Robbinssmed5561

Individuals with Lynch syndrome (LS), have an increased risk of developing cancer. Common genetic variants of telomerase reverse transcriptase (TERT) have been associated with a wide range of cancers, including colorectal cancer (CRC) in LS. We combined genotype data from 1881 LS patients, carrying pathogenic variants in MLH1, MSH2 or MSH6, for rs2075786 (G>A, intronic variant), 1207 LS patients for rs2736108 (C>T, upstream variant) and 1201 LS patients for rs7705526 (C>A, intronic variant). The risk of cancer was estimated by heterozygous/homozygous odds ratio (OR) with mixed-effects logistic regression to adjust for gene/gender/country of sample origin considering family identity. The AA genotype of SNP rs2075786 is associated with 85% higher odds at developing cancer compared to GG genotype in MSH2 pathogenic variant carriers (p = 0.0160). Kaplan-Meier analysis also shows an association for rs2075786; the AA allele for MSH2 variant carriers confers risk for earlier diagnosis of LS cancer (log-rank p = 0.0011). We report a polymorphism in TERT to be a possible modifier of disease risk in MSH2 pathogenic variant carriers. The rs2075786 SNP in TERT is associated with a differential risk of developing cancer for MSH2 pathogenic variant carriers. Use of this information has the potential to personalise screening protocols for LS patients.Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.Bile acid sodium symporter (BASS) family proteins encode a class of sodium/solute symporters. Even though the sodium transporting property of BASSs in mammals was well studied, their sodium transportability and functional roles in plant salt tolerance remained largely unknown. Here, BASS family members from 4 cotton species, as well as 30 other species were identified. Then, they were designated as members of BASS1 to BASS5 subfamilies according to their sequence similarity and phylogenetic relationships. There were 8, 11, 16 and 18 putative BASS genes in four cotton species. While whole-genome duplications (WGD) and segmental duplications rendered the expansion of the BASS gene family in cotton, BASS gene losses occurred in the tetraploid cotton during the evolution from diploids to allotetraploids. Concerning functional characterizations, the transcript profiling of GhBASSs revealed that they not only preferred tissue-specific expression but also were differently induced by various stressors and phytohormones. Gene silencing and overexpression experiments showed that GhBASS1 and GhBASS3 positively regulated, whereas GhBASS2, GhBASS4 and GhBASS5 negatively regulated plant salt tolerance. Taken together, BASS family genes have evolved before the divergence from the common ancestor of prokaryotes and eukaryotes, and GhBASSs are plastidial sodium-dependent metabolite co-transporters that can influence plant salt tolerance.Globally, kelp forests are threatened by multiple stressors, including increasing grazing by sea urchins. With coastal upwelling predicted to increase in intensity and duration in the future, understanding whether kelp forest and urchin barren urchins are differentially affected by upwelling-related stressors will give insight into how future conditions may affect the transition between kelp forests and barrens. We assessed how current and future-predicted changes in the duration and magnitude of upwelling-associated stressors (low pH, dissolved oxygen, and temperature) affected the performance of purple sea urchins (Strongylocentrotus purpuratus) sourced from rapidly-declining bull kelp (Nereocystis leutkeana) forests and nearby barrens and maintained on habitat-specific diets. Kelp forest urchins were of superior condition to barrens urchins, with ~ 6-9 times more gonad per body mass. Grazing and condition in kelp forest urchins were more negatively affected by distant-future and extreme upwelling conditions, whereas grazing and survival in urchins from barrens were sensitive to both current-day and all future-predicted upwelling, and to increases in acidity, hypoxia, and temperature regardless of upwelling. We conclude that urchin barren urchins are more susceptible to increases in the magnitude and duration of upwelling-related stressors than kelp forest urchins. These findings have important implications for urchin population dynamics and their interaction with kelp.Low energy surface coatings have found wide range of applications for generating hydrophobic and superhydrophobic surfaces. Most of the studies have been related to use of a single coating material over a single substrate or using a single technique. The degree of hydrophobicity is highly dependent on fabrication processes as well as materials being coated and as such warrants a high-level study using experimental optimization leading to the evaluation of the parametric behavior of coatings and their application techniques. Also, a single platform or system which can predict the required set of parameters for generating hydrophobic surface of required nature for given substrate is of requirement. This work applies the powerful machine learning algorithms (Levenberg Marquardt using Gauss Newton and Gradient methods) to evaluate the various processes affecting the anti-wetting behavior of coated printable paper substrates with the capability to predict the most optimized method of coating and materials that may lead to a desirable surface contact angle. The major application techniques used for this study pertain to dip coating, spray coating, spin coating and inkjet printing and silane and sol-gel base coating materials.Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features, such as speech and imaging. However, most tabular data do not assume a spatial relationship between features, and thus are unsuitable for modeling using CNNs. To meet this challenge, we develop a novel algorithm, image generator for tabular data (IGTD), to transform tabular data into images by assigning features to pixel positions so that similar features are close to each other in the image. The algorithm searches for an optimized assignment by minimizing the difference between the ranking of distances between features and the ranking of distances between their assigned pixels in the image. We apply IGTD to transform gene expression profiles of cancer cell lines (CCLs) and molecular descriptors of drugs into their respective image representations. Compared with existing transformation methods, IGTD generates compact image representations with better preservation of feature neighborhood structure. Evaluated on benchmark drug screening datasets, CNNs trained on IGTD image representations of CCLs and drugs exhibit a better performance of predicting anti-cancer drug response than both CNNs trained on alternative image representations and prediction models trained on the original tabular data.The evolution of obligate ectoparasitism in blowflies (Diptera Calliphoridae) has intrigued scientists for over a century, and surprisingly, the genetics underlying this lifestyle remain largely unknown. Blowflies use odors to locate food and oviposition sites; therefore, olfaction might have played a central role in niche specialization within the group. XST-14 concentration In insects, the coreceptor Orco is a required partner for all odorant receptors (ORs), a major gene family involved in olfactory-evoked behaviors. Hence, we characterized the Orco gene in the New World screwworm, Cochliomyia hominivorax, a blowfly that is an obligate ectoparasite of warm-blooded animals. In contrast, most of the closely related blowflies are scavengers that lay their eggs on dead animals. We show that the screwworm Orco orthologue (ChomOrco) is highly conserved within Diptera, showing signals of strong purifying selection. Expression of ChomOrco is broadly detectable in chemosensory appendages, and is related to morphological, developmental, and behavioral aspects of the screwworm biology. We used CRISPR/Cas9 to disrupt ChomOrco and evaluate the consequences of losing the OR function on screwworm behavior. In two-choice assays, Orco mutants displayed an impaired response to floral-like and animal host-associated odors, suggesting that OR-mediated olfaction is involved in foraging and host-seeking behaviors in C. hominivorax. These results broaden our understanding of the chemoreception basis of niche occupancy by blowflies.There are growing concerns on stress among nurses in low- and middle-income countries (LMICs) in South-East Asia. It is important to improve mental health among nurses in these countries. The objective of this study was to examine the efficacy of two types of newly developed smartphone-based stress management programs in improving depressive and anxiety symptoms among hospital nurses in Vietnam. This study was a three-arm (including two intervention groups and one control group) randomized trial. Participants were recruited from nurses in a large general hospital in Hanoi, Vietnam. Two types (free-choice and fixed sequential order) of smartphone-based stress management programs were developed. Participants were randomly allocated to Program A (a free-choice, multimodule stress management), Program B (a fixed-order, internet cognitive behavioral therapy, iCBT), or a control group (treatment as usual). The depressive and anxiety symptoms were measured by using the Depression Anxiety and Stress Scales at baseline, 3-, and 7-month follow-up surveys. 951 participants were randomly allocated to each of the three groups. Program B showed a statistically significant effect on improving depressive symptoms at 3-month (p = 0.048), but not at 7-month (p = 0.92); Cohen's d was - 0.18 (95% CI - 0.34 to - 0.02) and 0.03 (95% CI - 1.00 to 1.05), respectively. Program A failed to show a significant intervention effect on any of the outcomes at 3- or 7-month follow-up (p > 0.05). Despite the small effect size, the present fixed-order iCBT program seems effective in improving depression of hospital nurses in Vietnam. A public health impact of the intervention can be scalable, when considering its accessibility and minimal cost.Trial registration number The study protocol is registered at the UMIN Clinical Trials Registry (UMINCTR; ID = UMIN000033139). Registered date of the protocol is 1st Jul. 2018. https//upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000037796.