Xeroderma Pigmentosum Group C Deficiency Alters Cigarette Smoke DNA Damage Cell Fate and Accelerates Emphysema Development

Cigarette smoke (CS) exposure is a major risk factor for the development of emphysema, a common disease characterized by loss of cells comprising the lung parenchyma. The mechanisms of cell injury leading to emphysema are not completely understood but are thought to involve persistent cytotoxic or mutagenic DNA damage induced by CS. Using complementary cell culture and mouse models of CS exposure, we investigated the role of the DNA repair protein, xeroderma pigmentosum group C (XPC), on CS-induced DNA damage repair and emphysema. Expression of XPC was decreased in mouse lungs after chronic CS exposure and XPC knockdown in cultured human lung epithelial cells decreased their survival after CS exposure due to activation of the intrinsic apoptosis pathway. Similarly, cell autophagy and apoptosis were increased in XPC-deficient mouse lungs and were further increased by CS exposure. XPC deficiency was associated with structural and functional changes characteristic of emphysema, which were worsened by age, similar to levels observed with chronic CS exposure. Taken together, these findings suggest that repair of DNA damage by XPC plays an important and previously unrecognized role in the maintenance of alveolar structures. These findings support that loss of XPC, possibly due to chronic CS exposure, promotes emphysema development and further supports a link between DNA damage, impaired DNA repair, and development of emphysema

Cosmogenic ^3He production rate in ilmenite and the redistribution of spallation ^3He in fine-grained minerals

Cosmogenic nuclide surface exposure dating and erosion rate measurements in basaltic landscapes rely primarily on measurement of ^3He in olivine or pyroxene. However, geochemical investigations using ^3He have been impossible in the substantial fraction of basalts that lack separable olivine or pyroxene crystals, or where such crystals were present, but have been chemically weathered. Fine-textured basalts often contain small grains of ilmenite, a weathering-resistant mineral that is a target for cosmogenic ^3He production with good He retention and straightforward mineral separation, but with a poorly constrained production rate. Here we empirically calibrate the cosmogenic ^3He production rate in ilmenite by measuring ^3He concentrations in basalts with fine-grained (∼20 μm cross-section) ilmenite and co-existing pyroxene or olivine from the Columbia River and Snake River Plain basalt provinces in the western United States. The concentration ratio of ilmenite to pyroxene and olivine is 0.78 ± 0.02, yielding an apparent cosmogenic ^3He production rate of 93.6 ± 7.7 atom g^(−1) yr^(−1) that is 20–30% greater than expected from prior theoretical and empirical estimates for compositionally similar minerals. The production rate discrepancy arises from the high energy with which cosmic ray spallation reactions emit tritium and ^3He and the associated long stopping distances that cause them to redistribute within a rock. Fine-grained phases with low cosmogenic ^3He production rates, like ilmenite, will have anomalously high production rates owing to net implantation of ^3He from the surrounding, higher ^3He production rate, matrix. Semi-quantitative modeling indicates implantation of spallation ^3He increases with decreasing ilmenite grain size, leading to production rates that exceed those in a large grain by ∼10% when grain radii are <150 μm. The modeling predicts that for the ilmenite grain size in our samples, implantation causes production rates to be ∼20% greater than expected for a large grain, and within uncertainty resolves the discrepancy between our calibrated production rate, theory, and rates from previous work. The redistribution effect is maximized when the host rock and crystals differ substantially in mean atomic number, as they do between whole-rock basalt and ilmenite

VINEDA—Volcanic INfrasound Explosions Detector Algorithm

Infrasound is an increasingly popular tool for volcano monitoring, providing insights of the unrest by detecting and characterizing acoustic waves produced by volcanic processes, such as explosions, degassing, rockfalls, and lahars. Efficient event detection from large infrasound databases gathered in volcanic settings relies on the availability of robust and automated workflows. While numerous triggering algorithms for event detection have been proposed in the past, they mostly focus on applications to seismological data. Analyses of acoustic infrasound for signal detection is often performed manually or by application of the traditional short-term average/long-term average (STA/LTA) algorithms, which have shown limitations when applied in volcanic environments, or more generally to signals with poor signal-to-noise ratios. Here, we present a new algorithm specifically designed for automated detection of volcanic explosions from acoustic infrasound data streams. The algorithm is based on the characterization of the shape of the explosion signals, their duration, and frequency content. The algorithm combines noise reduction techniques with automatic feature extraction in order to allow confident detection of signals affected by non-stationary noise.We have benchmarked the performances of the new detector by comparison with both the STA/LTA algorithm and human analysts, with encouraging results. In this manuscript, we present our algorithm and make its software implementation available to other potential users. This algorithm has potential to either be implemented in near real-timemonitoring workflows or to catalog pre-existing databases.This research was partially funded by KNOWAVES TEC2015- 68752 (MINECO/FEDER), by NERC Grant NE/P00105X/1, by Spanish research grant MECD Jose Castillejo CAS17/00154 and by VOLCANOWAVES European Union’s Horizon 2020 Research and Innovation Programme Under the Marie Sklodowska-Curie Grant Agreement no 798480

Globally Distributed Drug Discovery of New Antibiotics: Design and Combinatorial Synthesis of Amino Acid Derivatives in the Organic Chemistry Laboratory

An experiment for the synthesis of N-acyl derivatives of natural amino acids has been developed as part of the Distributed Drug Discovery (D3) program. Students use solid-phase synthesis techniques to complete a three-step, combinatorial synthesis of six products, which are analyzed using LC–MS and NMR spectroscopy. This protocol is suitable for introductory organic laboratory students and has been successfully implemented at multiple academic sites internationally. Accompanying prelab activities introduce students to SciFinder and to medicinal chemistry design principles. Pairing of these activities with the laboratory work provides students an authentic and cohesive research project experience

Influence of advanced age of maternal grandmothers on Down syndrome

BACKGROUND: Down syndrome (DS) is the most common chromosomal anomaly associated with mental retardation. This is due to the occurrence of free trisomy 21 (92–95%), mosaic trisomy 21 (2–4%) and translocation (3–4%). Advanced maternal age is a well documented risk factor for maternal meiotic nondisjunction. In India three children with DS are born every hour and more DS children are given birth to by young age mothers than by advanced age mothers. Therefore, detailed analysis of the families with DS is needed to find out other possible causative factors for nondisjunction. METHODS: We investigated 69 families of cytogenetically confirmed DS children and constructed pedigrees of these families. We also studied 200 randomly selected families belonging to different religions as controls. Statistical analysis was carried out using logistic regression. RESULTS: Out of the 69 DS cases studied, 67 were free trisomy 21, two cases were mosaic trisomy 21 and there were none with translocation. The number of DS births was greater for the young age mothers compared with the advanced age mothers. It has also been recorded that young age mothers (18 to 29 years) born to their mothers at the age 30 years and above produced as high as 91.3% of children with DS. The logistic regression of case- control study of DS children revealed that the odds ratio of age of grandmother was significant when all the four variables were used once at a time. However, the effect of age of mother and father was smaller than the effect of age of maternal grandmother. Therefore, for every year of advancement of age of the maternal grandmother, the risk (odds) of birth of DS baby increases by 30%. CONCLUSION: Besides the known risk factors, mother's age, father's age, the age of the maternal grandmother at the time of birth of the mother is a risk factor for the occurrence of Down syndrome

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Changes in the Provision of Institutionalized Mental Health Care in Post-Communist Countries

PMCID: PMC3371010This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities

The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data

Sequencing of chemotherapy and radiation therapy for early breast cancer

Background After surgery for localised breast cancer, adjuvant radiotherapy improves both local control and breast cancer specific survival. In patients at risk of harbouring micro-metastatic disease, adjuvant chemotherapy improves 15-year survival. However, the best sequence of administering these two types of adjuvant therapy for early stage breast cancer is not clear