LLukas22/scidocs huggingface dataset:
First-in-Human Phase I Study of PRS-050 (Angiocal), an Anticalin Targeting and Antagonizing VEGF-A, in Patients with Advanced Solid Tumors

BACKGROUND
To report the nonrandomized first-in-human phase I trial of PRS-050, a novel, rationally engineered Anticalin based on human tear lipocalin that targets and antagonizes vascular endothelial growth factor A (VEGF-A).


METHODS
Patients with advanced solid tumors received PRS-050 at 0.1 mg/kg to 10 mg/kg by IV in successive dosing cohorts according to the 3+3 escalation scheme. The primary end point was safety.


RESULTS
Twenty-six patients were enrolled; 25 were evaluable. Two patients experienced dose-limiting toxicity, comprising grade (G) 3 hypertension and G3 pyrexia, respectively. The maximum tolerated dose was not reached. Most commonly reported treatment-emergent adverse events (AEs) included chills (52%; G3, 4%), fatigue (52%; G3, 4%), hypertension (44%; G3, 16%), and nausea (40%, all G1/2). No anti-PRS-050 antibodies following multiple administration of the drug were detected. PRS-050 showed dose-proportional pharmacokinetics (PK), with a terminal half-life of approximately 6 days. Free VEGF-A was detectable at baseline in 9/25 patients, becoming rapidly undetectable after PRS-050 infusion for up to 3 weeks. VEGF-A/PRS-050 complex was detectable for up to 3 weeks at all dose levels, including in patients without detectable baseline-free VEGF-A. We also detected a significant reduction in circulating matrix metalloproteinase 2, suggesting this end point could be a pharmacodynamic (PD) marker of the drug's activity.


CONCLUSIONS
PRS-050, a novel Anticalin with high affinity for VEGF-A, was well-tolerated when administered at the highest dose tested, 10 mg/kg. Based on target engagement and PK/PD data, the recommended phase II dose is 5 mg/kg every 2 weeks administered as a 120-minute infusion.


TRIAL REGISTRATION
ClinicalTrials.gov NCT01141257 http://clinicaltrials.gov/ct2/show/NCT01141257.
Evolution: A Collection of Misfits

Different strains of one genetic model species after another are turning out to have limited abilities to interbreed, as if they were on the way to becoming different species. Are model organisms aberrations, or are the first steps in speciation easier than they seem?
FTTH network economics: Key parameters impacting technology decisions

Different technology options are available to operators today for their Fiber-to-the-home (FTTH) network deployment strategy decisions. Gigabit-Passive Optical Network (GPON), Ethernet Passive Optical Network (EPON), Active Ethernet (AE) and Point-to-Point Ethernet (P2P) are the major competing technologies. There are a number of technical, economic and business drivers that impact the right choice for each specific network situation. When modeling network economics, it is important to consider a Total Cost of Ownership (TCO) model to enable operators to rightly evaluate these choices, instead of comparisons of only specific cost elements (e.g., port costs). On the other hand, in a network model with a large number of parameters it is often challenging to identify the key parameters that are critical to the decision-making. An operator runs the risk of picking an incorrect technology strategy if any of these key parameters are not identified and cost optimized. In this paper, we present the results obtained by modeling the capital investments and operations expenses incurred for some operator cases, and identify the key parameters that impact FTTH economics covering these major technologies. We show sensitivity analysis to identify the critical parameters. The methodology and results will enable operators quickly make the right FTTH technology deployment decisions.
Learning management systems and cloud file hosting services: A study on students' acceptance

The aim of this paper is to investigate the motivations that lead higher education students to replace several Learning Management Systems (LMS) services with cloud file hosting services for information sharing and collaboration among them. The research approach is based on the Technology Acceptance Model (TAM). More specifically, the model is devoted to identifying barriers and enablers to the acceptance of these technologies. A questionnaire comprising three factors (Attitude toward using technology, Perceived ease of use and Perceived usefulness) was applied to a sample consisting of 121 higher education students. Results show that the perceived ease of use of cloud file hosting services is above that of LMS tools and services and that cloud file hosting services presented higher levels of perceived usefulness than standard learning management tools. In addition, attitude toward using cloud file hosting services is well above that of using LMS tools. 2013 Elsevier Ltd. All rights reserved.
Quantitative changes in cytological molecular markers during primary medical treatment of breast cancer: A pilot study

Aim: To quantify the changes in biological molecular markers during primary medical treatment in patients with operable breast cancer and to assess their possible relationship with response to treatment. Methods: The treatment group consisted of 31 patients with operable breast carcinomas, median age 57 years (range 41–67), treated with four 3‐weekly cycles of chemotherapy with Mitoxantrone, methotrexate (± mitomycin C), and tamoxifen before surgery. Fine needle aspiration (FNA) was used to obtain samples from patients prior to and at 10 or 21 days post‐treatment. The following molecular markers were assessed: estrogen receptor (ER), progesterone receptor (PgR), p53, Bcl‐2, and Ki67 measured by immunocytochemistry, and ploidy and S‐phase fraction (SPF) by flow cytometry. To evaluate the reproducibility of the technique, repeat FNA was performed in a separate non‐treatment control group of 20 patients and the same molecular markers assessed, two weeks after the first sample with no intervening treatment. Results: The non‐treatment control group showed a high reproducibility for the measurement of molecular markers from repeat FNA. In the treatment group there was a non‐significant reduction in SPF and a significant reduction (p = 0.005) in Ki67. Patients who responded to neoadjuvant therapy were more likely to have a reduction in these two markers than those who failed to respond. Similarly, a reduction in ER scores was observed between the first and second samples (p = 0.04). For PgR, the change between the first and second samples was not significant although there was a significant difference between responders and non‐responders (p = 0.03). All nine patients with an increase in PgR were responders. No significant changes in p53 or Bcl‐2 were observed during treatment. Conclusion: Molecular markers can be adequately measured from FNA samples prior to and during neoadjuvant therapy. Changes in cellular proliferation and hormone receptors have been shown that may be related to tumour response. These relationships should be assessed in a larger cohort of patients.
Physical processes mediating climate impacts in shelf sea ecosystems

Oral presentation at European Geophysical Union Conference EGU General Assembly 2013, held 7-12 April, 2013 in Vienna, Austria. Abstract http://adsabs.harvard.edu/abs/2013EGUGA..15.7507H
Multitasking across generations: Multitasking choices and difficulty ratings in three generations of Americans

This study investigated whether changes in the technological/social environment in the United States over time have resulted in concomitant changes in the multitasking skills of younger generations. One thousand, three hundred and nineteen Americans from three generations were queried to determine their at-home multitasking behaviors. An anonymous online questionnaire asked respondents to indicate which everyday and technology-based tasks they choose to combine for multitasking and to indicate how difficult it is to multitask when combining the tasks. Combining tasks occurred frequently, especially while listening to music or eating. Members of the ‘‘Net Generation” reported more multitasking than members of ‘‘Generation X,” who reported more multitasking than members of the ‘‘Baby Boomer” generation. The choices of which tasks to combine for multitasking were highly correlated across generations, as were difficulty ratings of specific multitasking combinations. The results are consistent with a greater amount of general multitasking resources in younger generations, but similar mental limitations in the types of tasks that can be multitasked. 2008 Elsevier Ltd. All rights reserved.
Biosorption of heavy metals-An overview

During the last two decades, extensive attention has been paid on the management of environmental pollution causal by hazardous materials such as heavy metals. Decontamination of heavy metals in the soil and water around industrial plants has been a challenge for a long time. A number of methods have been developed for the removal of heavy metals from liquid wastes such as precipitation, evaporation, electroplating, ion exchange, membrane processes, etc. However, these methods have several disadvantages such as unpredictable metal ion removal, high reagent requirement, generation of toxic sludge, etc. Biosorption is a process, which represents a biotechnological innovation as well as a cost effective excellent tool for removing heavy metals from aqueous solutions. This article provides a selective overview of past achievements and present scenario of biosorption studies carried out on some promising natural biosorbents (algae, fungi, bacteria, yeast) and some waste materials which could serve as an economical means of treating effluents charged with toxic metallic ions.
The Blockchain-Based Digital Content Distribution System

The blockchain-based digital content distribution system was developed. Decentralized and pear-to-pear authentication mechanism can be considered as the ideal rights management mechanism. The blockchain has the potential to realize this ideal content distribution system. This is the successful model of the Superdistribution concept which was announced almost 30 years ago. The proposed system was demonstrated and got a lot of feedback for the future practical system.
Thermodynamics of complex formation in dimethylsulfoxide: The case of Co(II) complexes with nitrogen donor ligands and their O2 adducts

Abstract Data for complex formation of Co(II) with N -donors in dimethylsulfoxide are reviewed and rationalized on the basis of both solvational effects and ligand structural and electronic features. For the polyamine ligands, the number and stability of the species formed decreases with increasing number of N -methyl groups, due to the increase of the steric crowding and the relatively low basicity of the donor nitrogen. However also the stabilization through H-bond formation with the second-sphere solvent molecules is an important factor. The same factor causes a greater electron donation from the ligand to the metal ion stabilizing the complex as shown by the thermodynamic and structural data. When comparing the thermodynamic parameters with those available in water, it results that the stability constants are higher than those in water despite the stronger solvation of the metal ion in DMSO. This is assigned to the ligand solvation playing an important role, especially for primary and secondary amines. When ligands able to be only H-bond acceptors are considered (tertiary amines and pyridines) the stability of the complex expected on the basis of the metal ion solvation is observed. When considering the oxygen affinity of the Co(II) complexes in DMSO it results that the complexes with primary and secondary amines are able to bind O 2 . As O 2 uptake is a redox process it strongly depends on the ligand-metal charge transfer and on the solvation of the resulting complex. Thus, the same factors affecting the stability of the Co(II) complexes with the N -donor ligands considered also influence their dioxygen affinity. A correlation between enthalpy and electrochemical data in DMSO supports this hypothesis.
Electromyographic models to assess muscle fatigue.

Muscle fatigue is a common experience in daily life. Many authors have defined it as the incapacity to maintain the required or expected force, and therefore, force, power and torque recordings have been used as direct measurements of muscle fatigue. In addition, the measurement of these variables combined with the measurement of surface electromyography (sEMG) recordings (which can be measured during all types of movements) during exercise may be useful to assess and understand muscle fatigue. Therefore, there is a need to develop muscle fatigue models that relate changes in sEMG variables with muscle fatigue. However, the main issue when using conventional sEMG variables to quantify fatigue is their poor association with direct measures of fatigue. Therefore, using different techniques, several authors have combined sets of sEMG parameters to assess muscle fatigue. The aim of this paper is to serve as a state-of-the-art summary of different sEMG models used to assess muscle fatigue. This paper provides an overview of linear and non-linear sEMG models for estimating muscle fatigue, their ability to assess power loss and their limitations due to neuromuscular changes after a training period.
Independent validation of the prolonged length of stay score.

BACKGROUND
The prolonged length of stay (PLOS) score has recently been derived and validated in 2 independent national cohorts of acute stroke patients in Israel. The present study aimed to determine the performance of the PLOS score in an independent population-based cohort of stroke patients in a health care system considerably different from that in which the score was derived.


METHODS
The study was performed on all 434 patients with ischemic stroke or intracerebral hemorrhage hospitalized during the first 5 years of the population-based Oxford Vascular Study (OXVASC) in Oxfordshire, UK. Median (interquartile range) length of stay (LOS) and rates of LOS ≥7 days and LOS ≥30 days by the PLOS score were calculated. Model discrimination was assessed by the c-statistic and goodness of fit was evaluated with the Hosmer-Lemeshow test.


RESULTS
Median LOS and rates of LOS ≥7 days increased with the increase in PLOS score among all inpatients and hospital survivors. In the analysis of LOS ≥7 days, the PLOS c-statistic (95% CI) was 0.676 (0.618-0.734) for all inpatients and 0.722 (0.664-0.779) for hospital survivors. Findings were similar for LOS ≥30 days. The Hosmer-Lemeshow showed good calibration.


CONCLUSIONS
The PLOS score successfully predicted PLOS in the OXVASC population of acute stroke patients. Although the score was originally derived for the prediction of prolonged acute hospitalization, it successfully predicted prolonged total LOS.
Miniaturized Rat Race Coupler With Suppression of Spurious Passband

A new hybrid ring coupler design is devised for circuit miniaturization based on the periodic stepped-impedance ring resonator structure. The circuit has an area of 21.5% of a conventional rat race coupler and no passband up to the sixth harmonic of the design frequency. The designs are validated by comparing measured four-port parameters with the simulated results
Neural Reasoning for Legal Text Understanding

We propose a domain specific Question Answering system. We deviate from approaching this problem as a Textual Entailment task. We implemented a Memory Network-based Question Answering system which test a Machine’s understanding of legal text and identifies whether an answer to a question is correct or wrong, given some background knowledge. We also prepared a corpus of real USA MBE Bar exams for this task. We report our initial result and direction for future works.
Comparing the effects of two different break strategies on occupational sedentary behavior in a real world setting: A randomized trial

UNLABELLED
Developing interventions to reduce sedentary behavior in the workplace is an important public health priority. Furthermore, research is needed to determine whether different approaches to breaking up prolonged sitting during the workday are equally feasible and effective. Thus, the purpose of this study was to determine whether varying the frequency and duration of activity breaks during the workday would differentially impact sedentary behavior and health outcomes. Inactive females (N = 49) working full-time sedentary jobs were recruited for this parallel-group randomized trial. Participants were randomly assigned to take short, frequent breaks from sitting (1-2 min every half hour; SB) or longer, planned breaks from sitting (two 15-minute breaks per workday; LB) during each workday across an 8-week intervention. Sedentary time and health outcomes were assessed at baseline and post-intervention. The study ran from March 2014-June 2015. Results showed sedentary time during the workday decreased significantly in the SB group (- 35.6 min; d = - 0.75; p = 0.03), but did not change in the LB group (+ 4.5 min; d = 0.12). Participants in the SB group also demonstrated small-to-moderate declines in total cholesterol (d = - 0.33; p = 0.10), triglycerides (d = - 0.38; p = 0.06) and fasting blood glucose (d = - 0.29; p = 0.01) from pre to post-intervention. Health outcomes did not change in the LB group. This study demonstrated that taking short, frequent breaks from sitting during the workday is a feasible and effective approach for reducing sedentary time at work. These results have implications for the development of public health messages addressing sedentary behavior, and inform future interventions to reduce sedentary time in the workplace.


TRIAL REGISTRATION
This study is registered at www.clinicaltrials.gov: NCT02609438.
Workflow Quality of Service

Workflow management systems (WfMSs) have been used to support various types of business processes for more than a decade now. In ecommerce processes, suppliers and customers define a binding agreement or contract between the two parties, specifying quality of service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of service. Management of such QoS directly impacts success of organizations participating in e-commerce. Organizations operating in modern markets require an excellent degree of quality of service management. Products and services must be available to customers with well-defined specifications. A good management of quality leads to the creation of quality products and services, which in turn fulfills customer expectations and achieves customer satisfaction. Therefore, when services or products are created or managed using workflow processes, the underlying WfMS must accept the specification, be able to predict, monitor, and control the QoS rendered to customers. To achieve these objectives the first step is to develop an adequate QoS model for workflow processes and develop methods to compute QoS.
Short-term outcome of primary operated early breast cancer by hormone and HER-2 receptors

Introduction Prognostic subgroup classification of operable breast cancers using cDNA clustering of breast cancer-related genes resembles the classification based on the combined immunohistochemical (IHC) expression of the hormone and HER-2 receptors. We here report the short-term disease-free interval (DFI) of operable breast cancers by their joint hormone receptor/HER-2 phenotype. Patients and methods Short-term follow-up (FU) of a prospective cohort of 1,958 breast-cancer patients primary operated at our institution between 2000 and 2005. Receptors were evaluated using IHC. Steroid receptors were considered positive for any nuclear staining; HER-2 for strong (3+) membrane staining or positive fluorescence in situ hybridization (FISH). Kaplan–Meier (KM) DFI curves were calculated for any relapse defined as a local, regional, contralateral, or distant breast cancer event for the six predefined breast cancer subgroups: ER + PR + HER-2 − (PPN), ER + PR − HER-2 − (PNN), ER + PR + HER-2 + (PPP), ER – PR − HER-2 − (NNN), ER – PR − HER-2 + (NNP), and ER + PR − HER-2 + (PNP). P-values were calculated for comparison of the six different survival curves using two possible adaptations for multiple testing. A multivariate model for the receptors predicting DFI did incorporate local and systemic adjuvant therapy. Results Median patient age was 57 years (ranges 26–96) and median FU was 3.35 years. Overall, DFI at median FU was 91%; 94% for PPN, 89% for PNN, 86% for NNN, 81% for PPP, 80% for PNP, and 76% for NNP cases. Some receptor subgroups had a significantly better DFI than others based on multiple testing, especially when the PPN group was compared against the four most frequent subtypes. The multivariate model with local and systemic adjuvant therapy confirmed the prognostic value of ER, PR, and HER-2 for short-term DFI. Conclusion It is possible to distinguish short-term prognostic breast cancer subgroups only on the basis of ER, PR, and HER-2 even when stratified for local and systemic adjuvant therapy. While gene expression profiles based on microarray data of over hundreds of genes will probably teach us much about breast cancer biology, heterogeneity, and prognosis, we emphasize the important short-term prognostic value of currently used IHC markers for ER, PR, and HER-2.
Comparing Rule-Based and Deep Learning Models for Patient Phenotyping

Objective: We investigate whether deep learning techniques for natural language processing (NLP) can be used efficiently for patient phenotyping. Patient phenotyping is a classification task for determining whether a patient has a medical condition, and is a crucial part of secondary analysis of healthcare data. We assess the performance of deep learning algorithms and compare them with classical NLP approaches. Materials and Methods: We compare convolutional neural networks (CNNs), n-gram models, and approaches based on cTAKES that extract pre-defined medical concepts from clinical notes and use them to predict patient phenotypes. The performance is tested on 10 different phenotyping tasks using 1,610 discharge summaries extracted from the MIMIC-III database. Results: CNNs outperform other phenotyping algorithms in all 10 tasks. The average F1-score of our model is 76 (PPV of 83, and sensitivity of 71) with our model having an F1-score up to 37 points higher than alternative approaches. We additionally assess the interpretability of our model by presenting a method that extracts the most salient phrases for a particular prediction. Conclusion: We show that NLP methods based on deep learning improve the performance of patient phenotyping. Our CNN-based algorithm automatically learns the phrases associated with each patient phenotype. As such, it reduces the annotation complexity for clinical domain experts, who are normally required to develop task-specific annotation rules and identify relevant phrases. Our method performs well in terms of both performance and interpretability, which indicates that deep learning is an effective approach to patient phenotyping based on clinicians’ notes. *gehrmann@seas.harvard.edu
Review of neural network applications in medical imaging and signal processing

The current applications of neural networks to in vivo medical imaging and signal processing are reviewed. As is evident from the literature neural networks have already been used for a wide variety of tasks within medicine. As this trend is expected to continue this review contains a description of recent studies to provide an appreciation of the problems associated with implementing neural networks for medical imaging and signal processing.