Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a predictive miRNA signature for breast cancer risk among high-risk women

Significant limitations exist in our ability to predict breast cancer risk at the individual level. Circulating microRNAs (C-miRNAs) have emerged as measurable biomarkers (liquid biopsies) for cancer detection. We evaluated the ability of C-miRNAs to identify women most likely to develop breast cancer by profiling miRNA from serum obtained long before diagnosis. 24 breast cancer cases and controls (matched for risk and age) were identified from women enrolled in the High-Risk Breast Program at the UVM Cancer Center. Isolated RNA from serum was profiled for over 2500 human miRNAs. The miRNA expression data were input into a stepwise linear regression model to discover a multivariable miRNA signature that predicts long-term risk of breast cancer. 25 candidate miRNAs were identified that individually classified cases and controls based on statistical methodologies. A refined 6-miRNA risk-signature was discovered following regression modeling that distinguishes cases and controls (AUC0.896, CI 0.804-0.988) in this cohort. A functional relationship between miRNAs that cluster together when cases are contrasted against controls was suggested and confirmed by pathway analyses. The discovered 6 miRNA risk-signature can discriminate high-risk women who ultimately develop breast cancer from those who remain cancer-free, improving current risk assessment models. Future studies will focus on functional analysis of the miRNAs in this signature and testing in larger cohorts. We propose that the combined signature is highly significant for predicting cancer risk, and worthy of further screening in larger, independent clinical cohorts.
Performance Analysis for the ${N}$ -Continuous Precoded SM-OFDM System

Combined with N-continuous (NC) precoding, the spatial modulation (SM) orthogonal frequency division multiplexing (OFDM) system offers considerable sidelobe suppression for the downlink transmission, at the cost of additional interference to the transmit signal. Therefore, this paper focuses on investigating the impact of the NC precoder on the bit error rate (BER) performance of the SM-OFDM system. The BER performance is analyzed over the frequency-selective Rayleigh fading channel under two distinct scenarios, i.e., perfect channel estimation and interference suppression based minimum mean square error (MMSE) channel estimation. First, we propose an approximate system model for the NC precoded SM-OFDM system along with an analysis on the introduced interference, and then derive the average BER performance of the system with perfect channel estimation. Based on the above proposed approximate system model, we further analyze the interference based upon MMSE channel estimation, and investigate the characteristics of channel estimation errors. Furthermore, we derive the average BER performance of the NC precoded SM-OFDM system with imperfect channel estimation. The numerical results show that the analytical BER closely matches its simulated counterpart under different system configurations, and demonstrate that the proposed approximate system model is in good agreement with the precise one.
Identification of Ketene-Reactive Intermediate of Erlotinib Possibly Responsible for Inactivation of P450 Enzymes

Erlotinib (ELT), a tyrosine kinase inhibitor, is widely used for the treatment of nonsmall cell lung cancer in clinic. Unfortunately, severe drug-induced liver injury and other adverse effects occurred during the treatment. Meanwhile, ELT has been reported to be a mechanism-based inactivator of cytochrome P450(CYPs) 3A4 and 3A5. The objectives of this study were to identify ketene intermediate of ELT and investigate the association of the acetylenic bioactivation with the enzyme inactivation caused by ELT. A ketene intermediate was detected in human microsomal incubations of ELT, using 4-bromobenzylamine as a trapping agent. CYPs 3A4 and 3A5 mainly contributed to the bioactivation of ELT. Microsomal incubation study showed that the ketene intermediate covalently modified the enzyme protein at lysine residues and destroyed the structure of heme. The vinyl and ethyl analogs of ELT showed minor enzyme inhibitory effect (less than 20%), whereas ELT inactivated more than 60% of the enzyme. The present study provided a novel bioactivation pathway of ELT and facilitated the understanding of the mechanisms of ELT-induced mechanism-based enzyme inactivation and liver injury.
FE investigation of failure modes at the soffit of a steel plated RC beam

In recent decades, a significant research has been carried out towards understanding the behaviour of plated beam. Initially designed to achieve a desired capacity, the plated beams prematurely fail in undesirable modes of failure, such as debonding and peeling. The uncertainty related with such modes of failure poses a real challenge towards quantifying them. This field is far from being clearly understood. Therefore, an attempt is made in this thesis to accurately predict the behaviour of adhesively plated beams. [Continues. ]
End-to-End Driving Via Conditional Imitation Learning

Deep networks trained on demonstrations of human driving have learned to follow roads and avoid obstacles. However, driving policies trained via imitation learning cannot be controlled at test time. A vehicle trained end-to-end to imitate an expert cannot be guided to take a specific turn at an upcoming intersection. This limits the utility of such systems. We propose to condition imitation learning on high-level command input. At test time, the learned driving policy functions as a chauffeur that handles sensorimotor coordination but continues to respond to navigational commands. We evaluate different architectures for conditional imitation learning in vision-based driving. We conduct experiments in realistic three-dimensional simulations of urban driving and on a 1/5 scale robotic truck that is trained to drive in a residential area. Both systems drive based on visual input yet remain responsive to high-level navigational commands.
Reducing the Health Risks of Diabetes

Purpose The purpose of this study is to apply the self-determination theory (SDT) model of health behavior to predict medication adherence, quality of life, and physiological outcomes among patients with diabetes. Methods Patients with diabetes (N = 2973) receiving care from an integrated health care delivery system in 2003 and 2004 were identified from automated databases and invited to participate in this study. In 2005, patients responded to a mixed telephone-and-mail survey assessing perceived autonomy support from health care providers, autonomous self-regulation for medication use, perceived competence for diabetes self-management, medication adherence, and quality of life. In 2006, pharmacy claims data were used to indicate medication adherence, and patients' non—high-density lipoprotein (HDL) cholesterol, A1C, and glucose levels were assessed. Results The SDT model of health behavior provided adequate fit to the data. As hypothesized, perceived autonomy support from health care providers related positively to autonomous self-regulation for medication use, which in turn related positively to perceived competence for diabetes self-management. Perceived competence then related positively to quality of life and medication adherence, and the latter construct related negatively to non-HDL cholesterol, A1C, and glucose levels. Conclusions Health care providers' support for patients' autonomy and competence around medication use and diabetes self-management related positively to medication adherence, quality of life, and physiological outcomes among patients with diabetes.
Deep generative image model using a hybrid system of generative adversarial nets (GANs)

Synthesizing realistic images has been a challenge in machine learning, due to images being complex and high dimensional, thus making them hard to model well. Building on the recent progress made in both, generative multi adversarial nets (GMAN) and conditional generative adversarial nets (CGAN), this research aims at introducing a new method to improve image synthesis in generative adversarial networks (GAN). The research benefits from combining the best of both techniques to build a model (Hybrid-GAN) that produces higher images quality, which is hardly distinguished from real images. Furthermore, this model significantly enhances log-likelihood of test data under the conditional distributions. To validate the results, we have conducted a detailed comparison between images generated by our new model, Hybrid-GAN and those images produced by standard GANs. We execute the new model using MNIST dataset and demonstrated the results obtained from the generating task.
EFFICACY OF

COOLNESS and ~resence of mind under all circumstances, calmness amid storm, clearness of juc_gment in moments of grave peril, immobility and impassiveness are a/1 synonymous with imperturbability or equanimity. These qualities were of the highest order to be attained by physicians in the opinion of Sir William Osier (1). In the thre e generations since Osler uttered hi. ~ sermon on Aequanirmtas, physicians have beer, trying to transfer these qualities t 9 their patients because they know that mental stress and chronic anxie.3r aggravate physical debility and disease states. For many years the c|in~cian has employed such drugs a,; alcohol, barbiturates and other types of hypnotic,;, broInides, paraldehyde, and a variety of analgesicsedatives, to calm the anxious palaent. Success with these agents has been variable. Morphine is still the first choice for the rehef of traumatic pain. Sahcylate derivatives -)rovide excellent rebel from inflammatory and congestive pain and the assocmted mental anguish. Caffeine and 'amphetamine and their derivatives are still favourites ~foi the relief of mental depression and fatigue. The addictive properties cff most of these drugs is a serious problem, however. (The three most widely used drugs in the world have addicting propertiescaffeine, nicotine and alcohol. ) During the past decade many new kmds of behaviour altering drugs have been mtroduc~'d with great success. They not only suppress manic excitement and anxmty, but also counteract depressmn and promote stabtlity and imperturbabdity (2). The term "Atara)da" has been introduced by Fabmg to describe thas altered mood which can be produced by drugs. Because ~ e practising anaesthetist is in daffy contact with patients who have ma]or physical problems together with a strong psych c overlay of anxiety or depression, it is of the utmost ~aportance that he becomes ~amiliar with the growing variety of mood altering drugs. This knowledge will ensure their employment in a rational manner, to the advantage o~ the patient and the anaesthetist. Frequent review of experimental and chnical evaluations of these new drugs should' be the only basis for their use m general qhnical practice. The efficacy of each agent must be coupled with a precise knowledge of its multiple actions and of its main dangers, together with informahon on the experiences of others ( 3, 4, 5).
Effect of Age on High T1 Signal Intensity of the Dentate Nucleus and Globus Pallidus in a Large Population Exposed to Gadodiamide

Objective The purpose of this study was to assess the effect of age and number of previous injections of gadodiamide on the signal intensity of unenhanced T1-weighted (T1w) images of the dentate nucleus and globus pallidus in a large population. Materials and Methods A large, single-center retrospective population survey was designed and received institutional review board approval. Between January 2014 and December 2014, T1w signal intensity ratios were obtained from a large population of 2500 consecutive enhanced brain magnetic resonance imaging (MRI) scans. Of these, 1906 MRI scans of patients not previously exposed to any gadolinium (Gd)-based contrast agent were used as control group and were compared with 892 MRI scans of patients with documented prior exposure to intravenous gadodiamide. A quantitative study was conducted to assess the T1w signal intensity of dentate nucleus-to-pons (Dn/Po) and globus pallidus-to-thalamus (Gp/Th) ratios. Multiple regression analysis was used to test the effect of age, time delay, and number of previous Gd-based contrast agent injections as predictor variables of T1w signal intensity ratios. Results In the Gd-exposed patients, multivariate regression analysis showed age (&bgr; = −0.285; P < 0.0001) and the number of previous injections of gadodiamide (&bgr; = 0.224; P < 0.0001) to be powerful predictors of Dn/Po ratio. Similarly, age (&bgr; = 0.269; P < 0.0001) and the number of previous injections of gadodiamide (&bgr; = 0.127; P < 0.0001) predicted Gp/Th ratio. Conclusions In this study, we confirm that the number of previous gadodiamide injections is a powerful predictor of the signal intensity increase of the Dn/Po and Gp/Th ratios on unenhanced T1w images and demonstrate that aging influences the T1 signal intensity of DN and GP in Gd-naïve and in Gd-exposed subjects.
Distributed randomized singular value decomposition using count sketch

Compared with other recommendation algorithms, Matrix decomposition is frequently used in the current recommendation system. It can not only lead to better results, but also can fully take the influence of various factors into account, which explains its good scalability. Matrix decomposition includ-es SVD(Singular Value Decomposition), non-negative matrix decomposition, Latent Factor Model and some other traditional matrix decomposition techniques is designed to approximate a high-dimensional matrix with low-dimensional. As a perfect technique in recommendation system, SVD is traditionally expert at dense matrix decomposition. However, real rating matrix are sparse, and have high time complexity of SVD, if the matrix size increases rapidly, the efficiency must become unacceptable. The combination of random algorithm and matrix decomposition turns traditional matrix decomposition into random matrix decomposition technique under distributed system environment. The random singular value decomposition technique illustrated in the following content can be at the expense of little accuracy under the premise of greatly improving the efficiency of the calculation.
Some Observations Concerning Electronic Densities, Electrostatic Potentials and Chemical Potentials

The hypothesis that the electronic density distribution in a molecule is qualitatively similar to the nuclear potential is shown . to be in error in at least two cases-oxirane and cubane-although it does hold true in a' number of other systems. Its emphasis upon the dominant role played by electrostatic internctions with the nuclei is consistent with some approximate molecular energy formulas. However, taking the nuclear potential as an approximation to the electronic density misses the small effects that correspond to the formation of chemical bonds. It is suggested that the electronic density difference function should provide a rough picture of the local variations in the chemical potential that occur as atoms combine to form a molecule. Finally, the common practice of representing the energy and electronegativity of an interacting atom as functions only of the number of electrons associated with the atom is shown to be ina'dequate; some account should be taken of the changing internuclear separations.
An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

Abstract. Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.
Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials.

BACKGROUND The effects of dietary fats on the risk of coronary artery disease (CAD) have traditionally been estimated from their effects on LDL cholesterol. Fats, however, also affect HDL cholesterol, and the ratio of total to HDL cholesterol is a more specific marker of CAD than is LDL cholesterol. OBJECTIVE The objective was to evaluate the effects of individual fatty acids on the ratis of total to HDL cholesterol and on serum lipoproteins. DESIGN We performed a meta-analysis of 60 selected trials and calculated the effects of the amount and type of fat on total:HDL cholesterol and on other lipids. RESULTS The ratio did not change if carbohydrates replaced saturated fatty acids, but it decreased if cis unsaturated fatty acids replaced saturated fatty acids. The effect on total:HDL cholesterol of replacing trans fatty acids with a mix of carbohydrates and cis unsaturated fatty acids was almost twice as large as that of replacing saturated fatty acids. Lauric acid greatly increased total cholesterol, but much of its effect was on HDL cholesterol. Consequently, oils rich in lauric acid decreased the ratio of total to HDL cholesterol. Myristic and palmitic acids had little effect on the ratio, and stearic acid reduced the ratio slightly. Replacing fats with carbohydrates increased fasting triacylglycerol concentrations. CONCLUSIONS The effects of dietary fats on total:HDL cholesterol may differ markedly from their effects on LDL. The effects of fats on these risk markers should not in themselves be considered to reflect changes in risk but should be confirmed by prospective observational studies or clinical trials. By that standard, risk is reduced most effectively when trans fatty acids and saturated fatty acids are replaced with cis unsaturated fatty acids. The effects of carbohydrates and of lauric acid-rich fats on CAD risk remain uncertain.
Drug‐related problems identified during medication review before and after the introduction of a clinical decision support system

To facilitate the identification of drug‐related problems (DRPs) during medication review, several tools have been developed. Explicit criteria, like Beers criteria or STOPP (Screening Tool of Older Peoples’ Prescriptions) and START (Screening Tool to Alert doctors to Right Treatment) criteria, can easily be integrated into a clinical decision support system (CDSS). The aim of this study was to investigate the effect of adding a CDSS to medication review software on identifying and solving DRPs in daily pharmacy practice.
Development and Translational Application of a Minimal Physiologically Based Pharmacokinetic Model for a Monoclonal Antibody against Interleukin 23 (IL-23) in IL-23-Induced Psoriasis-Like Mice

The interleukin (IL)-23/Th17/IL-17 immune pathway has been identified to play an important role in the pathogenesis of psoriasis. Many therapeutic proteins targeting IL-23 or IL-17 are currently under development for the treatment of psoriasis. In the present study, a mechanistic pharmacokinetics (PK)/pharmacodynamics (PD) study was conducted to assess the target-binding and disposition kinetics of a monoclonal antibody (mAb), CNTO 3723, and its soluble target, mouse IL-23, in an IL-23-induced psoriasis-like mouse model. A minimal physiologically based pharmacokinetic model with target-mediated drug disposition features was developed to quantitatively assess the kinetics and interrelationship between CNTO 3723 and exogenously administered, recombinant mouse IL-23 in both serum and lesional skin site. Furthermore, translational applications of the developed model were evaluated with incorporation of human PK for ustekinumab, an anti-human IL-23/IL-12 mAb developed for treatment of psoriasis, and human disease pathophysiology information in psoriatic patients. The results agreed well with the observed clinical data for ustekinumab. Our work provides an example on how mechanism-based PK/PD modeling can be applied during early drug discovery and how preclinical data can be used for human efficacious dose projection and guide decision making during early clinical development of therapeutic proteins.
Adjacent graph-based block kernel nonnegative matrix factorization

Using block technique and graph theory, we present a variant of nonnegative matrix factorization (NMF) with high performance for face recognition. We establish a novel objective function in kernel space by the class label information and local scatter information. The class label information is implied in the block decomposition technique and intra-class covariance matrix, while the local scatter information is determined by the adjacent graph matrix. We theoretically construct an auxiliary function related to the objective function and then derive the iterative formulae of our method by solving the stable point of the auxiliary function. The property of auxiliary function shows that our algorithm is convergent. Finally, empirical results show that our method is effective.
Cohort Profile Cohort Profile : Tracing Achievements , Key processes and Efforts in professional care for Children and Adolescents REsearch ; TAKECARE

TAKECARE is a prospective cohort study designed in The Netherlands to obtain evidence on the care chain for children and adolescents with psychosocial problems, and its longterm outcomes. Little is known about the content of care as offered and on whether the care is adequate. The cohort consists of children and adolescents entering care for psychosocial problems (care sample, n1⁄4 1382) and a random sample of the general population (community sample, n1⁄4 666). Children were eligible for participation if they were aged 4–18 years (inclusive) and had estimated IQs of 70 and over. The care sample covers the fields of Preventive Child Healthcare (PCH), Child and Adolescent Social Care (CASC) and Child and Adolescent Mental Healthcare (CAMH). Children, parents or guardians and involved practitioners completed five questionnaires (baseline, and at 3, 12, 24 and 36 months thereafter). The main categories of data concern the sociodemographic characteristics of children and their parents or guardians, the characteristics of entry into care and care content, and intermediate and final treatment outcomes. Information about data access can be requested by e-mail: c4youth@umcg.nl.