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Anthropometric prevalence indicators such as stunting, wasting, and underweight are widely-used population-level tools used to track trends in childhood nutrition. Threats to the validity of these data can lead to erroneous decision making and improper allocation of finite resources intended to support some of the world’s most vulnerable populations. It has been demonstrated previously that aggregated prevalence rates for these indicators can be highly sensitive to biases in the presence of non-directional measurement errors, but the quantitative relationship between the contributing factors and the scale of this bias has not been fully described. In this work, a Monte Carlo simulation exercise was performed to generate high-statistics z-score distributions with a wide range of mean and standard deviation parameters relevant to the populations in low- and middle-income countries (LMIC). With the important assumption that the distribution’s standard deviation should be close to 1.0 in the absence of non-directional measurement errors, the shift in prevalence rate due to this common challenge is calculated and explored. Assuming access to a given z-score distribution’s mean and standard deviation values, this relationship can be used to evaluate the potential scale of prevalence bias for both historical and modern anthropometric indicator results. As a demonstration of the efficacy of this exercise, the bias scale for a set of 21 child anthropometry datasets collected in LMIC contexts is presented.

This dissertation presents the first measurement of the muon antineutrino charged current quasi-elastic double-differential cross section. These data significantly extend the knowledge of neutrino and antineutrino interactions in the GeV range, a region that has recently come under scrutiny due to a number of conflicting experimental results. To maximize the precision of this measurement, three novel techniques were employed to measure the neutrino background component of the data set. Representing the first measurements of the neutrino contribution to an accelerator-based antineutrino beam in the absence of a magnetic field, the successful execution of these techniques carry implications for current and future neutrino experiments. Finally, combined measurements of these antineutrino and the previously-published neutrino cross section data using the same apparatus maximize the extracted information from these results by exploiting correlated systematic uncertainties. The results of this analysis will help to understand signal and background processes in present and future long-baseline neutrino experiments, the principle goal of which is to measure the ordering of the neutrino masses and a process that may ultimately explain the origin of our matter-dominated universe.

SLITRK2 is a single-pass transmembrane protein expressed at postsynaptic neurons that regulates neurite outgrowth and excitatory synapse maintenance. In the present study, we report on rare variants (one nonsense and six missense variants) in SLITRK2 on the X chromosome identified by exome sequencing in individuals with neurodevelopmental disorders. Functional studies showed that some variants displayed impaired membrane transport and impaired excitatory synapse-promoting effects. Strikingly, these variations abolished the ability of SLITRK2 wild-type to reduce the levels of the receptor tyrosine kinase TrkB in neurons. Moreover, Slitrk2 conditional knockout mice exhibited impaired long-term memory and abnormal gait, recapitulating a subset of clinical features of patients with SLITRK2 variants. Furthermore, impaired excitatory synapse maintenance induced by hippocampal CA1-specific cKO of Slitrk2 caused abnormalities in spatial reference memory. Collectively, these data suggest that SLITRK2 is involved in X-linked neurodevelopmental disorders that are caused by perturbation of diverse facets of SLITRK2 function. The protein SLITRK2 plays an important role in synaptic communication. This study identifies X-linked SLITRK2 variants that underlie neurodevelopmental disorders by impairing excitatory synapses.

Ankita Patel and colleagues report microdeletions and microduplications on chromosome 1q21.1 in a series of individuals with features of microcephaly and macrocephaly, as well as developmental delay and neuropsychiatric abnormalities. Chromosome region 1q21.1 contains extensive and complex low-copy repeats, and copy number variants (CNVs) in this region have recently been reported in association with congenital heart defects 1 , developmental delay 2 , 3 , schizophrenia and related psychoses 4 , 5 . We describe 21 probands with the 1q21.1 microdeletion and 15 probands with the 1q21.1 microduplication. These CNVs were inherited in most of the cases in which parental studies were available. Consistent and statistically significant features of microcephaly and macrocephaly were found in individuals with microdeletion and microduplication, respectively. Notably, a paralog of the HYDIN gene located on 16q22.2 and implicated in autosomal recessive hydrocephalus 6 was inserted into the 1q21.1 region during the evolution of Homo sapiens 7 ; we found this locus to be deleted or duplicated in the individuals we studied, making it a probable candidate for the head size abnormalities observed. We propose that recurrent reciprocal microdeletions and microduplications within 1q21.1 represent previously unknown genomic disorders characterized by abnormal head size along with a spectrum of developmental delay, neuropsychiatric abnormalities, dysmorphic features and congenital anomalies. These phenotypes are subject to incomplete penetrance and variable expressivity.

The Sandia Fracture Challenges provide a forum for the mechanics community to assess its ability to predict ductile fracture through a blind, round-robin format where mechanicians are challenged to predict the deformation and failure of an arbitrary geometry given experimental calibration data. The Third Challenge (SFC3) required participants to predict fracture in an additively manufactured (AM) 316L stainless steel bar containing through holes and internal cavities that could not have been conventionally machined. The volunteer participants were provided extensive data including tension and notched tensions tests of 316L specimens built on the same build-plate as the Challenge geometry, micro-CT scans of the Challenge specimens and geometric measurements of the feature based on the scans, electron backscatter diffraction (EBSD) information on grain texture, and post-test fractography of the calibration specimens. Surprisingly, the global behavior of the SFC3 geometry specimens had modest variability despite being made of AM metal, with all of the SFC3 geometry specimens failing under the same failure mode. This is attributed to the large stress concentrations from the holes overwhelming the stochastic local influence of the AM voids and surface roughness. The teams were asked to predict a number of quantities of interest in the response based on global and local measures that were compared to experimental data, based partly on Digital Image Correlation (DIC) measurements of surface displacements and strains, including predictions of variability in the resulting fracture response, as the basis for assessment of the predictive capabilities of the modeling and simulation strategies. Twenty-one teams submitted predictions obtained from a variety of methods: the finite element method (FEM) or the mesh-free, peridynamic method; solvers with explicit time integration, implicit time integration, or quasi-statics; fracture methods including element deletion, peridynamics with bond damage, XFEM, damage (stiffness degradation), and adaptive remeshing. These predictions utilized many different material models: plasticity models including J2 plasticity or Hill yield with isotropic hardening, mixed Swift-Voce hardening, kinematic hardening, or custom hardening curves; fracture criteria including GTN model, Hosford-Coulomb, triaxiality-dependent strain, critical fracture energy, damage-based model, critical void volume fraction, and Johnson-Cook model; and damage evolution models including damage accumulation and evolution, crack band model, fracture energy, displacement value threshold, incremental stress triaxiality, Cocks-Ashby void growth, and void nucleation, growth, and coalescence. Teams used various combinations of calibration data from tensile specimens, the notched tensile specimens, and literature data. A detailed comparison of results based of these different methods is presented in this paper to suggest a set of best practices for modeling ductile fracture in situations like the SFC3 AM-material problem. All blind predictions identified the nominal crack path and initiation location correctly. The SFC3 participants generally fared better in their global predictions of deformation and failure than the participants in the previous Challenges, suggesting the relative maturity of the models used and adoption of best practices from previous Challenges. This paper provides detailed analyses of the results, including discussion of the utility of the provided data, challenges of the experimental-numerical comparison, defects in the AM material, and human factors.

We describe an approach to predict failure in a complex, additively-manufactured stainless steel part as defined by the third Sandia Fracture Challenge. A viscoplastic internal state variable constitutive model was calibrated to fit experimental tension curves in order to capture plasticity, necking, and damage evolution leading to failure. Defects such as gas porosity and lack of fusion voids were represented by overlaying a synthetic porosity distribution onto the finite element mesh and computing the elementwise ratio between pore volume and element volume to initialize the damage internal state variables. These void volume fraction values were then used in a damage formulation accounting for growth of these existing voids, while new voids were allowed to nucleate based on a nucleation rule. Blind predictions of failure are compared to experimental results. The comparisons indicate that crack initiation and propagation were correctly predicted, and that an initial porosity field superimposed as higher initial damage may provide a path forward for capturing material strength uncertainty. The latter conclusion was supported by predicted crack face tortuosity beyond the usual mesh sensitivity and variability in predicted strain to failure; however, it bears further inquiry and a more conclusive result is pending compressive testing of challenge-built coupons to de-convolute materials behavior from the geometric influence of significant porosity.

Duchenne muscular dystrophy (DMD) is an incurable degenerative muscle disorder. We injected WT mouse induced pluripotent stem cells (iPSCs) into mdx and mdx∶utrophin mutant blastocysts, which are predisposed to develop DMD with an increasing degree of severity (mdx <<< mdx∶utrophin). In mdx chimeras, iPSC-dystrophin was supplied to the muscle sarcolemma to effect corrections at morphological and functional levels. Dystrobrevin was observed in dystrophin-positive and, at a lesser extent, utrophin-positive areas. In the mdx∶utrophin mutant chimeras, although iPSC-dystrophin was also supplied to the muscle sarcolemma, mice still displayed poor skeletal muscle histopathology, and negligible levels of dystrobrevin in dystrophin- and utrophin-negative areas. Not only dystrophin-expressing tissues are affected by iPSCs. Mdx and mdx∶utrophin mice have reduced fat/body weight ratio, but iPSC injection normalized this parameter in both mdx and mdx∶utrophin chimeras, despite the fact that utrophin was compromised in the mdx∶utrophin chimeric fat. The results suggest that the presence of utrophin is required for the iPSC-corrections in skeletal muscle. Furthermore, the results highlight a potential (utrophin-independent) non-cell autonomous role for iPSC-dystrophin in the corrections of non-muscle tissue like fat, which is intimately related to the muscle.

Objectives: Registro Informatizado de Enfermedad TromboEmbólica (RIETE) database was used to investigate whether neurosurgical patients with venous thromboembolism (VTE) were more likely to die of bleeding or VTE and the influence of anticoagulation on these outcomes. Methods: Clinical characteristics, treatment details, and 3-month outcomes were assessed in those who developed VTE after neurosurgery. Results: Of 40 663 patients enrolled, 392 (0.96%) had VTE in less than 60 days after neurosurgery. Most patients in the cohort (89%) received initial therapy with low-molecular-weight heparin, (33% received subtherapeutic doses). In the first week, 10 (2.6%) patients died (8 with pulmonary embolism [PE], no bleeding deaths; P = .005). After the first week, 20 (5.1%) patients died (2 with fatal bleeding, none from PE). Overall, this cohort was more likely to develop a fatal PE than a fatal bleed (8 vs 2 deaths, P = .058). Conclusions: Neurosurgical patients developing VTE were more likely to die from PE than from bleeding in the first week, despite anticoagulation.