Environmental Stimulation Chamber for Nanosatellite Functional Testing

The goal of this project is to develop a nanosatellite thermal testing chamber for the Robotic Systems Laboratory at Santa Clara University. The nanosatellite industry has thrived in recent years and continues to grow at the level of universities and small businesses. To meet this demand, the team designed and built a testing bed capable of achieving environmental conditions adequate for testing nanosatellite hardware as a low-cost and low-maintenance alternative to more expensive and robust systems. Furthermore, the design can be fully manufactured and assembled at the university or small business level with inexpensive, sustainable, and commercially available components. The final product will save money and decrease energy consumption while fully realizing the thermal testing needs for nanosatellite communication hardware

Relationship between magnetic resonance imaging findings and histological grade in spinal peripheral nerve sheath tumors in dogs

BackgroundPeripheral nerve sheath tumors (PNSTs) are a group of neoplasms originating from Schwann cells or pluripotent cell of the neural crest. Therapeutic options and prognosis are influenced by their degree of malignancy and location.Hypothesis/ObjectivesIdentify magnetic resonance imaging (MRI) features predictive of PNST histologic grade.AnimalsForty‐four dogs with histopathological diagnosis of spinal PNSTs and previous MRI investigation.MethodsA multicenter retrospective study including cases with (a) histopathologic diagnosis of PNST and (b) MRI studies available for review. Histologic slides were reviewed and graded by a board‐certified pathologist according to a modified French system (FNCLCC) for grading soft tissue sarcomas. The MRI studies were reviewed by 2 board‐certified radiologists blinded to the grade of the tumor and the final decision on the imaging characteristics was reached by consensus. Relationships between tumor grade and histological and MRI findings were assessed using statistical analysis.ResultsForty‐four cases met inclusion criteria; 16 patients were PNSTs Grade 1 (low‐grade), 19 were PNSTs Grade 2 (medium‐grade), and 9 were PNSTs Grade 3 (high‐grade). Large volume (P = .03) and severe peripheral contrast enhancement (P = .04) were significantly associated with high tumor grade. Degree of muscle atrophy, heterogeneous signal and tumor growth into the vertebral canal were not associated with grade.Conclusions and Clinical ImportanceGrade of malignancy was difficult to identify based on diagnostic imaging alone. However, some MRI features were predictive of high‐grade PNSTs including tumor size and peripheral contrast enhancement

Estimating CDKN2A mutation carrier probability among global familial melanoma cases using GenoMELPREDICT

Background: Although rare in the general population, highly penetrant germline mutations in CDKN2A are responsible for 5%-40% of melanoma cases reported in melanoma-prone families. We sought to determine whether MELPREDICT was generalizable to a global series of families with melanoma and whether performance improvements can be achieved. Methods: In total, 2116 familial melanoma cases were ascertained by the international GenoMEL Consortium. We recapitulated the MELPREDICT model within our data (GenoMELPREDICT) to assess performance improvements by adding phenotypic risk factors and history of pancreatic cancer. We report areas under the curve (AUC) with 95% confidence intervals (CIs) along with net reclassification indices (NRIs) as performance metrics. Results: MELPREDICT performed well (AUC 0.752, 95% CI 0.730-0.775), and GenoMELPREDICT performance was similar (AUC 0.748, 95% CI 0.726-0.771). Adding a reported history of pancreatic cancer yielded discriminatory improvement (P < .0001) in GenoMELPREDICT (AUC 0.772, 95% CI 0.750-0.793, NRI 0.40). Including phenotypic risk factors did not improve performance. Conclusion: The MELPREDICT model functioned well in a global data set of familial melanoma cases. Adding pancreatic cancer history improved model prediction. GenoMELPREDICT is a simple tool for predicting CDKN2A mutational status among melanoma patients from melanoma-prone families and can aid in directing these patients to receive genetic testing or cancer risk counseling

Scanning and filling : ultra-dense SNP genotyping combining genotyping-by-sequencing, SNP array and whole-genome resequencing data

Genotyping-by-sequencing (GBS) represents a highly cost-effective high-throughput genotyping approach. By nature, however, GBS is subject to generating sizeable amounts of missing data and these will need to be imputed for many downstream analyses. The extent to which such missing data can be tolerated in calling SNPs has not been explored widely. In this work, we first explore the use of imputation to fill in missing genotypes in GBS datasets. Importantly, we use whole genome resequencing data to assess the accuracy of the imputed data. Using a panel of 301 soybean accessions, we show that over 62,000 SNPs could be called when tolerating up to 80% missing data, a five-fold increase over the number called when tolerating up to 20% missing data. At all levels of missing data examined (between 20% and 80%), the resulting SNP datasets were of uniformly high accuracy (96– 98%). We then used imputation to combine complementary SNP datasets derived from GBS and a SNP array (SoySNP50K). We thus produced an enhanced dataset of >100,000 SNPs and the genotypes at the previously untyped loci were again imputed with a high level of accuracy (95%). Of the >4,000,000 SNPs identified through resequencing 23 accessions (among the 301 used in the GBS analysis), 1.4 million tag SNPs were used as a reference to impute this large set of SNPs on the entire panel of 301 accessions. These previously untyped loci could be imputed with around 90% accuracy. Finally, we used the 100K SNP dataset (GBS + SoySNP50K) to perform a GWAS on seed oil content within this collection of soybean accessions. Both the number of significant marker-trait associations and the peak significance levels were improved considerably using this enhanced catalog of SNPs relative to a smaller catalog resulting from GBS alone at 20% missing data. Our results demonstrate that imputation can be used to fill in both missing genotypes and untyped loci with very high accuracy and that this leads to more powerful genetic analyses

Analysis of high-identity segmental duplications in the grapevine genome

<p>Abstract</p> <p>Background</p> <p>Segmental duplications (SDs) are blocks of genomic sequence of 1-200 kb that map to different loci in a genome and share a sequence identity > 90%. SDs show at the sequence level the same characteristics as other regions of the human genome: they contain both high-copy repeats and gene sequences. SDs play an important role in genome plasticity by creating new genes and modeling genome structure. Although data is plentiful for mammals, not much was known about the representation of SDs in plant genomes. In this regard, we performed a genome-wide analysis of high-identity SDs on the sequenced grapevine (<it>Vitis vinifera</it>) genome (PN40024).</p> <p>Results</p> <p>We demonstrate that recent SDs (> 94% identity and >= 10 kb in size) are a relevant component of the grapevine genome (85 Mb, 17% of the genome sequence). We detected mitochondrial and plastid DNA and genes (10% of gene annotation) in segmentally duplicated regions of the nuclear genome. In particular, the nine highest copy number genes have a copy in either or both organelle genomes. Further we showed that several duplicated genes take part in the biosynthesis of compounds involved in plant response to environmental stress.</p> <p>Conclusions</p> <p>These data show the great influence of SDs and organelle DNA transfers in modeling the <it>Vitis vinifera </it>nuclear DNA structure as well as the impact of SDs in contributing to the adaptive capacity of grapevine and the nutritional content of grape products through genome variation. This study represents a step forward in the full characterization of duplicated genes important for grapevine cultural needs and human health.</p

PINK1 Is Necessary for Long Term Survival and Mitochondrial Function in Human Dopaminergic Neurons

Parkinson's disease (PD) is a common age-related neurodegenerative disease and it is critical to develop models which recapitulate the pathogenic process including the effect of the ageing process. Although the pathogenesis of sporadic PD is unknown, the identification of the mendelian genetic factor PINK1 has provided new mechanistic insights. In order to investigate the role of PINK1 in Parkinson's disease, we studied PINK1 loss of function in human and primary mouse neurons. Using RNAi, we created stable PINK1 knockdown in human dopaminergic neurons differentiated from foetal ventral mesencephalon stem cells, as well as in an immortalised human neuroblastoma cell line. We sought to validate our findings in primary neurons derived from a transgenic PINK1 knockout mouse. For the first time we demonstrate an age dependent neurodegenerative phenotype in human and mouse neurons. PINK1 deficiency leads to reduced long-term viability in human neurons, which die via the mitochondrial apoptosis pathway. Human neurons lacking PINK1 demonstrate features of marked oxidative stress with widespread mitochondrial dysfunction and abnormal mitochondrial morphology. We report that PINK1 plays a neuroprotective role in the mitochondria of mammalian neurons, especially against stress such as staurosporine. In addition we provide evidence that cellular compensatory mechanisms such as mitochondrial biogenesis and upregulation of lysosomal degradation pathways occur in PINK1 deficiency. The phenotypic effects of PINK1 loss-of-function described here in mammalian neurons provides mechanistic insight into the age-related degeneration of nigral dopaminergic neurons seen in PD

Reduced fire severity offers near-term buffer to climate-driven declines in conifer resilience across the western United States

Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration. © 2023 the Author(s)

Cardiovascular Magnetic Resonance Reference Ranges From the Healthy Hearts Consortium

Background: The absence of population-stratified cardiovascular magnetic resonance (CMR) reference ranges from large cohorts is a major shortcoming for clinical care. Objectives: This paper provides age-, sex-, and ethnicity-specific CMR reference ranges for atrial and ventricular metrics from the Healthy Hearts Consortium, an international collaborative comprising 9,088 CMR studies from verified healthy individuals, covering the complete adult age spectrum across both sexes, and with the highest ethnic diversity reported to date. Methods: CMR studies were analyzed using certified software with batch processing capability (cvi42, version 5.14 prototype, Circle Cardiovascular Imaging) by 2 expert readers. Three segmentation methods (smooth, papillary, anatomic) were used to contour the endocardial and epicardial borders of the ventricles and atria from long- and short-axis cine series. Clinically established ventricular and atrial metrics were extracted and stratified by age, sex, and ethnicity. Variations by segmentation method, scanner vendor, and magnet strength were examined. Reference ranges are reported as 95% prediction intervals. Results: The sample included 4,452 (49.0%) men and 4,636 (51.0%) women with average age of 61.1 ± 12.9 years (range: 18-83 years). Among these, 7,424 (81.7%) were from White, 510 (5.6%) South Asian, 478 (5.3%) mixed/other, 341 (3.7%) Black, and 335 (3.7%) Chinese ethnicities. Images were acquired using 1.5-T (n = 8,779; 96.6%) and 3.0-T (n = 309; 3.4%) scanners from Siemens (n = 8,299; 91.3%), Philips (n = 498; 5.5%), and GE (n = 291, 3.2%). Conclusions: This work represents a resource with healthy CMR-derived volumetric reference ranges ready for clinical implementation

Particulate matter exposure during pregnancy is associated with birth weight, but not gestational age, 1962-1992: a cohort study

<p>Abstract</p> <p>Background</p> <p>Exposure to air pollutants is suggested to adversely affect fetal growth, but the evidence remains inconsistent in relation to specific outcomes and exposure windows.</p> <p>Methods</p> <p>Using birth records from the two major maternity hospitals in Newcastle upon Tyne in northern England between 1961 and 1992, we constructed a database of all births to mothers resident within the city. Weekly black smoke exposure levels from routine data recorded at 20 air pollution monitoring stations were obtained and individual exposures were estimated via a two-stage modeling strategy, incorporating temporally and spatially varying covariates. Regression analyses, including 88,679 births, assessed potential associations between exposure to black smoke and birth weight, gestational age and birth weight standardized for gestational age and sex.</p> <p>Results</p> <p>Significant associations were seen between black smoke and both standardized and unstandardized birth weight, but not for gestational age when adjusted for potential confounders. Not all associations were linear. For an increase in whole pregnancy black smoke exposure, from the 1^st(7.4 μg/m³) to the 25^th(17.2 μg/m³), 50^th(33.8 μg/m³), 75^th(108.3 μg/m³), and 90^th(180.8 μg/m³) percentiles, the adjusted estimated decreases in birth weight were 33 g (SE 1.05), 62 g (1.63), 98 g (2.26) and 109 g (2.44) respectively. A significant interaction was observed between socio-economic deprivation and black smoke on both standardized and unstandardized birth weight with increasing effects of black smoke in reducing birth weight seen with increasing socio-economic disadvantage.</p> <p>Conclusions</p> <p>The findings of this study progress the hypothesis that the association between black smoke and birth weight may be mediated through intrauterine growth restriction. The associations between black smoke and birth weight were of the same order of magnitude as those reported for passive smoking. These findings add to the growing evidence of the harmful effects of air pollution on birth outcomes.</p