LLukas22/scidocs huggingface dataset:
Toward new vital signs : tools and methods for dense physiologic data capture, analysis, and decision support in critical care.

SIMON (Signal Interpretation and MONitoring) continuously collects, permanently stores, and processes bedside medical device data. Since 1998 SIMON has monitored over 3500 trauma intensive care unit (TICU) patients, representing approximately 250,000 hours of continuous monitoring and two billion data points, and is currently operational on all 14 TICU beds at Vanderbilt University Medical Center. This repository of dense physiologic data (heart rate, arterial, pulmonary, central venous, intracranial, and cerebral perfusion pressures, arterial and venous oxygen saturations, and other parameters sampled second-by-second) supports research to identify “new vital signs” features of patient physiology only observable through dense data capture and analysis more predictive of patient status than current measures. SIMON’s alerting and reporting capabilities, including web-based display, sentinel event notification via alphanumeric pagers, and daily summary reports of vital sign statistics, allow these discoveries to be rapidly tested and implemented in a working clinical environment. This
End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights

1 data -module: data.insuranceqa.v2 2 model -module: model.ap_lstm 3 training -module: training.dynamic 4 evaluation -module: evaluation.default 5 6 data: 7 embeddings: data/glove.6B.100d.txt 8 insuranceqa: data/insuranceQA 9 lowercased: true 10 .. 11 12 model: 13 lstm_cell_size: 141 14 margin: 0.2 15 trainable_embeddings: true 16 .. 17 18 training: 19 batchsize: 20 20 epochs: 100 21 save_folder: checkpoints/ap_lstm 22 dropout: 0.3 23 optimizer: adam 24 initial_learning_rate: 0.001 25 scorer: accuracy 26 .. 27 28 evaluation: 29 skip: true
Morphology of the Insertions of the Superficial Medial Collateral Ligament and Posterior Oblique Ligament Using 3-Dimensional Computed Tomography: A Cadaveric Study.

PURPOSE
To describe the insertions of the superficial medial collateral ligament (sMCL) and posterior oblique ligament (POL) and their related osseous landmarks.


METHODS
Insertions of the sMCL and POL were identified and marked in 22 unpaired human cadaveric knees. The surface area, location, positional relations, and morphology of the sMCL and POL insertions and related osseous structures were analyzed on 3-dimensional images.


RESULTS
The femoral insertion of the POL was located 18.3 mm distal to the apex of the adductor tubercle (AT). The femoral insertion of the sMCL was located 21.1 mm distal to the AT and 9.2 mm anterior to the POL. The angle between the femoral axis and femoral insertion of the sMCL was 18.6°, and that between the femoral axis and the POL insertion was 5.1°. The anterior portions of the distal fibers of the POL were attached to the fascia cruris and semimembranosus tendon, whereas the posterior fibers were attached to the posteromedial side of the tibia directly. The tibial insertion of the POL was located just proximal and medial to the superior edge of the semimembranosus groove. The tibial insertion of the sMCL was attached firmly and widely to the tibial crest. The mean linear distances between the tibial insertion of the POL or sMCL and joint line were 5.8 and 49.6 mm, respectively.


CONCLUSIONS
This study used 3-dimensional images to assess the insertions of the sMCL and POL and their related osseous landmarks. The AT was identified clearly as an osseous landmark of the femoral insertions of the sMCL and POL. The tibial crest and semimembranosus groove served as osseous landmarks of the tibial insertions of the sMCL and POL.


CLINICAL RELEVANCE
By showing further details of the anatomy of the knee, the described findings can assist surgeons in anatomic reconstruction of the sMCL and POL.
FACTS-based reactive power compensation of wind energy conversion system

Voltage control and reactive power compensation in a distribution network with embedded wind energy conversion system (WECS) represent main concern of this paper. The WECS is of a fixed speed/constant frequency type that is equipped with an induction generator driven by an unregulated wind turbine. The problem is viewed from shortterm (10 seconds) and mid-term (10 minutes) time domain responses of the system to different wind speed changes. Being disturbed by a variable wind speed, the WECS injects variable active and reactive power into the distribution network exposing nearby consumers to excessive voltage changes. In the FACTS-based solution approach, the Unified Power Flow Controller (UPFC) is used at the point of the WECS network connection to help solve technical issues related to voltage support and series reactive power flow control. Index Terms wind energy conversion system (WECS), FACTS, UPFC, voltage control, reactive power compensation
Statins promote potent systemic antioxidant effects through specific inflammatory pathways.

BACKGROUND
The pleiotropic actions of hydroxymethylglutaryl CoA reductase inhibitors (statins) include antiinflammatory and antioxidant actions. We recently reported that statins induce reductions in plasma protein levels of nitrotyrosine (NO2Tyr), a modification generated by nitric oxide-derived oxidants. Whether alternative oxidative pathways are suppressed in vivo after statin administration has not yet been reported.


METHODS AND RESULTS
As an extension of our prior study, hypercholesterolemic subjects with no known coronary artery disease were evaluated at baseline and after 12 weeks of atorvastatin therapy (10 mg/d). Plasma levels of protein-bound chlorotyrosine, NO2Tyr, dityrosine, and orthotyrosine, specific molecular fingerprints for distinct oxidative pathways upregulated in atheroma, were determined by mass spectrometry. In parallel, alterations in lipoproteins and C-reactive protein were determined. Statin therapy caused significant reductions in chlorotyrosine, NO2Tyr, and dityrosine (30%, 25%, and 32%, respectively; P<0.02 each) that were similar in magnitude to reductions in total cholesterol and apolipoprotein B-100 (25% and 29%, P<0.001 each). Nonsignificant decreases in orthotyrosine and C-reactive protein levels were observed (9% and 11%, respectively; P>0.10 each). Statin-induced reductions in oxidation markers were independent of decreases in lipids and lipoproteins.


CONCLUSIONS
Statins promote potent systemic antioxidant effects through suppression of distinct oxidation pathways. The major pathways inhibited include formation of myeloperoxidase-derived and nitric oxide-derived oxidants, species implicated in atherogenesis. The present results suggest potential mechanisms that may contribute to the beneficial actions of statins. They also have important implications for monitoring the antiinflammatory and antioxidant actions of these agents.
8.8 iRazor: 3-transistor current-based error detection and correction in an ARM Cortex-R4 processor

It is well known that technology scaling has led to increasing process/voltage/temperature/aging margins that substantially degrade performance and power in modern processors and SoCs. One approach to address these large timing margins is the use of specialized registers on critical paths that perform error detection and correction (EDAC) [1-5]. While promising, the previously proposed implementations have been limited in several ways. Most notably, they often incur large overheads beyond conventional register designs (e.g., 8-to-44 additional transistors per register). This becomes an obstacle for commercial designs and, hence, there have been no reported implementations of EDAC approaches within substantial commercial processors. Finally, the performance gain from EDAC approaches has not been thoroughly quantified in relation to competing, lower overhead approaches such as frequency binning and canary circuits/critical path monitors [6].
Oral treatment of metabolic acidosis in hemodialyzed patients and the implications on the hemodynamic status.

UNLABELLED
Metabolic acidosis slowly develops during renal impairment natural evolution towards ESRD and represents an important contributing factor of CKD progression. Although, several clinical and experimental trials reported the major impact of metabolic acidosis on CKD evolution, the pathophysiology mechanism remains a matter of debate. Furthermore, international guidelines do not impose a specific treatment scheme for metabolic acidosis in CKD patients, and metabolic acidosis is not fully compensated once hemodialysis starts. Therefore, the aim of our study was to determine an adequate follow-up of metabolic acidosis therapy benefits and risks in HD patients.


PATIENTS AND METHODS
164 HD patients were evaluated according to the following protocol: bioumoral laboratory tests, the measure of different important parameters (residual diuresis, UF, BP, LVMI, volemia status). The assessed data were statistic analyzed using non-paired Student's t-test for continuous variables and chi-square (χ²) test for qualitative parameters (p-value <0.05 was considered statistically significant).


RESULTS
HD individuals were followed-up depending on their predialysis-alkaline reserve value. After therapy started, predialysis-alkaline reserve mean level increased from 19.4 mEq/L to 22.6 mEq/L (p<0.001). Furthermore, we observed a significant decrease of nitrogenous waste products values (T=10.87<1.66) and intradialytic hypotension events (p<0.001).


CONCLUSIONS
Our findings emphasize the beneficial effects of correcting metabolic acidosis using the proposed treatment scheme with direct impact on hemodynamic status improvement.
Polymorphic variants of folate metabolism genes and the risk of laryngeal cancer

Carcinogenesis may result from abnormal methylation of cancer-related genes regulatory sequence. Though, the polymorphic variants of genes encoding enzymes of folate and methionine metabolism may have an effect on DNA methylation. Using PCR-RFLPs, we examined the polymorphism distribution of genes encoding methionine synthase (MTR); 5,10-methylenetetrahydrofolate dehydrogenase, 5,10-methenyltetrahydrofolate cyclohydrolase and 10-formyltetrahydrofolate synthetase (MTHFD1); and methylenetetrahydrofolate reductase (MTHFR) in patients with larynx cancer (n = 131) and controls (n = 250). Patients with MTR 2756AG or GG genotypes displayed a 1.856 -fold increased risk of larynx cancer (95% CI = 1.1860–2.903, P = 0.0076). However, we did not observe an increased risk for the homozygous GG genotype OR = 1.960 (95% CI = 0.6722–5.713, P = 0.2535). Moreover, we did not observe statistical differences in distribution of MTHFR 677C>T, 1298A>C and MTHFD1 1958G>A allele and genotype frequencies in patients and controls. Our findings confirm the significance of the role of the methyl cycle in etiopathogenesis of laryngeal cancer.
Feature-Based Classification of Networks

Network representations of systems from various scientific and societal domains are neither completely random nor fully regular, but instead appear to contain recurring structural building blocks [1]. These features tend to be shared by networks belonging to the same broad class, such as the class of social networks or the class of biological networks. At a finer scale of classification within each such class, networks describing more similar systems tend to have more similar features. This occurs presumably because networks representing similar purposes or constructions would be expected to be generated by a shared set of domain specific mechanisms, and it should therefore be possible to classify these networks into categories based on their features at various structural levels. Here we describe and demonstrate a new, hybrid approach that combines manual selection of features of potential interest with existing automated classification methods. In particular, selecting well-known and well-studied features that have been used throughout social network analysis and network science [2, 3] and then classifying with methods such as random forests [4] that are of special utility in the presence of feature collinearity, we find that we achieve higher accuracy, in shorter computation time, with greater interpretability of the network classification results. Past work in the area of network classification has primarily focused on distinguishing networks from different categories using two different broad classes of approaches. In the first approach , network classification is carried out by examining certain specific structural features and investigating whether networks belonging to the same category are similar across one or more dimensions as defined by these features [5, 6, 7, 8]. In other words, in this approach the investigator manually chooses the structural characteristics of interest and more or less manually (informally) determines the regions of the feature space that correspond to different classes. These methods are scalable to large networks and yield results that are easily interpreted in terms of the characteristics of interest, but in practice they tend to lead to suboptimal classification accuracy. In the second approach, network classification is done by using very flexible machine learning classi-fiers that, when presented with a network as an input, classify its category or class as an output To somewhat oversimplify, the first approach relies on manual feature specification followed by manual selection of a classification system, whereas the second approach is its opposite, relying on automated feature detection followed by automated classification. While …
Triglyceride to High-Density Lipoprotein Cholesterol Ratio Predicts Cardiovascular Outcomes in Prevalent Dialysis Patients

Triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, an indicator of atherogenic dyslipidemia, is a predictor of cardiovascular (CV) outcomes in the general population and has been correlated with atherosclerotic events. Whether the TG/HDL-C ratio can predict CV outcomes and survival in dialysis patients is unknown. We performed this prospective, observational cohort study and enrolled 602 dialysis patients (539 hemodialysis and 63 peritoneal dialysis) from a single center in Taiwan followed up for a median of 3.9 years. The outcomes were the occurrence of CV events, CV death, and all-cause mortality during follow-up. The association of baseline TG/HDL-C ratio with outcomes was explored with Cox regression models, which were adjusted for demographic parameters and inflammatory/nutritional markers. Overall, 203 of the patients experienced CV events and 169 patients died, of whom 104 died due to CV events. Two hundred fifty-four patients reached the composite CV outcome. Patients with higher TG/HDL-C levels (quintile 5) had a higher incidence of CV events (adjusted hazard ratio [HR] 2.03, 95% confidence interval [CI] 1.19-3.47), CV mortality (adjusted HR 1.91, 95% CI 1.07-3.99), composite CV outcome (adjusted HR 2.2, 95% CI 1.37-3.55), and all-cause mortality (adjusted HR 1.94, 95% CI 1.1-3.39) compared with the patients in quintile 1. However, in diabetic dialysis patients, the TG/HDL-C ratio did not predict the outcomes. The TG/HDL-C ratio is a reliable and easily accessible predictor to evaluate CV outcomes and survival in prevalent nondiabetic dialysis patients. ClinicalTrials.gov: NCT01457625.
Low-Dimensional Polytope Approximation and Its Applications to Nonnegative Matrix Factorization

In this study, nonnegative matrix factorization is recast as the problem of approximating a polytope on the probability simplex by another polytope with fewer facets. Working on the probability simplex has the advantage that data are limited to a compact set with known boundary, making it easier to trace the approximation procedure. In particular, the supporting hyperplane that separates a point from a disjoint polytope, a fact asserted by the HahnBanach theorem, can be calculated in finitely many steps. This approach leads to a convenient way of computing the proximity map which, in contrast to most existing algorithm where only an approximate map is used, finds the unique and global minimum per iteration. This paper sets up a theoretical framework, outlines a numerical algorithm and suggests an effective implementation. Testing results strongly evidence that this approach obtains better low rank nonnegative matrix approximation in fewer steps than conventional methods. AMS subject classifications. 41A36, 65D18, 46A22, 90C25, 65F30
Hand gesture recognition for human-computer interaction

This paper focus on advance study of Gesture control based robot. The first part of the paper provides an overview of the current state of the art regarding the recognition of hand gestures as these are observed and recorded by typical video cameras. We derive a set of motion features based on smoothed optical flow estimates. A usercentric representation of these features is obtained using face detection, and an efficient classifier is learned to discriminate between gestures. A number of hand gesture recognition technologies and applications for Human Vehicle Interaction (HVI) are also discussed including a summary of current automotive hand gesture recognition research.
Fundamental growth principles of colloidal metal nanoparticles - a new perspective†

In the past few decades, much effort was put into the development of synthetic strategies to produce nanoparticles of different sizes and morphologies and a large number of scientific contributions is dedicated to the characterization and application of metal nanoparticles. In contrast, only few studies deal with particle formation mechanisms. As a consequence, theoretical concepts that describe particle growth processes are very rare and the few existing models are hardly able to explain how synthesis parameters influence the final particle size distribution. This contribution discusses recent experimental results from which a novel growth concept based on colloidal stability is deduced. The growth concept is in contrast to nucleation models and allows a description of colloidal growth processes from a different perspective. It states that for most syntheses the minimal particle size is rather determined by colloidal than thermodynamic stability making a nucleation model irrelevant.
The heart in Friedreich ataxia: definition of cardiomyopathy, disease severity, and correlation with neurological symptoms.

BACKGROUND
This cross-sectional study provides a practical approach for the clinical assessment of Friedreich ataxia (FA) cardiomyopathy (FA-CM).


METHODS AND RESULTS
A comprehensive cardiac assessment, including standard echocardiography, color Doppler myocardial imaging, cardiac magnetic resonance imaging, ECG, and exercise stress testing, was performed in 205 FA patients. To assess myocardial hypertrophy in FA-CM, the end-diastolic interventricular septal wall thickness (IVSTd) was found to be the best echocardiographic parameter compared with cardiac magnetic resonance imaging-determined left ventricular mass. With the use of this parameter, 4 groups of patients with FA-CM could be defined. Patients with normal values for IVSTd (31.7%) were classified as having no FA-CM. Patients with an IVSTd exceeding the predicted normal IVSTd were classified as having mild FA-CM (40%) if IVSTd exceeded the normal value by <18% or as having intermediate FA-CM (16.1%) if IVSTd exceeded the normal value by ≥18%. Patients with ejection fraction <50% were classified as having severe FA-CM (12.2%). In addition to increased myocardial mass, severe FA-CM was further characterized by dilatation of the left ventricle, reduced systolic strain rate of the posterior wall, and ECG abnormalities. Regional myocardial function correlated negatively with FA-CM groups. Younger patients had a tendency for more advanced FA-CM. Importantly, no clear correlation was found between FA-CM groups and neurological function.


CONCLUSIONS
We provide and describe a readily applicable clinical grouping of the cardiomyopathy associated with FA based on echocardiographic IVSTd and ejection fraction data. Because no distinct interrelations between FA-CM and neurological status could be determined, regular follow-up of potential cardiac involvement in FA patients is essential in clinical practice.
Network analysis of quantitative proteomics on asthmatic bronchi: effects of inhaled glucocorticoid treatment

BACKGROUND
Proteomic studies of respiratory disorders have the potential to identify protein biomarkers for diagnosis and disease monitoring. Utilisation of sensitive quantitative proteomic methods creates opportunities to determine individual patient proteomes. The aim of the current study was to determine if quantitative proteomics of bronchial biopsies from asthmatics can distinguish relevant biological functions and whether inhaled glucocorticoid treatment affects these functions.


METHODS
Endobronchial biopsies were taken from untreated asthmatic patients (n = 12) and healthy controls (n = 3). Asthmatic patients were randomised to double blind treatment with either placebo or budesonide (800 μg daily for 3 months) and new biopsies were obtained. Proteins extracted from the biopsies were digested and analysed using isobaric tags for relative and absolute quantitation combined with a nanoLC-LTQ Orbitrap mass spectrometer. Spectra obtained were used to identify and quantify proteins. Pathways analysis was performed using Ingenuity Pathway Analysis to identify significant biological pathways in asthma and determine how the expression of these pathways was changed by treatment.


RESULTS
More than 1800 proteins were identified and quantified in the bronchial biopsies of subjects. The pathway analysis revealed acute phase response signalling, cell-to-cell signalling and tissue development associations with proteins expressed in asthmatics compared to controls. The functions and pathways associated with placebo and budesonide treatment showed distinct differences, including the decreased association with acute phase proteins as a result of budesonide treatment compared to placebo.


CONCLUSIONS
Proteomic analysis of bronchial biopsy material can be used to identify and quantify proteins using highly sensitive technologies, without the need for pooling of samples from several patients. Distinct pathophysiological features of asthma can be identified using this approach and the expression of these features is changed by inhaled glucocorticoid treatment. Quantitative proteomics may be applied to identify mechanisms of disease that may assist in the accurate and timely diagnosis of asthma.


TRIAL REGISTRATION
ClinicalTrials.gov registration NCT01378039.