LLukas22/scidocs huggingface dataset:
Extracellular matrix signatures of human mammary carcinoma identify novel metastasis promoters

The extracellular matrix (ECM) is a major component of tumors and a significant contributor to cancer progression. In this study, we use proteomics to investigate the ECM of human mammary carcinoma xenografts and show that primary tumors of differing metastatic potential differ in ECM composition. Both tumor cells and stromal cells contribute to the tumor matrix and tumors of differing metastatic ability differ in both tumor- and stroma-derived ECM components. We define ECM signatures of poorly and highly metastatic mammary carcinomas and these signatures reveal up-regulation of signaling pathways including TGFβ and VEGF. We further demonstrate that several proteins characteristic of highly metastatic tumors (LTBP3, SNED1, EGLN1, and S100A2) play causal roles in metastasis, albeit at different steps. Finally we show that high expression of LTBP3 and SNED1 correlates with poor outcome for ER(-)/PR(-)breast cancer patients. This study thus identifies novel biomarkers that may serve as prognostic and diagnostic tools. DOI: http://dx.doi.org/10.7554/eLife.01308.001.
A prospective study of obesity and risk of coronary heart disease among diabetic women.

OBJECTIVE
To examine the relationship of obesity, measured as BMI, and weight change to incidence of coronary heart disease (CHD) among women with diabetes.


RESEARCH DESIGN AND METHODS
We followed 5,897 women with type 2 diabetes in the Nurses' Health Study for < or = 20 years. Women were aged 40-74 years and had no history of cardiovascular disease or cancer at the beginning of the follow-up period. BMI values from three time points (age 18 years, year 1976, and current) were derived from the reported height (1976) and corresponding reported weight. Weight changes between age 18 years and 1976 and after diagnosis of diabetes were calculated. Women reported diagnoses of diabetes and CHD every 2 years. Incident CHD cases were confirmed by medical record review.


RESULTS
During follow-up, we documented 418 incident cases of CHD (236 of nonfatal myocardial infarction and 182 of fatal CHD). After adjustment for age, smoking, and other coronary risk factors, current BMI was strongly associated with increased risk of CHD among diabetic women. The multivariate relative risks across increasing categories of BMI (<23.0, 23.0-24.9, 25.0-26.9, 27.0-29.9, 30.0-34.9, and > or = 35.0 kg/m(2)) were 1.0, 1.58, 1.85, 1.95, 2.80, and 3.21, respectively (P for trend <0.001). Increasing BMI values from age 18 years to 1976, before diagnosis of diabetes, were also positively associated with risk of CHD. Weight gain before the diagnosis of diabetes was related to increased risk of CHD. In contrast, weight change after diagnosis of diabetes was not associated with risk of CHD.


CONCLUSIONS
These findings provide strong evidence that obesity and weight gain before diagnosis of diabetes are associated with future risk of CHD among women with type 2 diabetes.
Annual Iron Loss Associated with Hemodialysis.

BACKGROUND
In order to keep up the optimal iron status in chronic hemodialysis patients, it is important to know how much iron is lost due to hemodialysis. Residual blood associated with the hemodialysis procedure together with blood sampling inevitably causes the loss of iron in chronic hemodialysis patients. Recent advances in hemodialysis techniques might have reduced this complication. In this cross-sectional study, we directly measured total iron loss by hemodialysis.


METHODS
Two hundred thirty-nine patients who received chronic hemodialysis at Otowa Memorial Hospital were enrolled; 65.7% of patients were men, and mean age was 67 ± 6.4 years (mean ± SD) and 43.2% were diabetic. Residual blood in blood tubing set and dialyzer after rinse back with saline was collected and homogenized. The iron content including free, protein-bound and heme iron was measured using an atomic absorption spectrometry.


RESULTS
The mean iron content in residual blood was 1,247.3 ± 796.2 µg (mean ± SD) and the median was 1,002 µg (95% CI 377.6-3,461.6 µg), indicating 160.8 mg (95% CI 58.9-540.0 mg) iron loss annually when hemodialysis was performed 156 times a year. Fifty milliliter whole blood for monthly blood test and another 2 ml of whole blood lost by paracentesis at every dialysis session contains 228.6 and 118.9 mg iron at 11 g/dl hemoglobin, respectively. Therefore, an annual total iron loss due to hemodialysis comes to 508.3 mg (95% CI 406.4-887.5 mg).


CONCLUSIONS
Five hundred milligram of annual iron supplementation might be sufficient to maintain iron status in hemodialysis patients, which is less than the dose recommended as 1,000-2,000 mg a year. Further study will be required to verify this iron supplementation dosage with recent hemodialysis procedure.
Time to initiate antiretroviral therapy between 4 weeks and 12 weeks of tuberculosis treatment in HIV-infected patients: results from the TIME study.

BACKGROUND
Optimal timing for initiation of antiretroviral therapy (ART) among HIV-infected patients with tuberculosis (TB) is not well established.


METHODS
HIV/TB-coinfected patients were randomized to initiate tenofovir/lamivudine/efavirenz at 4 weeks (4-week group) or 12 weeks (12-week group) of TB treatment. The primary outcome was 1-year all-cause mortality.


RESULTS
Of 156 patients, 79 were in 4-week group and 77 in 12-week group. Overall, median (interquartile range) CD4 was 43 (47-106) cells per cubic millimeter and median (interquartile range) HIV-1 RNA was 5.8 (5.4-6.3) log copies per milliliter. Eleven (7%) mortalities occurred in a total follow-up period of 137 patient-years. Seven percent (6/79, 8.76 per 100 patient-years) mortalities were in 4-week group, and 6% (5/77, 7.25 per 100 person-years) mortalities were in 12-week group [relative risk (RR) = 0.845, 95% confidence interval (CI) = 0.247 to 2.893]. Twenty-eight (35%) patients in 4-week group and 25 (32%) patients in 12-week group were hospitalized (RR = 1.142, 95% CI = 0.588 to 2.217). Grade 2-4 adverse events were 39% (31/79) in 4-week group and 34% (26/77) in 12-week group (RR = 1.267, 95% CI = 0.659 to 2.435). In multivariate analysis, "low albumin" (RR = 2.695, 95% CI = 1.353 to 5.475) and "low baseline CD4 count" (RR = 4.878, 95% CI = 1.019 to 23.256) were the independent predictors of mortality. Immune reconstitution inflammatory syndrome was more frequent in 4-week group with an incidence of 8.86 versus 5.02 per 100 person-months in 12-week group over the first 6 months of ART (P = 0.069).


CONCLUSIONS
In middle-income countries where ART is initiated at CD4 count of <350 cells per cubic millimeter, immediate initiation of ART in HIV-infected patients with active TB was not associated with survival advantage when compared to initiation of ART at 12 weeks.
Computing machinery and intelligence . 1950 Universal Turing

Many security experts would agree that, had it not been for mobile configurations, the synthesis of online algorithms might never have occurred. In fact, few computational biologists would disagree with the evaluation of von Neumann machines. We construct a peer-to-peer tool for harnessing Smalltalk, which we call TalmaAment.
Changes of cartilage and bone markers after intra-articular glucocorticoid treatment with and without postinjection rest in patients with rheumatoid arthritis.

BACKGROUND
Joint immobilisation improves the therapeutic effect of intra-articular glucocorticoid injection for knee synovitis. This may be due to retarded steroid resorption by immobilisation, a procedure that also could influence cartilage and bone metabolism.


OBJECTIVE
To evaluate changes in cartilage and bone turnover after intra-articular glucocorticoid treatment for knee synovitis with and without postinjection rest.


METHODS
20 patients with rheumatoid arthritis and knee synovitis were randomised to 24 hour bed rest or to normal activity after intra-articular glucocorticoid treatment. Serum and urine markers of cartilage and bone turnover were studied for two weeks. Cartilage oligomeric matrix protein (COMP) was used as a marker of cartilage turnover, osteocalcin as marker of bone formation, and deoxipyridinoline (DPD) as marker of bone resorption.


RESULTS
After the glucocorticoid injection COMP levels decreased in both groups (p<0.001), but significantly more in resting patients. Serum osteocalcin levels decreased significantly (p<0.001) without any difference between the groups. DPD was unchanged in both groups.


CONCLUSIONS
Intra-articular glucocorticoid treatment for knee synovitis reduced serum COMP, which suggests that such treatment may have a cartilage protective effect. The slightly larger decrease of serum COMP in the resting group may reflect a lower clearance of COMP from the joint cavity. Serum osteocalcin was temporarily reduced, indicating a reversible suppression of bone formation.
Evaluation and Measurement of Software Process Improvement—A Systematic Literature Review

BACKGROUND-Software Process Improvement (SPI) is a systematic approach to increase the efficiency and effectiveness of a software development organization and to enhance software products. OBJECTIVE-This paper aims to identify and characterize evaluation strategies and measurements used to assess the impact of different SPI initiatives. METHOD-The systematic literature review includes 148 papers published between 1991 and 2008. The selected papers were classified according to SPI initiative, applied evaluation strategies, and measurement perspectives. Potential confounding factors interfering with the evaluation of the improvement effort were assessed. RESULTS-Seven distinct evaluation strategies were identified, wherein the most common one, “Pre-Post Comparison,” was applied in 49 percent of the inspected papers. Quality was the most measured attribute (62 percent), followed by Cost (41 percent), and Schedule (18 percent). Looking at measurement perspectives, “Project” represents the majority with 66 percent. CONCLUSION-The evaluation validity of SPI initiatives is challenged by the scarce consideration of potential confounding factors, particularly given that “Pre-Post Comparison” was identified as the most common evaluation strategy, and the inaccurate descriptions of the evaluation context. Measurements to assess the short and mid-term impact of SPI initiatives prevail, whereas long-term measurements in terms of customer satisfaction and return on investment tend to be less used.
Nurses' practice environments, error interception practices, and inpatient medication errors.

PURPOSE
Medication errors remain a threat to patient safety. Therefore, the purpose of this study was to determine the relationships among characteristics of the nursing practice environment, nurse staffing levels, nurses' error interception practices, and rates of nonintercepted medication errors in acute care hospitals.


DESIGN
This study, using a nonexperimental design, was conducted in a sample of 82 medical-surgical units recruited from 14 U.S. acute care hospitals. Registered nurses (RNs) on the 82 units were surveyed, producing a sample of 686 staff nurses.


METHODS
Data collected for the 8-month study period included the number of medication errors per 1,000 patient days and the number of RN hours per patient day. Nurse survey data included the Practice Environment Scale of the Nursing Work Index as a measure of environmental characteristics; a metric of nurses' interception practices was developed for the study. All survey measures were aggregated to the unit level prior to analysis with hierarchical linear modeling.


FINDINGS
A supportive practice environment was positively associated with error interception practices among nurses in the sample of medical-surgical units. Importantly, nurses' interception practices were inversely associated with medication error rates.


CONCLUSIONS
A supportive practice environment enhances nurses' error interception practices. These interception practices play a role in reducing medication errors.


CLINICAL RELEVANCE
When supported by their practice environments, nurses employ practices that can assist in interrupting medication errors before they reach the patients.
Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets

Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models with respect to the state-of-the-art machine learning models and prognostic scoring systems on publicly available healthcare datasets. In this paper, we present the benchmarking results for several clinical prediction tasks such as mortality prediction, length of stay prediction, and ICD-9 code group prediction using Deep Learning models, ensemble of machine learning models (Super Learner algorithm), SAPS II and SOFA scores. We used the Medical Information Mart for Intensive Care III (MIMIC-III) (v1.4) publicly available dataset, which includes all patients admitted to an ICU at the Beth Israel Deaconess Medical Center from 2001 to 2012, for the benchmarking tasks. Our results show that deep learning models consistently outperform all the other approaches especially when the ‘raw’ clinical time series data is used as input features to the models.
Computer vision for assistive technologies

In the last decades there has been a tremendous increase in demand for Assistive Technologies (AT) useful to overcome functional limitations of individuals and to improve their quality of life. As a consequence, different research papers addressing the development of assistive technologies have appeared into the literature pushing the need to organize and categorize them taking into account the application assistive aims. Several surveys address the categorization problem for works concerning a specific need, hence giving the overview on the state of the art technologies supporting the related function for the individual. Unfortunately, this “user-need oriented” way of categorization considers each technology as a whole and then a deep and critical explanation of the technical knowledge used to build the operative tasks as well as a discussion on their cross-contextual applicability is completely missing making thus existing surveys unlikely to be technically inspiring for functional improvements and to explore new technological frontiers. To overcome this critical drawback, in this paper an original “task oriented” way to categorize the state of the art of the AT works has been introduced: it relies on the split of the final assistive goals into tasks that are then used as pointers to the works in literature in which each of them has been used as a component. In particular this paper concentrates on a set of cross-application Computer Vision tasks that are set as the pivots to establish a categorization of the AT already used to assist some of the user’s needs. For each task the paper analyzes the Computer Vision algorithms recently involved in the development of AT and, finally, it tries to catch a glimpse of the possible paths in the short and medium term that could allow a real improvement of the assistive outcomes. The potential impact on the assessment of AT considering users, medical, economical and social perspective is also addressed. © 2016 Elsevier Inc. All rights reserved.
Input/output-to-state stability and state-norm estimators for switched nonlinear systems

In this paper, the concepts of input/output-to-state stability (IOSS) and state-norm estimators are considered for switched nonlinear systems under average dwell-time switching signals. We show that when the average dwell-time is large enough, a switched system is IOSS if all of its constituent subsystems are IOSS. Moreover, under the same conditions, a non-switched state-norm estimator exists for the switched system. Furthermore, if some of the constituent subsystems are not IOSS, we show that still IOSS can be established for the switched system, if the activation time of the non-IOSS subsystems is not too big. Again, under the same conditions, a state-norm estimator exists for the switched system. However, in this case, the state-norm estimator is a switched system itself, consisting of two subsystems. We show that this state-norm estimator can be constructed such that its switching times are independent of the switching times of the switched system it is designed for. © 2012 Elsevier Ltd. All rights reserved.
Influence of ionic and non-ionic radiographic contrast media on leukocyte adhesion molecules.

BACKGROUND
Many papers have focused on the importance of granulocytes in the process of reperfusion and ischemia. Most of the clinical studies measured several parameters of this process during and after coronary angiography, without taking into account the effect of the radiographic contrast media (RCM) used during this procedure.


MATERIALS AND METHODS
We performed a randomized patient study (n = 37) to evaluate the effect of ionic and non-ionic RCM on granulocyte adhesion during coronary angiography. We also evaluated the influence of the ionicity and osmolarity of the different substances on granulocyte adhesion molecules in in vitro experiments.


RESULTS
The osmolarity of patient serum samples increased from 302 +/- 1 to 309 +/- 1 mOsm/kg (p < 0.05) after infusion of RCM. The CD11b expression in the samples of the non-ionic RCM treated group increased from 221 +/- 21 MFI to 377 +/- 30 MFI (p < 0.05) measured as the absolute mean fluorescence intensity (MFI), yet did not alter significantly in the ionic RCM group. In contrast, the in vitro experiments showed a reduction of the CD11b expression from 360 +/- 70 MFI to 149 +/- 30 MFI (p < 0.05) in the ionic RCM group.


CONCLUSIONS
The upregulation of adhesion molecules was significantly reduced in vivo with ionic RCM, while ionic substances caused opposite effects in vitro. This effect should be taken into account when performing leukocyte functional analysis of samples taken during angiography.
Blockade of Interferon‐γ Normalizes Interferon‐Regulated Gene Expression and Serum CXCL10 Levels in Patients With Systemic Lupus Erythematosus

OBJECTIVE
To assess the safety and immunologic impact of inhibiting interferon-γ (IFNγ) with AMG 811, a human IgG1 monoclonal antibody against IFNγ, in patients with systemic lupus erythematosus (SLE).


METHODS
Twenty-six patients with mild-to-moderate, stable SLE were administered placebo or a single dose of AMG 811, ranging from 2 mg to 180 mg subcutaneously or 60 mg intravenously.


RESULTS
Similar to results previously reported following inhibition of type I IFNs, treatment of SLE patients with AMG 811 led to a dose-dependent modulation of the expression of genes associated with IFN signaling, as assessed by microarray analysis of the whole blood. The list of impacted genes overlapped with that identified by stimulating human whole blood with IFNγ and with those gene sets reported in the literature to be differentially expressed in SLE patients. Serum levels of IFNγ-induced chemokines, including IFNγ-inducible protein 10 (IP-10), were found to be elevated at baseline in SLE patients as compared to healthy volunteers. In contrast to previously reported results from studies using type I IFN-blocking agents, treatment with AMG 811 led to dose-related reductions in the serum levels of CXCL10 (IP-10).


CONCLUSION
The scope and nature of the biomarkers impacted by AMG 811 support targeting of IFNγ as a therapeutic strategy for SLE.
Systematic literature review and validity evaluation of the Expanded Disability Status Scale (EDSS) and the Multiple Sclerosis Functional Composite (MSFC) in patients with multiple sclerosis

BACKGROUND
There are a number of instruments that describe severity and progression of multiple sclerosis and they are increasingly used as endpoints to assess the effectiveness of therapeutic interventions. We examined to what extent the psychometric properties of two accepted instruments--EDSS and MSFC--meet methodological standards and the value they have in clinical trials.


METHODS
We conducted a systematic literature search in relevant databases [MEDLINE (PubMed), ISI Web of Science, EMBASE, PsycINFO & PSYNDEX, CINAHL] yielding 3,860 results. Relevant full-text publications were identified using abstract and then full-text reviews, and the literature was reviewed.


RESULTS
For evaluation of psychometric properties (validity, reliability, sensitivity of change) of EDSS and MSFC, 120 relevant full-text publications were identified, 54 of them assessed the EDSS, 26 the MSFC and 40 included both instruments. The EDSS has some documented weaknesses in reliability and sensitivity to change. The main limitations of the MSFC are learning effects and the z-scores method used to calculate the total score. However, the methodological criterion of validity applies sufficiently for both instruments.For use in clinical studies, we found the EDSS to be preferred as a primary and secondary outcome measure in recent studies (50 EDSS, 9 MSFC).


CONCLUSIONS
Recognizing their strengths and weaknesses, both EDSS and MSFC are suitable to detect the effectiveness of clinical interventions and to monitor disease progression. Almost all publications identify the EDSS as the most widely used tool to measure disease outcomes in clinical trials. Despite some limitations, both instruments are accepted as endpoints and neither are discussed as surrogate parameters in identified publications. A great advantage of the EDSS is its international acceptance (e.g. by EMA) as a primary endpoint in clinical trials and its broad use in trials, enabling cross-study comparisons.
Flexible, Dynamic, and Scalable Service Composition for Active Routers

This paper describes a novel model for the provision of service composites for active routers. The service composition framework enables flexible programmability of the router's data path through dynamically loadable software components, called 'active components'. The composition model promotes transparent and dynamic creation of network-side services and allows independent users to partake in this process. A prototype implementation has revealed that the composition model using packet filters and a classification graph structure as a means to integrate active components into the forwarding path enables the dynamic alteration of the elements of a composite at run-time and permits scalability in the generation of such composites. Furthermore, it allows the flexible provision of a unique service profile for each packet passing through an active router. We show that the overhead of this composition model does not significantly affect the performance of the router.
Analysis of message sequences and encoding efficiency for electric vehicle to grid interconnections

Grid compatibility is a major issue for charging infrastructures of electric vehicles especially in low voltage systems. In order to respect dynamic grid limitations during the charging process, electric vehicles and charging infrastructures have to negotiate charge and grid parameters autonomosly. The ISO/IEC Joint Working Group 15118 is working on the Vehicle to Grid Communication Interface enabling user-friendly plug & charge functionality and also allowing for grid compatible charging processes. This paper describes current efforts being conducted in the standardization group, discusses the current state of the protocol in terms of message specifications, and maps various V2G use cases to the current protocol draft. The evaluation focuses on the message exchange patterns between the electric vehicle and the charge spot. Due to the adoption of highly embedded devices in electric vehicles an analysis on the application layer protocol efficiency is provided in this work. It focuses on data encoding efficiency with respect to the current state of the protocol specification. Detailed investigations on physical and data link layers are not part of this work.