31 research outputs found
Fast Nonlinear Vector Quantile Regression
Quantile regression (QR) is a powerful tool for estimating one or more
conditional quantiles of a target variable given explanatory
features . A limitation of QR is that it is only
defined for scalar target variables, due to the formulation of its objective
function, and since the notion of quantiles has no standard definition for
multivariate distributions. Recently, vector quantile regression (VQR) was
proposed as an extension of QR for vector-valued target variables, thanks to a
meaningful generalization of the notion of quantiles to multivariate
distributions via optimal transport. Despite its elegance, VQR is arguably not
applicable in practice due to several limitations: (i) it assumes a linear
model for the quantiles of the target given the
features ; (ii) its exact formulation is intractable
even for modestly-sized problems in terms of target dimensions, number of
regressed quantile levels, or number of features, and its relaxed dual
formulation may violate the monotonicity of the estimated quantiles; (iii) no
fast or scalable solvers for VQR currently exist. In this work we fully address
these limitations, namely: (i) We extend VQR to the non-linear case, showing
substantial improvement over linear VQR; (ii) We propose {vector monotone
rearrangement}, a method which ensures the quantile functions estimated by VQR
are monotone functions; (iii) We provide fast, GPU-accelerated solvers for
linear and nonlinear VQR which maintain a fixed memory footprint, and
demonstrate that they scale to millions of samples and thousands of quantile
levels; (iv) We release an optimized python package of our solvers as to
widespread the use of VQR in real-world applications.Comment: 35 pages, 15 figures, code: https://github.com/vistalab-technion/vq
PhysioZoo: A Novel Open Access Platform for Heart Rate Variability Analysis of Mammalian Electrocardiographic Data
Background: The time variation between consecutive heartbeats is commonly referred to as heart rate variability (HRV). Loss of complexity in HRV has been documented in several cardiovascular diseases and has been associated with an increase in morbidity and mortality. However, the mechanisms that control HRV are not well understood. Animal experiments are the key to investigating this question. However, to date, there are no standard open source tools for HRV analysis of mammalian electrocardiogram (ECG) data and no centralized public databases for researchers to access.Methods: We created an open source software solution specifically designed for HRV analysis from ECG data of multiple mammals, including humans. We also created a set of public databases of mammalian ECG signals (dog, rabbit and mouse) with manually corrected R-peaks (>170,000 annotations) and signal quality annotations. The platform (software and databases) is called PhysioZoo.Results: PhysioZoo makes it possible to load ECG data and perform very accurate R-peak detection (F1 > 98%). It also allows the user to manually correct the R-peak locations and annotate low signal quality of the underlying ECG. PhysioZoo implements state of the art HRV measures adapted for different mammals (dogs, rabbits, and mice) and allows easy export of all computed measures together with standard data representation figures. PhysioZoo provides databases and standard ranges for all HRV measures computed on healthy, conscious humans, dogs, rabbits, and mice at rest. Study of these measures across different mammals can provide new insights into the complexity of heart rate dynamics across species.Conclusion: PhysioZoo enables the standardization and reproducibility of HRV analysis in mammalian models through its open source code, freely available software, and open access databases. PhysioZoo will support and enable new investigations in mammalian HRV research. The source code and software are available on www.physiozoo.com
PhysioZoo: The Open Digital Physiological Biomarkers Resource
PhysioZoo is a collaborative platform designed for the analysis of continuous
physiological time series. The platform currently comprises four modules, each
consisting of a library, a user interface, and a set of tutorials: (1)
PhysioZoo HRV, dedicated to studying heart rate variability (HRV) in humans and
other mammals; (2) PhysioZoo SPO2, which focuses on the analysis of digital
oximetry biomarkers (OBM) using continuous oximetry (SpO2) measurements from
humans; (3) PhysioZoo ECG, dedicated to the analysis of electrocardiogram (ECG)
time series; (4) PhysioZoo PPG, designed to study photoplethysmography (PPG)
time series. In this proceeding, we introduce the PhysioZoo platform as an open
resource for digital physiological biomarkers engineering, facilitating
streamlined analysis and data visualization of physiological time series while
ensuring the reproducibility of published experiments. We welcome researchers
to contribute new libraries for the analysis of various physiological time
series, such as electroencephalography, blood pressure, and phonocardiography.
You can access the resource at physiozoo.com. We encourage researchers to
explore and utilize this platform to advance their studies in the field of
continuous physiological time-series analysis.Comment: 4 pages, 2 figure, 50th Computing in Cardiology conference in
Atlanta, Georgia, USA on 1st - 4th October 202
Transcriptional Profiling of Plasmodium falciparum Parasites from Patients with Severe Malaria Identifies Distinct Low vs. High Parasitemic Clusters
Background:
In the past decade, estimates of malaria infections have dropped from 500 million to 225 million per year; likewise, mortality rates have dropped from 3 million to 791,000 per year. However, approximately 90% of these deaths continue to occur in sub-Saharan Africa, and 85% involve children less than 5 years of age. Malaria mortality in children generally results from one or more of the following clinical syndromes: severe anemia, acidosis, and cerebral malaria. Although much is known about the clinical and pathological manifestations of CM, insights into the biology of the malaria parasite, specifically transcription during this manifestation of severe infection, are lacking.
Methods and Findings:
We collected peripheral blood from children meeting the clinical case definition of cerebral malaria from a cohort in Malawi, examined the patients for the presence or absence of malaria retinopathy, and performed whole genome transcriptional profiling for Plasmodium falciparum using a custom designed Affymetrix array. We identified two distinct physiological states that showed highly significant association with the level of parasitemia. We compared both groups of Malawi expression profiles with our previously acquired ex vivo expression profiles of parasites derived from infected patients with mild disease; a large collection of in vitro Plasmodium falciparum life cycle gene expression profiles; and an extensively annotated compendium of expression data from Saccharomyces cerevisiae. The high parasitemia patient group demonstrated a unique biology with elevated expression of Hrd1, a member of endoplasmic reticulum-associated protein degradation system.
Conclusions:
The presence of a unique high parasitemia state may be indicative of the parasite biology of the clinically recognized hyperparasitemic severe disease syndrome
Psychometric properties of the Problematic Internet Use Questionnaire Short-Form (PIUQ-SF-6) in a nationally representative sample of adolescents
Despite the large number of measurement tools developed to assess problematic Internet use, numerous studies use measures with only modest investigation into their psychometric properties. The goal of the present study was to validate the short (6-item) version of the Problematic Internet Use Questionnaire (PIUQ) on a nationally representative adolescent sample (n = 5,005; mean age 16.4 years, SD = 0.87) and to determine a statistically established cut-off value. Data were collected within the framework of the European School Survey Project on Alcohol and Other Drugs project. Results showed an acceptable fit of the original three-factor structure to the data. In addition, a MIMIC model was carried out to justify the need for three distinct factors. The sample was divided into users at-risk of problematic Internet use and those with no-risk using a latent profile analysis. Two latent classes were obtained with 14.4% of adolescents belonging to the at-risk group. Concurrent and convergent validity were tested by comparing the two groups across a number of variables (i.e., time spent online, academic achievement, self-esteem, depressive symptoms, and preferred online activities). Using the at-risk latent profile analysis class as the gold standard, a cut-off value of 15 (out of 30) was suggested based on sensitivity and specificity analyses. In conclusion, the brief version of the (6-item) PIUQ also appears to be an appropriate measure to differentiate between Internet users at risk of developing problematic Internet use and those not at risk. Furthermore, due to its brevity, the shortened PIUQ is advantageous to utilize within large-scale surveys assessing many different behaviors and/or constructs by reducing the overall number of survey questions, and as a consequence, likely increasing completion rates
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Whole exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer
Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two prostate cancer patients including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early-trunk and 56 metastatic-trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic
Signatures of the autonomic nervous system and the heartâs pacemaker cells in canine electrocardiograms and their applications to humans
Abstract Heart rate and heart rate variability (HRV) are mainly determined by the autonomic nervous system (ANS), which interacts with receptors on the sinoatrial node (SAN; the heartâs primary pacemaker), and by the âcoupled-clockâ system within the SAN cells. HRV changes are associated with cardiac diseases. However, the relative contributions of the ANS and SAN to HRV are not clear, impeding effective treatment. To discern the SANâs contribution, we performed HRV analysis on canine electrocardiograms containing basal and ANS-blockade segments. We also analyzed human electrocardiograms of atrial fibrillation and heart failure patients, as well as healthy aged subjects. Finally, we used a mathematical model to simulate HRV under decreased âcoupled-clockâ regulation. We found that (a) in canines, the SAN and ANS contribute mainly to long- and short-term HRV, respectively; (b) there is evidence suggesting a similar relative SAN contribution in humans; (c) SAN features can be calculated from beat-intervals obtained in-vivo, without intervention; (d) ANS contribution can be modeled by sines embedded in white noise; (e) HRV changes associated with cardiac diseases and aging can be interpreted as deterioration of both SAN and ANS; and (f) SAN clock-coupling can be estimated from changes in HRV. This may enable future non-invasive diagnostic applications