LLukas22/scidocs huggingface dataset:
A placebo-controlled, double-blind, randomized trial of an extract of Ginkgo biloba for dementia. North American EGb Study Group.

CONTEXT
EGb 761 is a particular extract of Ginkgo biloba used in Europe to alleviate symptoms associated with numerous cognitive disorders. Its use in dementias is based on positive results from only a few controlled clinical trials, most of which did not include standard assessments of cognition and behavior.


OBJECTIVE
To assess the efficacy and safety of EGb in Alzheimer disease and multi-infarct dementia.


DESIGN
A 52-week, randomized double-blind, placebo-controlled, parallel-group, multicenter study.


PATIENTS
Mildly to severely demented outpatients with Alzheimer disease or multi-infarct dementia, without other significant medical conditions.


INTERVENTION
Patients assigned randomly to treatment with EGb (120 mg/d) or placebo. Safety, compliance, and drug dispensation were monitored every 3 months with complete outcome evaluation at 12, 26, and 52 weeks.


PRIMARY OUTCOME MEASURES
Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog), Geriatric Evaluation by Relative's Rating Instrument (GERRI), and Clinical Global Impression of Change (CGIC).


RESULTS
From 309 patients included in an intent-to-treat analysis, 202 provided evaluable data for the 52-week end point analysis. In the intent-to-treat analysis, the EGbgroup had an ADAS-Cog score 1.4 points better than the placebo group (P=.04) and a GERRI score 0.14 points better than the placebo group (P=.004). The same patterns were observed with the evaluable data set in which 27% of patients treated with EGb achieved at least a 4-point improvement on the ADAS-Cog, compared with 14% taking placebo (P=.005); on the GERRI, 37% were considered improved with EGb, compared with 23% taking placebo (P=.003). No difference was seen in the CGIC. Regarding the safety profile of EGb, no significant differences compared with placebo were observed in the number of patients reporting adverse events or in the incidence and severity of these events.


CONCLUSIONS
EGb was safe and appears capable of stabilizing and, in a substantial number of cases, improving the cognitive performance and the social functioning of demented patients for 6 months to 1 year. Although modest, the changes induced by EGb were objectively measured by the ADAS-Cog and were of sufficient magnitude to be recognized by the caregivers in the GERRI.
Development of gene therapy for hematopoietic stem cells using lentiviral vectors

Lentiviral vectors are promising tools for the development of gene therapy since they can transduce both quiescent and dividing target cells. Lentiviral vectors may be particularly promising gene delivery tools for hematopoietic stem cells since these target cells tend to be quiescent and are therefore difficult target cells for vectors that require dividing targets. Human hematopoietic stem cells that can repopulate NOD/SCID mice have been efficiently transduced using HIV-1-based lentiviral vectors and similar vectors can also transduce murine hematopoietic stem cells. HIV-1 vectors that contain strong general promoters can generate high levels of transgene expression and very high expression levels can be generated in erythroid cells in vivo using β-globin regulatory sequences to control the expression of the transgene. Current lentiviral vectors have a similar level of biosafety as oncoretroviral vectors and can therefore theoretically be used in clinical gene therapy protocols. Future challenges include the generation of lentiviral vectors that can express more than one transgene at high levels and the generation of safe permanent packaging cells for practical use in clinical gene therapy trials.
Spatiotemporal distribution modeling of PET tracer uptake in solid tumors.

OBJECTIVE
Distribution of PET tracer uptake is elaborately modeled via a general equation used for solute transport modeling. This model can be used to incorporate various transport parameters of a solid tumor such as hydraulic conductivity of the microvessel wall, transvascular permeability as well as interstitial space parameters. This is especially significant because tracer delivery and drug delivery to solid tumors are determined by similar underlying tumor transport phenomena, and quantifying the former can enable enhanced prediction of the latter.


METHODS
We focused on the commonly utilized FDG PET tracer. First, based on a mathematical model of angiogenesis, the capillary network of a solid tumor and normal tissues around it were generated. The coupling mathematical method, which simultaneously solves for blood flow in the capillary network as well as fluid flow in the interstitium, is used to calculate pressure and velocity distributions. Subsequently, a comprehensive spatiotemporal distribution model (SDM) is applied to accurately model distribution of PET tracer uptake, specifically FDG in this work, within solid tumors.


RESULTS
The different transport mechanisms, namely convention and diffusion from vessel to tissue and in tissue, are elaborately calculated across the domain of interest and effect of each parameter on tracer distribution is investigated. The results show the convection terms to have negligible effect on tracer transport and the SDM can be solved after eliminating these terms.


CONCLUSION
The proposed framework of spatiotemporal modeling for PET tracers can be utilized to comprehensively assess the impact of various parameters on the spatiotemporal distribution of PET tracers.
Single-channel EEG sleep stage classification based on a streamlined set of statistical features in wavelet domain

The main objective of this study was to enhance the performance of sleep stage classification using single-channel electroencephalograms (EEGs), which are highly desirable for many emerging technologies, such as telemedicine and home care. The proposed method consists of decomposing EEGs by a discrete wavelet transform and computing the kurtosis, skewness and variance of its coefficients at selected levels. A random forest predictor is trained to classify each epoch into one of the Rechtschaffen and Kales’ stages. By performing a comprehensive set of tests on 106,376 epochs available from the Physionet public database, it is demonstrated that the use of these three statistical moments has enhanced performance when compared to their application in the time domain. Furthermore, the chosen set of features has the advantage of exhibiting a stable classification performance for all scoring systems, i.e., from 2- to 6-state sleep stages. The stability of the feature set is confirmed with ReliefF tests which show a performance reduction when any individual feature is removed, suggesting that this group of feature cannot be further reduced. The accuracies and kappa coefficients yield higher than 90 % and 0.8, respectively, for all of the 2- to 6-state sleep stage classification cases.
Patient safety culture: factors that influence clinician involvement in patient safety behaviours.

OBJECTIVES
To develop an understanding of the factors that influence patient safety-related behaviours by nurses, doctors and allied health staff employed by Queensland Health, using a theory-driven behavioural model.


DESIGN
Cross-sectional survey analysed with multiple logistic regression.


SETTING
Metropolitan, regional and rural public hospitals in Queensland, Australia.


PARTICIPANTS
5294 clinical and managerial staff.


MAIN OUTCOME MEASURES
The Theory of Planned Behaviour was used to develop behavioural models for high-level Patient Safety Behavioural Intent (PSBI) of senior and junior doctors, senior and junior nurses, and allied health professionals. Multiple logistic regression analysis was used to identify factors that significantly influenced PSBI between the five professional groups.


RESULTS
The factors that influence high-level PSBI give rise to unique predictive models for each professional group. Two factors stand out as influencing high-level PSBI for all healthcare workers (HCWs): (1) Preventive Action Beliefs (adjusted OR 2.38), HCWs' belief that engaging in the target behaviours will lead to improved patient safety; and (2) Professional Peer Behaviour (adjusted OR 1.79), perceptions about the patient safety-related behaviours of one's professional colleagues.


CONCLUSIONS
Professional peer-modelling behaviours and individuals' beliefs about the value of those behaviours in improving patient safety are important predictors of HCWs' patient safety behaviour. These findings may help explain the limitations of current knowledge-based educational approaches to patient safety reform. Use of the behavioural models developed in this study when designing future patient safety improvement initiatives may prove more effective in driving the behavioural change necessary for improved patient safety.
Holographic Recurrent Networks

Holographic Recurrent Networks (HRNs) are recurrent networks which incorporate associative memory techniques for storing sequential structure. HRNs can be easily and quickly trained using gradient descent techniques to generate sequences of discrete outputs and trajectories through continuous space. The performance of HRNs is found to be superior to that of ordinary recurrent networks on these sequence generation tasks.
Bioactive glasses as carriers for bioactive molecules and therapeutic drugs: a review.

Bioactive glasses (BG) show great promise for bone tissue engineering based on their key properties, e.g., biocompatibility, biodegradability, osteoconductivity as well as osteogenic and angiogenic potential, which make them excellent candidates for bone tissue scaffolds and bone substitute materials. Recent work has shown that dissolution products of bioactive glasses have the potential to induce angiogenesis in addition to their known effect of influencing gene expression and promoting osteoblastic differentiation. One of the most interesting features of BG is their ability to bond both to soft and hard tissues, depending on their composition. To intensify the positive impact of BG for medical applications, there are considerable research efforts on using bioactive glass based platforms as carriers for the encapsulation, delivery and controlled release of bioactive molecules and therapeutic drugs. Different types of bioactive glasses have been considered in combination with different therapeutic drugs, hormones, growth factors and peptides. Using bioactive glasses as drug delivery system combines thus the effectiveness of therapeutic drugs (or bioactive/signaling molecules) with the intrinsic advantages of this inorganic biomaterial. Considering research carried out in the last 15 years, this review presents the different chemical compositions and morphologies of bioactive glasses used as carrier for bioactive molecules and therapeutic drugs and discusses the expanding potential of BG with drug delivery capability focusing in the field of bone tissue engineering.
Image processing with neural networks - a review

We review more than 200 applications of neural networks in image processing and discuss the present and possible future role of neural networks, especially feed-forward neural networks, Kohonen feature maps and Hop1eld neural networks. The various applications are categorised into a novel two-dimensional taxonomy for image processing algorithms. One dimension speci1es the type of task performed by the algorithm: preprocessing, data reduction=feature extraction, segmentation, object recognition, image understanding and optimisation. The other dimension captures the abstraction level of the input data processed by the algorithm: pixel-level, local feature-level, structure-level, object-level,ion level of the input data processed by the algorithm: pixel-level, local feature-level, structure-level, object-level, object-set-level and scene characterisation. Each of the six types of tasks poses speci1c constraints to a neural-based approach. These speci1c conditions are discussed in detail. A synthesis is made of unresolved problems related to the application of pattern recognition techniques in image processing and speci1cally to the application of neural networks. Finally, we present an outlook into the future application of neural networks and relate them to novel developments. ? 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Interactions between single nucleotide polymorphism of SERPINA1 gene and smoking in association with COPD: a case–control study

BACKGROUND
SERPINA1 gene has been implicated in the pathogenesis of chronic obstructive pulmonary disease (COPD), while smoking is a known risk factor for COPD. Little is known on the effect of SERPINA1 gene and its interaction with smoking in the Chinese population. In this study, the effect of SERPINA1 gene polymorphisms on COPD risk and its interaction with smoking status has been investigated.


METHOD
A total of 120 COPD patients and 481 healthy controls were recruited at The Armed Police Corps Hospital. Data on demographic variables, smoking status, history of occupational dust exposure, and allergies were collected. Genotyping for single nucleotide polymorphism's (SNP) rs1243160, rs2854254, and rs8004738 was performed in all participants.


RESULTS
SNP rs8004738 genotype was associated with a significantly higher risk for COPD (odds ratio (OR) =1.835, 95% confidence interval (CI): 1.002-3.360), whereas SNPs rs1243160 and rs2854254 did not exhibit such an association. Smoking habit also significantly increased the risk for COPD (OR =2.306, 95% CI: 1.537-3.459). On stepwise logistic regression analysis, advanced age, smoking, and SNP rs8004738 variant were associated with increased risk for COPD, while female gender and higher educational status decreased the risk. On additive interaction analysis, a significant interactive effect of SNP rs8004738 and smoking was observed in this population (relative excess risk due to interaction =0.478; attributable proportion due to interaction (AP) =0.123; S=1.197).


CONCLUSION
SNP rs8004738 of SERPINA1 gene significantly interacted with smoking status and was associated with a higher risk for COPD in the Chinese population.
Investor Sentiment and Stock Returns: Evidence from Romania

The attitude of individual investors is strongly correlated with their sentiment, so their behavior on the stock market can generate important changes in price fluctuations. The aim of our study was to provide evidence regarding the relationship between the evolution of stock market and the individual investor sentiment, proxy by the consumer confidence index. This study is conducted on the Bucharest Stock Exchange (BSE) for a 10 year time period, starting from 2002 to 2011 and includes 120 observations. The results proved that there is a positive correlation between changes in consumer confidence and stock market returns, demonstrating that individual investor sentiment affects stock prices. However, the influence of individual investor sentiment seems to be quickly removed by the force of arbitrage. The price adjustments are realized in less than a month. Moreover, the influence of individual investor sentiment on the prices of the most 10 liquid companies from BSE is not statistically significant.
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks

The term ‘Big Data’ has spread rapidly in the framework of Data Mining and Business Intelligence. This new scenario can be defined by means of those problems that cannot be effectively or efficiently addressed using the standard computing resources that we currently have. We must emphasize that Big Data does not just imply large volumes of data but also the necessity for scalability, i.e., to ensure a response in an acceptable elapsed time. When the scalability term is considered, usually traditional parallel-type solutions are contemplated, such as the Message Passing Interface or high performance and distributed Database Management Systems. Nowadays there is a new paradigm that has gained popularity over the latter due to the number of benefits it offers. This model is Cloud Computing, and among its main features we has to stress its elasticity in the use of computing resources and space, less management effort, and flexible costs. In this article, we provide an overview on the topic of Big Data, and how the current problem can be addressed from the perspective of Cloud Computing and its programming frameworks. In particular, we focus on those systems for large-scale analytics based on the MapReduce scheme and Hadoop, its open-source implementation. We identify several libraries and software projects that have been developed for aiding practitioners to address this new programming model. We also analyze the advantages and disadvantages of MapReduce, in contrast to the classical solutions in this field. Finally, we present a number of programming frameworks that have been proposed as an alternative to MapReduce, developed under the premise of solving the shortcomings of this model in certain scenarios and platforms. © 2014 John Wiley & Sons, Ltd.
A Permanent Magnet Linear Motor for Micro Robots

Linear micro motors play a key role in micro robotic systems. They can greatly simplify the drive mechanisms and this is crucial for micro systems. By using permanent magnets, much higher force-to-volume ratios can be acquired than using electromagnets and better drive performance can be obtained. This paper describes the development of a tubular permanent magnet linear motor for the actuation of micro robots. Important design criteria are established by analytical method and numerical method is applied to obtain detailed characteristics of the micro motor. The performances of the micro motor are analyzed and predicted by the finite element analysis and dynamic modeling. The derived motor model is implemented in SIMULINK and is capable of being extending to complex robotic applications. The simulation of the motor operation shows that the dynamic performance is quite satisfactory
Deep brain stimulation plus best medical therapy versus best medical therapy alone for advanced Parkinson's disease (PD SURG trial): a randomised, open-label trial

BACKGROUND
Surgical intervention for advanced Parkinson's disease is an option if medical therapy fails to control symptoms adequately. We aimed to assess whether surgery and best medical therapy improved self-reported quality of life more than best medical therapy alone in patients with advanced Parkinson's disease.


METHODS
The PD SURG trial is an ongoing randomised, open-label trial. At 13 neurosurgical centres in the UK, between November, 2000, and December, 2006, patients with Parkinson's disease that was not adequately controlled by medical therapy were randomly assigned by use of a computerised minimisation procedure to immediate surgery (lesioning or deep brain stimulation at the discretion of the local clinician) and best medical therapy or to best medical therapy alone. Patients were analysed in the treatment group to which they were randomised, irrespective of whether they received their allocated treatment. The primary endpoint was patient self-reported quality of life on the 39-item Parkinson's disease questionnaire (PDQ-39). Changes between baseline and 1 year were compared by use of t tests. This trial is registered with Current Controlled Trials, number ISRCTN34111222.


FINDINGS
366 patients were randomly assigned to receive immediate surgery and best medical therapy (183) or best medical therapy alone (183). All patients who had surgery had deep brain stimulation. At 1 year, the mean improvement in PDQ-39 summary index score compared with baseline was 5.0 points in the surgery group and 0.3 points in the medical therapy group (difference -4.7, 95% CI -7.6 to -1.8; p=0.001); the difference in mean change in PDQ-39 score in the mobility domain between the surgery group and the best medical therapy group was -8.9 (95% CI -13.8 to -4.0; p=0.0004), in the activities of daily living domain was -12.4 (-17.3 to -7.5; p<0.0001), and in the bodily discomfort domain was -7.5 (-12.6 to -2.4; p=0.004). Differences between groups in all other domains of the PDQ-39 were not significant. 36 (19%) patients had serious surgery-related adverse events; there were no suicides but there was one procedure-related death. 20 patients in the surgery group and 13 in the best medical therapy group had serious adverse events related to Parkinson's disease and drug treatment.


INTERPRETATION
At 1 year, surgery and best medical therapy improved patient self-reported quality of life more than best medical therapy alone in patients with advanced Parkinson's disease. These differences are clinically meaningful, but surgery is not without risk and targeting of patients most likely to benefit might be warranted.
Epsilon' from supersymmetry with non universal A terms?

In supersymmetric theories with a motivated flavour structure, we investigate the possibility that an epsilon' parameter as large as the measured value be generated without conflicting with the bounds from electron and neutron electric dipoles and mu --> e gamma.
A clinical prediction rule and platelet count predict esophageal varices in children.

BACKGROUND & AIMS
The validation of noninvasive tests to diagnose esophageal varices is a priority in children because repeated endoscopic evaluations are too invasive. We measured the ability of a previously developed noninvasive clinical prediction rule (CPR) to predict the presence of esophageal varices in children.


METHODS
We analyzed data from 108 children, younger than age 18, who received endoscopies at 8 centers, to assess portal hypertension from chronic liver disease or portal vein obstruction. Blood test and abdominal ultrasound scan results were obtained within 4 months of endoscopy. Grading of varices identified by endoscopy was confirmed by independent blinded review. Spleen size, based on data from the ultrasound scan, was expressed as a standard deviation score relative to normal values for age.


RESULTS
Of the children studied, 74 had esophageal varices (69%), including 35 with large varices (32%). The best noninvasive predictors of esophageal varices of any size were as follows: platelet:spleen size z-score ratio (area under the receiver operating characteristic curve [AUROC], 0.84; 95% confidence interval [CI] 0.75-0.93), CPR (AUROC, 0.80; 95% CI, 0.70-0.91), and platelet count (AUROC, 0.79; 95% CI, 0.69-0.90). The positive predictive values for the CPR and platelet count were 0.87 and 0.86, the negative predictive values were 0.64 and 0.63, the positive likelihood ratios were 3.06 and 2.76, and the negative likelihood ratios were 0.64 and 0.63, respectively. Based on positive and negative predictive values, the most accurate noninvasive tests were the CPR and platelet counts.


CONCLUSIONS
Noninvasive tests such as CPR and platelet count can assist in triaging children for endoscopy to identify esophageal varices.
The tail at scale

Software techniques that tolerate latency variability are vital to building responsive large-scale Web services.
Circle grid fractal pattern for calibration at different camera zoom levels

Camera calibration patterns and fiducial markers are basic technique for 3D measurement to create Computer Graphics (CG) and Augmented Reality (AR). A checkerboard is widely used as a calibration pattern and a circle or ring grid provides higher precision [Datta et al. 2009], and matrix codes are common as AR markers.