1,010 results on '"Bobak, P"'
Search Results
152. Trajectories in physical functioning at older age in relation to childhood and adulthood SES and social mobility: a population-based cohort study
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Andrzej Pająk, Maciej Polak, Magdalena Kozela, Agnieszka Doryńska, and Martin Bobak
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physical functioning ,socioeconomic status ,social mobility ,aging ,cohort study ,Public aspects of medicine ,RA1-1270 - Abstract
IntroductionOlder age is associated with the deterioration of physical functioning (PF), and low PF is strongly related to poor quality of life among older people. We conducted a study to examine the trajectories of PF between middle and old age, considering sex differences as well as the association between socioeconomic status (SES) at different life stages and changes in PF.MethodsWe analyzed data from the Polish arm of the HAPIEE (Health, Alcohol and Psychosocial factors In Eastern Europe) study, including 1,116 men and 1,178 women aged 45–64 years at baseline. Adult and childhood SES and social mobility were assessed using a retrospectively focused questionnaire. PF was assessed using the 10-question SF-36 scale at baseline examination, face-to-face re-examination, and three postal surveys, covering up to 20 years (on average, 18 years). We employed Generalized Estimating Equations models to assess changes in PF scores over time and compare PF trajectories across different SES categories.ResultsAfter adjusting for age and other covariates, we found that, in both sexes, participants with always middle or high SES, as well as those who reported upward mobility, had higher PF scores at baseline compared to those with always low SES. A decline in PF between middle and old age was observed in all SES groups; however, the decline was slower in participants with always middle or high SES compared to those with always low SES.ConclusionThis cohort study revealed that lower SES and downward social mobility were cross-sectionally associated with poorer PF, while upward social mobility seemed to largely reverse the effect of low childhood SES. In addition to the cross-sectional associations observed at baseline, advantaged SES was also significantly associated with a slower decline in PF over an 18-year follow-up period.
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- 2023
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153. Pulmonary delivery of siRNA-loaded lipid-polymer hybrid nanoparticles: Effect of nanoparticle size
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Abishek Wadhwa, Thomas R. Bobak, Lennart Bohrmann, Reka Geczy, Sathiya Sekar, Gowtham Sathyanarayanan, Jörg P. Kutter, Henrik Franzyk, Camilla Foged, Katayoun Saatchi, and Urs O. Häfeli
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Microfluidics ,siRNA ,Lipid-polymer hybrid nanoparticles (LPNs) ,Size modulation ,SPECT/CT ,Pulmonary delivery ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Nanomedicines based on nanoparticles rely both on the potency of the drug as well as the efficiency of the delivery system, for which particle size plays a crucial role. For the intracellular delivery of small interference RNA (siRNA), lipid-polymer nanoparticle (LPN) hybrid systems constitute a safe and highly effective class of delivery systems. In the present study, we employ a microfluidics method for the manufacturing of spherical siRNA-loaded LPNs for pulmonary delivery with distinct size distributions with average diameters of approximately 70, 110, and 220 nm. We designed an optically clear, inexpensive thiol-ene polymeric microfluidic chip prototype that is compatible with standard ‘soft-lithography’ techniques, allows for replica molding, and is resistant to harsh solvents. By using SPECT/CT in vivo imaging, we show comparable pulmonary clearance patterns of all three differently sized LPN formulations following intratracheal administration. Also, negligible accumulation in the liver was observed.
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- 2023
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154. Explainable Prediction of Adverse Outcomes Using Clinical Notes
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Lovelace, Justin R., Hurley, Nathan C., Haimovich, Adrian D., and Mortazavi, Bobak J.
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Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
Clinical notes contain a large amount of clinically valuable information that is ignored in many clinical decision support systems due to the difficulty that comes with mining that information. Recent work has found success leveraging deep learning models for the prediction of clinical outcomes using clinical notes. However, these models fail to provide clinically relevant and interpretable information that clinicians can utilize for informed clinical care. In this work, we augment a popular convolutional model with an attention mechanism and apply it to unstructured clinical notes for the prediction of ICU readmission and mortality. We find that the addition of the attention mechanism leads to competitive performance while allowing for the straightforward interpretation of predictions. We develop clear visualizations to present important spans of text for both individual predictions and high-risk cohorts. We then conduct a qualitative analysis and demonstrate that our model is consistently attending to clinically meaningful portions of the narrative for all of the outcomes that we explore., Comment: Machine Learning for Health (ML4H) at NeurIPS 2019 - Extended Abstract
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- 2019
155. The Effect of Erasure Coding on the Burstiness of Packet Loss
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McCann, Bobak and Fendick, Kerry
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Computer Science - Information Theory ,Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing ,Electrical Engineering and Systems Science - Signal Processing - Abstract
The perceived quality of real-time media delivered over IP networks depends on both the rate and burstiness of packet loss. In this paper, we develop a new mathematical model for the residual burstiness of loss under erasure coding. We derive the expected number of consecutive losses in a burst as a function of erasure coding parameters and the network loss probability assuming a Bernoulli model for network losses.
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- 2019
156. Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
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Paine, Tom Le, Gulcehre, Caglar, Shahriari, Bobak, Denil, Misha, Hoffman, Matt, Soyer, Hubert, Tanburn, Richard, Kapturowski, Steven, Rabinowitz, Neil, Williams, Duncan, Barth-Maron, Gabriel, Wang, Ziyu, de Freitas, Nando, and Team, Worlds
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
This paper introduces R2D3, an agent that makes efficient use of demonstrations to solve hard exploration problems in partially observable environments with highly variable initial conditions. We also introduce a suite of eight tasks that combine these three properties, and show that R2D3 can solve several of the tasks where other state of the art methods (both with and without demonstrations) fail to see even a single successful trajectory after tens of billions of steps of exploration.
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- 2019
157. A Survey of Challenges and Opportunities in Sensing and Analytics for Cardiovascular Disorders
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Hurley, Nathan C., Spatz, Erica S., Krumholz, Harlan M., Jafari, Roozbeh, and Mortazavi, Bobak J.
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Electrical Engineering and Systems Science - Signal Processing ,Computer Science - Computers and Society ,Computer Science - Machine Learning - Abstract
Cardiovascular disorders account for nearly 1 in 3 deaths in the United States. Care for these disorders are often determined during visits to acute care facilities, such as hospitals. While the length of stay in these settings represents just a small proportion of patients' lives, they account for a disproportionately large amount of decision making. To overcome this bias towards data from acute care settings, there is a need for longitudinal monitoring in patients with cardiovascular disorders. Longitudinal monitoring can provide a more comprehensive picture of patient health, allowing for more informed decision making. This work surveys the current field of sensing technologies and machine learning analytics that exist in the field of remote monitoring for cardiovascular disorders. We highlight three primary needs in the design of new smart health technologies: 1) the need for sensing technology that can track longitudinal trends in signs and symptoms of the cardiovascular disorder despite potentially infrequent, noisy, or missing data measurements; 2) the need for new analytic techniques that model data captured in a longitudinal, continual fashion to aid in the development of new risk prediction techniques and in tracking disease progression; and 3) the need for machine learning techniques that are personalized and interpretable, allowing for advancements in shared clinical decision making. We highlight these needs based upon the current state-of-the-art in smart health technologies and analytics and discuss the ample opportunities that exist in addressing all three needs in the development of smart health technologies and analytics applied to the field of cardiovascular disorders and care., Comment: 32 pages, 3 figures, to be submitted to ACM Transactions on Computing for Healthcare (HEALTH), Special Issue on Wearable Technologies for Smart Health 2019
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- 2019
158. Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction
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Farzin, Bobak, Czapla, Piotr, and Howard, Jeremy
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Computer Science - Computation and Language - Abstract
Our entry into the HAHA 2019 Challenge placed $3^{rd}$ in the classification task and $2^{nd}$ in the regression task. We describe our system and innovations, as well as comparing our results to a Naive Bayes baseline. A large Twitter based corpus allowed us to train a language model from scratch focused on Spanish and transfer that knowledge to our competition model. To overcome the inherent errors in some labels we reduce our class confidence with label smoothing in the loss function. All the code for our project is included in a GitHub repository for easy reference and to enable replication by others., Comment: IberLEF 2019 Workshop
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- 2019
159. Visualization of Emergency Department Clinical Data for Interpretable Patient Phenotyping
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Hurley, Nathan C., Haimovich, Adrian D., Taylor, R. Andrew, and Mortazavi, Bobak J.
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Computer Science - Human-Computer Interaction ,Computer Science - Machine Learning ,Statistics - Machine Learning ,00A66 68U35 91C20 - Abstract
Visual summarization of clinical data collected on patients contained within the electronic health record (EHR) may enable precise and rapid triage at the time of patient presentation to an emergency department (ED). The triage process is critical in the appropriate allocation of resources and in anticipating eventual patient disposition, typically admission to the hospital or discharge home. EHR data are high-dimensional and complex, but offer the opportunity to discover and characterize underlying data-driven patient phenotypes. These phenotypes will enable improved, personalized therapeutic decision making and prognostication. In this work, we focus on the challenge of two-dimensional patient projections. A low dimensional embedding offers visual interpretability lost in higher dimensions. While linear dimensionality reduction techniques such as principal component analysis are often used towards this aim, they are insufficient to describe the variance of patient data. In this work, we employ the newly-described non-linear embedding technique called uniform manifold approximation and projection (UMAP). UMAP seeks to capture both local and global structures in high-dimensional data. We then use Gaussian mixture models to identify clusters in the embedded data and use the adjusted Rand index (ARI) to establish stability in the discovery of these clusters. This technique is applied to five common clinical chief complaints from a real-world ED EHR dataset, describing the emergent properties of discovered clusters. We observe clinically-relevant cluster attributes, suggesting that visual embeddings of EHR data using non-linear dimensionality reduction is a promising approach to reveal data-driven patient phenotypes. In the five chief complaints, we find between 2 and 6 clusters, with the peak mean pairwise ARI between subsequent training iterations to range from 0.35 to 0.74.
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- 2019
160. Effects of Short Scale Roughness and Wave Breaking Efficiency on Sea Spray Aerosol Production: Multisensor Field Observations
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Hwang, Paul A., Savelyev, Ivan B., Means, Steve L., Anguelova, Magdalena D., Schindall, Jeffrey A., Frick, Glendon M., Dowgiallo, David J., and Bobak, Justin P.
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Physics - Atmospheric and Oceanic Physics - Abstract
Simultaneous measurements of sea spray aerosol (SSA), wind, wave, underwater acoustic noise, and microwave brightness temperature are obtained in the open ocean. These data are analyzed to clarify the ocean surface processes important to SSA production. Parameters are formulated to represent surface processes with characteristic length scales over a broad range, from tens of meters to a few centimeters. The result shows that the correlation coefficients between SSA properties (number, volume and flux) and surface process parameters improve toward the shortest length scale. This suggests that whereas surface wave breaking is a necessary initial and boundary condition, the final state of the atmospheric SSA properties is controlled primarily by turbulent processes characterized by the ocean surface roughness. The investigation also reveals distinct differences of the SSA properties in rising winds and falling winds, with higher efficiency of breaking production in low or falling winds. Previous studies show that the length scale of breaking waves is shorter in mixed seas than in wind seas. Combining the observations together, it is suggestive that larger air cavities are entrained in rising winds (with wind seas more likely). The larger air cavities escape before they can be fully broken down into small bubbles for the subsequent SSA production. In contrast, the shorter breakers in low or falling winds (with mixed seas more likely) trap smaller air cavities that stay underwater longer for more efficient bubble breakup by turbulence.
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- 2019
161. Spin-glass-like ordering in a frustrated $J_1-J_2$ Ising antiferromagnet on a honeycomb lattice
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Žukovič, M., Borovský, M., Bobák, A., Balcerzak, T., and Szałowski, K.
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Condensed Matter - Statistical Mechanics - Abstract
We study the nature of a low-temperature phase in the frustrated honeycomb-lattice Ising model with first- and second-neighbor antiferromagnetic (AF) interactions, $J_1$ and $J_2$, respectively, for $R = J_2/J_1 > 1/4$. It is known that for $R < 1/4$ there is a phase transition at low temperatures to the AF phase. Nevertheless, little is known about the critical behavior of the model for $R > 1/4$, except for recent effective field results which detected no phase transition down to zero temperature. Our Monte Carlo results suggest that for $R > 1/4$ there is at least one peculiar phase transition accompanied by a spin-glass-like freezing to a highly degenerate state consisting of frozen domains with stripe-type AF ordering separated by zero-energy domain walls. In spite of the local ordering within the respective domains there is no ordering among them and thus, unlike in the corresponding square-lattice model with $R > 1/2$, there is no conventional magnetic long-range ordering spanning the entire system., Comment: CSMAG conference contribution, 6 pages, 3 figures
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- 2019
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162. Magnetism of the diluted Ising antiferromagnet in a magnetic field on the Kagome lattice: single-spin cluster approximation
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Bobák, A., Lučivjanský, T., and Žukovič, M.
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Condensed Matter - Statistical Mechanics ,Condensed Matter - Strongly Correlated Electrons - Abstract
An effective-field theory based on the single-spin cluster has been used to study of a diluted spin-$1/2$ Ising antiferromagnet on the Kagome lattice with nearest-neighbor interactions. We observe five plateaus in the magnetization curve of the diluted antiferromagnet when a magnetic field is applied which is in agreement with Monte Carlo calculation. The effect of the site-dilution on the magnetic susceptibility is also investigated and discussed. In particular, we have found that the frustrated Kagome lattice inverse susceptibility fall to zero at $0$K., Comment: 6 pages, 4 figures, work to be presented at CSMAG conference
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- 2019
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163. LHC analysis-specific datasets with Generative Adversarial Networks
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Hashemi, Bobak, Amin, Nick, Datta, Kaustuv, Olivito, Dominick, and Pierini, Maurizio
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High Energy Physics - Experiment ,Computer Science - Machine Learning ,High Energy Physics - Phenomenology - Abstract
Using generative adversarial networks (GANs), we investigate the possibility of creating large amounts of analysis-specific simulated LHC events at limited computing cost. This kind of generative model is analysis specific in the sense that it directly generates the high-level features used in the last stage of a given physics analyses, learning the N-dimensional distribution of relevant features in the context of a specific analysis selection. We apply this idea to the generation of muon four-momenta in $Z \to \mu\mu$ events at the LHC. We highlight how use-case specific issues emerge when the distributions of the considered quantities exhibit particular features. We show how substantial performance improvements and convergence speed-up can be obtained by including regression terms in the loss function of the generator. We develop an objective criterion to assess the geenrator performance in a quantitative way. With further development, a generalization of this approach could substantially reduce the needed amount of centrally produced fully simulated events in large particle physics experiments., Comment: 14 pages, 11 figures
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- 2019
164. Towards an Algebraic Network Information Theory: Simultaneous Joint Typicality Decoding
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Lim, Sung Hoon, Feng, Chen, Pastore, Adriano, Nazer, Bobak, and Gastpar, Michael
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Computer Science - Information Theory - Abstract
Consider a receiver in a multi-user network that wishes to decode several messages. Simultaneous joint typicality decoding is one of the most powerful techniques for determining the fundamental limits at which reliable decoding is possible. This technique has historically been used in conjunction with random i.i.d. codebooks to establish achievable rate regions for networks. Recently, it has been shown that, in certain scenarios, nested linear codebooks in conjunction with "single-user" or sequential decoding can yield better achievable rates. For instance, the compute-forward problem examines the scenario of recovering $L \le K$ linear combinations of transmitted codewords over a $K$-user multiple-access channel (MAC), and it is well established that linear codebooks can yield higher rates. Here, we develop bounds for simultaneous joint typicality decoding used in conjunction with nested linear codebooks, and apply them to obtain a larger achievable region for compute-forward over a $K$-user discrete memoryless MAC. The key technical challenge is that competing codeword tuples that are linearly dependent on the true codeword tuple introduce statistical dependencies, which requires careful partitioning of the associated error events., Comment: 24 pages, 5 figures, submitted to IEEE Transactions on Information Theory
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- 2019
165. Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models
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Ardywibowo, Randy, Zhao, Guang, Wang, Zhangyang, Mortazavi, Bobak, Huang, Shuai, and Qian, Xiaoning
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Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
Emerging wearable sensors have enabled the unprecedented ability to continuously monitor human activities for healthcare purposes. However, with so many ambient sensors collecting different measurements, it becomes important not only to maintain good monitoring accuracy, but also low power consumption to ensure sustainable monitoring. This power-efficient sensing scheme can be achieved by deciding which group of sensors to use at a given time, requiring an accurate characterization of the trade-off between sensor energy usage and the uncertainty in ignoring certain sensor signals while monitoring. To address this challenge in the context of activity monitoring, we have designed an adaptive activity monitoring framework. We first propose a switching Gaussian process to model the observed sensor signals emitting from the underlying activity states. To efficiently compute the Gaussian process model likelihood and quantify the context prediction uncertainty, we propose a block circulant embedding technique and use Fast Fourier Transforms (FFT) for inference. By computing the Bayesian loss function tailored to switching Gaussian processes, an adaptive monitoring procedure is developed to select features from available sensors that optimize the trade-off between sensor power consumption and the prediction performance quantified by state prediction entropy. We demonstrate the effectiveness of our framework on the popular benchmark of UCI Human Activity Recognition using Smartphones., Comment: to appear in AISTATS 2019
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- 2019
166. Stevens-Johnson syndrome and toxic epidermal necrolysis in pregnant patients: A systematic review
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Sharma, Ajay N, Hedayati, Bobak, Mesinkovska, Natasha A, and Worswick, Scott
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Reproductive Medicine ,Biomedical and Clinical Sciences ,Prevention ,Pediatric ,Infant Mortality ,Perinatal Period - Conditions Originating in Perinatal Period ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Reproductive health and childbirth ,Infection ,Good Health and Well Being ,Pregnancy ,Pregnant ,SJS ,Stevens-Johnson syndrome ,TEN ,Toxic epidermal necrolysis - Abstract
BackgroundStevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are two of the most severe dermatologic emergencies. Although pregnant women comprise a subset of individuals at risk for SJS and TEN development, little is known with regard to outcomes and treatment.ObjectiveThis study aimed to conduct a systematic review to characterize the risk factors, outcomes, and treatment of SJS and TEN in pregnant patients and newborns.MethodsA primary literature search was conducted using PubMed in September 2019, using the following search terms entered in separate pairs: pregnant or pregnancy and stevens-johnson or SJS or toxic epidermal necrolysis. Reviews, studies in a language other than English, and articles not including pregnant patients were excluded.ResultsTwenty-six articles were included for review, including a total of 177 patients. The average maternal age for a reaction was 29.9 years, gestational age was 24.9 weeks, and time to reaction after drug initiation was 27.5 days. Approximately 85% of pregnant women in this review were infected with HIV. The most common causative medications were antiretroviral therapy (90% of all cases), antibiotics (3%), and gestational drugs (2%). Of the 94 cases in which outcome data were available, the survival rates of pregnant women and newborns after delivery were 98% and 96%, respectively. Withdrawal of the offending agent and supportive care was often sufficient for treatment, but antibiotics, steroids, and intravenous immunoglobulin were implemented in some cases. Complications included preterm labor, vaginal stenosis, and vaginal adhesions.ConclusionGiven the predominance of studies focusing on the subset of pregnant patients who are infected with HIV, SJS and TEN is most commonly reported in young patients after antiretroviral therapy, primarily nevirapine. Overall mortality is lower than that of the general population, but similar to the expected mortality rates of younger adults. Early recognition and withdrawal of the offending agent is essential to mitigate the distinct consequences of these conditions in the pregnant population.
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- 2020
167. Expression of ACE2, the SARS-CoV-2 Receptor, and TMPRSS2 in Prostate Epithelial Cells.
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Song, Hanbing, Seddighzadeh, Bobak, Cooperberg, Matthew R, and Huang, Franklin W
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Prostate ,Humans ,Pneumonia ,Viral ,Coronavirus Infections ,Peptidyl-Dipeptidase A ,Gene Expression Regulation ,Male ,Pandemics ,Biomarkers ,Betacoronavirus ,Urology & Nephrology ,Clinical Sciences - Published
- 2020
168. Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning
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Baskaran, Lohendran, Al’Aref, Subhi J, Maliakal, Gabriel, Lee, Benjamin C, Xu, Zhuoran, Choi, Jeong W, Lee, Sang-Eun, Sung, Ji Min, Lin, Fay Y, Dunham, Simon, Mosadegh, Bobak, Kim, Yong-Jin, Gottlieb, Ilan, Lee, Byoung Kwon, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, Shin, Sanghoon, Choi, Jung Hyun, Chinnaiyan, Kavitha, Hadamitzky, Martin, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Leipsic, Jonathon A, Raff, Gilbert L, Virmani, Renu, Samady, Habib, Stone, Peter H, Berman, Daniel S, Narula, Jagat, Bax, Jeroen J, Chang, Hyuk-Jae, Min, James K, and Shaw, Leslee J
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Biomedical Imaging ,Heart Disease ,Cardiovascular ,Aged ,Computed Tomography Angiography ,Coronary Vessels ,Deep Learning ,Female ,Heart ,Heart Atria ,Heart Ventricles ,Humans ,Male ,Middle Aged ,General Science & Technology - Abstract
OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level.
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- 2020
169. Random deep neural networks are biased towards simple functions
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De Palma, Giacomo, Kiani, Bobak Toussi, and Lloyd, Seth
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Statistics - Machine Learning ,Condensed Matter - Disordered Systems and Neural Networks ,Computer Science - Machine Learning ,Mathematical Physics ,Quantum Physics - Abstract
We prove that the binary classifiers of bit strings generated by random wide deep neural networks with ReLU activation function are biased towards simple functions. The simplicity is captured by the following two properties. For any given input bit string, the average Hamming distance of the closest input bit string with a different classification is at least sqrt(n / (2{\pi} log n)), where n is the length of the string. Moreover, if the bits of the initial string are flipped randomly, the average number of flips required to change the classification grows linearly with n. These results are confirmed by numerical experiments on deep neural networks with two hidden layers, and settle the conjecture stating that random deep neural networks are biased towards simple functions. This conjecture was proposed and numerically explored in [Valle P\'erez et al., ICLR 2019] to explain the unreasonably good generalization properties of deep learning algorithms. The probability distribution of the functions generated by random deep neural networks is a good choice for the prior probability distribution in the PAC-Bayesian generalization bounds. Our results constitute a fundamental step forward in the characterization of this distribution, therefore contributing to the understanding of the generalization properties of deep learning algorithms.
- Published
- 2018
170. Information-Distilling Quantizers
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Bhatt, Alankrita, Nazer, Bobak, Ordentlich, Or, and Polyanskiy, Yury
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Computer Science - Information Theory - Abstract
Let $X$ and $Y$ be dependent random variables. This paper considers the problem of designing a scalar quantizer for $Y$ to maximize the mutual information between the quantizer's output and $X$, and develops fundamental properties and bounds for this form of quantization, which is connected to the log-loss distortion criterion. The main focus is the regime of low $I(X;Y)$, where it is shown that, if $X$ is binary, a constant fraction of the mutual information can always be preserved using $\mathcal{O}(\log(1/I(X;Y)))$ quantization levels, and there exist distributions for which this many quantization levels are necessary. Furthermore, for larger finite alphabets $2 < |\mathcal{X}| < \infty$, it is established that an $\eta$-fraction of the mutual information can be preserved using roughly $(\log(| \mathcal{X} | /I(X;Y)))^{\eta\cdot(|\mathcal{X}| - 1)}$ quantization levels.
- Published
- 2018
171. Quantum variational algorithms are swamped with traps
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Eric R. Anschuetz and Bobak T. Kiani
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Science - Abstract
Implementations of shallow quantum machine learning models are a promising application of near-term quantum computers, but rigorous results on their trainability are sparse. Here, the authors demonstrate settings where such models are untrainable.
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- 2022
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172. Reliability and predictive validity of two scales of self-rated health in China: results from China Health and Retirement Longitudinal Study (CHARLS)
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Yuwei Pan, Jitka Pikhartova, Martin Bobak, and Hynek Pikhart
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Reliability ,Validity ,Health status indicators ,China ,Longitudinal studies ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background Despite the widespread use of the single item self-rated health (SRH) question, its reliability has never been evaluated in Chinese population. Methods We used data from the China Health and Retirement Longitudinal Study, waves 1–4 (2011–2019). In wave 1, the same SRH question was asked twice, separated by other questions, on a subset of 4533 subjects, allowing us to examine the test–retest reliability of SRH. In addition, two versions of SRH questions (the WHO and US versions) were asked (n = 11,429). Kappa (κ), weighted kappa ( $${\kappa}_{w}$$ κ w ), and polychoric correlation coefficient (ρ) were used for reliability assessment. Cox proportional-hazards models were estimated to assess the predictive validity of SRH measurement for mortality over 7 years of follow up. To do so, relative index of inequality (RII) and slope index of inequality (SII) were estimated for each SRH scale. Results There was moderate to substantial test–retest reliability (κ = 0.54, $${\kappa}_{w}$$ κ w =0.63) of SRH; 31% of respondents who used the same scale twice changed their ratings after answering other questions. There was strong positive association between the two SRH measured by the two scales (ρ > 0.8). Compared with excellent/very good SRH, adjusted hazard ratios (HR) of death are 2.30 (95% CI, 1.70–3.13) for the US version and 1.86 (95% CI, 1.33–2.60) for the WHO version. Using slope indices of inequality, the WHO version estimated slightly larger mortality differences (RII = 3.50, SII = 15.53) than the US version (RII = 3.25, SII = 14.80). Conclusions In Chinese middle-aged and older population, the reliability of SRH is generally good, although the two commonly used versions of SRH scales could not be compared directly. Both indices predict mortality, with similar predictive validity.
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- 2022
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173. Tumor-produced and aging-associated oncometabolite methylmalonic acid promotes cancer-associated fibroblast activation to drive metastatic progression
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Zhongchi Li, Vivien Low, Valbona Luga, Janet Sun, Ethan Earlie, Bobak Parang, Kripa Shobana Ganesh, Sungyun Cho, Jennifer Endress, Tanya Schild, Mengying Hu, David Lyden, Wenbing Jin, Chunjun Guo, Noah Dephoure, Lewis C. Cantley, Ashley M. Laughney, and John Blenis
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Science - Abstract
Methylmalonic acid (MMA) is increased in aging as well as produced by advanced tumors, and can drive pro-aggressive changes in these tumor cells. Here, the authors show that MMA can also act on fibroblasts in the tumor microenvironment, recruiting and activating them to further support tumor progression.
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- 2022
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174. Diabetic retinopathy in African–Americans with end-stage kidney disease: a cross-sectional study on prevalence and impact on quality of life
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Guillermo E Umpierrez, Priyathama Vellanki, Rodolfo J Galindo, Rozalina Grubina McCoy, Limin Peng, Michelle Egeolu, Ramoncito L Caleon, Exaucee Manishimwe, Zohyra E Zabala, Bobak Moazzami, Amany Gerges, Ghazala D O’Keefe, and Jose Navarrete
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Diseases of the endocrine glands. Clinical endocrinology ,RC648-665 - Abstract
Introduction The prevalence, severity, and quality of life (QoL) impact of diabetic retinopathy (DR) among African–Americans (AAs) with end-stage kidney disease (ESKD) undergoing dialysis are unknown.Research design and methods A cross-sectional study was conducted on 93 AA adults with diabetes and ESKD. The diagnosis of DR was based on a review of medical records and/or a positive photograph with a portable hand-held device reviewed by both artificial intelligence software and a retinal specialist. QoL, physical disability social determinants of health (SDoHs) were assessed by standardized questionnaires.Results The prevalence of DR was 75%, with 33% of participants having mild, 9.6% moderate and 57.4% severe DR. A total of 43% had normal visual acuity; 45% had moderate visual impairment; and 12% had severe visual impairment. We found a high burden of disease, multiple SDoH challenges, and low QoL and general health among patients with ESKD. The presence of DR had no significant impact on physical health and QoL compared with participants without DR.Conclusions DR is present in 75% of AA patients with diabetes and ESKD on haemodialysis. ESKD has a significant burden on general health and QoL; however, DR has a minor additional impact on the overall physical health and QoL in people with ESKD.
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- 2023
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175. Importance for humans of recently discovered protein compounds – yolkin and yolk glycopeptide 40, present in the plasma of hen egg yolk
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Aleksandra Zambrowicz, Agnieszka Zabłocka, Dominika Bednarz, and Łukasz Bobak
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yolkin ,yolk glycopeptide 40 ,vitellogenin ,immunomodulatory activity ,neuroprotective activity ,Animal culture ,SF1-1100 - Abstract
ABSTRACT: Vitellogenin (Vt) is considered the primary protein precursor of egg yolk, serving as a source of protein- and lipid-rich nutrients for the developing embryo. However, recent research has revealed that the functions of Vt and Vt-derived polypeptides, such as yolkin (Y) and yolk glycopeptide 40 (YGP40), extend beyond their nutritional roles as a source of amino acids. Emerging evidence has demonstrated that both Y and YGP40 possess immunomodulatory properties and can contribute to host immune defenses. Additionally, Y polypeptides have been shown to exhibit neuroprotective activity, participating in the modulation of neurons’ survival and activity, inhibiting neurodegeneration processes, and improving cognitive functions in rats. These non-nutritional functions not only enhance our understanding of the physiological roles of these molecules during embryonic development but also offer a promising basis for the potential application of these proteins in human health.
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- 2023
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176. Classification of blood pressure during sleep impacts designation of nocturnal nondipping.
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Bobak J Mortazavi, Josefa L Martinez-Brockman, Baylah Tessier-Sherman, Matthew Burg, Mary Miller, Zhale Nowroozilarki, O Peter Adams, Rohan Maharaj, Cruz M Nazario, Maxine Nunez, Marcella Nunez-Smith, and Erica S Spatz
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
The identification of nocturnal nondipping blood pressure (< 10% drop in mean systolic blood pressure from awake to sleep periods), as captured by ambulatory blood pressure monitoring, is a valuable element of risk prediction for cardiovascular disease, independent of daytime or clinic blood pressure measurements. However, capturing measurements, including determination of wake/sleep periods, is challenging. Accordingly, we sought to evaluate the impact of different definitions and algorithms for defining sleep onset on the classification of nocturnal nondipping. Using approaches based upon participant self-reports, applied definition of a common sleep period (12 am -6 am), manual actigraphy, and automated actigraphy we identified changes to the classification of nocturnal nondipping, and conducted a secondary analysis on the potential impact of an ambulatory blood pressure monitor on sleep. Among 61 participants in the Eastern Caribbean Health Outcomes Research Network hypertension study with complete ambulatory blood pressure monitor and sleep data, the concordance for nocturnal nondipping across methods was 0.54 by Fleiss' Kappa (depending on the method, 36 to 51 participants classified as having nocturnal nondipping). Sleep quality for participants with dipping versus nondipping was significantly different for total sleep length when wearing the ambulatory blood pressure monitor (shorter sleep duration) versus not (longer sleep duration), although there were no differences in sleep efficiency or disturbances. These findings indicate that consideration of sleep time measurements is critical for interpreting ambulatory blood pressure. As technology advances to detect blood pressure and sleep patterns, further investigation is needed to determine which method should be used for diagnosis, treatment, and future cardiovascular risk.
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- 2023
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177. Anastomotic biliary stricture following liver transplantation and management analysis: 15 years of experience at a high-volume transplant center
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Eslami, Omid, Moazzami, Bobak, Zabala, Zohyra E., Roushan, Nader, Dashti, Habibollah, Fakhar, Nasir, Saberi, Hazhir, Jafarian, Ali, and Toosi, Mohssen Nassiri
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- 2022
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178. Testing Changes in Communities for the Stochastic Block Model
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Gangrade, Aditya, Venkatesh, Praveen, Nazer, Bobak, and Saligrama, Venkatesh
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Computer Science - Information Theory ,Computer Science - Machine Learning ,Computer Science - Social and Information Networks ,Mathematics - Statistics Theory - Abstract
We propose and analyze the problems of \textit{community goodness-of-fit and two-sample testing} for stochastic block models (SBM), where changes arise due to modification in community memberships of nodes. Motivated by practical applications, we consider the challenging sparse regime, where expected node degrees are constant, and the inter-community mean degree ($b$) scales proportionally to intra-community mean degree ($a$). Prior work has sharply characterized partial or full community recovery in terms of a "signal-to-noise ratio" ($\mathrm{SNR}$) based on $a$ and $b$. For both problems, we propose computationally-efficient tests that can succeed far beyond the regime where recovery of community membership is even possible. Overall, for large changes, $s \gg \sqrt{n}$, we need only $\mathrm{SNR}= O(1)$ whereas a na\"ive test based on community recovery with $O(s)$ errors requires $\mathrm{SNR}= \Theta(\log n)$. Conversely, in the small change regime, $s \ll \sqrt{n}$, via an information-theoretic lower bound, we show that, surprisingly, no algorithm can do better than the na\"ive algorithm that first estimates the community up to $O(s)$ errors and then detects changes. We validate these phenomena numerically on SBMs and on real-world datasets as well as Markov Random Fields where we only observe node data rather than the existence of links., Comment: Version 3 includes material on unbalanced but linearly sized communities. This version is to appear in NeurIPS 2019
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- 2018
179. Phase Diagram of the $J_1$ - $J_2$ Frustrated Anisotropic Antiferromagnet with Spin $S=1$ on the Quadratic Lattice
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Balcerzak, T., Szałowski, K., Bobák, A., and Žukovič, M.
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Condensed Matter - Statistical Mechanics - Abstract
In the paper the phase diagram of $J_1-J_2$ frustrated antiferromagnet with spin $S=1$ and single-ion anisotropy is studied on the planar quadratic lattice in the cluster approximation. The Bogolyubov inequality is adopted for the Gibbs energy calculation for the case of $2 \times 2$ and $4 \times 4$ clusters. On this basis, the ranges of existence of the anfiferromagnetic, superantiferromagnetic and paramagnetic phases are investigated for the antiferromagnetic nearest-neighbour ($J_1<0$) and next-nearest-neighbour ($J_2<0$) interactions. In particular, the occurrence of tricritical and triple points is discussed and a comparison between the results for $2 \times 2$ and $4 \times 4$ clusters is made. The results are also compared with the classical MFA method, adopted here for the model in question, as well as with selected literature results for particular choices of interaction parameters.
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- 2018
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180. Thermodynamic and critical properties of an antiferromagnetically stacked triangular Ising antiferromagnet in a field
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Žukovič, M., Borovský, M., and Bobák, A.
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Condensed Matter - Statistical Mechanics - Abstract
We study a stacked triangular lattice Ising model with both intra- and inter-plane antiferromagnetic interactions in a field, by Monte Carlo simulation. We find only one phase transition from a paramagnetic to a partially disordered phase, which is of second order and 3D XY universality class. At low temperatures we identify two highly degenerate phases: at smaller (larger) fields the system shows long-range ordering in the stacking direction (within planes) but not in the planes (stacking direction). Nevertheless, crossovers to these phases do not have a character of conventional phase transitions but rather linear-chain-like excitations., Comment: 18 pages, 8 figures
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- 2018
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181. Predicting the effects of supplemental EPA and DHA on the omega-3 index
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Walker, Rachel E, Jackson, Kristina Harris, Tintle, Nathan L, Shearer, Gregory C, Bernasconi, Aldo, Masson, Serge, Latini, Roberto, Heydari, Bobak, Kwong, Raymond Y, Flock, Michael, Kris-Etherton, Penny M, Hedengran, Anne, Carney, Robert M, Skulas-Ray, Ann, Gidding, Samuel S, Dewell, Antonella, Gardner, Christopher D, Grenon, S Marlene, Sarter, Barbara, Newman, John W, Pedersen, Theresa L, Larson, Mark K, and Harris, William S
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Biomedical and Clinical Sciences ,Nutrition and Dietetics ,Dietary Supplements ,Nutrition ,Prevention ,Complementary and Integrative Health ,Women's Health ,3.3 Nutrition and chemoprevention ,Bayes Theorem ,Docosahexaenoic Acids ,Eicosapentaenoic Acid ,Erythrocytes ,Female ,Humans ,Male ,Middle Aged ,Models ,Biological ,n-3 fatty acids ,omega-3 index ,dietary supplements ,EPA ,DHA ,statistical models ,n–3 fatty acids ,Engineering ,Medical and Health Sciences ,Nutrition & Dietetics ,Clinical sciences ,Nutrition and dietetics - Abstract
BackgroundSupplemental long-chain omega-3 (n-3) fatty acids (EPA and DHA) raise erythrocyte EPA + DHA [omega-3 index (O3I)] concentrations, but the magnitude or variability of this effect is unclear.ObjectiveThe purpose of this study was to model the effects of supplemental EPA + DHA on the O3I.MethodsDeidentified data from 1422 individuals from 14 published n-3 intervention trials were included. Variables considered included dose, baseline O3I, sex, age, weight, height, chemical form [ethyl ester (EE) compared with triglyceride (TG)], and duration of treatment. The O3I was measured by the same method in all included studies. Variables were selected by stepwise regression using the Bayesian information criterion.ResultsIndividuals supplemented with EPA + DHA (n = 846) took a mean ± SD of 1983 ± 1297 mg/d, and the placebo controls (n = 576) took none. The mean duration of supplementation was 13.6 ± 6.0 wk. The O3I increased from 4.9% ± 1.7% to 8.1% ± 2.7% in the supplemented individuals ( P
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- 2019
182. Association of polymorphisms of genes SLC30A8 and MC4R with the prognosis of the development of type 2 diabetes mellitus
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E. S. Mel’nikova, S. V. Mustafina, O. D. Rymar, A. A. Ivanova, L. V. Shcherbakova, M. Bobak, S. K. Maljutina, M. I. Voevoda, and V. N. Maksimov
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type 2 diabetes mellitus ,single nucleotide polymorphism ,rs13266634 ,slc30a8 ,rs17782313 ,mc4r ,prognosis ,risk meter ,Nutritional diseases. Deficiency diseases ,RC620-627 - Abstract
BACKGROUND: The prevalence of Type 2 diabetes mellitus (T2DM) has reached epidemic proportions and it is estimated to affect over 400 million people worldwide. Moreover, the incidence of diabetes is expected to continue to rise and it is projected to affect nearly one of the three individuals by the year 2050. These alarming projections suggest that there is an urgent need for the development and implementation of novel prevention and treatment strategies to combat the rise in T2DM.AIM: To study the possibility of using polymorphisms of genes SLC30A8 and MC4R as markers for predicting the development of T2D in the population of Novosibirsk.MATERIALS AND METHODS: On the basis of prospective follow-up of a representative population sample of residents of Novosibirsk (The HAPIEE Project), 2 groups were formed according to the “case-control” principle (case — people who had diabetes mellitus 2 over 10 years of follow-up, and control — people who did not developed disorders of carbohydrate metabolism). T2D group (n = 443, mean age 56.2 ± 6.7 years, men — 29.6%, women — 70.4%), control group (n = 532, mean age 56.1 ± 7.1 years, men — 32.7%, women — 67.3%). DNA was isolated by phenol-chloroform extraction. Genotyping was performed by the method of polymerase chain reaction with subsequent analysis of restriction fragment length polymorphism, polymerase chain reaction in real time. Statistical processing was carried out using the SPSS 16.0 software package.RESULTS: Genotype TT rs13266634 of the SLC30A8 gene was associated with the risk of developing T2D (relative risk — RR 1.51, 95% confidence interval — CI 1.11–2.05, p =0.008). The CC genotype rs13266634 of the SLC30A8 gene was associated with a protective effect against T2D (RR 0.57, 95% CI 0.35–0.92, p=0.026). No significant effect of rs17782313 of the MC4R gene on the risk of developing T2D was found.CONCLUSION: The rs13266634 polymorphism of the SLC30A8 gene confirmed its association with the prognosis of the development of T2D, which indicates the possibility of considering it as a candidate for inclusion in a diabetes risk score. The association between polymorphisms rs17782313 of the MC4R gene and the prognosis of the development of T2D was not found.
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- 2022
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183. Association between marital status and age dynamics of cognitive functions in ageing in a Russian population sample
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A. V. Titarenko, S. V. Shishkin, L. V. Shcherbakova, E. G. Verevkin, J. A. Hubacek, M. Bobak, and S. K. Malyutina
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cognitive functions ,family status ,population ,ageing ,cognitive decline ,hapiee cohort ,Medicine - Abstract
Introduction. The identification of risk factors for cognitive decline during ageing is of great importance for prevention of dementia. Being married or cohabited is considered a protective factor for health. The impact of marital status on age-related decrease of cognitive functions (CF) is understudied.The aim of the study was to investigate the relationship between the indicators of CF and marital status in a cross-sectional analysis and in 2 serial measurements over 9 years in a population sample of middle to older age in Russia.Materials and methods. The study was based on a random population sample of men and women aged 45–69 years old examined at baseline in 2003–2005 in Novosibirsk (n = 9360, HAPIEE project). Present analysis included a subsample of persons with repeated serial measurements – 3153 people. The average follow-up period was 9.2 (SD = 0.7) years. CF was assessed using standard validated methods, including immediate and delayed recall of 10 words, semantic verbal fluency and letter cancellation test. Marital status was determined by standardized questionnaires, groups of single and married/cohabiting participants were identified.Results. In studied population sample (n = 3153, 62% of women), the mean age of participants at baseline examination was 60.3 ± 6.8 years old, and at follow-up examination – 69.5 ± 6.9 years old. During the 9-year follow-up, a significant negative dynamics of the studied cognitive domains (p
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- 2022
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184. Stress Perfusion Cardiac Magnetic Resonance Imaging With a 3.0-Tesla Scanner for Myocardial Viability in a Patient With a Conditional PacemakerNovel Teaching Points
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Pouya Motazedian, MD, Graeme Prosperi-Porta, MD, MASc, Mobeen Ahmed, MBBS, Moiz Hafeez, MD, MSc, Naeem Merchant, MD, and Bobak Heydari, MD, MPH
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Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Abstract
Cardiac magnetic resonance (CMR) imaging provides images with high spatial and temporal resolution, with high diagnostic and prognostic performance. An abundance of data indicate the safety and efficacy of noncardiac magnetic resonance imaging at both 1.5 Tesla (T) and 3T in patients with cardiac implantable electronic devices (CIEDs). Safety and efficacy have also been evaluated for stress perfusion (SP)-CMR for pateints with CIEDs, using 1.5T scanners, but no previous reports have been made of SP-CMR using 3T scanners. Herein, we report a case of a patient with a CIED who successfully and safely underwent SP-CMR imaging using a 3T scanner. Résumé: L’imagerie par résonance magnétique cardiaque (IRMC) procure des images à haute résolution spatiale et temporelle en plus d’offrir une capacité diagnostique et pronostique élevée, mais une multitude de données mettent en lumière l’innocuité et l’efficacité de l’imagerie non cardiaque réalisée au moyen d’appareils d’IRM produisant un champ magnétique de 1,5 ou de 3 teslas (T) chez des patients porteurs d’un dispositif cardiaque électronique implantable (DCEI). L’innocuité et l’efficacité de l’évaluation de la perfusion à l’effort (EPE) par IRMC ont aussi été évaluées chez des patients porteurs d'un DCEI au moyen d’appareils produisant un champ magnétique de 1,5 T, mais pas au moyen d’appareils produisant un champ magnétique de 3 T. Nous rapportons ici le cas d’un patient porteur d’un DCEI ayant subi avec succès et en toute sécurité une EPE par IRMC réalisée au moyen d’un appareil produisant un champ magnétique de 3 T.
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- 2022
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185. Automated Diet Capture Using Voice Alerts and Speech Recognition on Smartphones: Pilot Usability and Acceptability Study
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Lucy Chikwetu, Shaundra Daily, Bobak J Mortazavi, and Jessilyn Dunn
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Medicine - Abstract
BackgroundEffective monitoring of dietary habits is critical for promoting healthy lifestyles and preventing or delaying the onset and progression of diet-related diseases, such as type 2 diabetes. Recent advances in speech recognition technologies and natural language processing present new possibilities for automated diet capture; however, further exploration is necessary to assess the usability and acceptability of such technologies for diet logging. ObjectiveThis study explores the usability and acceptability of speech recognition technologies and natural language processing for automated diet logging. MethodsWe designed and developed base2Diet—an iOS smartphone application that prompts users to log their food intake using voice or text. To compare the effectiveness of the 2 diet logging modes, we conducted a 28-day pilot study with 2 arms and 2 phases. A total of 18 participants were included in the study, with 9 participants in each arm (text: n=9, voice: n=9). During phase I of the study, all 18 participants received reminders for breakfast, lunch, and dinner at preselected times. At the beginning of phase II, all participants were given the option to choose 3 times during the day to receive 3 times daily reminders to log their food intake for the remainder of the phase, with the ability to modify the selected times at any point before the end of the study. ResultsThe total number of distinct diet logging events per participant was 1.7 times higher in the voice arm than in the text arm (P=.03, unpaired t test). Similarly, the total number of active days per participant was 1.5 times higher in the voice arm than in the text arm (P=.04, unpaired t test). Furthermore, the text arm had a higher attrition rate than the voice arm, with only 1 participant dropping out of the study in the voice arm, while 5 participants dropped out in the text arm. ConclusionsThe results of this pilot study demonstrate the potential of voice technologies in automated diet capturing using smartphones. Our findings suggest that voice-based diet logging is more effective and better received by users compared to traditional text-based methods, underscoring the need for further research in this area. These insights carry significant implications for the development of more effective and accessible tools for monitoring dietary habits and promoting healthy lifestyle choices.
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- 2023
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186. Investigation of SARS-CoV-2 seroprevalence in relation to natural infection and vaccination between October 2020 and September 2021 in the Czech Republic: a prospective national cohort study
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Martin Bobak, Hynek Pikhart, Jana Klánová, Pavel Piler, Vojtěch Thon, Tomáš Pavlík, Lenka Andrýsková, Kamil Doležel, and David Kostka
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Medicine - Abstract
Objective Examine changes in SARS-CoV-2 seropositivity before and during the national vaccination campaign in the Czech Republic.Design Prospective national population-based cohort study.Setting Masaryk University, RECETOX, Brno.Participants 22 130 persons provided blood samples at two time points approximately 5–7 months apart, between October 2020 and March 2021 (phase I, before vaccination), and between April and September 2021 (during vaccination campaign).Outcome measures Antigen-specific humoral immune response was analysed by detection of IgG antibodies against the SARS-CoV-2 spike protein by commercial chemiluminescent immunoassays. Participants completed a questionnaire that included personal information, anthropometric data, self-reported results of previous RT-PCR tests (if performed), history of symptoms compatible with COVID-19 and records of COVID-19 vaccination. Seroprevalence was compared between calendar periods, previous RT-PCR results, vaccination and other individual characteristics.Results Before vaccination (phase I), seroprevalence increased from 15% in October 2020 to 56% in March 2021. By the end of phase II, in September 2021, prevalence increased to 91%; the highest seroprevalence was seen among vaccinated persons with and without previous SARS-CoV-2 infection (99.7% and 97.2%, respectively), while the lowest seroprevalence was found among unvaccinated persons with no signs of disease (26%). Vaccination rates were lower in persons who were seropositive in phase I but increased with age and body mass index. Only 9% of unvaccinated subjects who were seropositive in phase I became seronegative by phase II.Conclusions The rapid increase in seropositivity during the second wave of the COVID-19 epidemic (covered by phase I of this study) was followed by a similarly steep rise in seroprevalence during the national vaccination campaign, reaching seropositivity rates of over 97% among vaccinated persons.
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- 2023
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187. Comparison of social gradient in cardiometabolic health in Czechia and Venezuela: a cross-sectional study
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Jeffrey I Mechanick, Martin Bobak, Hynek Pikhart, Anna Bartoskova Polcrova, Ramfis Nieto-Martinez, Geraldo A Maranhao Neto, Maria M Infante-Garcia, Jose Medina-Inojosa, and Juan P Gonzalez-Rivas
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Medicine - Abstract
Objectives This study compared the relationships of social determinants with cardiometabolic risk in different socioeconomic contexts: sociopolitically unstable Venezuela (VE) and stable Czechia (CZ).Design: cross-sectional analysis involving two population-based studies.Setting Brno, Czechia and 23 cities of Venezuela.Participants 25–64 years old subjects from CZ (2013–2014, n=1579, 56% females) and VE (2014–2017, n=1652, 70% females).Main outcome measures The composite cardiometabolic risk score (CMRS) (scaled 0–8) was calculated using eight biomarkers (body mass index, waist circumference, blood glucose, systolic and diastolic blood pressure, total and high-density lipoprotein-cholesterol, triglycerides). Social characteristics included education in both countries, income in CZ and a composite measure of social position (SP) in VE. Sex stratified ordinal regression examined the social gradient in having less favourable CMRS.Results In CZ, men and women with low education and women with low income had higher odds of higher CMRS compared with those with high education and income with OR 1.45 (95% CI 1.01 to 2.21), 2.29 (95% CI 1.62 to 3.24) and 1.69 (95% CI 1.23 to 2.35). In VE, women with low education and low SP had higher odds to have higher CMRS OR 1.47 (95% CI 1.09 to 1.97) and 1.51 (95% CI 1.16 to 1.97), while men with low education and low SP had lower odds to have higher CMRS OR 0.64 (95% CI 0.41 to 1.00) and 0.61 (95% CI 0.40 to 0.97), compared with those with high education and high SP. Independently of age, sex and socioeconomic characteristics, Venezuelans had higher odds to have higher CMRS than Czechs (OR 2.70; 95% CI 2.37 to 3.08).Conclusions The results suggest that the associations of socioeconomic status indices and cardiometabolic risk differed between CZ and VE, likely reflecting differences in the social environment among countries. Further research is needed to confirm and quantify these differences.
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- 2023
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188. ATHLOS Healthy Aging Scale score as the predictor of all-cause mortality in Poland and Czechia
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Magdalena Kozela, Andrzej Pająk, Krystyna Szafraniec, José Luis Ayuso-Mateos, Martin Bobak, Wentian Lu, Hynek Pikhart, Maciej Polak, Albert Sanchez-Niubo, Urszula Stepaniak, and Josep Maria Haro
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healthy aging ,scale ,mortality ,Central and Eastern Europe (CEE) ,aging ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundThe ATHLOS consortium (Aging Trajectories of Health–Longitudinal Opportunities and Synergies) used data from several aging cohorts to develop a novel scale measuring healthy aging comprehensively and globally (ATHLOS Healthy Aging Scale). In the present study, we assessed the predictive performance of the ATHLOS Healthy Aging Scale for all-cause mortality in middle-aged and older adults.MethodsData from the Polish and Czech HAPIEE (Health Alcohol and Psychosocial factors In Eastern Europe) prospective cohorts were used. There were 10,728 Poles and 8,857 Czechs recruited. The ATHLOS Healthy Aging Scale score was calculated for all participants using data from the baseline examination carried out from 2002 to 2005. The follow-up for all-cause mortality was completed over 14 years. The associations between quintiles of the ATHLOS Healthy Aging Scale and all-cause mortality were estimated using Cox proportional hazards models.ResultsA total of 9,922 Polish and 8,518 Czech participants contributed ATHLOS Healthy Aging Scale and mortality data with 1,828 and 1,700 deaths, respectively. After controlling for age, the ATHLOS Healthy Aging Scale score was strongly associated with mortality in a graded fashion for both genders and countries (hazard ratios for lowest vs. highest quintile were 2.98 and 1.96 for Czech and Polish women and 2.83 and 2.66 for Czech and Polish men, respectively). The associations were only modestly attenuated by controlling for education, economic activity, and smoking, and there was further modest attenuation after additional adjustment for self-rated health.ConclusionThe novel ATHLOS Healthy Aging Scale is a good predictor of all-cause mortality in Central European urban populations, suggesting that this comprehensive measure is a useful tool for the assessment of the future health trajectories of older persons.
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- 2023
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189. Predictive importance of the visceral adiposity index and atherogenic index of plasma of all-cause and cardiovascular disease mortality in middle-aged and elderly Lithuanian population
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Abdonas Tamosiunas, Dalia Luksiene, Daina Kranciukaite-Butylkiniene, Ricardas Radisauskas, Diana Sopagiene, and Martin Bobak
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visceral adiposity index ,atherogenic index of plasma ,cardiovascular diseases ,mortality ,gender ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundTwo indices: visceral adiposity index (VAI) and atherogenic index of plasma (AIP) during several recent years were implemented into epidemiological studies for predicting of cardiovascular diseases (CVD) and mortality risk. Our study aimed to evaluate the association of VAI and AIP with the risk of all-cause and CVD mortality among the Lithuanian urban population aged 45–72 years.MethodsIn the baseline survey (2006–2008), 7,115 men and women 45–72 years of age were examined within the framework of the international study Health, Alcohol and Psychosocial Factors in Eastern Europe (HAPIEE). Six thousand six hundred and seventy-one participants (3,663 women and 3,008 men) were available for statistical analysis (after excluding 429 respondents with the missed information on study variables) and for them, VAI and AIP were calculated. The questionnaire evaluated lifestyle behaviors, including smoking and physical activity. All participants in the baseline survey were followed up for all-cause and CVD mortality events until December 31st, 2020. Multivariable Cox regression models were applied for statistical data analysis.ResultsAfter accounting for several potential confounders, higher levels of VAI (compared 5th quintile to 1st quintile) were associated with significantly higher CVD mortality in men [Hazards ratio (HR) = 1.38] and all-cause mortality in women (HR = 1.54) after 10-year follow-up. CVD mortality significantly increased in men with 0 the highest AIP quintile compared with that for the lowest quintile (HR = 1.40). In women, all-cause mortality was significantly higher for the 4th quintile of AIP as compared with the 1st quintile (HR = 1.36).ConclusionsHigh-risk VAI levels were statistically significantly associated with all-cause mortality risk in men and women groups. The higher AIP level (5th quintile vs. 1st quintile—in men and 4th quintile vs. 1st quintile—in women) was significantly associated with increased mortality from CVD in the men group and increased all-cause mortality in the women group.
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- 2023
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190. Work stress, overcommitment personality and alcohol consumption based on the Effort–Reward Imbalance model: A population–based cohort study
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Sung-Wei Chen, Hynek Pikhart, Anne Peasey, Andrzej Pajak, Ruzena Kubinova, Sofia Malyutina, and Martin Bobak
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Work stress ,Effort–Reward Imbalance ,Personality ,Overcommitment ,Alcohol consumption ,Drinking ,Public aspects of medicine ,RA1-1270 ,Social sciences (General) ,H1-99 - Abstract
Work stress has been extensively supported to predict health outcomes like health behaviors. Evidence has linked work stress and personality independently to health, but the interrelationships between work stress and personality and their joint effects on health might deserve more attention in research. This study attempts to integrate recent developments in psychological research (diverse roles of personality in stress processes) into the well–established Effort–Reward Imbalance (ERI) model for work stress. Based on the ERI model, this population–based cohort study aims to investigate the relationships between work stress, personality and alcohol consumption; it particularly focuses on potential roles of overcommitment (OC) personality in ERI–drinking relations, including modifying, antecedent, mediator or direct effects. This two–wave cohort study was conducted in population samples of 3782 men and 3731 women (aged 45–69 years) from Czech Republic, Poland and Russia. Alcohol consumption was assessed by three drinking outcomes: binge drinking, heavy drinking and problem drinking. To assess modifying effect of OC in ERI–drinking relations, logistic regression was used. To assess antecedent or mediator role of OC in ERI–drinking relations, path analysis with the autoregressive and cross–lagged model was conducted. The results showed that OC had no significantly modifying effect in ERI–drinking relations. OC and ERI might have bidirectional relationships in the average follow–up period of 3.5 years; the effect of OC on ERI was remarkably stronger than the reversed causation. Antecedent role of OC in ERI–drinking relationship was significant, but mediator role of OC was not. In conclusion, our findings imply that “antecedent role” of OC in ERI–drinking relations is significant and promising as a potential target for individual intervention; future interventions are suggested to identify and target potential cognitive–behavioral mechanisms via which personality might influence work stress and subsequently health behaviors.
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- 2023
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191. The Impact of Semester-Long Authentic Research on Student Experiences
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Fornsaglio, Jamie L., Sheffler, Zachary, Hull, David C., and Bobak, Angela
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Contemporary research suggests an urgent need for educators to improve the quality of STEM teaching and learning. We developed a semester-long model curriculum for STEM teaching and learning. The overarching goal of this study was to establish an authentic inquiry approach to advanced laboratory courses that is interdisciplinary, collaborative, and utilizes algorithm-generated student grouping strategies. We assessed the effects of the model curriculum on student understanding of scientific concepts and processes, perceptions of their learning, and attitudes toward science and research. Students in a biology laboratory course collaborated with students in biochemistry and mathematics courses. The differences between pre- and post-Participant Perception Indicator (PPI) survey responses (relative to the baseline semester) indicated that, when paired with similarly-performing students, higher-performing students are more likely to report improvements in "understanding," "skills," "integration of learning," and "meeting learning objectives." Mid-level performing students report significant improvements in "understanding," "attitudes," "integration of learning," and "meeting learning objectives." Lower-level performing students report regressions. Performance quiz data reveal improvements in understanding of scientific concepts following the implementation of our model curriculum. Our findings warrant future studies on the relationships among grouping, student perceptions, and academic performance.
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- 2021
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192. Author Correction: Palaeogenomics of Upper Palaeolithic to Neolithic European hunter-gatherers
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Posth, Cosimo, Yu, He, Ghalichi, Ayshin, Rougier, Hélène, Crevecoeur, Isabelle, Huang, Yilei, Ringbauer, Harald, Rohrlach, Adam B., Nägele, Kathrin, Villalba-Mouco, Vanessa, Radzeviciute, Rita, Ferraz, Tiago, Stoessel, Alexander, Tukhbatova, Rezeda, Drucker, Dorothée G., Lari, Martina, Modi, Alessandra, Vai, Stefania, Saupe, Tina, Scheib, Christiana L., Catalano, Giulio, Pagani, Luca, Talamo, Sahra, Fewlass, Helen, Klaric, Laurent, Morala, André, Rué, Mathieu, Madelaine, Stéphane, Crépin, Laurent, Caverne, Jean-Baptiste, Bocaege, Emmy, Ricci, Stefano, Boschin, Francesco, Bayle, Priscilla, Maureille, Bruno, Le Brun-Ricalens, Foni, Bordes, Jean-Guillaume, Oxilia, Gregorio, Bortolini, Eugenio, Bignon-Lau, Olivier, Debout, Grégory, Orliac, Michel, Zazzo, Antoine, Sparacello, Vitale, Starnini, Elisabetta, Sineo, Luca, van der Plicht, Johannes, Pecqueur, Laure, Merceron, Gildas, Garcia, Géraldine, Leuvrey, Jean-Michel, Garcia, Coralie Bay, Gómez-Olivencia, Asier, Połtowicz-Bobak, Marta, Bobak, Dariusz, Le Luyer, Mona, Storm, Paul, Hoffmann, Claudia, Kabaciński, Jacek, Filimonova, Tatiana, Shnaider, Svetlana, Berezina, Natalia, González-Rabanal, Borja, González Morales, Manuel R., Marín-Arroyo, Ana B., López, Belén, Alonso-Llamazares, Carmen, Ronchitelli, Annamaria, Polet, Caroline, Jadin, Ivan, Cauwe, Nicolas, Soler, Joaquim, Coromina, Neus, Rufí, Isaac, Cottiaux, Richard, Clark, Geoffrey, Straus, Lawrence G., Julien, Marie-Anne, Renhart, Silvia, Talaa, Dorothea, Benazzi, Stefano, Romandini, Matteo, Amkreutz, Luc, Bocherens, Hervé, Wißing, Christoph, Villotte, Sébastien, de Pablo, Javier Fernández-López, Gómez-Puche, Magdalena, Esquembre-Bebia, Marco Aurelio, Bodu, Pierre, Smits, Liesbeth, Souffi, Bénédicte, Jankauskas, Rimantas, Kozakaitė, Justina, Cupillard, Christophe, Benthien, Hartmut, Wehrberger, Kurt, Schmitz, Ralf W., Feine, Susanne C., Schüler, Tim, Thevenet, Corinne, Grigorescu, Dan, Lüth, Friedrich, Kotula, Andreas, Piezonka, Henny, Schopper, Franz, Svoboda, Jiří, Sázelová, Sandra, Chizhevsky, Andrey, Khokhlov, Aleksandr, Conard, Nicholas J., Valentin, Frédérique, Harvati, Katerina, Semal, Patrick, Jungklaus, Bettina, Suvorov, Alexander, Schulting, Rick, Moiseyev, Vyacheslav, Mannermaa, Kristiina, Buzhilova, Alexandra, Terberger, Thomas, Caramelli, David, Altena, Eveline, Haak, Wolfgang, and Krause, Johannes
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- 2023
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193. Lifestyle factors and psychological well-being: 10-year follow-up study in Lithuanian urban population
- Author
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Sapranaviciute-Zabazlajeva, Laura, Sileikiene, Lolita, Luksiene, Dalia, Tamosiunas, Abdonas, Radisauskas, Ricardas, Milvidaite, Irena, and Bobak, Martin
- Published
- 2022
- Full Text
- View/download PDF
194. Interface astrogliosis in contact sport head impacts and military blast exposure
- Author
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Babcock, Katharine J., Abdolmohammadi, Bobak, Kiernan, Patrick T., Mahar, Ian, Cherry, Jonathan D., Alvarez, Victor E., Goldstein, Lee E., Stein, Thor D., McKee, Ann C., and Huber, Bertrand R.
- Published
- 2022
- Full Text
- View/download PDF
195. Automated multilabel diagnosis on electrocardiographic images and signals
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Sangha, Veer, Mortazavi, Bobak J., Haimovich, Adrian D., Ribeiro, Antônio H., Brandt, Cynthia A., Jacoby, Daniel L., Schulz, Wade L., Krumholz, Harlan M., Ribeiro, Antonio Luiz P., and Khera, Rohan
- Published
- 2022
- Full Text
- View/download PDF
196. Mid-wall striae fibrosis predicts heart failure admission, composite heart failure events, and life-threatening arrhythmias in dilated cardiomyopathy
- Author
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Purmah, Yanish, Cornhill, Aidan, Lei, Lucy Y., Dykstra, Steven, Mikami, Yoko, Satriano, Alessandro, Labib, Dina, Flewitt, Jacqueline, Rivest, Sandra, Sandonato, Rosa, Seib, Michelle, Howarth, Andrew G., Lydell, Carmen P., Heydari, Bobak, Merchant, Naeem, Bristow, Michael, Kolman, Louis, Fine, Nowell M., and White, James A.
- Published
- 2022
- Full Text
- View/download PDF
197. Tumor-produced and aging-associated oncometabolite methylmalonic acid promotes cancer-associated fibroblast activation to drive metastatic progression
- Author
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Li, Zhongchi, Low, Vivien, Luga, Valbona, Sun, Janet, Earlie, Ethan, Parang, Bobak, Shobana Ganesh, Kripa, Cho, Sungyun, Endress, Jennifer, Schild, Tanya, Hu, Mengying, Lyden, David, Jin, Wenbing, Guo, Chunjun, Dephoure, Noah, Cantley, Lewis C., Laughney, Ashley M., and Blenis, John
- Published
- 2022
- Full Text
- View/download PDF
198. A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project
- Author
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Barmpas, Petros, Tasoulis, Sotiris, Vrahatis, Aristidis G., Georgakopoulos, Spiros V., Anagnostou, Panagiotis, Prina, Matthew, Ayuso-Mateos, José Luis, Bickenbach, Jerome, Bayes, Ivet, Bobak, Martin, Caballero, Francisco Félix, Chatterji, Somnath, Egea-Cortés, Laia, García-Esquinas, Esther, Leonardi, Matilde, Koskinen, Seppo, Koupil, Ilona, Paja̧k, Andrzej, Prince, Martin, Sanderson, Warren, Scherbov, Sergei, Tamosiunas, Abdonas, Galas, Aleksander, Haro, Josep Maria, Sanchez-Niubo, Albert, Plagianakos, Vassilis P., and Panagiotakos, Demosthenes
- Published
- 2022
- Full Text
- View/download PDF
199. A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations
- Author
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Khera, Rohan, Mortazavi, Bobak J., Sangha, Veer, Warner, Frederick, Patrick Young, H., Ross, Joseph S., Shah, Nilay D., Theel, Elitza S., Jenkinson, William G., Knepper, Camille, Wang, Karen, Peaper, David, Martinello, Richard A., Brandt, Cynthia A., Lin, Zhenqiu, Ko, Albert I., Krumholz, Harlan M., Pollock, Benjamin D., and Schulz, Wade L.
- Published
- 2022
- Full Text
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200. Reliability and predictive validity of two scales of self-rated health in China: results from China Health and Retirement Longitudinal Study (CHARLS)
- Author
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Pan, Yuwei, Pikhartova, Jitka, Bobak, Martin, and Pikhart, Hynek
- Published
- 2022
- Full Text
- View/download PDF
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