Concentration of anti-Müllerian hormone in dairy heifers is positively associated with productive herd life

Reliable biomarkers predictive of productive herd life (time in herd after birth of first calf) have heretofore not been discovered in dairy cattle. However, circulating concentrations of anti-Müllerian hormone (AMH) are positively associated with number of follicles or antral follicle count (AFC), ovarian function, and fertility, and approximately 25% of cows have a relatively low AFC and low AMH concentrations. The present study tested the hypothesis that heifers with the lowest AMH concentrations have suboptimal fertility and are removed from a herd for poor reproductive performance at a greater rate, and therefore have a shorter productive herd life compared with age-matched herdmates with higher AMH. To test this hypothesis, 11- to 15-mo-old Holstein heifers (n=281) were subjected to a single measurement of AMH. All heifers not removed from the herd had the opportunity to complete 2 lactations and start their third lactation after calving. During this time, performance and health parameters for each individual were recorded daily by herd managers. Results showed that the quartile of heifers with the lowest AMH concentration also had, on average, a shorter productive herd life (by 196 d), a reduced survival rate after birth of the first calf, the lowest level of milk production (first lactation), the lowest total percentage of cows pregnant (across all lactations), the highest culling rates (first and second lactations and overall), and the highest culling rate for poor reproduction (first lactation) compared with age-matched herdmates with higher AMH. We concluded that a single determination of AMH concentration in young adult dairy heifers may be a simple diagnostic method to predict herd longevity, and AMH may be a useful phenotypic marker to improve longevity of dairy cows

Whole genome sequencing and progress toward full inbreeding of the mouse collaborative cross population

Two key features of recombinant inbred panels are well-characterized genomes and reproducibility. Here we report on the sequenced genomes of six additional Collaborative Cross (CC) strains and on inbreeding progress of 72 CC strains. We have previously reported on the sequences of 69 CC strains that were publicly available, bringing the total of CC strains with whole genome sequence up to 75. The sequencing of these six CC strains updates the efforts toward inbreeding undertaken by the UNC Systems Genetics Core. The timing reflects our competing mandates to release to the public as many CC strains as possible while achieving an acceptable level of inbreeding. The new six strains have a higher than average founder contribution from non-domesticus strains than the previously released CC strains. Five of the six strains also have high residual heterozygosity (.14%), which may be related to non-domesticus founder contributions. Finally, we report on updated estimates on residual heterozygosity across the entire CC population using a novel, simple and cost effective genotyping platform on three mice from each strain. We observe a reduction in residual heterozygosity across all previously released CC strains. We discuss the optimal use of different genetic resources available for the CC population

Processing GOTO data with the Rubin Observatory LSST Science Pipelines I: Production of coadded frames

The past few decades have seen the burgeoning of wide field, high cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory. So new is the field of systematic time-domain survey astronomy, however, that major scientific insights will continue to be obtained using smaller, more flexible systems than the LSST. One such example is the Gravitational-wave Optical Transient Observer (GOTO), whose primary science objective is the optical follow-up of Gravitational Wave events. The amount and rate of data production by GOTO and other wide-area, high-cadence surveys presents a significant challenge to data processing pipelines which need to operate in near real-time to fully exploit the time-domain. In this study, we adapt the Rubin Observatory LSST Science Pipelines to process GOTO data, thereby exploring the feasibility of using this "off-the-shelf" pipeline to process data from other wide-area, high-cadence surveys. In this paper, we describe how we use the LSST Science Pipelines to process raw GOTO frames to ultimately produce calibrated coadded images and photometric source catalogues. After comparing the measured astrometry and photometry to those of matched sources from PanSTARRS DR1, we find that measured source positions are typically accurate to sub-pixel levels, and that measured L-band photometries are accurate to ∼50 mmag at mL∼16 and ∼200 mmag at mL∼18. These values compare favourably to those obtained using GOTO's primary, in-house pipeline, GOTOPHOTO, in spite of both pipelines having undergone further development and improvement beyond the implementations used in this study. Finally, we release a generic "obs package" that others can build-upon should they wish to use the LSST Science Pipelines to process data from other facilities

Forest Biodiversity Assessment in Peruvian Andean Montane Cloud Forest

Cloud forests are unusual and fragile habitats, being one of the least studied and least understood ecosystems. The tropical Andean dominion is considered one of the most significant places in the world as rega rds biological diversity, with a very high level of endemism. The biodiversity was analysed in an isolated remnant area of a tropical montane cloud forest known as the ?Bosque de Neblina de Cuyas?, in the North of the Peruvian Andean range. Composition, structure and dead wood were measured or estimated. The values obtained were compared with other cloud forests. The study revealed a high level of forest biodiversity, although the level of biodiversity differs from one area to another: in the inner areas, where human pressure is almost inexistent, the biodiversity values increase. The high species richness and the low dominance among species bear testimony to this montane cloud forest as a real enclave of biodiversity

The evolution of language: a comparative review

For many years the evolution of language has been seen as a disreputable topic, mired in fanciful "just so stories" about language origins. However, in the last decade a new synthesis of modern linguistics, cognitive neuroscience and neo-Darwinian evolutionary theory has begun to make important contributions to our understanding of the biology and evolution of language. I review some of this recent progress, focusing on the value of the comparative method, which uses data from animal species to draw inferences about language evolution. Discussing speech first, I show how data concerning a wide variety of species, from monkeys to birds, can increase our understanding of the anatomical and neural mechanisms underlying human spoken language, and how bird and whale song provide insights into the ultimate evolutionary function of language. I discuss the ‘‘descended larynx’ ’ of humans, a peculiar adaptation for speech that has received much attention in the past, which despite earlier claims is not uniquely human. Then I will turn to the neural mechanisms underlying spoken language, pointing out the difficulties animals apparently experience in perceiving hierarchical structure in sounds, and stressing the importance of vocal imitation in the evolution of a spoken language. Turning to ultimate function, I suggest that communication among kin (especially between parents and offspring) played a crucial but neglected role in driving language evolution. Finally, I briefly discuss phylogeny, discussing hypotheses that offer plausible routes to human language from a non-linguistic chimp-like ancestor. I conclude that comparative data from living animals will be key to developing a richer, more interdisciplinary understanding of our most distinctively human trait: language

Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data

The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the vast incoming data stream. A problem that arises in real-world applications of learning algorithms for classification is imbalanced data, where a class of objects within the data is underrepresented, leading to a bias for over-represented classes in the ML and DL classifiers. We present a recurrent neural network (RNN) classifier that takes in photometric time-series data and additional contextual information (such as distance to nearby galaxies and on-sky position) to produce real-time classification of objects observed by the Gravitational-wave Optical Transient Observer (GOTO), and use an algorithm-level approach for handling imbalance with a focal loss function. The classifier is able to achieve an Area Under the Curve (AUC) score of 0.972 when using all available photometric observations to classify variable stars, supernovae, and active galactic nuclei. The RNN architecture allows us to classify incomplete light curves, and measure how performance improves as more observations are included. We also investigate the role that contextual information plays in producing reliable object classification

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele