42 research outputs found
A risk prediction model for the assessment and triage of women with hypertensive disorders of pregnancy in low-resourced settings: the miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) multi-country prospective cohort study.
BACKGROUND: Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications. METHODS AND FINDINGS: From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735-0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658-0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability. CONCLUSIONS: The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care
Thin film thermistor with positive temperature coefficient of resistance based on phase separated blends of ferroelectric and semiconducting polymers
Sorafenib in patients with advanced biliary tract carcinoma: a phase II trial
BACKGROUND: Advanced biliary tract carcinoma has a very poor prognosis, with chemotherapy being the mainstay of treatment. Sorafenib, a multikinase inhibitor of VEGFR-2/-3, PDGFR-beta, B-Raf, and C-Raf, has shown to be active in preclinical models of cholangiocarcinoma. METHODS: We conducted a phase II trial of single-agent sorafenib in patients with advanced biliary tract carcinoma. Sorafenib was administered at a dose of 400 mg twice a day. The primary end point was the disease control rate at 12 weeks. RESULTS: A total of 46 patients were treated. In all, 26 (56%) had received chemotherapy earlier, and 36 patients completed at least 45 days of treatment. In intention-to-treat analysis, the objective response was 2% and the disease control rate at 12 weeks was 32.6%. Progression-free survival (PFS) was 2.3 months (range: 0-12 months), and the median overall survival was 4.4 months (range: 0-22 months). Performance status was significantly related to PFS: median PFS values for ECOG 0 and 1 were 5.7 and 2.1 months, respectively (P=0.0002). The most common toxicities were skin rash (35%) and fatigue (33%), requiring a dose reduction in 22% of patients. CONCLUSIONS: Sorafenib as a single agent has a low activity in cholangiocarcinoma. Patients having a good performance status have a better PFS. The toxicity profile is manageable
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Dissipative adaptation in driven self-assembly leading to self-dividing fibrils
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Electro-deposition as a repair method for embedded metal grids
A method is presented to self-repair cracks in embedded silver grid structures used in large area organic electronics. The repair procedure is based on electro-deposition, incited by the application of a moderate DC voltage across the crack. During this process the organic anode that is in direct electrical contact with the silver grid, functions as an appropriate medium for ion migration. Restoration of conductivity is achieved by the formation of dendritic metal structures that connect the cathodic to the anodic side of the crack. The metal dendrites decrease the gap resistance by one order of magnitude. Subsequently, another three orders of magnitude are gained upon sintering the dendrites using a high voltage pulse, yielding restored conductance levels nearly within one order of magnitude difference from native track conductance. (C) 2016 Elsevier B.V. All rights reserved
Thin film thermistor with positive temperature coefficient of resistance based on phase separated blends of ferroelectric and semiconducting polymers
We demonstrate that ferroelectric memory diodes can be utilized as switching type positive temperature coefficient (PTC) thermistors. The diode consists of a phase separated blend of a ferroelectric and a semiconducting polymer stacked between two electrodes. The current through the semiconducting polymer depends on the ferroelectric polarization. At the Curie temperature the ferroelectric polymer depolarizes and consequently the current density through the semiconductor decreases by orders of magnitude. The diode therefore acts as switching type PTC thermistor. Unlike their inorganic counterparts, the PTC thermistors presented here are thin film devices. The switching temperature can be tuned by varying the Curie temperature of the ferroelectric polymer.Novel Aerospace Material
Associative Interactions in Crowded Solutions of Biopolymers Counteract Depletion Effects
The cytosol of Escherichia coli is an extremely crowded environment, containing high concentrations of biopolymers which occupy 20-30% of the available volume. Such conditions are expected to yield depletion forces, which strongly promote macromolecular complexation. However, crowded macromolecule solutions, like the cytosol, are very prone to nonspecific associative interactions that can potentially counteract depletion. It remains unclear how the cytosol balances these opposing interactions. We used a FRET-based probe to systematically study depletion in vitro in different crowded environments, including a cytosolic mimic, E. coli lysate. We also studied bundle formation of FtsZ protofilaments under identical crowded conditions as a probe for depletion interactions at much larger overlap volumes of the probe molecule. The FRET probe showed a more compact conformation in synthetic crowding agents, suggesting strong depletion interactions. However, depletion was completely negated in cell lysate and other protein crowding agents, where the FRET probe even occupied slightly more volume. In contrast, bundle formation of FtsZ protofilaments proceeded as readily in E. coli lysate and other protein solutions as in synthetic crowding agents. Our experimental results and model suggest that, in crowded biopolymer solutions, associative interactions counterbalance depletion forces for small macromolecules. Furthermore, the net effects of macromolecular crowding will be dependent on both the size of the macromolecule and its associative interactions with the crowded background