Electron-phonon interaction in a local region

The paper reports on a study of electron-phonon interaction within a limited nanosized region. We invoked the modified Fr\"{o}hlich's Hamiltonian to calculate the electron self-energy, as well as the elastic and inelastic scattering cross sections. New effects have been revealed, more specifically: a bound state forms within the limited nanosized region, electrons undergo resonant elastic scattering, with strong inelastic scattering being possible from this state even at low electron energies. The effect of scattering on the magnetic-field-independent dephasing time, in particular, in a diamond-decorated carbon nanotube, has been determined. The effect of strong inelastic electron scattering on thermal resistance at the metal-insulator interface is discussed.Comment: 13 pages, 2 figure

Traditional knowledge of wild edible plants used in Palestine (Northern West Bank): A comparative study

<p>Abstract</p> <p>Background</p> <p>A comparative food ethnobotanical study was carried out in fifteen local communities distributed in five districts in the Palestinian Authority, PA (northern West Bank), six of which were located in Nablus, two in Jenin, two in Salfit, three in Qalqilia, and two in Tulkarm. These are among the areas in the PA whose rural inhabitants primarily subsisted on agriculture and therefore still preserve the traditional knowledge on wild edible plants.</p> <p>Methods</p> <p>Data on the use of wild edible plants were collected for one-year period, through informed consent semi-structured interviews with 190 local informants. A semi-quantitative approach was used to document use diversity, and relative importance of each species.</p> <p>Results and discussion</p> <p>The study recorded 100 wild edible plant species, seventy six of which were mentioned by three informants and above and were distributed across 70 genera and 26 families. The most significant species include <it>Majorana syriaca, Foeniculum vulgare, Malvasylvestris</it>, <it>Salvia fruticosa, Cyclamen persicum, Micromeria fruticosa, Arum palaestinum, Trigonella foenum-graecum</it>, <it>Gundelia tournefortii</it>, and <it>Matricaria aurea</it>. All the ten species with the highest mean cultural importance values (mCI), were cited in all five areas. Moreover, most were important in every region. A common cultural background may explain these similarities. One taxon (<it>Majoranasyriaca</it>) in particular was found to be among the most quoted species in almost all areas surveyed. CI values, as a measure of traditional botanical knowledge, for edible species in relatively remote and isolated areas (Qalqilia, and Salfit) were generally higher than for the same species in other areas. This can be attributed to the fact that local knowledge of wild edible plants and plant gathering are more spread in remote or isolated areas.</p> <p>Conclusion</p> <p>Gathering, processing and consuming wild edible plants are still practiced in all the studied Palestinian areas. About 26 % (26/100) of the recorded wild botanicals including the most quoted and with highest mCI values, are currently gathered and utilized in all the areas, demonstrating that there are ethnobotanical contact points among the various Palestinian regions. The habit of using wild edible plants is still alive in the PA, but is disappearing. Therefore, the recording, preserving, and infusing of this knowledge to future generations is pressing and fundamental.</p

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs

Matriptase: Potent Proteolysis on the Cell Surface

Matriptase is a type II transmembrane serine protease expressed in most human epithelia, where it is coexpressed with its cognate transmembrane inhibitor, hepatocyte growth factor activator inhibitor (HAI)-1. Activation of the matriptase zymogen requires sequential N-terminal cleavage, activation site autocleavage, and transient association with HAI-1. Matriptase has an essential physiological role in profilaggrin processing, corneocyte maturation, and lipid matrix formation associated with terminal differentiation of the oral epithelium and the epidermis, and is also critical for hair follicle growth. Matriptase and HAI expression are frequently dysregulated in human cancer, and matriptase expression that is unopposed by HAI-1 potently promotes carcinogenesis and metastatic dissemination in animal models

Polygenic risk scores for prediction of breast cancer and breast cancer subtypes

Abstract Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57–1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628–0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs