Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Disease Risk Using Bootstrap Ranking and Classification Algorithms

Genome-wide association studies (GWAS) are widely used to search for genetic loci that underlie human disease. Another goal is to predict disease risk for different individuals given their genetic sequence. Such predictions could either be used as a “black box” in order to promote changes in life-style and screening for early diagnosis, or as a model that can be studied to better understand the mechanism of the disease. Current methods for risk prediction typically rank single nucleotide polymorphisms (SNPs) by the p-value of their association with the disease, and use the top-associated SNPs as input to a classification algorithm. However, the predictive power of such methods is relatively poor. To improve the predictive power, we devised BootRank, which uses bootstrapping in order to obtain a robust prioritization of SNPs for use in predictive models. We show that BootRank improves the ability to predict disease risk of unseen individuals in the Wellcome Trust Case Control Consortium (WTCCC) data and results in a more robust set of SNPs and a larger number of enriched pathways being associated with the different diseases. Finally, we show that combining BootRank with seven different classification algorithms improves performance compared to previous studies that used the WTCCC data. Notably, diseases for which BootRank results in the largest improvements were recently shown to have more heritability than previously thought, likely due to contributions from variants with low minimum allele frequency (MAF), suggesting that BootRank can be beneficial in cases where SNPs affecting the disease are poorly tagged or have low MAF. Overall, our results show that improving disease risk prediction from genotypic information may be a tangible goal, with potential implications for personalized disease screening and treatment.
Use of a clinical decision support system to increase osteoporosis screening

Background In 2002, the US Preventive Services Task Force recommended routine osteoporosis screening for women aged 65 years or older. However, studies have indicated that osteoporosis remains underdiagnosed, and various methods such as the use of health information technology have been tried to increase screening rates. We investigated whether we could boost the low rates of bone mineral density testing with implementation of a point-of-care clinical decision support system in our primary care practice. Methods We retrospectively reviewed the medical records of female patients eligible for osteoporosis screening who had no prior bone mineral density test who were seen at our primary care practice sites in 2007 or 2008 (before and after implementation of a point-of-care clinical decision support system). Results Overall, screening rates were 80.1% in 2007 and 84.1% in 2008 (P < 0.001). Of patients who did not have osteoporosis screening before the visit, 5.87% completed the screening after the visit in 2007, compared with 9.79% in 2008 (when the clinical support system was implemented), a 66.7% improvement (P = 0.025). Conclusion Clinical decision support for primary care doctors significantly improved osteoporosis screening rates among eligible women. Carefully designed clinical decision support systems can optimize care delivery, ensuring that important preventive services such as osteoporosis screening for patients at risk for fracture are performed while unnecessary testing is avoided.
Exact and Stable Covariance Estimation From Quadratic Sampling via Convex Programming

Statistical inference and information processing of high-dimensional data often require an efficient and accurate estimation of their second-order statistics. With rapidly changing data, limited processing power and storage at the acquisition devices, it is desirable to extract the covariance structure from a single pass over the data and a small number of stored measurements. In this paper, we explore a quadratic (or rank-one) measurement model which imposes minimal memory requirements and low computational complexity during the sampling process, and is shown to be optimal in preserving various low-dimensional covariance structures. Specifically, four popular structural assumptions of covariance matrices, namely, low rank, Toeplitz low rank, sparsity, jointly rank-one and sparse structure, are investigated, while recovery is achieved via convex relaxation paradigms for the respective structure. The proposed quadratic sampling framework has a variety of potential applications, including streaming data processing, high-frequency wireless communication, phase space tomography and phase retrieval in optics, and noncoherent subspace detection. Our method admits universally accurate covariance estimation in the absence of noise, as soon as the number of measurements exceeds the information theoretic limits. We also demonstrate the robustness of this approach against noise and imperfect structural assumptions. Our analysis is established upon a novel notion called the mixed-norm restricted isometry property (RIP-ℓ2/ℓ1), as well as the conventional RIP-ℓ2/ℓ2 for near-isotropic and bounded measurements. In addition, our results improve upon the best-known phase retrieval (including both dense and sparse signals) guarantees using PhaseLift with a significantly simpler approach.
THE AVAILABILITY OF PHYTIC ACID PHOSPHORUS FOR CHICKS. 4. THE AVAILABILITY OF NATURAL PLANT PHOSPHORUS.

Abstract PUBLISHED reports are not in complete agreement concerning the availability of the phosphorus in plant materials, commonly known as phytin phosphorus. Phosphorus extracted from various plant materials was poorly available for chicks and rats in studies reported by Lowe et al. (1939), Krieger et al. (1940, 1941), Spitzer et al. (1948), Gillis et al. (1949, 1957) and Matterson et al. (1946). However, the last group stated that one should not infer from the poor availability of the extracted plant phosphate that phosphorus of natural plant material is necessarily unavailable. The reports of Heuser et al. (1943) and McGinnis et al. (1944) suggested limited availability of phosphorus from plant sources. Gillis et al. (1949) indicated that phosphorus present in natural plant ingredients was a slightly more effective source of phosphorus than that extracted as calcium phytate. Singsen et al. (1947) reported that phosphorus in a mixture of cereal grains was relatively…
Long‐term incubation with IL‐4 and IL‐10 oppositely modifies procoagulant activity of monocytes and modulates the surface expression of tissue factor and tissue factor pathway inhibitor

Monocytes can be induced to express both tissue factor (TF) and its inhibitor, TF pathway inhibitor‐1 (TFPI‐1). A short incubation (<6 h) with interleukin (IL)‐4 and IL‐10, two potent deactivators of monocyte functions, has been shown to modulate the synthesis and expression of TF by monocytes activated by lipopolysaccharide, but the consequences of longer incubations (up to 96 h) on both TF and TFPI‐1 are unknown. The results of this study showed that adherent monocytes in culture spontaneously expressed TF and TFPI and that prolonged incubation with IL‐10 induced a time‐ and dose‐dependent decrease of monocyte TF synthesis, and an accumulation of TF/TFPI‐1 complexes at the moncyte surface, suggesting a decreased clearance of these complexes. In contrast, IL‐4 induced a time‐ and dose‐dependent increase in TF synthesis, which remained intracytoplasmic, as shown by confocal microscopy. Surprisingly, TF:antigen (Ag) was decreased at the monocyte surface, but the procoagulant activity (PCA) of IL‐4‐treated monocytes was increased, as a result of more pronounced decrease of TFPI‐1:Ag expression than that of TF. In conclusion, prolonged incubation with IL‐4 and IL‐10 oppositely modified PCA of cultured monocytes, and altered TF and TFPI trafficking and clearance. These data explain the respective deleterious or benefit effects of IL‐4 or IL‐10 in atherothrombosis.
An improved approach to video target tracking based on Mean Shift

This paper proposes an algorithm based on Mean Shift, which improves on the kernel function, alterative weights, combing with Kalman filter and neighborhood searching. These improvements not only enhance the capacity of target tracking, but also reduce the computations to satisfy the need of the real-time job. Furthermore, experimental results illuminate that the proposed algorithm can cope with clutter, target partial occlusions, scale variations and fast moving in the real-time video target tracking.
The clinically important difference on the unified Parkinson's disease rating scale.

OBJECTIVE To determine the estimates of minimal, moderate, and large clinically important differences (CIDs) for the Unified Parkinson's Disease Rating Scale (UPDRS). DESIGN Cross-sectional analysis of the CIDs for UPDRS total and motor scores was performed on patients with Parkinson disease (PD) using distribution- and anchor-based approaches based on the following 3 external standards: disability (10% on the Schwab and England Activities of Daily Living Scale), disease stage (1 stage on the Hoehn and Yahr Scale), and quality of life (1 SD on the 12-Item Short Form Health Survey). SETTING University of Maryland Parkinson Disease and Movement Disorders Center, Patients Six hundred fifty-three patients with PD. RESULTS A minimal CID was 2.3 to 2.7 points on the UPDRS motor score and 4.1 to 4.5 on the UPDRS total score. A moderate CID was 4.5 to 6.7 points on the UPDRS motor score and 8.5 to 10.3 on the UPDRS total score. A large CID was 10.7 to 10.8 points on the UPDRS motor score and 16.4 to 17.8 on the UPDRS total score. CONCLUSIONS Concordance among multiple approaches of analysis based on subjective and objective data show that reasonable estimates for the CID on the UPDRS motor score are 2.5 points for minimal, 5.2 for moderate, and 10.8 for large CIDs. Estimates for the UPDRS total score are 4.3 points for minimal, 9.1 for moderate, and 17.1 for large CIDs. These estimates will assist in determining clinically meaningful changes in PD progression and response to therapeutic interventions.
Learning to Read Vertical Text in Peripheral Vision

Purpose English-language text is almost always written horizontally. Text can be formatted to run vertically, but this is seldom used. Several studies have found that horizontal text can be read faster than vertical text in the central visual field. No studies have investigated the peripheral visual field. Studies have also concluded that training can improve reading speed in the peripheral visual field for horizontal text. We aimed to establish whether the horizontal vertical differences are maintained and if training can improve vertical reading in the peripheral visual field. Methods Eight normally sighted young adults participated in the first study. Rapid serial visual presentation (RSVP) reading speed was measured for horizontal and vertical text in the central visual field and at 10 degrees eccentricity in the upper or lower (horizontal text) and right or left (vertical text) visual fields. Twenty-one normally sighted young adults split equally between two training groups and one control group participated in the second study. Training consisted of RSVP reading using either vertical text in the left visual field or horizontal text in the inferior visual field. Subjects trained daily over 4 days. Pre- and post- horizontal and vertical RSVP reading speeds were carried out for all groups. For the training groups, these measurements were repeated 1 week and 1 month posttraining. Results Before training, RSVP reading speeds were faster for horizontal text in the central and peripheral visual fields when compared with vertical text. Training vertical reading improved vertical reading speeds by an average factor of 2.8. There was partial transfer of training to the opposite (right) hemifield. The training effects were retained for up to a month. Conclusions Rapid serial visual presentation training can improve RSVP vertical text reading in peripheral vision. These findings may have implications for patients with macular degeneration or hemianopic field loss.
On the Impact of Oscillator Phase Noise on the Uplink Performance in a Massive MIMO-OFDM System

In this work we study the effect of oscillator phase noise on the uplink performance of a massive multiple-input multiple output system. Specifically, we consider an orthogonal frequency division multiplexing-based uplink transmission and analyze two scenarios: (a) all the base station (BS) antennas are fed by a common oscillator, and (b) each of the BS antennas is fed by a different oscillator. For the scenarios considered, we derive the instantaneous signal-to-noise ratio on each subcarrier and analyze the ergodic capacity when a linear receiver is used. Furthermore, we propose a phase noise tracking algorithm based on Kalman filtering that mitigates the effect of phase noise on the system performance.
Who's Afraid of George Kingsley Zipf?

We explore the statistical distributions of natural language known as Zipf’s law and develop a new approach to assess the properties of the underlying grammar given a sample of linguistic production. Focusing on language acquisition, we show that the item or usage based approach to language and language learning fails to provide adequate statistical tests of linguistic productivity, and that even very young children’s grammar is abstract, systematic, and fully generative.
The role of RANTES as a crucial downstream cytokine in calcineurin‐dependent VSMC apoptosis stimulated by INFγ and CD40L

Many studies have suggested that VSMC (vascular smooth muscle cell) apoptosis plays a key role in destabilization and rupture of atherosclerotic plaques. Therefore protection for VSMCs from apoptosis is a promising approach to stabilize ‘vulnerable’ lesions. However, the mechanisms as to why VSMCs in the fibrous cap often appear as profilerated in early stages, but turn apoptotic in advanced stages, are still unknown. In the present study, using RNAi (RNA interference) technology and a CaN (calcineurin) antagonist, the correlation between CaN and RANTES (regulated upon activation, normal T‐cell expressed and secreted) in cultured rat apoptotic VSMCs stimulated by IFNγ (interferon γ; 20 ng/ml) and CD40L (CD40 ligand; 100 ng/ml) was investigated. RANTES released from VSMCs in each group was measured by ELISA and its mRNA in VSMCs was determined by RT (reverse transcription)–PCR. The total activity and expression of CaN in VSMCs were detected by the zymochemistry method and Western blot analysis respectively. From the results of the present study it can be hypothesized that an elevated CaN concentration in endochylema, by the CD40–CD40L signal pathway, induces VSMC apoptosis accomplished by the overexpression of RANTES. Therefore RANTES is a potential target for treating vulnerable atherosclerotic plaques owing to its crucial downstream regulating role in CaN‐dependent VSMC apoptosis.
The Contraceptive Depot Medroxyprogesterone Acetate Impairs Mycobacterial Control and Inhibits Cytokine Secretion in Mice Infected with Mycobacterium tuberculosis

ABSTRACT The contraceptive depot medroxyprogesterone acetate (DMPA), with progestin as the single active compound, possesses selective glucocorticoid activity and can alter the expression of glucocorticoid receptor-regulated genes. We therefore propose that pharmacological doses of DMPA used for endocrine therapy could have significant immune modulatory effects and impact on susceptibility to, as well as clinical manifestation and outcome of, infectious diseases. We investigated the effect of contraceptive doses of DMPA in two different murine Mycobacterium tuberculosis models. Multiplex bead array analysis revealed that DMPA altered serum cytokine levels of tumor necrosis factor alpha (TNF-α), granulocyte colony-stimulating factor (G-CSF), and interleukin 10 (IL-10) in C57BL/6 mice and gamma interferon (IFN-γ) in BALB/c mice. DMPA also suppressed antigen-specific production of TNF-α, G-CSF, IL-10, and IL-6 and induced the production of IP-10 in C57BL/6 mice. In BALB/c mice, DMPA altered the antigen-specific secretion of IFN-γ, IL-17, granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-6, and monocyte chemotactic protein 1 (MCP-1). Furthermore, we show that C57BL/6 mice treated with doses of DMPA, which result in serum concentrations similar to those observed in contraceptive users, have a significantly higher bacterial load in their lungs. Our data show for the first time that DMPA impacts tuberculosis (TB) disease severity in a mouse model and that the effects of this contraceptive are not confined to infections of the genital tract. This could have major implications for the contraceptive policies not only in developing countries like South Africa but also worldwide.
Granulin–Epithelin Precursor Overexpression Promotes Growth and Invasion of Hepatocellular Carcinoma

Purpose: Granulin–epithelin precursor (GEP) is a novel growth factor. Our earlier cDNA microarray study indicated that GEP was overexpressed in hepatocellular carcinoma (HCC). The aim of this study was to investigate the clinical significance of GEP expression and its potential as a therapeutic target in HCC. Experimental Design: A total of 110 pairs of HCCs and adjacent nontumor liver tissues, and 22 normal liver tissues were examined. The GEP RNA level was examined by quantitative reverse transcription-PCR, and protein localization by immunohistochemistry. The GEP function was examined by transfection experiments. Results: The RNA levels of the HCCs were significantly higher than those of the nontumor liver tissues and normal livers (P < 0.001). GEP protein staining was observed in tumor cytoplasm, and the GEP protein levels of the HCCs were also significantly higher than those of the nontumor liver tissues and normal livers (P < 0.001). The majority of HCCs demonstrated up-regulation of GEP protein compared with their adjacent liver tissues [79 (71.8%) of 110]. Positive correlation of GEP RNA with protein levels was observed in HCCs (P < 0.01). Strong GEP expression was associated with large HCCs, venous infiltration, and early intrahepatic recurrence (P < 0.05). Functional studies on the HCC cell line Hep3B demonstrated that reduction of GEP protein levels resulted in decreased cell prolifera-tion rates, tumor invasion ability, anchorage-independent growth in soft agar, and tumorigenicity in nude mice (P < 0.05). Conclusion: GEP is an important factor for HCC growth, invasion, and metastasis. GEP has the potential to serve as a tumor marker and therapeutic target.
Observer Design with Disturbance Rejection by Acceleration Feedforward

Abstract This paper addresses observer design of mechanical systems subject to unknown external disturbances and unmodeled dynamics. For fast-acting disturbance forces, realistic and accurate physical models do not always exist, such as for dynamic positioning of marine vessels in ice-infested waters. To accommodate such forces and provide disturbance rejection, a delayed acceleration measurement is used to form an acceleration feedforward which captures the perturbations and enhances the observer phase margins. Through the acceleration measurement, an inherent sensor bias is introduced, creating a pseudo-force in the system. This is tracked and compensates by a bias estimate. The theoretical foundation is exemplified by the derivation of a DP observer and a simulation study featuring an inverted pendulum.
Peroxisome Proliferator–Activated Receptor δ Promotes the Progression of Posttraumatic Osteoarthritis in a Mouse Model

Osteoarthritis (OA) is a serious disease of the entire joint, characterized by articular cartilage degeneration, subchondral bone changes, osteophyte formation, and synovial hyperplasia. Currently, there are no pharmaceutical treatments that can slow the disease progression, resulting in greatly reduced quality of life for patients and the need for joint replacement surgeries in many cases. The lack of available treatments for OA is partly due to our incomplete understanding of the molecular mechanisms that promote disease initiation and progression. The purpose of the present study was to examine the role of the nuclear receptor peroxisome proliferator–activated receptor δ (PPARδ) as a promoter of cartilage degeneration in a mouse model of posttraumatic OA.
Simulation experiments: Better data, not just big data

Data mining tools have been around for several decades, but the term “big data” has only recently captured widespread attention. Numerous success stories have been promulgated as organizations have sifted through massive volumes of data to find interesting patterns that are, in turn, transformed into actionable information. Yet a key drawback to the big data paradigm is that it relies on observational data-limiting the types of insights that can be gained. The simulation world is different. A “data farming” metaphor captures the notion of purposeful data generation from simulation models. Large-scale designed experiments let us grow the simulation output efficiently and effectively. We can explore massive input spaces, uncover interesting features of complex simulation response surfaces, and explicitly identify cause-and-effect relationships. With this new mindset, we can achieve quantum leaps in the breadth, depth, and timeliness of the insights yielded by simulation models.
Resolving multiple epigenetic pathways to adolescent depression.

BACKGROUND Genotype x environment interaction (G x E) arises when genes influence sensitivity to the environment. G x E is easily recognized in experimental organisms that permit randomization of genotypes over fixed environmental treatments. Genotype-environment correlation (rGE) arises when genetic effects create or evoke exposure to environmental differences. Simultaneous analysis of G x E and such 'active' or 'evocative' rGE in humans is intractable with linear structural models widely used in behavioral genetics because environments are random effects often correlated with genotype. The causes of the environmental variation, therefore, need to be modeled at the same time as the primary outcome. METHODS A Markov Chain Monte Carlo approach is used to resolve three distinct pathways involving genes and life events affecting the development of post-pubertal depression in female twins and its relationship to pre-pubertal anxiety: 1) the main of genes and environment; 2) the interaction of genes and environment (G x E); and 3) genotype-environment correlation (rGE). RESULTS A model including G x E and rGE in addition to the main effects of genes and environment yields significant estimates of the parameters reflecting G x E and rGE. Omission of either G x E or rGE leads to overestimation of the effects of the measured environment and the unique random environment within families. CONCLUSIONS 1) Genetic differences in anxiety create later genetic differences in depression; 2) genes that affect early anxiety increase sensitivity (G x E) to adverse life events; 3) genes that increase risk to early anxiety increase exposure to depressogenic environmental influences (rGE). Additional genetic effects, specific to depression, further increase sensitivity to adversity. Failure to take into account the effects of G x E and rGE will lead to misunderstanding how genes and environment affect complex behavior.