LLukas22/scidocs huggingface dataset:
Vedolizumab as induction and maintenance therapy for ulcerative colitis.

BACKGROUND
Gut-selective blockade of lymphocyte trafficking by vedolizumab may constitute effective treatment for ulcerative colitis.


METHODS
We conducted two integrated randomized, double-blind, placebo-controlled trials of vedolizumab in patients with active disease. In the trial of induction therapy, 374 patients (cohort 1) received vedolizumab (at a dose of 300 mg) or placebo intravenously at weeks 0 and 2, and 521 patients (cohort 2) received open-label vedolizumab at weeks 0 and 2, with disease evaluation at week 6. In the trial of maintenance therapy, patients in either cohort who had a response to vedolizumab at week 6 were randomly assigned to continue receiving vedolizumab every 8 or 4 weeks or to switch to placebo for up to 52 weeks. A response was defined as a reduction in the Mayo Clinic score (range, 0 to 12, with higher scores indicating more active disease) of at least 3 points and a decrease of at least 30% from baseline, with an accompanying decrease in the rectal bleeding subscore of at least 1 point or an absolute rectal bleeding subscore of 0 or 1.


RESULTS
Response rates at week 6 were 47.1% and 25.5% among patients in the vedolizumab group and placebo group, respectively (difference with adjustment for stratification factors, 21.7 percentage points; 95% confidence interval [CI], 11.6 to 31.7; P<0.001). At week 52, 41.8% of patients who continued to receive vedolizumab every 8 weeks and 44.8% of patients who continued to receive vedolizumab every 4 weeks were in clinical remission (Mayo Clinic score ≤2 and no subscore >1), as compared with 15.9% of patients who switched to placebo (adjusted difference, 26.1 percentage points for vedolizumab every 8 weeks vs. placebo [95% CI, 14.9 to 37.2; P<0.001] and 29.1 percentage points for vedolizumab every 4 weeks vs. placebo [95% CI, 17.9 to 40.4; P<0.001]). The frequency of adverse events was similar in the vedolizumab and placebo groups.


CONCLUSIONS
Vedolizumab was more effective than placebo as induction and maintenance therapy for ulcerative colitis. (Funded by Millennium Pharmaceuticals; GEMINI 1 ClinicalTrials.gov number, NCT00783718.).
An Integrated Success Model for Evaluating Information System in Public Sectors

This study modified the dimensions of the TAM and D&M IS Success Models and added additional two success dimensions (Management support and Training). An integrated model for evaluating IS success was generated; the proposed model has been validated by an empirical study based on a questionnaire. The results indicated that information quality has a strong significant influence on IS success (81.9%) followed by Behavioral intention (80.2%); Perceived usefulness (78.8%); whereas the least one is user involvement (70%). The overall results show that the proposed model can be beneficial for decision makers in organizations on evaluating the implementation of information systems. Key wards: DeLone & McLean IS success model, Technology Acceptance Model, Integrated IS Success Model
Using the taxonomy of cognitive learning to model online searching

In this research, we investigated whether a learning process has unique information searching characteristics. The results of this research show that information searching is a learning process with unique searching characteristics specific to particular learning levels. In a laboratory experiment, we studied the searching characteristics of 72 participants engaged in 426 searching tasks. We classified the searching tasks according to Anderson and Krathwohl’s taxonomy of the cognitive learning domain. Research results indicate that applying and analyzing, the middle two of the six categories, generally take the most searching effort in terms of queries per session, topics searched per session, and total time searching. Interestingly, the lowest two learning categories, remembering and understanding, exhibit searching characteristics similar to the highest order learning categories of evaluating and creating. Our results suggest the view of Web searchers having simple information needs may be incorrect. Instead, we discovered that users applied simple searching expressions to support their higher-level information needs. It appears that searchers rely primarily on their internal knowledge for evaluating and creating information needs, using search primarily for fact checking and verification. Overall, results indicate that a learning theory may better describe the information searching process than more commonly used paradigms of decision making or problem solving. The learning style of the searcher does have some moderating effect on exhibited searching characteristics. The implication of this research is that rather than solely addressing a searcher’s expressed information need, searching systems can also address the underlying learning need of the user. 2009 Elsevier Ltd. All rights reserved.
Morphological, physical, antimicrobial and release properties of ZnO nanoparticles-loaded bacterial cellulose films.

Bacterial cellulose (BC) monolayer and multilayer films, incorporating 5wt.% ZnO nanoparticles (NPs) have been obtained. Ultrasound (US) irradiation (40kHz) was applied during ZnO-BC nanocomposites preparation. X-ray diffraction (XRD) patterns showed that ZnO NPs were crystallized in their pure phase. SEM scanning electron microscopy (SEM) results indicated that US treatment causes to decrease ZnO particle size, forming a stable hybrid nanostructure and evenly distributed ZnO NPs coated BC nanofibers. ZnO NPs enhanced the mechanical properties and diminished water vapor permeability and moisture absorption of BC films. Antibacterial activity of ZnO-BC films against Staphylococcus aureus was more than Escherichia coli. The antibacterial activity was enhanced with the utilization of US irradiation. The ZnO release was influenced by films composition; the multilayer and US treated films being promising in order to achieve controlled release of ZnO. Results suggest that ZnO-BC films may be used as controlled release antimicrobial food active packaging.
Anorectal malformations and pregnancy-related disorders: a registry-based case-control study in 17 European regions.

OBJECTIVE
To identify pregnancy-related risk factors for different manifestations of congenital anorectal malformations (ARMs).


DESIGN
A population-based case-control study.


SETTING
Seventeen EUROCAT (European Surveillance of Congenital Anomalies) registries, 1980-2008.


POPULATION
The study population consisted of 1417 cases with ARM, including 648 cases of isolated ARM, 601 cases of ARM with additional congenital anomalies, and 168 cases of ARM-VACTERL (vertebral, anal, cardiac, tracheo-esophageal, renal, and limb defects), along with 13 371 controls with recognised syndromes or chromosomal abnormalities.


METHODS
Multiple logistic regression analyses were used to calculate adjusted odds ratios (ORs) for potential risk factors for ARM, such as fertility treatment, multiple pregnancy, primiparity, maternal illnesses during pregnancy, and pregnancy-related complications.


MAIN OUTCOME MEASURES
Adjusted ORs for pregnancy-related risk factors for ARM.


RESULTS
The ARM cases were more likely to be firstborn than the controls (OR 1.6, 95% CI 1.4-1.8). Fertility treatment and being one of twins or triplets seemed to increase the risk of ARM in cases with additional congenital anomalies or VACTERL (ORs ranging from 1.6 to 2.5). Maternal fever during pregnancy and pre-eclampsia were only associated with ARM when additional congenital anomalies were present (OR 3.9, 95% CI 1.3-11.6; OR 3.4, 95% CI 1.6-7.1, respectively), whereas maternal epilepsy during pregnancy resulted in a five-fold elevated risk of all manifestations of ARM (OR 5.1, 95% CI 1.7-15.6).


CONCLUSIONS
This large European study identified maternal epilepsy, fertility treatment, multiple pregnancy, primiparity, pre-eclampsia, and maternal fever during pregnancy as potential risk factors primarily for complex manifestations of ARM with additional congenital anomalies and VACTERL.
Semantic agent technologies for tactical sensor networks

Recent advances in wireless communication and microelectronics have enabled the development of low-cost sensor devices leading to interest in large-scale sensor networks for military applications. Sensor networks consist of large numbers of networked sensors that can be dynamically deployed and used for tactical situational awareness. One critical challenge is how to dynamically integrate these sensor networks with information fusion processes to support real-time sensing, exploitation and decision-making in a rich tactical environment. In this paper, we describe our work on an extensible prototype to address the challenge. The prototype and its constituent technologies provide a proof-of-concept that demonstrates several fundamental new approaches for implementing next generation battlefield information systems. Many cutting-edge technologies are used to implement this system, including semantic web, web services, peer-to-peer network and content-based routing. This prototype system is able to dynamically integrate various distributed sensors and multi-level information fusion services into new applications and run them across a distributed network to support different mission goals. Agent technology plays a role in two fundamental ways: resources are described, located and tasked using semantic descriptions based on ontologies and semantic services; tracking, fusion and decision-making logic is implemented using agent objects and semantic descriptions as well.
Short-term and long-term outcome of endoluminal gastroplication for the treatment of GERD: the first multicenter trial in Japan

Endoluminal gastroplication (ELGP) was the first endoscopic therapy for gastroesophageal reflux disease (GERD). Data on the long-term outcomes, including the plication status and data from Asian populations, are limited. The aim of this study was to evaluate the short-term and long-term effectiveness and safety of ELGP for GERD in the Japanese population. This was an open-label, prospective, multicenter trial of ELGP. Forty-eight patients with GERD were enrolled. The procedure involved placing circumferential plications 1–2 cm below the GE junction using the EndoCinch system. Outcome measurements were improvement of heartburn, medication use, endoscopic Los Angeles grade, durability of plications, 24-h esophageal acid exposure, esophageal manometry, and frequency of adverse events. During the 24-month follow-up, the rate of complete resolution of heartburn ranged from 54 to 66%, the rate of discontinuation or reduction of PPI/H2RA use ranged from 65 to 76%, and the rate of endoscopic classification to grade O ranged from 66 to 81%. The status with more than one plication remaining was associated with higher rates of improvement of heartburn, PPI/H2RA use, and endoscopic findings as compared with those associated with the loss of all plications. A modest decrease of the esophageal acid exposure level, but no change of the manometric parameters, was observed after ELGP. No serious adverse events were observed. In this 24-month follow-up study conducted in Japanese subjects, ELGP was found to be effective in about 60% of patients with GERD, and the procedure was safe.
Odanacatib, a selective cathepsin K inhibitor to treat osteoporosis: safety, tolerability, pharmacokinetics and pharmacodynamics--results from single oral dose studies in healthy volunteers.

AIMS
To evaluate the safety, tolerability, pharmacokinetics and pharmacodynamics of odanacatib (ODN), a cathepsin K inhibitor, in humans.


METHODS
Two double-blind, randomized, placebo-controlled, single oral dose studies were performed with ODN (2-600 mg) in 44 healthy volunteers (36 men and eight postmenopausal women).


RESULTS
Adverse experiences (AEs) with single doses of ODN were transient and mild to moderate, with the exception of one severe AE of gastroenteritis. Headache was the most frequent AE. After absorption of ODN (initial peak concentrations 4-6 h postdose), plasma concentrations exhibited a monophasic decline, with an apparent terminal half-life of ∼40-80 h. The area under the curve0-24 hours (AUC(0-24 h)), concentration at 24 hours (C(24 h)) and maximum concentration (C(max,overal)) increased in a less than dose-proportional manner from 2 to 600 mg. Administration of ODN with a high-fat meal led to ∼100% increases in AUC(0-24 h), C(max,day1), C(max,overall) and C(24 h) relative to the fasted state, while administration with a low-fat meal led to a ∼30% increase in those parameters. Reduction of biomarkers of bone resorption, the C- and N-telopeptides of cross-links of type I collagen, (CTx and NTx, respectively), was noted at 24 h for doses ≥5 mg and at 168 h postdose for ≥10 mg. In postmenopausal women administered 50 mg ODN, reductions in serum CTx of -66% and urine NTx/creatinine (uNTx/Cr) of -51% relative to placebo were observed at 24 h. At 168 h, reductions in serum CTx (-70%) and uNTx/Cr (-78%) were observed relative to baseline. Pharmacokinetic/pharmacodynamic modeling characterized the ODN concentration/uNTx/Cr relation, with a modeled EC50 value of 43.8 nM and ∼80% maximal reduction.


CONCLUSIONS
Odanacatib was well tolerated and has a pharmacokinetic and pharmacodynamic profile suitable for once weekly dosing.
SNORTRAN : An Optimizing Compiler for Snort Rules

We developed an optimizing compiler for intrusion detection rules popularized by an open-source Snort Network Intrusion Detection System (www.snort.org). While Snort and Snort-like rules are usually thought of as a list of independent patterns to be tested in a sequential order, we demonstrate that common compilation techniques are directly applicable to Snort rule sets and are able to produce high-performance matching engines. SNORTRAN combines several compilation techniques, including cost-optimized decision trees, pattern matching precompilation, and string set clustering. Although all these techniques have been used before in other domain-specific languages, we believe their synthesis in SNORTRAN is original and unique. Introduction Snort [RO99] is a popular open-source Network Intrusion Detection System (NIDS). Snort is controlled by a set of pattern/action rules residing in a configuration file of a specific format. Due to Snort’s popularity, Snort-like rules are accepted by several other NIDS [FSTM, HANK]. In this paper we describe an optimizing compiler for Snort rule sets called SNORTRAN that incorporates ideas of pattern matching compilation based on cost-optimized decision trees [DKP92, KS88] with setwise string search algorithms popularized by recent research in highperformance NIDS detection engines [FV01, CC01, GJMP]. The two main design goals were performance and compatibility with the original Snort rule interpreter. The primary application area for NIDS is monitoring IP traffic inside and outside of firewalls, looking for unusual activities that can be attributed to external attacks or internal misuse. Most NIDS are designed to handle T1/partial T3 traffic, but as the number of the known vulnerabilities grows and more and more weight is given to internal misuse monitoring on high-throughput networks (100Mbps/1Gbps), it gets harder to keep up with the traffic without dropping too many packets to make detection ineffective. Throwing hardware at the problem is not always possible because of growing maintenance and support costs, let alone the fact that the problem of making multi-unit system work in realistic environment is as hard as the original performance problem. Bottlenecks of the detection process were identified by many researchers and practitioners [FV01, ND02, GJMP], and several approaches were proposed [FV01, CC01]. Our benchmarking supported the performance analysis made by M. Fisk and G. Varghese [FV01], adding some interesting findings on worst-case behavior of setwise string search algorithms in practice. Traditionally, NIDS are designed around a packet grabber (system-specific or libcap) getting traffic packets off the wire, combined with preprocessors, packet decoders, and a detection engine looking for a static set of signatures loaded from a rule file at system startup. Snort [SNORT] and
User needs for location-aware mobile services

 Mobile contexts of use vary a lot, and may even be continuously changing during use. The context is much more than location, but its other elements are still difficult to identify or measure. Location information is becoming an integral part of different mobile devices. Current mobile services can be enhanced with location-aware features, thus providing the user with a smooth transition towards context-aware services. Potential application fields can be found in areas such as travel information, shopping, entertainment, event information and different mobile professions. This paper studies location-aware mobile services from the user's point of view. The paper draws conclusions about key issues related to user needs, based on user interviews, laboratory and field evaluations with users, and expert evaluations of location-aware services. The user needs are presented under five main themes: topical and comprehensive contents, smooth user interaction, personal and user-generated contents, seamless service entities and privacy issues.
Dual CNN Models for Unsupervised Monocular Depth Estimation

A lot of progress has been made to solve the depth estimation problem in stereo vision. Though, a very satisfactory performance is observed by utilizing the deep learning in supervised manner for depth estimation. This approach needs huge amount of ground truth training data as well as depth maps which is very laborious to prepare and many times it is not available in real scenario. Thus, the unsupervised depth estimation is the recent trend by utilizing the binocular stereo images to get rid of depth map ground truth. In unsupervised depth computation, the disparity images are generated by training the CNN with an image reconstruction loss based on the epipolar geometry constraints. The effective way of using CNN as well as investigating the better losses for the said problem needs to be addressed. In this paper, a dual CNN based model is presented for unsupervised depth estimation with 6 losses (DNM6) with individual CNN for each view to generate the corresponding disparity map. The proposed dual CNN model is also extended with 12 losses (DNM12) by utilizing the cross disparities. The presented DNM6 and DNM12 models are experimented over KITTI driving and Cityscapes urban database and compared with the recent state-of-the-art result of unsupervised depth estimation. 1
Renin-Angiotensin System Inhibitors, Type 2 Diabetes and Fibrosis Progression: An Observational Study in Patients with Nonalcoholic Fatty Liver Disease

BACKGROUND
The clinical determinants of fibrosis progression in nonalcoholic fatty liver disease (NAFLD) are still under definition.


AIM
To assess the clinical determinants of fibrosis progression rate (FPR) in NAFLD patients with baseline and follow-up histological evaluation, with a special focus on the impact of pharmacological therapy.


METHODS
In an observational cohort of 118 Italian patients from tertiary referral centers, liver histology was evaluated according to Kleiner. Independent predictors of FPR were selected by a stepwise regression approach.


RESULTS
Median follow-up was 36 months (IQR 24-77). Twenty-five patients (18%) showed some amelioration, 63 (53%) had stability, 30 (25%) had progression of fibrosis. Patients with nonalcoholic steatohepatitis (NASH) had similar demographic and anthropometric features, but a higher prevalence of type 2 diabetes (T2D; p = 0.010), and use of renin-angiotensin axis system (RAS) inhibitors (p = 0.005). Fibrosis progression was dependent of the length of follow-up, and was associated with, but did not require, the presence of NASH (p<0.05). Both fibrosis progression and faster FPR were independently associated with higher APRI score at follow-up, absence of treatment with RAS inhibitors, and T2D diagnosis at baseline (p<0.05). There was a significant interaction between use of RAS inhibitors and T2D on FPR (p = 0.002). RAS inhibitors were associated with slower FPR in patients with (p = 0.011), but not in those without (p = NS) T2D.


CONCLUSIONS
NASH is not required for fibrosis progression in NAFLD, whereas T2D seems to drive fibrogenesis independently of hepatic inflammation. Use of RAS inhibitors may contrast fibrosis progression especially in high-risk patients affected by T2D.
Nutritional screening and early treatment of malnutrition in cancer patients

BACKGROUND: Malnutrition is a frequent complication in patients with cancer and can negatively affect the outcome of treatments. On the other hand, side effects of anticancer therapies can also lead to inadequate nutrient intake and subsequent malnutrition. The nutritional screening aims to identify patients at risk of malnutrition for prompt treatment and/or careful follow-up. METHODS AND RESULTS: This manuscript highlights the need of an interdisciplinary approach (oncologist, nutritionist, dietitian, psychologist, etc.) to empower patients who are experiencing loss of physiological and biological function, fatigue, malnutrition, psychological distress, etc., as a result of cancer disease or its treatment, and maintain an acceptable quality of life. CONCLUSIONS: It is necessary to make all healthcare professionals aware of the opportunity to identify cancer patients at risk of malnutrition early in order to plan the best possible intervention and follow-up during cancer treatment and progression.
Expert Stock Picker: The Wisdom of (Experts in) Crowds

The phrase "the wisdom of crowds" suggests that good verdicts can be achieved by averaging the opinions and insights of large, diverse groups of people who possess varied types of information. Online user-generated content enables researchers to view the opinions of large numbers of users publicly. These opinions, in the form of reviews and votes, can be used to automatically generate remarkably accurate verdicts-collective estimations of future performance-about companies, products, and people on the Web to resolve very tough problems. The wealth and richness of user-generated content may enable firms and individuals to aggregate consumer-think for better business understanding. Our main contribution, here applied to user-generated stock pick votes from a widely used online financial newsletter, is a genetic algorithm approach that can be used to identify the appropriate vote weights for users based on their prior individual voting success. Our method allows us to identify and rank "experts" within the crowd, enabling better stock pick decisions than the S&P 500. We show that the online crowd performs better, on average, than the S&P 500 for two test time periods, 2008 and 2009, in terms of both overall returns and risk-adjusted returns, as measured by the Sharpe ratio. Furthermore, we show that giving more weight to the votes of the experts in the crowds increases the accuracy of the verdicts, yielding an even greater return in the same time periods. We test our approach by utilizing more than three years of publicly available stock pick data. We compare our method to approaches derived from both the computer science and finance literature. We believe that our approach can be generalized to other domains where user opinions are publicly available early and where those opinions can be evaluated. For example, YouTube video ratings may be used to predict downloads, or online reviewer ratings on Digg may be used to predict the success or popularity of a story.