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We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.

Harnessing the rich nonlinear dynamics of highly deformable materials has the potential to unlock the next generation of functional smart materials and devices. However, unlocking such potential requires effective strategies to spatially engineer material architectures within the nonlinear dynamic regime. Here we introduce an inverse-design framework to discover flexible mechanical metamaterials with a target nonlinear dynamic response. The desired dynamic task is encoded via optimal tuning of the full-scale metamaterial geometry through an inverse-design approach powered by a fully differentiable simulation environment. By deploying such a strategy, mechanical metamaterials are tailored for energy focusing, energy splitting, dynamic protection and nonlinear motion conversion. Furthermore, our design framework can be expanded to automatically discover reprogrammable architectures capable of switching between different dynamic tasks. For instance, we encode two strongly competing tasks-energy focusing and dynamic protection-within a single architecture, using static precompression to switch between these behaviours. The discovered designs are physically realized and experimentally tested, demonstrating the robustness of the engineered tasks. Our approach opens an untapped avenue towards designer materials with tailored robotic-like reprogrammable functionalities., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Humans can learn complex functional relationships between variables from small amounts of data. In doing so, they draw on prior expectations about the form of these relationships. In three experiments, we show that people learn to adjust these expectations through experience, learning about the likely forms of the functions they will encounter. Previous work has used Gaussian processes-a statistical framework that extends Bayesian nonparametric approaches to regression-to model human function learning. We build on this work, modeling the process of learning to learn functions as a form of hierarchical Bayesian inference about the Gaussian process hyperparameters., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

We report the development of an open-source experimental design via Bayesian optimization platform for multi-objective reaction optimization. Using high-throughput experimentation (HTE) and virtual screening data sets containing high-dimensional continuous and discrete variables, we optimized the performance of the platform by fine-tuning the algorithm components such as reaction encodings, surrogate model parameters, and initialization techniques. Having established the framework, we applied the optimizer to real-world test scenarios for the simultaneous optimization of the reaction yield and enantioselectivity in a Ni/photoredox-catalyzed enantioselective cross-electrophile coupling of styrene oxide with two different aryl iodide substrates. Starting with no previous experimental data, the Bayesian optimizer identified reaction conditions that surpassed the previously human-driven optimization campaigns within 15 and 24 experiments, for each substrate, among 1728 possible configurations available in each optimization. To make the platform more accessible to nonexperts, we developed a graphical user interface (GUI) that can be accessed online through a web-based application and incorporated features such as condition modification on the fly and data visualization. This web application does not require software installation, removing any programming barrier to use the platform, which enables chemists to integrate Bayesian optimization routines into their everyday laboratory practices.

Juniper (Juniperus) is an ecologically important conifer genus of the Northern Hemisphere, the members of which are often foundational tree species of arid regions. The serrate leaf margin clade is native to topologically variable regions in North America, where hybridization has likely played a prominent role in their diversification. Here we use a reduced-representation sequencing approach (ddRADseq) to generate a phylogenomic data set for 68 accessions representing all 22 species in the serrate leaf margin clade, as well as a number of close and distant relatives, to improve understanding of diversification in this group. Phylogenetic analyses using three methods (SVDquartets, maximum likelihood, and Bayesian) yielded highly congruent and well-resolved topologies. These phylogenies provided improved resolution relative to past analyses based on Sanger sequencing of nuclear and chloroplast DNA, and were largely consistent with taxonomic expectations based on geography and morphology. Calibration of a Bayesian phylogeny with fossil evidence produced divergence time estimates for the clade consistent with a late Oligocene origin in North America, followed by a period of elevated diversification between 12 and 5 Mya. Comparison of the ddRADseq phylogenies with a phylogeny based on Sanger-sequenced chloroplast DNA revealed five instances of pronounced discordance, illustrating the potential for chloroplast introgression, chloroplast transfer, or incomplete lineage sorting to influence organellar phylogeny. Our results improve understanding of the pattern and tempo of diversification in Juniperus, and highlight the utility of reduced-representation sequencing for resolving phylogenetic relationships in non-model organisms with reticulation and recent divergence., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Reaction optimization is fundamental to synthetic chemistry, from optimizing the yield of industrial processes to selecting conditions for the preparation of medicinal candidates 1 . Likewise, parameter optimization is omnipresent in artificial intelligence, from tuning virtual personal assistants to training social media and product recommendation systems 2 . Owing to the high cost associated with carrying out experiments, scientists in both areas set numerous (hyper)parameter values by evaluating only a small subset of the possible configurations. Bayesian optimization, an iterative response surface-based global optimization algorithm, has demonstrated exceptional performance in the tuning of machine learning models 3 . Bayesian optimization has also been recently applied in chemistry 4-9 ; however, its application and assessment for reaction optimization in synthetic chemistry has not been investigated. Here we report the development of a framework for Bayesian reaction optimization and an open-source software tool that allows chemists to easily integrate state-of-the-art optimization algorithms into their everyday laboratory practices. We collect a large benchmark dataset for a palladium-catalysed direct arylation reaction, perform a systematic study of Bayesian optimization compared to human decision-making in reaction optimization, and apply Bayesian optimization to two real-world optimization efforts (Mitsunobu and deoxyfluorination reactions). Benchmarking is accomplished via an online game that links the decisions made by expert chemists and engineers to real experiments run in the laboratory. Our findings demonstrate that Bayesian optimization outperforms human decisionmaking in both average optimization efficiency (number of experiments) and consistency (variance of outcome against initially available data). Overall, our studies suggest that adopting Bayesian optimization methods into everyday laboratory practices could facilitate more efficient synthesis of functional chemicals by enabling better-informed, data-driven decisions about which experiments to run.

Background: Gene flow and polyploidy have been found to be important in Juniperus evolution. However, little evidence has been published elucidating the association of both phenomena in juniper taxa in the wild. Two main areas were studied in Spain (Eastern Iberian Range and Sierra de Baza) with both diploid and tetraploid taxa present in sympatry. Gene flow and ploidy level were assessed for these taxa and the resulted offspring., Results: Twenty-two allo-triploid hybrids between J. sabina var. sabina and J. thurifera were found in the Eastern Iberian Range population. However, in the Sierra de Baza population no triploids were found. Instead, 18 allo-tetraploid hybrids between two tetraploid taxa: J. sabina var. balkanensis and J. thurifera were discovered. High genetic diversity was exhibited among the tetraploid hybrids at Sierra de Baza, in contrast to the genetically identical triploid hybrids at the Eastern Iberian Range; this suggests meiotic difficulties within the triploid hybrids. In addition, unidirectional gene flow was observed in both studied areas., Conclusion: Polyploidy and hybridization can be complementary partners in the evolution of Juniperus taxa in sympatric occurrences. Juniperus was shown to be an ideal coniferous model to study these two phenomena, independently or in concert.

Cellular mechanical metamaterials are a special class of materials whose mechanical properties are primarily determined by their geometry. However, capturing the nonlinear mechanical behavior of these materials, especially those with complex geometries and under large deformation, can be challenging due to inherent computational complexity. In this work, we propose a data-driven multiscale computational scheme as a possible route to resolve this challenge. We use a neural network to approximate the effective strain energy density as a function of cellular geometry and overall deformation. The network is constructed by "learning" from the data generated by finite element calculation of a set of representative volume elements at cellular scales. This effective strain energy density is then used to predict the mechanical responses of cellular materials at larger scales. Compared with direct finite element simulation, the proposed scheme can reduce the computational time up to two orders of magnitude. Potentially, this scheme can facilitate new optimization algorithms for designing cellular materials of highly specific mechanical properties.

Hundreds of plant mitogenomes have been sequenced from angiosperms, but relatively few mitogenomes are available from its sister lineage, gymnosperms. To examine mitogenomic diversity among extant gymnosperms, we generated draft mitogenomes from 11 diverse species and compared them with four previously published mitogenomes. Examined mitogenomes from Pinaceae and cycads retained all 41 protein genes and 26 introns present in the common ancestor of seed plants, whereas gnetophyte and cupressophyte mitogenomes experienced extensive gene and intron loss. In Pinaceae and cupressophyte mitogenomes, an unprecedented number of exons are distantly dispersed, requiring trans-splicing of 50-70% of mitochondrial introns to generate mature transcripts. RNAseq data confirm trans-splicing of these dispersed exons in Pinus. The prevalence of trans-splicing in vascular plant lineages with recombinogenic mitogenomes suggests that genomic rearrangement is the primary cause of shifts from cis- to trans-splicing in plant mitochondria., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Terpenes, volatile plant secondary compounds produced by woody plants, have historically been thought to act as feeding deterrents for mammalian herbivores. However, three species of woodrats, Neotoma stephensi, N. lepida, and N. albigula, regularly consume juniper, which is high in terpenes, and N. stephensi and N. lepida are considered juniper specialists. By investigating the terpene profiles in Juniperus monosperma and J. osteosperma, which are browsed or avoided by woodrats in the field, and recording the caching and consumption of juniper foliage by woodrats in the lab, we have evidence that terpenes may serve as feeding and/or foraging cues. The obligate specialist N. stephensi chose to forage on trees higher in p-cymene and preferred to consume juniper rather than caching it in a laboratory setting. These observations provide evidence that terpenes serve as a feeding cue and that the obligate specialist's physiological mechanism for metabolizing the terpenes present in juniper may negate the need for caching. The facultative specialist N. lepida chose to forage on trees lower in four terpenes and cached more juniper than the obligate specialist N. stephensi, providing evidence that terpenes serve as a feeding deterrent for N. lepida and that this woodrat species relies on behavioral mechanisms to minimize terpene intake. The generalist N. albigula foraged on trees with higher terpenes levels but consumed the least amount of juniper in the lab and preferred to cache juniper rather than consume it, evidence that terpenes act as foraging but not feeding cues in the generalist. Our findings suggest that volatile plant secondary compounds can act as feeding and/or foraging cues and not just feeding deterrents in mammalian herbivores.

Recent research suggests that the frequency of polyploidy may have been underestimated in gymnosperms. One notable example is in the conifer genus Juniperus , where there are already a few reports of polyploids although data are still missing for most species. In this study, we evaluated the extent of polyploidy in Juniperus by conducting the first comprehensive screen across nearly all of the genus. Genome size data from fresh material, together with chromosome counts, were used to demonstrate that genome sizes estimated from dried material could be used as reliable proxies to uncover the extent of ploidy diversity across the genus. Our analysis revealed that 16 Juniperus taxa were polyploid, with tetraploids and one hexaploid being reported. Furthermore, by analyzing the genome size and chromosome data within a phylogenetic framework we provide the first evidence of possible lineage-specific polyploidizations within the genus. Genome downsizing following polyploidization is moderate, suggesting limited genome restructuring. This study highlights the importance of polyploidy in Juniperus , making it the first conifer genus and only the second genus in gymnosperms where polyploidy is frequent. In this sense, Juniperus represents an interesting model for investigating the genomic and ecological consequences of polyploidy in conifers.

When confronted with a substance of unknown identity, researchers often perform mass spectrometry on the sample and compare the observed spectrum to a library of previously collected spectra to identify the molecule. While popular, this approach will fail to identify molecules that are not in the existing library. In response, we propose to improve the library's coverage by augmenting it with synthetic spectra that are predicted from candidate molecules using machine learning. We contribute a lightweight neural network model that quickly predicts mass spectra for small molecules, averaging 5 ms per molecule with a recall-at-10 accuracy of 91.8%. Achieving high-accuracy predictions requires a novel neural network architecture that is designed to capture typical fragmentation patterns from electron ionization. We analyze the effects of our modeling innovations on library matching performance and compare our models to prior machine-learning-based work on spectrum prediction., Competing Interests: The authors declare no competing financial interest.

Biological interpretation of genome-wide association study data frequently involves assessing whether SNPs linked to a biological process, for example, binding of a transcription factor, show unsigned enrichment for disease signal. However, signed annotations quantifying whether each SNP allele promotes or hinders the biological process can enable stronger statements about disease mechanism. We introduce a method, signed linkage disequilibrium profile regression, for detecting genome-wide directional effects of signed functional annotations on disease risk. We validate the method via simulations and application to molecular quantitative trait loci in blood, recovering known transcriptional regulators. We apply the method to expression quantitative trait loci in 48 Genotype-Tissue Expression tissues, identifying 651 transcription factor-tissue associations including 30 with robust evidence of tissue specificity. We apply the method to 46 diseases and complex traits (average n = 290 K), identifying 77 annotation-trait associations representing 12 independent transcription factor-trait associations, and characterize the underlying transcriptional programs using gene-set enrichment analyses. Our results implicate new causal disease genes and new disease mechanisms.

Background: Phylogenetic relationships among Eastern Hemisphere cypresses, Western Hemisphere cypresses, junipers, and their closest relatives are controversial, and generic delimitations have been in flux for the past decade. To address relationships and attempt to produce a more robust classification, we sequenced 11 new plastid genomes (plastomes) from the five variously described genera in this complex (Callitropsis, Cupressus, Hesperocyparis, Juniperus, and Xanthocyparis) and compared them with additional plastomes from diverse members of Cupressaceae., Results: Phylogenetic analysis of protein-coding genes recovered a topology in which Juniperus is sister to Cupressus, whereas a tree based on whole plastomes indicated that the Callitropsis-Hesperocyparis-Xanthocyparis (CaHX) clade is sister to Cupressus. A sliding window analysis of site-specific phylogenetic support identified a ~ 15 kb region, spanning the genes ycf1 and ycf2, which harbored an anomalous signal relative to the rest of the genome. After excluding these genes, trees based on the remainder of the genes and genome consistently recovered a topology grouping the CaHX clade and Cupressus with strong bootstrap support. In contrast, trees based on the ycf1 and ycf2 region strongly supported a sister relationship between Cupressus and Juniperus., Conclusions: These results demonstrate that standard phylogenomic analyses can result in strongly supported but conflicting trees. We suggest that the conflicting plastomic signals result from an ancient introgression event involving ycf1 and ycf2 that occurred in an ancestor of this species complex. The introgression event was facilitated by plastomic recombination in an ancestral heteroplasmic individual carrying distinct plastid haplotypes, offering further evidence that recombination occurs between plastomes. Finally, we provide strong support for previous proposals to recognize five genera in this species complex: Callitropsis, Cupressus, Hesperocyparis, Juniperus, and Xanthocyparis.

We report a method to convert discrete representations of molecules to and from a multidimensional continuous representation. This model allows us to generate new molecules for efficient exploration and optimization through open-ended spaces of chemical compounds. A deep neural network was trained on hundreds of thousands of existing chemical structures to construct three coupled functions: an encoder, a decoder, and a predictor. The encoder converts the discrete representation of a molecule into a real-valued continuous vector, and the decoder converts these continuous vectors back to discrete molecular representations. The predictor estimates chemical properties from the latent continuous vector representation of the molecule. Continuous representations of molecules allow us to automatically generate novel chemical structures by performing simple operations in the latent space, such as decoding random vectors, perturbing known chemical structures, or interpolating between molecules. Continuous representations also allow the use of powerful gradient-based optimization to efficiently guide the search for optimized functional compounds. We demonstrate our method in the domain of drug-like molecules and also in a set of molecules with fewer that nine heavy atoms., Competing Interests: The authors declare no competing financial interest.

The objective of this research was to evaluate effects of replacing sorghum × Sudangrass hay with ground juniper in gestating ewe supplements on pre- and postpartum growth performance, serum metabolites and hormonal concentrations, milk fatty acid composition, and progeny preweaning performance. In a completely randomized design, commercial Rambouillet ewes (age = 3 to 5 yr; initial BW = 65.2 ± 1.6 kg) on a base diet of long-stem sorghum × Sudangrass hay were assigned to 1 of 4 dietary supplements in which ground juniper replaced 0% (CNTL), 33% (18JUN), 66% (36JUN), or 100% (54JUN) of the ground sorghum × Sudangrass hay in a pelleted supplement with ground juniper from d 38 ± 4 of gestation to 2 d postpartum. Treatment DM diet intake overall (g/kg BW) in ewes receiving no juniper was similar ( ≥ 0.38) to that of those receiving increasing concentrations of juniper. Changes in ewe BW and BCS were similar ( ≥ 0.24) in ewes throughout gestation. All serum metabolites and hormones were within normal clinical ranges; however, serum IGF-1 decreased linearly ( = 0.003), alanine increased (linear; = 0.003), and serum Na decreased (linear; = 0.049) as the percentage of juniper increased in the diet. Ewe milk fatty acid composition was similar ( > 0.05) for the majority of fatty acids across treatment groups, with the exception of arachidonic acid (C20:4n6) being greater ( < 0.02) in 54JUN vs. CNTL ewe milk. Lamb birth weights were similar ( = 0.13), whereas lamb ADG tended to differ (quadratic; = 0.06) from d 0 to 14, with 18JUN being the least. At weaning, BW tended ( = 0.09) to linearly decrease in lambs born to ewes consuming greater concentrations of juniper but were not different ( = 0.26) between CNTL and 18JUN, 36JUN, and 54JUN. Results indicated that feeding increasing levels of ground juniper in supplements did not negatively alter ewe performance or serum metabolites and hormones measured pre- and postpartum. Lamb birth weight and preweaning performance appeared unaffected by maternal consumption of ground juniper containing supplements. Results also provide novel information regarding the effects of plant secondary compound consumption throughout pregnancy on ewe and progeny performance and health.

Iron deficiency anemia (IDA) is a nutritional disorder that impacts over one billion people worldwide; it may cause permanent cognitive impairment in children, fatigue in adults, and suboptimal outcomes in pregnancy. IDA can be diagnosed by detection of red blood cells (RBCs) that are characteristically small (microcytic) and deficient in hemoglobin (hypochromic), typically by examining the results of a complete blood count performed by a hematology analyzer. These instruments are expensive, not portable, and require trained personnel; they are, therefore, unavailable in many low-resource settings. This paper describes a low-cost and rapid method to diagnose IDA using aqueous multiphase systems (AMPS)-thermodynamically stable mixtures of biocompatible polymers and salt that spontaneously form discrete layers having sharp steps in density. AMPS are preloaded into a microhematocrit tube and used with a drop of blood from a fingerstick. After only two minutes in a low-cost centrifuge, the tests (n = 152) were read by eye with a sensitivity of 84% (72-93%) and a specificity of 78% (68-86%), corresponding to an area under the curve (AUC) of 0.89. The AMPS test outperforms diagnosis by hemoglobin alone (AUC = 0.73) and is comparable to methods used in clinics like reticulocyte hemoglobin concentration (AUC = 0.91). Standard machine learning tools were used to analyze images of the resulting tests captured by a standard desktop scanner to 1) slightly improve diagnosis of IDA-sensitivity of 90% (83-96%) and a specificity of 77% (64-87%), and 2) predict several important red blood cell parameters, such as mean corpuscular hemoglobin concentration. These results suggest that the use of AMPS combined with machine learning provides an approach to developing point-of-care hematology.

Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.

Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that 3D mouse pose dynamics are structured at the sub-second timescale. Computational modeling of these fast dynamics effectively describes mouse behavior as a series of reused and stereotyped modules with defined transition probabilities. We demonstrate this combined 3D imaging and machine learning method can be used to unmask potential strategies employed by the brain to adapt to the environment, to capture both predicted and previously hidden phenotypes caused by genetic or neural manipulations, and to systematically expose the global structure of behavior within an experiment. This work reveals that mouse body language is built from identifiable components and is organized in a predictable fashion; deciphering this language establishes an objective framework for characterizing the influence of environmental cues, genes and neural activity on behavior., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Palbociclib, an oral small-molecule inhibitor of cyclin-dependent kinases 4 and 6, was recently approved by the U.S. Food and Drug Administration in combination with letrozole for postmenopausal women with advanced hormone receptor-positive, her2-negative breast cancer. Patients with loss of CDKN2A (p16), an inherent negative regulator of cyclin-dependent kinases 4 and 6, were not separately studied because of the significant response of the patients selected based only on receptor status. Here, we report a patient with metastatic estrogen receptor- positive, her2-negative breast cancer with CDKN2A loss who experienced a clinical response to palbociclib.

Objective: To pilot and feasibility-test supervised final year undergraduate pharmacy student-led medication reviews for patients with diabetes to enable definitive trial design., Method: Third year pharmacy students were recruited from one UK School of Pharmacy and trained to review patient's medical records and provide face-to-face consultations under supervision while situated within the patient's medical practice. Patients with type 2 diabetes were recruited by postal invitation letter from their medical practice and randomised via automated system to intervention or usual care. Diabetes-related clinical data, quality of life, patient reported beliefs, adherence and satisfaction with medicines information were collected with validated tools at baseline and 6 months postintervention. The process for collecting resource utilisation data was tested. Stakeholder meetings were held before and after intervention to develop study design and learn from its implementation. Recruitment and attrition rates were determined plus the quality of the outcome data. Power calculations for a definitive trial were performed on the different outcome measures to identify the most appropriate primary outcome measure., Results: 792 patients were identified as eligible from five medical practices. 133 (16.8%) were recruited and randomised to control (n=66) or usual care (n=67). 32 students provided the complete intervention to 58 patients. Initial data analysis showed potential for impact in the right direction for some outcomes measured including glycated haemoglobin, quality of life and patient satisfaction with information about medicines. The intervention was found to be feasible and acceptable to patients. The pilot and feasibility study enabled the design of a future full randomised controlled trial., Conclusions: Student and patient recruitment are possible. The intervention was well received and demonstrated some potential benefits. While the intervention was relatively inexpensive and provided an experiential learning opportunity for pharmacy students, its cost-effectiveness remains to be determined., Trial Registration Number: ISRCTN26445805; Results., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Rising feed costs and recurring feed shortages necessitate the investigation into alternative and underutilized feed resources. Nutritional characteristics of species are either unknown or limited to leaves and ground material from small stems. Therefore, the objective was to quantify nutritional characteristics, 48-h true IVDMD (tIVDMD), microbial gas production, and secondary compound characteristics of entire woody plant material of 4 species-, , , and -at immature and mature stages of growth. Immature plants had greater CP concentrations and lower NDF concentrations ( < 0.001) than mature plants regardless of species. Mature plants also had greater ( < 0.001) concentrations of ADF compared with immature plants with the exception of . In general, immature , , and had greater ( < 0.02) tIVDMD and total 48-h and asymptotic gas production than mature plants. Immature and plants were more digested (tIVDMD; < 0.001) than immature and , but tIVDMD did not differ in mature plant material across species. Condensed tannins (CT) were greater ( < 0.001) in immature and than mature plants; differences in CT concentrations among immature species were also detected ( < 0.04). Volatile oil yields were similar across maturity and species with 1 exception: immature yielded more ( < 0.02) volatile oil than mature material. Volatile oil composition across species varied and contained a range of 65 to 70 terpene compounds. The dominant terpenes across species were generally greater ( < 0.05) in immature vs. mature plant material with the exception of . Labdane acids were negligible in , , and and greater in ( < 0.001). Ground material from mature juniper species, although inferior in nutritional quality compared with immature plants, is comparable to traditional low-quality roughage ingredients. Given that has been successfully fed in lamb feedlot diets, the similarities of , and suggest that all three species have potential to be effective roughage ingredients.

The chemical composition and radical-scavenging activity of wood samples from 10 main Spanish olive cultivars were studied. The wood samples were collected during the pruning works from trees growing under the same agronomical and environmental conditions. The 10 ethyl acetate extracts were submitted to HPLC-DAD/ESI-MS analysis to determine the phenolic constituents. Seventeen compounds were identified (10 secoiridoids, 3 lignans, 2 phenol alcohols, 1 iridoid, and 1 flavonoid) by comparison with authentic samples. Significant quantitative and qualitative differences were found among olive cultivars. The lignan (+)-1-hydroxypinoresinol 1-O-β-d-glucopyranoside was the major compound in all olive cultivars, except in cultivars 'Farga' and 'Picual'. The multivariate analysis of all data revealed three sets of cultivars with similar compositions. Cultivars 'Gordal sevillana' and 'Picual' had the most distinct chemical profiles. With regard to the radical-scavenging activity, cultivar 'Picual', with oleuropein as the major phenolic, showed the highest activity (91.4 versus 18.6-32.7%).

All Qinghai-Tibetan Plateau (QTP) endemic species are assumed to have originated recently, although very rare species most likely diverged early. These ancient species provide an excellent model to examine the origin and evolution of QTP endemic plants in response to the QTP uplifts and the climate changes that followed in this high altitude region. In this study, we examined these hypotheses by employing sequence variation from multiple nuclear and chloroplast DNA of 239 individuals of Juniperus microsperma and its five congeners. Both phylogenetic and population genetic analyses revealed that J. microsperma diverged from its sister clade comprising two species with long isolation around the Early Miocene, which corresponds to early QTP uplift. Demographic modeling and coalescent tests suggest that J. microsperma experienced an obvious bottleneck event during the Quaternary when the global climate greatly oscillated. The results presented here support the hypotheses that the QTP uplifts and Quaternary climate changes played important roles in shaping the evolutionary history of this rare juniper.

Cardiovascular variables such as heart rate (HR) and blood pressure (BP) are regulated by an underlying control system, and therefore, the time series of these vital signs exhibit rich dynamical patterns of interaction in response to external perturbations (e.g., drug administration), as well as pathological states (e.g., onset of sepsis and hypotension). A question of interest is whether "similar" dynamical patterns can be identified across a heterogeneous patient cohort, and be used for prognosis of patients' health and progress. In this paper, we used a switching vector autoregressive framework to systematically learn and identify a collection of vital sign time series dynamics, which are possibly recurrent within the same patient and may be shared across the entire cohort. We show that these dynamical behaviors can be used to characterize the physiological "state" of a patient. We validate our technique using simulated time series of the cardiovascular system, and human recordings of HR and BP time series from an orthostatic stress study with known postural states. Using the HR and BP dynamics of an intensive care unit (ICU) cohort of over 450 patients from the MIMIC II database, we demonstrate that the discovered cardiovascular dynamics are significantly associated with hospital mortality (dynamic modes 3 and 9, p=0.001, p=0.006 from logistic regression after adjusting for the APACHE scores). Combining the dynamics of BP time series and SAPS-I or APACHE-III provided a more accurate assessment of patient survival/mortality in the hospital than using SAPS-I and APACHE-III alone (p=0.005 and p=0.045). Our results suggest that the discovered dynamics of vital sign time series may contain additional prognostic value beyond that of the baseline acuity measures, and can potentially be used as an independent predictor of outcomes in the ICU.

Understanding the extent and distribution of genetic diversity is crucial for the conservation and management of endangered species. Cupressus chengiana, C. duclouxiana, C. gigantea, and C. funebris are four ecologically and economically important species in China. We investigated their genetic diversity, population structure, and extant effective population size (35 populations, 484 individuals) employing six pairs of nuclear microsatellite markers (selected from 53). Their genetic diversity is moderate among conifers, and genetic differentiation among populations is much lower in C. gigantea than in the other three species; the estimated effective population size was largest for C. chengiana, at 1.70, 2.91, and 3.91 times the estimates for C. duclouxiana, C. funebris, and C. gigantea, respectively. According to Bayesian clustering analysis, the most plausible population subdivision scheme within species is two groups in C. chengiana, three groups in C. duclouxiana, and a single group for both C. funebris and C. gigantea. We propose a conservation strategy for these cypress species.

Most land plant plastomes contain two copies of a large inverted repeat (IR) that promote high-frequency homologous recombination to generate isomeric genomic forms. Among conifer plastomes, this canonical IR is highly reduced in Pinaceae and completely lost from cupressophytes. However, both lineages have acquired short, novel IRs, some of which also exhibit recombinational activity to generate genomic structural diversity. This diversity has been shown to exist between, and occasionally within, cupressophyte species, but it is not known whether multiple genomic forms coexist within individual plants. To examine the recombinational potential of the novel cupressophyte IRs within individuals and between species, we sequenced the plastomes of four closely related species of Juniperus. The four plastomes have identical gene content and genome organization except for a large 36 kb inversion between approximately 250 bp IR containing trnQ-UUG. Southern blotting showed that different isomeric versions of the plastome predominate among individual junipers, whereas polymerase chain reaction and high-throughput read-pair mapping revealed the substoichiometric presence of the alternative isomeric form within each individual plant. Furthermore, our comparative genomic studies demonstrate that the predominant and substoichiometric arrangements of this IR have changed several times in other cupressophytes as well. These results provide compelling evidence for substoichiometric shifting of plastomic forms during cupressophyte evolution and suggest that substoichiometric shifting activity in plastid genomes may be adaptive.

Effects of using ground redberry juniper and dried distillers grains with solubles (DDGS) in Rambouillet lamb (n = 45) feedlot diets on growth, blood serum, fecal, and wool characteristics were evaluated. In a randomized design study with 2 feeding periods (Period 1 = 64% concentrate diet, 35 d; Period 2 = 85% concentrate diet, 56 d), lambs were individually fed 5 isonitrogenous diets: a control diet (CNTL) that contained oat hay but not DDGS or juniper or DDGS-based diets in which 0 (0JUN), 33 (33JUN), 66 (66JUN), or 100% (100JUN) of the oat hay was replaced by juniper. During Period 1, lambs fed CNTL had greater (P < 0.05) DMI and ADG and tended to have greater (P < 0.10) G:F than lambs fed 0JUN or lambs fed DDGS-based diets. Lamb DMI, ADG, and G:F quadratically increased (P < 0.008) as juniper increased in the DDGS-based diets. During Period 2, lambs fed CNTL had greater (P < 0.05) DMI than lambs fed 0JUN or lambs fed DDGS-based diets, but ADG was similar (P > 0.41). Compared to 0JUN, lambs fed CNTL had similar (P = 0.12) G:F and tended to have less G:F (P = 0.07) than lambs fed DDGS-based diets. Among lambs fed DDGS-based diets, DMI was similar (P > 0.19), ADG increased linearly (P = 0.03), and G:F tended to decrease quadratically (P = 0.06) as juniper increased in the diet. Serum IGF-1, serum urea N (SUN), and fecal N were greater (P < 0.05) and serum Ca and P and fecal P were similar (P > 0.13) for lambs fed CNTL vs. lambs fed DDGS-based diets (CNTL). Within lambs fed DDGS-based diets, SUN increased quadratically (P = 0.01) and fecal N increased linearly (P = 0.004), which can partially be attributed to increased dietary urea and condensed tannin intake. Most wool characteristics were not affected, but wool growth per kilogram of BW decreased quadratically (P = 0.04) as percentage of juniper increased in the DDGS-based diets. When evaluating the entire 91-d feeding trial, results indicated that replacing all of the ground oat hay with ground juniper leaves and stems in lamb growing and finishing diets is not detrimental to animal performance and that DDGS-based diets can reduce total feedlot costs, as compared to sorghum grain and cottonseed meal-based diets. However, compared to using juniper or oat hay as the sole roughage source, using both during the growing period (Period 1) enhanced growth performance and further reduced total feedlot costs.

Biophysical characteristics of cells are attractive as potential diagnostic markers for cancer. Transformation of cell state or phenotype and the accompanying epigenetic, nuclear, and cytoplasmic modifications lead to measureable changes in cellular architecture. We recently introduced a technique called deformability cytometry (DC) that enables rapid mechanophenotyping of single cells in suspension at rates of 1000 cells/s-a throughput that is comparable to traditional flow cytometry. We applied this technique to diagnose malignant pleural effusions, in which disseminated tumor cells can be difficult to accurately identify by traditional cytology. An algorithmic diagnostic scoring system was developed on the basis of quantitative features of two-dimensional distributions of single-cell mechanophenotypes from 119 samples. The DC scoring system classified 63% of the samples into two high-confidence regimes with 100% positive predictive value or 100% negative predictive value, and achieved an area under the curve of 0.86. This performance is suitable for a prescreening role to focus cytopathologist analysis time on a smaller fraction of difficult samples. Diagnosis of samples that present a challenge to cytology was also improved. Samples labeled as "atypical cells," which require additional time and follow-up, were classified in high-confidence regimes in 8 of 15 cases. Further, 10 of 17 cytology-negative samples corresponding to patients with concurrent cancer were correctly classified as malignant or negative, in agreement with 6-month outcomes. This study lays the groundwork for broader validation of label-free quantitative biophysical markers for clinical diagnoses of cancer and inflammation, which could help to reduce laboratory workload and improve clinical decision-making.

Physiologic systems generate complex dynamics in their output signals that reflect the changing state of the underlying control systems. In this work, we used a switching vector autoregressive (switching VAR) framework to systematically learn and identify a collection of vital sign dynamics, which can possibly be recurrent within the same patient and shared across the entire cohort. We show that these dynamical behaviors can be used to characterize and elucidate the progression of patients' states of health over time. Using the mean arterial blood pressure time series of 337 ICU patients during the first 24 hours of their ICU stays, we demonstrated that the learned dynamics from as early as the first 8 hours of patients' ICU stays can achieve similar hospital mortality prediction performance as the well-known SAPS-I acuity scores, suggesting that the discovered latent dynamics structure may yield more timely insights into the progression of a patient's state of health than the traditional snapshot-based acuity scores.

Model identification for physiological systems is complicated by changes between operating regimes and measurement artifacts. We present a solution to these problems by assuming that a cohort of physiological time series is generated by switching among a finite collection of physiologically-constrained dynamical models and artifactual segments. We model the resulting time series using the switching linear dynamical systems (SLDS) framework, and present a novel learning algorithm for the class of SLDS, with the objective of identifying time series dynamics that are predictive of physiological regimes or outcomes of interest. We present exploratory results based on a simulation study and a physiological classification example of decoding postural changes from heart rate and blood pressure. We demonstrate a significant improvement in classification over methods based on feature learning via expectation maximization. The proposed learning algorithm is general, and can be extended to other applications involving state-space formulations.

Modern clinical databases include time series of vital signs, which are often recorded continuously during a hospital stay. Over several days, these recordings may yield many thousands of samples. In this work, we explore the feasibility of characterizing the "state of health" of a patient using the physiological dynamics inferred from these time series. The ultimate objective is to assist clinicians in allocating resources to high-risk patients. We hypothesize that "similar" patients exhibit similar dynamics and the properties and duration of these states are indicative of health and disease. We use Bayesian nonparametric machine learning methods to discover shared dynamics in patients' blood pressure (BP) time series. Each such "dynamic" captures a distinct pattern of evolution of BP and is possibly recurrent within the same time series and shared across multiple patients. Next, we examine the utility of this low-dimensional representation of BP time series for predicting mortality in patients. Our results are based on an intensive care unit (ICU) cohort of 480 patients (with 16% mortality) and indicate that the dynamics of time series of vital signs can be an independent useful predictor of outcome in ICU.

Cardiovascular variables such as heart rate (HR) and blood pressure (BP) are robustly regulated by an underlying control system. Time series of HR and BP exhibit distinct dynamical patterns of interaction in response to perturbations (e.g., drugs or exercise) as well as in pathological states (e.g., excessive sympathetic activation). A question of interest is whether "similar" dynamical patterns can be identified across a heterogeneous patient cohort. In this work, we present a technique based on switching linear dynamical systems for identification of shared dynamical patterns in the time series of HR and BP recorded from a patient cohort. The technique uses a mixture of linear dynamical systems, the components of which are shared across all patients, to capture both nonlinear dynamics and non-Gaussian perturbations. We present exploratory results based on a simulation study of the cardiovascular system, and real recordings from 10 healthy subjects undergoing a tilt-table test. These results demonstrate the ability of the proposed technique to identify similar dynamical patterns present across multiple time series.

• A central aim of biogeography is to understand when and how modern patterns of species diversity and distribution developed. Many plant groups have disjunct distributions within the Northern Hemisphere, but among these very few have been studied that prefer warm semi-arid habitats. • Here we examine the biogeography and diversification history of Juniperus, which occurs in semi-arid habitats through much of the Northern Hemisphere. A phylogeny was generated based on > 10,000 bp of cpDNA for 51 Juniperus species plus many outgroups. Phylogenies based on fewer species were also constructed based on nuclear internal transcribed spacer (nrITS) and combined nrITS/cpDNA data sets to check for congruence. Divergence time-scales and ancestral distributions were further inferred. • Both long dispersal and migration across land bridges probably contributed to the modern range of Juniperus, while long-term climatic changes and the uplift of the Qinghai-Tibetan plateau probably drove its diversification. Diversification apparently slowed down during climate-stable period of the Oligocene, and then speeded up from the Miocene onwards. • Juniperus probably originated in Eurasia, and was a part of the south Eurasian Tethyan vegetation of the Eocene to Oligocene. It reached America once at this time, once in the Miocene and once more recently.

Background: Advanced topical hemostatic agents are increasingly utilized to control traumatic hemorrhage. We sought to determine the efficacy of three chitosan based hemostatic agents in a lethal groin injury model when applied by combat medic first responders., Methods: After creation of a standardized femoral artery injury in a goat model, medics attempted hemorrhage control with standard gauze dressing followed by randomization to one of three hemostatic agents in this two tiered study. In the first tier, medics were randomized to either a chitosan based one-sided wafer (OS) or a dual-sided, flexible, roll (DS). In the second tier, medics were randomized to the flexible DS dressing or a chitosan powder (CP). Efficacy of gauze, each chitosan agent, proper application, and participant surveys were obtained and included for analysis using univariate techniques., Results: From January 2007 to June 2007, 55 (45%) DS, 36 (29%) OS, and 32 (26%) CP agents were used to treat 123 actively bleeding arterial injuries in 62 animals. Standard gauze failed to stop hemorrhage in 122 (99%) groins. Although all three chitosan agents were marginally effective at 2 min, the recommended time for application, hemostasis improved after 4 min. The DS dressing was the most effective, controlling hemorrhage 76% at 4 min. Of the failures, 3 (23%) DS and 9 (53%) OS were due to improper application. End-user survey results demonstrated that medics preferred the DS dressing 77% and 60% over the OS and CP, respectively., Conclusions: Chitosan based bandages are significantly more effective at hemorrhage control compared to standard gauze field dressings. The dual-sided chitosan dressing demonstrated better hemorrhage control than the one-sided dressing and the chitosan powder, and was less likely to fail despite application errors.

This study is a quantitative examination of primate feeding selectivity in relation to secondary chemistry within a single plant species, Hymenaea courbaril. It provides the first evidence that sesquiterpenes may act as feeding deterrents in mantled howler monkeys. A free-ranging group of mantled howler monkeys at the study site of Sector Santa Rosa, Area de Conservacion Guanacaste, Costa Rica were observed for the 2-month period of H. courbaril leaf flush in 1999. Tree characteristic data and leaf specimens were collected from 22 focal trees. Gas chromatography and mass spectrometry were used to estimate relative percentages of sesquiterpenes in leaf specimens. The monkeys fed only on the youngest leaves and only from particular trees. Whereas leaf stage selectivity was likely governed by tannin content and structural carbohydrates in younger and older leaf stages, respectively, differential tree use may be related to variability in sesquiterpene content. There is evidence that alpha-copaene may have played a role in interindividual tree use, and that cyperene may also be implicated. However, there is no reported evidence of antiherbivore activity for cyperene.

cDNA cloning of a monoterpene synthase from Perilla frutescens whose steam-distilled oil contains 92.9% perillaketone, was performed by the PCR method using primers designed based on limonene synthase. The full-length nucleotide sequence of this cDNA consisted of 1978 bp including a 1827-bp translational region encoding a deduced protein of 608 amino acids, which was similar to that of limonene synthase from P. frutescens (85% identity). Functional expression of this clone in Escherichia coli yielded an active monoterpene synthase enzyme, which converted geranyl diphosphate into 53.8% myrcene, 20.9% sabinene, 19.8% linalool and 5.5% limonene. As for the extraction of reaction products, we performed SPME (solid phase micro extraction) as well as conventional solvent extraction, and compared these two extraction methods.

A new species of conifer was recently discovered in northern Vietnam. In a preliminary phylogenetic analysis of morphological data a possible sister species, Chamaecyparis nootkatensis (D. Don) Spach, was identified; however, because of the presumed phylogenetic remoteness of these two species to the remainder of the Cupressaceae, a new genus-Xanthocyparis-was described to accommodate both species. Here an analysis of ITS (nrDNA), matK, and rbcL sequence data in combination with 58 informative morphological characters was aimed at testing the monophyly of the remainder of Chamaecyparis and evaluating the placement and monophyly of Xanthocyparis. Chamaecyparis, minus C. nootkatensis, was resolved as a monophyletic group, remote from Cupressus and Xanthocyparis. Cupressus, Juniperus, and Xanthocyparis formed a very highly supported monophyletic group. However, Cupressus was not monophyletic. Instead the Old World species sampled were resolved sister to a clade containing a monophyletic Juniperus, a monophyletic Xanthocyparis, and a clade of New World Cupressus species. If both species of Xanthocyparis are to be treated as members of the same genus, then due to the principal of priority they will have to be recognized in the genus Callitropsis. Research is continuing to resolve the status of New World and Old World Cupressus.

A hydrocarbon that is widespread in Juniperus foliage was isolated from Juniperus erectopatens (Cheng and L. K. Fu) R. P. Adams and identified as (E,E,E)-1,7-dimethylcyclodeca-1,4,7-triene (pregeijerene B). Geometry of the disubstituted double bond was determined by IR and NMR spectroscopy, while that of the trisubstituted double bonds was proven by comparison of the products of selective hydrogenation of the title compound and of pregeijerene. Common biosynthesis of pregeijerene B and a germacrane sesquiterpenoid, 8alpha-acetoxyhedycaryol, is inferred from their co-occurrence in foliage of 24 Juniperus species.

Variations in the composition of the leaf essential oils and DNA fingerprints (RAPDs) of Juniperus excelsa, J. polycarpos, J. seravschanica, and J. turcomanica were examined. Juniperus procera was also included in the analyses to aid in determining the specific status of J. polycarpos. Based on these analyses, J. polycarpos is recognized as a distinct species from J. excelsa. The common, multi-seeded juniper of central Asia is J. polycarpos. Juniperus seravschanica and J. turcomanica are treated as part of the J. polycarpos complex but are not recognized as formal taxonomic groups at this time. The Balochistan, Pakistan juniper, usually called J. excelsa var. polycarpos or J. macropoda should be referred to as J. polycarpos in the future.

The volatile leaf essential compositions of all 17 serrate leaf margin species of Juniperus (sect. Sabina) of the western hemisphere are reported and compared: J. angosturana, J. ashei, J. californica, J. coahuilensis, J. comitana, J. deppeana, J. durangensis, J. flaccida, J. gamboana, J. jaliscana, J. monosperma, J. monticola, J. osteosperma, J. occidentalis, J. pinchotii, J. saltillensis, and J. standleyi. A number of previously unidentified compounds of the leaf essential oils have now been identified. In addition, DNA data (RAPDs) of all these species were analyzed. Both the leaf essential oils and DNA show these species to be quite distinct with few apparent subgroups, such that the species groupings were not strong in either data set. These data support the hypothesis that this group of junipers originated in Mexico as part of the Madro-Tertiary flora by rapid radiation into new arid land habitats, leaving few extant intermediate taxa.

The composition of the leaf essential oils of all the species of Juniperus in sect. Juniperus (=sect. Oxycedrus) are reported and compared (J. brevifolia, J. cedrus, J. communis, J. c. var. saxatilis, J. c. var. oblonga, J. formosana, J. oxycedrus, J. o. subsp. badia, J. o. subsp. macrocarpa, J. o. subsp. transtagana, J. rigida, J. r. subsp. conferta, J. sibirica, J. taxifolia and J. t. var. lutchuensis). In addition, DNA fingerprinting by RAPDs was utilized. Based on these data, several taxa remained at the same taxonomic level: J. brevifolia, J. cedrus, J. communis, J. c. var. saxatilis, J. formosana, J. oxycedrus, J. rigida, J. r. var. conferta, and J. taxifolia. However, several taxa exhibited considerable differentiation that warranted their recognition at the specific level: J. oblonga M.-Bieb. (=J. communis var. oblonga), J. badia H. Gay (=J. oxycedrus subsp. badia), J. macrocarpa Sibth. and Sm. (=J. oxycedrus subsp. macrocarpa), J. navicularis Gand. (=J. oxycedrus subsp. transtagana), J. sibirica Brugsd. (=J. communis var. saxatilis in part), and J. lutchuensis Koidz. (= J. taxifolia var. lutchuensis).

The compositions of the leaf essential oils of all the one seed/cone species of Juniperus (sect. Sabina) of the eastern hemisphere are reported and compared (J. convallium, J. convallium var. microsperma, J. indica, J. komarovii, J. pingii, J. pingii var. carinata, J. prezewalskii, J. pseudosabina, J. recurva, J. recurva var. coxii, J. saltuaria, J. squamata, J. squamata var. morrisonicola, J. tibetica, J. wallachiana). In addition, DNA fingerprinting by RAPDs was utilized. The combined terpenoid and DNA data supported the continued recognition of the aforementioned taxa as distinct species except for four varieties which were recognized at the specific level: Juniperus carinata (Y.K. Yu & L.K. Fu) R.P. Adams, stat. nov. (Syn.: J. pingii var. carinata); J. coxii A.B. Jacks. (Syn.: J. recurva var. coxii); Juniperus microsperma (Cheng & L.K. Fu) R.P. Adams, stat. nov. (Syn.: J. convallium var. microsperma); J. morrisonicola Hayata (Syn.: J. squamata var. morrisonicola).

Study Objective: To evaluate the importance of regression to the mean in the assessment of asymptomatic hypertension in the emergency department., Methods: This was an historical cohort study of patients in the adult ED of a large urban teaching hospital. THe main outcome was changed in diastolic blood pressure (DBP). Subjects were 195 consecutive hypertensive patients with two sets of vital signs. Patients with specified acute conditions potentially associated with abnormal blood pressure were excluded, as were patients given vasoactive medications., Results: A statistical formula was used to predict the average blood pressure for hypertensive patients, using the observed mean and standard deviation of an all-patient sample. Given a threshold of 90 mm Hg, the expected mean DBP for hypertensive patients was 102.7 mm Hg, compared with an observed value of 104.5 mm Hg. Given an observed correlation coefficient of .73 between first and second measurements, a formula for regression to the mean predicted a spontaneous blood pressure decline of 7.2 mn Hg. A mean decline if 11.6 mm Hg was observed. The decline of 4.4 mm Hg more than expected among asymptomatic hypertensives was similar to the spontaneous decline of 3.7 mm Hg observed in the all-patient sample., Conclusion: Patients who present with asymptomatic hypertension in the ED on average experience a spontaneous decline in blood pressure after they arrive. Most of this effect can be explained by regression to the mean. A small amount of this drop may represent attenuation of an initial alerting reaction.

Three plant species, spinach, juniper and broccoli, were stored in different alcohol solutions, and the DNAs were examined to determine changes in the quality and quantity of DNA over time. The smallest changes in the genomic DNA were found in the samples stored in the lower mol wt alcohols (100% methanol and 100% and 95% ethanol) and when proteinase (Pronase E) was used in the extraction procedure. After 11 months of storage in ethanol, excellent yields of high mol wt DNA were obtained, but only when the procedure utilized Pronase E. The use of proteinase was found to be essential to obtain DNA from preserved specimens of spinach and broccoli. This appears to explain the previous reports of failures to obtain DNA from alcohol-preserved specimens. Vacuum infiltration of ethanol resulted in better DNA preservation than passive infiltration of ethanol.