95 research outputs found
Polyvinylidene Fluoride Aerogels with Tailorable Crystalline Phase Composition
In this work, polyvinylidene fluoride (PVDF) aerogels with a tailorable phase composition
were prepared by following the crystallization-induced gelation principle. A series of PVDF wet gels
(5 to 12 wt.%) were prepared from either PVDFβDMF solutions or a mixture of DMF and ethanol
as non-solvent. The effects of the non-solvent concentration on the crystalline composition of the
PVDF aerogels were thoroughly investigated. It was found that the nucleating role of ethanol can be
adjusted to produce low-density PVDF aerogels, whereas the changes in composition by the addition
of small amounts of water to the solution promote the stabilization of the valuable Ξ² and Ξ³ phases.
These phases of the aerogels were monitored by FTIR and Raman spectroscopies. Furthermore, the
crystallization process was followed by in-time and in situ ATRβFTIR spectroscopy. The obtained
aerogels displayed specific surface areas > 150 m2 gβ1, with variable particle morphologies that are
dependent on the non-solvent composition, as observed by using SEM and Synchrotron Radiation
Computed micro-Tomography (SR-ΞΌC
The International Academy of Health Sciences Informatics (IAHSI): 2020 Report
Objectives: To summarize the major activities of the International Academy of Health Sciences Informatics (IAHSI) in the 2020 time period and to welcome its 2020 Class of Fellows. Method: Report from the members of the Academy's Board. Results: Due to the SARS-CoV-2 pandemic, both Plenary meetings in 2020 had to be organized as virtual meetings. Scientific discussions, focusing on mobilizing computable biomedical knowledge and on data standards and interoperability formed major parts of these meetings. A statement on the use of informatics in pandemic situations was elaborated and sent to the World Health Organization. A panel on data standards and interoperability started its work. 34 Fellows were welcomed in the 2020 Class of Fellows so that the Academy now consists of 179 members. Conclusions: There was a shift from supporting to strategic activities in the Academy's work. After having achieved organizational stability, the Academy can now focus on its strategic work and so on its main objective.S
An Insecticidal N-Acetylglucosamine-Specific Lectin Gene from Griffonia simplicifolia (Leguminosae)
The legume pod borer, Maruca vitrata Fabricius (Lepidoptera: Crambidae), an important insect pest of cowpea: a review emphasizing West Africa
The legume pod borer Maruca vitrata Fabricius (Lepidoptera: Crambidae) is a pantropical insect pest of legumes. In West Africa M. vitrata is the most devastating insect pest of cowpea, a food crop providing much-needed, inexpensive protein to farmers and consumers. Various approaches to controlling this pest have been tried, including cultural management, host plant resistance and use of synthetic and botanical pesticides, all with limited success. In this review we present information on the distribution, morphology, molecular characteristics, behavior and host plants of M. vitrata. We give especial attention to innovative management tactics being developed for West Africa, including genetically engineered Bt cowpea, new biopesticides and use of exotic parasitoids. We discuss research needs for enhancing integrated pest management (IPM) for M. vitrata in Africa
New resampling method for evaluating stability of clusters
<p>Abstract</p> <p>Background</p> <p>Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in clustering procedures. Statistical methods are required to distinguish between real and random clusters. Several methods for assessing cluster stability have been published, including resampling methods such as the bootstrap.</p> <p>We propose a new resampling method based on continuous weights to assess the stability of clusters in hierarchical clustering. While in bootstrapping approximately one third of the original items is lost, continuous weights avoid zero elements and instead allow non integer diagonal elements, which leads to retention of the full dimensionality of space, i.e. each variable of the original data set is represented in the resampling sample.</p> <p>Results</p> <p>Comparison of continuous weights and bootstrapping using real datasets and simulation studies reveals the advantage of continuous weights especially when the dataset has only few observations, few differentially expressed genes and the fold change of differentially expressed genes is low.</p> <p>Conclusion</p> <p>We recommend the use of continuous weights in small as well as in large datasets, because according to our results they produce at least the same results as conventional bootstrapping and in some cases they surpass it.</p
A Meta-Analysis of Effects of Bt Crops on Honey Bees (Hymenoptera: Apidae)
L.) are the most important pollinators of many agricultural crops worldwide and are a key test species used in the tiered safety assessment of genetically engineered insect-resistant crops. There is concern that widespread planting of these transgenic crops could harm honey bee populations.We conducted a meta-analysis of 25 studies that independently assessed potential effects of Bt Cry proteins on honey bee survival (or mortality). Our results show that Bt Cry proteins used in genetically modified crops commercialized for control of lepidopteran and coleopteran pests do not negatively affect the survival of either honey bee larvae or adults in laboratory settings.Although the additional stresses that honey bees face in the field could, in principle, modify their susceptibility to Cry proteins or lead to indirect effects, our findings support safety assessments that have not detected any direct negative effects of Bt crops for this vital insect pollinator
Phase I/IIa study of intratumoral/intracerebral or intravenous/intracerebral administration of Parvovirus H-1 (ParvOryx) in patients with progressive primary or recurrent glioblastoma multiforme: ParvOryx01 protocol
A Naturally Occurring Plant Cysteine Protease Possesses Remarkable Toxicity against Insect Pests and Synergizes Bacillus thuringiensis Toxin
When caterpillars feed on maize (Zea maize L.) lines with native resistance to several Lepidopteran pests, a defensive cysteine protease, Mir1-CP, rapidly accumulates at the wound site. Mir1-CP has been shown to inhibit caterpillar growth in vivo by attacking and permeabilizing the insect's peritrophic matrix (PM), a structure that surrounds the food bolus, assists in digestion and protects the midgut from microbes and toxins. PM permeabilization weakens the caterpillar defenses by facilitating the movement of other insecticidal proteins in the diet to the midgut microvilli and thereby enhancing their toxicity. To directly determine the toxicity of Mir1-CP, the purified recombinant enzyme was directly tested against four economically significant Lepidopteran pests in bioassays. Mir1-CP LC50 values were 1.8, 3.6, 0.6, and 8.0 ppm for corn earworm, tobacco budworm, fall armyworm and southwestern corn borer, respectively. These values were the same order of magnitude as those determined for the Bacillus thuringiensis toxin Bt-CryIIA. In addition to being directly toxic to the larvae, 60 ppb Mir1-CP synergized sublethal concentrations of Bt-CryIIA in all four species. Permeabilization of the PM by Mir1-CP probably provides ready access to Bt-binding sites on the midgut microvilli and increases its activity. Consequently, Mir1-CP could be used for controlling caterpillar pests in maize using non-transgenic approaches and potentially could be used in other crops either singly or in combination with Bt-toxins
An epidemiological model for prediction of endometrial cancer risk in Europe
Endometrial cancer (EC) is the fourth most frequent cancer in women in Europe, and as its incidence is increasing, prevention strategies gain further pertinence. Risk prediction models can be a useful tool for identifying women likely to benefit from targeted prevention measures. On the basis of data from 201,811 women (mostly aged 30β65 years) including 855 incident EC cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict EC was developed. A step-wise model selection process was used to select confirmed predictive epidemiologic risk factors. Piece-wise constant hazard rates in 5-year age-intervals were estimated in a cause-specific competing risks model, five-fold-cross-validation was applied for internal validation. Risk factors included in the risk prediction model were body-mass index (BMI), menopausal status, age at menarche and at menopause, oral contraceptive use, overall and by different BMI categories and overall duration of use, parity, age at first full-term pregnancy, duration of menopausal hormone therapy and smoking status (specific for pre, peri- and post-menopausal women). These variables improved the discriminating capacity to predict risk over 5 years from 71 % for a model based on age alone to 77 % (overall C statistic), and the model was well-calibrated (ratio of expected to observed cases = 0.99). Our model could be used for the identification of women at increased risk of EC in Western Europe. To achieve an EC-risk model with general validity, a large-scale cohort-consortium approach would be needed to assess and adjust for population variation
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