SuperCam Calibration Targets: Design and Development

SuperCam is a highly integrated remote-sensing instrumental suite for NASA's Mars 2020 mission. It consists of a co-aligned combination of Laser-Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman and Luminescence (TRR/L), Visible and Infrared Spectroscopy (VISIR), together with sound recording (MIC) and high-magnification imaging techniques (RMI). They provide information on the mineralogy, geochemistry and mineral context around the Perseverance Rover. The calibration of this complex suite is a major challenge. Not only does each technique require its own standards or references, their combination also introduces new requirements to obtain optimal scientific output. Elemental composition, molecular vibrational features, fluorescence, morphology and texture provide a full picture of the sample with spectral information that needs to be co-aligned, correlated, and individually calibrated. The resulting hardware includes different kinds of targets, each one covering different needs of the instrument. Standards for imaging calibration, geological samples for mineral identification and chemometric calculations or spectral references to calibrate and evaluate the health of the instrument, are all included in the SuperCam Calibration Target (SCCT). The system also includes a specifically designed assembly in which the samples are mounted. This hardware allows the targets to survive the harsh environmental conditions of the launch, cruise, landing and operation on Mars during the whole mission. Here we summarize the design, development, integration, verification and functional testing of the SCCT. This work includes some key results obtained to verify the scientific outcome of the SuperCam system.

Estimating the local false discovery rate via a bootstrap solution to the reference class problem

Methods of estimating the local false discovery rate (LFDR) have been applied to different types of datasets such as high-throughput biological data, diffusion tensor imaging (DTI), and genome-wide association (GWA) studies. We present a model for LFDR estimation that incorporates a covariate into each test. Incorporating the covariates may improve the performance of testing procedures, because it contains additional information based on the biological context of the corresponding test. This method provides different estimates depending on a tuning parameter. We estimate the optimal value of that parameter by choosing the one that minimizes the estimated LFDR resulting from the bias and variance in a bootstrap approach. This estimation method is called an adaptive reference class (ARC) method. In this study, we consider the performance of ARC method under certain assumptions on the prior probability of each hypothesis test as a function of the covariate. We prove that, under these assumptions, the ARC method has a mean squared error asymptotically no greater than that of the other method where the entire set of hypotheses is used and assuming a large covariate effect. In addition, we conduct a simulation study to evaluate the performance of estimator associated with the ARC method for a finite number of hypotheses. Here, we apply the proposed method to coronary artery disease (CAD) data taken from a GWA study and diffusion tensor imaging (DTI) data.

Nutritional Programming of Bone Structure in Male Offspring by Maternal Consumption of Citrus Flavanones

Maternal exposure to hesperidin (HSP) and naringin (NAR) during pregnancy and lactation transiently compromised bone mineral density (BMD) and bone structure at the proximal tibia in female CD-1 offspring. We examined whether maternal consumption of HSP + NAR during pregnancy and lactation compromises BMD, bone structure, and bone strength in male CD-1 offspring. Male CD-1 offspring, from mothers fed a control diet (CON, n = 10) or a 0.5% HSP + 0.25% NAR diet (HSP + NAR, n = 8) for 5 weeks before mating and throughout pregnancy and lactation, were weaned and fed CON until 6 months of age. In vivo micro-computed tomography (µCT) measured tibia BMD and structure at 2, 4, and 6 months of age. Ex vivo µCT measured femur and lumbar vertebrae (LV) structure at age 6 months. Ex vivo BMD (femur, LV) and biomechanical strength (femur and tibia midpoint, femur neck) were assessed at age 6 months by dual energy x-ray absorptiometry and strength testing, respectively. At all ages, HSP + NAR offspring had greater (p < 0.05) proximal tibia cortical structure compared to CON offspring. At age 4 months, proximal tibia trabecular structure was greater (p < 0.05) than CON offspring. At age 6 months, femur neck and LV trabecular structure were greater (p < 0.05) than CON offspring. Our results demonstrate that unlike our previous study of female offspring, maternal consumption of HSP + NAR resulted in greater bone structure at the proximal tibia in male CD-1 offspring that persisted to 6 months of age. Thus, maternal programming of offspring BMD and bone structure from consumption of HSP + NAR occurred as a sex-specific response.

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing

Alternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.

Protein-protein interaction networks have been extensively used in systems biology to study the role of proteins in cell function and disease. However, current network biology studies typically assume that one gene encodes one protein isoform, ignoring the effect of alternative splicing. Alternative splicing allows a gene to produce multiple protein isoforms, by alternatively selecting distinct regions in the gene to be translated to protein products. Here, we present a computational method to predict and analyze the large-scale effect of alternative splicing on protein-protein interaction networks. Starting with a reference protein-protein interaction network determined by experiments, our method annotates protein-protein interactions with domain-domain interactions, and predicts that a protein isoform loses an interaction if it loses the domain mediating the interaction as a result of alternative splicing. Our predictions reveal the central role of alternative splicing in extensively remodeling the human protein-protein interaction network, and in increasing the functional complexity of the human cell. Our prediction method complements ongoing experimental efforts by predicting isoform-specific interactions for genes not tested yet by experiments and providing insights into the functional impact of alternative splicing.

Pharmacokinetics of Lidocaine Hydrochloride Administered with or without Adrenaline for the Paravertebral Brachial Plexus Block in Dogs

Adrenaline is known to prolong the duration of local anesthesia but its effects on the pharmacokinetic processes of local anesthetic drugs are not fully understood. Our objective was to develop a compartmental model for quantification of adrenaline’s impact on the pharmacokinetics of perineurally-injected lidocaine in the dog. Dogs were subjected to paravertebral brachial plexus block using lidocaine alone or adrenalinated lidocaine. Data was collected through a prospective, randomised, blinded crossover protocol performed over three periods. Blood samples were collected during 180 minutes following block execution. Compartmental pharmacokinetic models were developed and their goodness-of-fit were compared. The lowering effects of adrenaline on the absorption of lidocaine were statistically determined with one-sided tests. A one-compartment disposition model with two successive zero-order absorption processes best fitted our experimental data. Adrenaline decreased the peak plasma lidocaine concentration by approximately 60% (P < 0.001), decreased this local anesthetic’s fast and slow zero-order absorption rates respectively by 50% and 90% (P = 0.046, and P < 0.001), which respective durations were prolonged by 90% and 1300% (P < 0.020 and P < 0.001). Lidocaine demonstrated a previously unreported atypical absorption profile following its paravertebral injection in dogs. Adrenaline decreased the absorption rate of lidocaine and prolonged the duration of its absorption.