to better understand how each person is moving outside of therapy and throughout the recovery and reintegration phase. Insights gained from monitoring stroke survivors arm/hand use in the home and community is the first step towards informing future research with an emphasis on causal mechanisms with clinical relevance.
Parental Risk Perception: Influence of Disease Perceived Controllability, Experience and Severity
Authors: Sylvestre Philippe , Enok Bonong Pascal Roland , Perez Tamara , Drouin Olivier 
Published: January 2023

AbstractOptimistic health bias is widespread in adults, impacting responsiveness to information regarding health risks. Comparatively little is known about parents’ perception of their child’s likelihood of developing disease, despite the frequency with which parents make decisions about their child’s health. We hypothesized that parental optimism about their child’s likelihood of developing disease would be greater for diseases perceived as more controllable and those with which parents do not have experience.Parents of children <18 years complete an online survey. Primary outcome was participants’ perceived comparative likelihood of their child developing appendicitis, dental caries, head lice, leukemia, food allergies, pneumonia, asthma and obesity. Optimism was defined as the belief that one’s child was less likely than average to develop a given disease. Logistic regression models were used to examine the relationship between parental optimism and four independent variables: perceived disease controllability; knowing someone with the disease; child’s history of the disease; perceived disease severity.Among 374 participants, the proportion of optimistic parents ranged from 35.3% (appendicitis) to 65.0% (obesity). Perceived controllability increased the odds of parental optimism (adjusted odds ratio [ aOR] range: 1.57 for asthma to 4.48 for head lice). Odds of optimism were lower if participants knew somebody with the disease (aOR range: 0.42 for head lice to 0.81 for leukemia) or if the child had a history of the disease (aOR range: 0.27 for dental caries to 0.47 for head lice).These findings are important to enhance parental counseling effectiveness regarding child health behaviors.
Vaccine-elicited B and T cell immunity to SARS-CoV-2 is impaired in chronic lung disease patients
Authors: Liu Haolin , Aviszus Katja , Zelarney Pearlanne , Liao Shu-Yi , Gerber Anthony N. , Make Barry , Wechsler Michael E. , Marrack Philippa , Reinhardt R. Lee 
Published: January 2023

AbstractThe protection afforded by vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to individuals with chronic lung disease is not well established. To understand how chronic lung disease impacts SARS-CoV-2 vaccine-elicited immunity we performed deep immunophenotyping of the humoral and cell mediated SARS-CoV-2 vaccine response in an investigative cohort of vaccinated patients with diverse pulmonary conditions including asthma, chronic obstructive pulmonary disease (COPD), and interstitial lung disease (ILD). Compared to healthy controls, 48% of vaccinated patients with chronic lung diseases had reduced antibody titers to the SARS-CoV-2 vaccine antigen as early as 3-4 months after vaccination, correlating with decreased vaccine-specific memory B cells. Vaccine-specific CD4 and CD8 T cells were also significantly reduced in patients with asthma, COPD, and a subset of ILD patients compared to healthy controls. These findings reveal the complex nature of vaccine-elicited immunity in high-risk patients with chronic lung disease.
Efficacy of recombinant human epidermal growth factor (rhEGF) incorporated in an absorbable collagen membrane for the management of gingival recession defects
Authors: Chandra Rampalli Viswa , Bindu Kotha Sushmitha , Reddy Aileni Amarendhar 
Published: January 2023

ABSTRACTAim & ObjectivesThe aim of the present study is to evaluate the regeneration efficacy of rhEGF impregnated in collagen membrane for the management of Millers class I & class II gingival recession defects.Patients and methods18 patients with 30 Millers class I & class II gingival recession defects were treated with one of the following interventions and randomly allocated into each of the following experimental groups; Test group: rhEGF impregnated in collagen membrane, Control group: plain collagen membrane. Clinical measurements at baseline, 3 months and 6 months included decreased probing depth, recession depth and increase in width of keratinized gingiva.ResultsThere was an improvement in tissue biotype in test group and statistically significant increase in KGW from baseline to 3 months which remained constant from 3 months to 6 months(p≤0.001) in both the groups. Similarly, RD shows constant increase from baseline to 6 months in test group whereas there is reduction in control group (p≤0.003). There was significant difference in clinical parameters in both test and control groups. All the patients had an uneventful healing phase.ConclusionThe beneficial effects of rhEGF resulted in healthy wound healing process with less scarring offers more potential properties showed promising results over collagen membrane. Further larger samples are required to confirm the efficacy of rhEGF in root coverage for soft tissue regeneration.
Expected reduction in obesity of a 20% and 30% tax to Sugar-Sweetened-Beverages in Brazil: a modeling study
Authors: Basto-Abreu Ana , Torres-Alvarez Rossana , Barrientos-Gutierrez Tonatiuh , Pereda Paula , Duran Ana Clara 
Published: January 2023

ABSTRACTBackgroundThe consumption of sugar-sweetened beverages (SSB) is associated with obesity, metabolic diseases, and incremental healthcare costs. Given their health consequences, the World Health Organization (WHO) recommended that countries implement taxes to SSB. Over the last 10 years, Brazil has almost doubled its obesity prevalence, yet, in 2016, the Brazilian government cut 23 percentage points to existing federal SSB taxes to their current 4%. To simulate the potential impact of updating the fiscal policy towards SSB in Brazil, we aimed to estimate the price-elasticity of SSB and model the potential impact of a new 20 or 30% excise SSB tax on consumption, obesity prevalence, and healthcare costs.Methods and FindingsUsing household purchases data from the Brazilian Household Budget Survey (POF) from 2017/2018, we estimated constant elasticity regressions using a log-log specification by income level for all beverage categories: (1) sugar-sweetened beverages, (2) alcoholic beverages, (3) other beverages, and (4) low-calorie sweetened beverages. We estimated baseline intake for each beverage group using 24h dietary recall data from POF 2017/2018. Applying the price and cross-price elasticities to the baseline intake, we obtained changes in caloric intake. The caloric reduction was introduced into an individual dynamic model to estimate changes in weight and obesity prevalence. By multiplying the reduction in obesity cases during 10 years by the obesity costs per capita, we predicted the reduction in obesity costs attributable to the sweetened beverage tax. SSB price elasticities were higher in the low (−1.24) than in the high-income tertile (−1.13); cross-price elasticities suggest SSB were weakly substituted by milk, water, and 100% fruit juices. We estimated a caloric change of -17.3 kcal/day/person under a 20% excise tax and -25.9 kcal/day/person for a 30% tax. 10 years after implementation, a 20% tax is expected to reduce obesity prevalence by 6.7% and 9.1% for a 30% tax. These reductions translate into a -2.8 million and -3.8 million obesity cases for a 20 and 30% tax, respectively, and a reduction of $US -257.4 million and $US -345.9 million obesity costs over 10 years for a 20 and 30% tax, respectively.ConclusionsAdding a 20 to 30% excise tax on top of Brazil’s current federal tax in Brazil could help reduce the consumption of ultra-processed beverages, empty calories, and body weight while avoiding large health-related costs. Given the recent cuts to SSB taxes in Brazil, a program to revise and implement excise taxes could prove beneficial for the Brazilian population.
Altered sex differences in hippocampal subfield volumes in schizophrenia
Authors: Barth Claudia , Nerland Stener , Jørgensen Kjetil N. , Haatveit Beathe , Wortinger Laura A. , Melle Ingrid , Haukvik Unn K. , Ueland Torill , Andreassen Ole A. , Agartz Ingrid 
Published: January 2023

AbstractObjectiveThe hippocampus is a heterogenous brain structure that differs between the sexes and has been implicated in the pathophysiology of psychiatric illnesses. Here, we explored sex and diagnostic group differences in hippocampal subfield volumes, in individuals with schizophrenia spectrum disorder (SZ), bipolar disorders (BD) and healthy controls.Methods1,521 participants underwent T1-weighted magnetic resonance imaging (SZ, n = 452, mean age 30.7 ± 9.2 [SD] years, males 59.1%; BD, n = 316, 33.7 ± 11.4, 41.5%; healthy controls, n = 753, 34.1 ± 9.1, 55.6%). Total hippocampal, subfield, and intracranial volumes were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple regression models were fitted to examine sex-by-diagnostic (sub)group interactions in volume. In SZ and BD, separately, associations between volumes and clinical as well as cognitive measures were examined between the sexes using regression models.ResultsSignificant sex-by-group interactions were found for the total hippocampus, dentate gyrus, molecular layer, presubiculum, fimbria, HATA, and CA4, indicating a larger volumetric deficit in male patients relative to female patients when compared with same-sex healthy controls. Subgroup analyses revealed that this interaction was driven by males with schizophrenia. Effect sizes were overall small (partial η2< 0.02). We found no significant sex differences in the associations between hippocampal volumes and clinical or cognitive measures in SZ and BD.ConclusionsUsing a well-powered sample, our findings indicate that the pattern of morphological sex differences in hippocampal subfields is altered in individuals with schizophrenia relative to healthy controls, due to higher volumetric deficits in males.
scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data
Authors: Ding Liang , Shi Hao , Qian Chenxi , Burdyshaw Chad , Veloso Joao Pedro , Khatamian Alireza , Pan Qingfei , Dhungana Yogesh , Xie Zhen , Risch Isabel , Yang Xu , Huang Xin , Yan Lei , Rusch Michael , Brewer Michael , Yan Koon-Kiu , Chi Hongbo , Yu Jiyang 
Published: January 2023

AbstractThe sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as “hidden drivers”, are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via:https://github.com/jyyulab/scMINER.
The LCLAT1/LYCAT acyltransferase is required for EGF-mediated phosphatidylinositol-3,4,5-trisphosphate generation and Akt signalling
Authors: Chan Victoria , Camardi Cristina , Zhang Kai , Orofiamma Laura A. , Anderson Karen E. , Hoque Jafarul , Bone Leslie N. , Awadeh Yasmin , Lee Daniel K. C. , Fu Norman J. , Chow Jonathan T. S. , Salmena Leonardo , Stephens Len R. , Hawkins Phillip T. , Antonescu Costin N. , Botelho Roberto J. 
Published: January 2023

AbstractReceptor tyrosine kinases such as epidermal growth factor receptor (EGFR) stimulate phosphoinositide 3-kinases (PI3Ks) to convert phosphatidylinositol-4,5-bisphosophate [PtdIns(4,5)P2] into phosphatidylinositol-3,4,5-trisphosphate [PtdIns(3,4,5)P3]. PtdIns(3,4,5)P3then remodels actin and gene expression, and boosts cell survival and proliferation. PtdIns(3,4,5)P3partly achieves these functions by triggering activation of the kinase Akt, which phosphorylates targets like Tsc2 and GSK3β. Consequently, unchecked upregulation of PtdIns(3,4,5)P3-Akt signalling promotes tumour progression. Interestingly, 50-70% of PtdIns and PtdInsPs have stearate and arachidonate atsn-1 andsn-2 positions of glycerol, respectively, forming a species known as 38:4-PtdIns/PtdInsPs. LCLAT1 and MBOAT7 acyltransferases partly enrich PtdIns in this acyl format. We previously showed that disruption of LCLAT1 lowered PtdIns(4,5)P2levels and perturbed endocytosis and endocytic trafficking. However, the role of LCLAT1 in receptor tyrosine kinase and PtdIns(3,4,5)P3signaling was not explored. Here, we show that LCLAT1 silencing in MDA-MB-231 and ARPE-19 cells abated the levels of PtdIns(3,4,5)P3in response to EGF signalling. Importantly, LCLAT1-silenced cells were also impaired for EGF-driven and insulin-driven Akt activation and downstream signalling. Thus, our work provides first evidence that the LCLAT1 acyltransferase is required for receptor tyrosine kinase signalling.
Adaptation of Graph Convolutional Neural Networks and Graph Layer-wise Relevance Propagation to the Spektral library with application to gene expression data of Colorectal Cancer patients
Authors: Lutz Sebastian , Auer Florian , Hartmann Dennis , Chereda Hryhorii , Beißbarth Tim , Kramer Frank 
Published: January 2023

AbstractMotivationColorectal Cancer has the second-highest mortality rate worldwide, which requires advanced diagnostics and individualized therapies to be developed. Information about the interactions between molecular entities provides valuable information to detect the responsible genes driving cancer progression. Graph Convolutional Neural Networks are able to utilize the prior knowledge provided by interaction networks and the Spektral library adds a performance increase in contrast to standard implementations. Furthermore, machine learning technology shows great potential to assist medical professionals through guided clinical decision support. However, the deep learning models are limited in their application in precision medicine due to their lack to explain the factors contributing to a prediction. Adaption of the Graph Layer-Wise Relevance Propagation methodology to graph-based deep learning models allows to attribute the learned outcome to single genes and determine their relevance. The resulting patient-specific subnetworks then can be used to identify potentially targetable genes.ResultsWe present an implementation of Graph Convolutional Neural Networks using the Spektral library in combination with adapted functions for Graph Layer-Wise Relevance Propagation. Deep learning models were trained on a newly composed large gene expression dataset of Colorectal Cancer patients with different molecular interaction networks as prior knowledge: Protein-protein interactions from the Human Protein Reference Database and STRING, and pathways from the Reactome database. Our implementation performs comparably with the original implementation while reducing the computation time, especially for large networks. Further, the generated subnetworks are similar to those of the initial implementation and reveal possible, and even more distant, biomarkers and drug targets.AvailabilityThe implementation details and corresponding dataset including their visualizations can be found athttps://github.com/frankkramer-lab/spektral-gcnn-glrp-on-crc-dataContactsebastian.lutz@uni-a.de
Prediction of brain age using structural magnetic resonance imaging: A comparison of accuracy and test-retest reliability of publicly available software packages
Authors: Dörfel Ruben P. , Arenas-Gomez Joan M. , Fisher Patrick M. , Ganz Melanie , Knudsen Gitte M. , Svensson Jonas , Plavén-Sigray Pontus 
Published: January 2023

AbstractBackgroundBrain age prediction algorithms using structural magnetic resonance imaging (MRI) aim to assess the biological age of the human brain. The difference between a person’s chronological age and the estimated brain age is thought to reflect deviations from a normal aging trajectory, indicating a slower, or accelerated, biological aging process. Several pre-trained software packages for predicting brain age are publicly available. In this study, we perform a head-to-head comparison of such packages with respect to 1) predictive accuracy, 2) test-retest reliability, and 3) the ability to track age progression over time.MethodsWe evaluated the six brain age prediction packages: brainageR, DeepBrainNet, brainage, ENIGMA, pyment, and mccqrnn. The accuracy and test-retest reliability were assessed on MRI data from 372 healthy people aged between 18.4 and 86.2 years (mean 38.7 ± 17.5 years).ResultsAll packages showed significant correlations between predicted brain age and chronological age (r = 0.66 to 0.97, p < 0.001), with pyment displaying the strongest correlation. The mean absolute error was between 3.56 (pyment) and 9.54 years (ENIGMA). brainageR, pyment, and mccqrnn were superior in terms of reliability (ICC values between 0.94 - 0.98), as well as predicting age progression over a longer time span.ConclusionOf the six packages, pyment and brainageR consistently showed the highest accuracy and test-retest reliability.
The sequence of regional structural disconnectivity due to multiple sclerosis lesions
Authors: Tozlu Ceren , Olafson Emily , Jamison Keith , Demmon Emily , Kaunzner Ulrike , Marcille Melanie , Zinger Nicole , Michaelson Nara , Safi Neha , Nguyen Thanh , Gauthier Susan , Kuceyeski Amy 
Published: January 2023

ABSTRACTObjectivePrediction of disease progression is challenging in multiple sclerosis (MS) as the sequence of lesion development and retention of inflammation within a subset of chronic lesions is heterogeneous among patients. We investigated the sequence of lesion-related regional structural disconnectivity across the spectrum of disability and cognitive impairment in MS.MethodsIn a full cohort of 482 patients, the Expanded Disability Status Scale was used to classify patients into (i) no or mild vs (ii) moderate or severe disability groups. In 363 out of 482 patients, Quantitative Susceptibility Mapping was used to identify paramagnetic rim lesions (PRL), which are maintained by a rim of iron-laden innate immune cells. In 171 out of 482 patients, Brief International Cognitive Assessment was used to identify subjects with cognitive impairment. Network Modification Tool was used to estimate the regional structural disconnectivity due to MS lesions. Discriminative event-based modeling was applied to investigate the sequence of regional structural disconnectivity due to all representative lesions across the spectrum of disability and cognitive impairment.ResultsStructural disconnection in the ventral attention and subcortical networks was an early biomarker of moderate or severe disability. The earliest biomarkers of disability progression were structural disconnections due to PRL in the motor-related regions. Subcortical structural disconnection was an early biomarker of cognitive impairment.InterpretationMS lesion-related structural disconnections in the subcortex is an early biomarker for both disability and cognitive impairment in MS. PRL-related structural disconnection in the motor cortex may identify the patients at risk for moderate or severe disability in MS.
Deep learning enables fast, gentle STED microscopy
Authors: Ebrahimi Vahid , Stephan Till , Kim Jiah , Carravilla Pablo , Eggeling Christian , Jakobs Stefan , Han Kyu Young 
Published: January 2023

AbstractSTED microscopy is widely used to image subcellular structures with super-resolution. Here, we report that denoising STED images with deep learning can mitigate photobleaching and photodamage by reducing the pixel dwell time by one or two orders of magnitude. Our method allows for efficient and robust restoration of noisy 2D and 3D STED images with multiple targets and facilitates long-term imaging of mitochondrial dynamics.