LUX-ZEPLIN (LZ) Technical Design Report

In this Technical Design Report (TDR) we describe the LZ detector to be built at the Sanford Underground Research Facility (SURF). The LZ dark matter experiment is designed to achieve sensitivity to a WIMP-nucleon spin-independent cross section of three times ten to the negative forty-eighth square centimeters

Machine Learning Approach for Prescriptive Plant Breeding

We explored the capability of fusing high dimensional phenotypic trait (phenomic) data with a machine learning (ML) approach to provide plant breeders the tools to do both in-season seed yield (SY) prediction and prescriptive cultivar development for targeted agro-management practices (e.g., row spacing and seeding density). We phenotyped 32 SoyNAM parent genotypes in two independent studies each with contrasting agro-management treatments (two row spacing, three seeding densities). Phenotypic trait data (canopy temperature, chlorophyll content, hyperspectral reflectance, leaf area index, and light interception) were generated using an array of sensors at three growth stages during the growing season and seed yield (SY) determined by machine harvest. Random forest (RF) was used to train models for SY prediction using phenotypic traits (predictor variables) to identify the optimal temporal combination of variables to maximize accuracy and resource allocation. RF models were trained using data from both experiments and individually for each agro-management treatment. We report the most important traits agnostic of agro-management practices. Several predictor variables showed conditional importance dependent on the agro-management system. We assembled predictive models to enable in-season SY prediction, enabling the development of a framework to integrate phenomics information with powerful ML for prediction enabled prescriptive plant breeding

The Interaction Between Pubertal Timing and Peer Popularity for Boys and Girls: An Integration of Biological and Interpersonal Perspectives on Adolescent Depression

The transition to adolescence marks a time of sharply increased vulnerability to the development of depression, particularly among girls. Past research has examined isolated risk factors from individual theoretical models (e.g., biological, interpersonal, and cognitive) of depression, but few have examined integrative models. This study investigated the conjoint effects of early pubertal timing and popularity in the longitudinal prediction of depressive symptoms. A total of 319 girls and 294 boys (ages 11–14) provided information on their pubertal status, depressive symptoms, and the social status (i.e., popularity) of their peers. Adolescents completed a second measure of depressive symptoms 11 months after the initial time point. Findings supported an integrated biological-interpersonal model in explaining the development of depressive symptoms during adolescence. Early pubertal development was associated with increase in depressive symptoms only when accompanied by low levels of popularity. High levels of popularity buffered the association between early pubertal development and later depressive symptoms. Unexpectedly, these results were significant both for girls and boys. Results are discussed in terms of dynamic systems theories

Relevance of laboratory testing for the diagnosis of primary immunodeficiencies: a review of case-based examples of selected immunodeficiencies

The field of primary immunodeficiencies (PIDs) is one of several in the area of clinical immunology that has not been static, but rather has shown exponential growth due to enhanced physician, scientist and patient education and awareness, leading to identification of new diseases, new molecular diagnoses of existing clinical phenotypes, broadening of the spectrum of clinical and phenotypic presentations associated with a single or related gene defects, increased bioinformatics resources, and utilization of advanced diagnostic technology and methodology for disease diagnosis and management resulting in improved outcomes and survival. There are currently over 200 PIDs with at least 170 associated genetic defects identified, with several of these being reported in recent years. The enormous clinical and immunological heterogeneity in the PIDs makes diagnosis challenging, but there is no doubt that early and accurate diagnosis facilitates prompt intervention leading to decreased morbidity and mortality. Diagnosis of PIDs often requires correlation of data obtained from clinical and radiological findings with laboratory immunological analyses and genetic testing. The field of laboratory diagnostic immunology is also rapidly burgeoning, both in terms of novel technologies and applications, and knowledge of human immunology. Over the years, the classification of PIDs has been primarily based on the immunological defect(s) ("immunophenotype") with the relatively recent addition of genotype, though there are clinical classifications as well. There can be substantial overlap in terms of the broad immunophenotype and clinical features between PIDs, and therefore, it is relevant to refine, at a cellular and molecular level, unique immunological defects that allow for a specific and accurate diagnosis. The diagnostic testing armamentarium for PID includes flow cytometry - phenotyping and functional, cellular and molecular assays, protein analysis, and mutation identification by gene sequencing. The complexity and diversity of the laboratory diagnosis of PIDs necessitates many of the above-mentioned tests being performed in highly specialized reference laboratories. Despite these restrictions, there remains an urgent need for improved standardization and optimization of phenotypic and functional flow cytometry and protein-specific assays. A key component in the interpretation of immunological assays is the comparison of patient data to that obtained in a statistically-robust manner from age and gender-matched healthy donors. This review highlights a few of the laboratory assays available for the diagnostic work-up of broad categories of PIDs, based on immunophenotyping, followed by examples of disease-specific testing

The LUX-ZEPLIN (LZ) Experiment

We describe the design and assembly of the LUX-ZEPLIN experiment, a direct detection search for cosmic WIMP dark matter particles. The centerpiece of the experiment is a large liquid xenon time projection chamber sensitive to low energy nuclear recoils. Rejection of backgrounds is enhanced by a Xe skin veto detector and by a liquid scintillator Outer Detector loaded with gadolinium for efficient neutron capture and tagging. LZ is located in the Davis Cavern at the 4850' level of the Sanford Underground Research Facility in Lead, South Dakota, USA. We describe the major subsystems of the experiment and its key design features and requirements

Going Through the Rites of Passage: Timing and Transition of Menarche, Childhood Sexual Abuse, and Anxiety Symptoms in Girls

Menarche is a discrete, transitional event that holds considerable personal, social, biological, and developmental significance. The present longitudinal study examined both the transition and timing of menarche on the trajectory of anxiety in girls with histories of childhood maltreatment (N = 93; 63% European American, 14% multiracial, 10% Latino, 9% African American, and 4% Native American). We hypothesized that because menarche is a novel, unfamiliar experience, girls would show greater anxiety around the time of menarche. The anxiety-provoking nature of menarche may be accentuated among earlier-maturing girls and girls with histories of childhood sexual abuse. Results indicated that earlier-maturing girls were more anxious in the pre- and peri-menarche periods than their later-maturing peers; however, their anxiety declined after menarche. Childhood sexual abuse was associated with heightened anxiety throughout this transition. The developmental significance of the timing and transition of menarche in relation to childhood sexual abuse and anxiety is discussed

Cancer stem cell metabolism

Cancer is now viewed as a stem cell disease. There is still no consensus on the metabolic characteristics of cancer stem cells, with several studies indicating that they are mainly glycolytic and others pointing instead to mitochondrial metabolism as their principal source of energy. Cancer stem cells also seem to adapt their metabolism to microenvironmental changes by conveniently shifting energy production from one pathway to another, or by acquiring intermediate metabolic phenotypes. Determining the role of cancer stem cell metabolism in carcinogenesis has become a major focus in cancer research, and substantial efforts are conducted towards discovering clinical targets