Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials.

The elastic constant tensor of an inorganic compound provides a complete description of the response of the material to external stresses in the elastic limit. It thus provides fundamental insight into the nature of the bonding in the material, and it is known to correlate with many mechanical properties. Despite the importance of the elastic constant tensor, it has been measured for a very small fraction of all known inorganic compounds, a situation that limits the ability of materials scientists to develop new materials with targeted mechanical responses. To address this deficiency, we present here the largest database of calculated elastic properties for inorganic compounds to date. The database currently contains full elastic information for 1,181 inorganic compounds, and this number is growing steadily. The methods used to develop the database are described, as are results of tests that establish the accuracy of the data. In addition, we document the database format and describe the different ways it can be accessed and analyzed in efforts related to materials discovery and design.

White matter disease in the brain increases with age and cardiovascular disease, emerging in midlife, and these associations may be influenced by both genetic and environmental factors. We examined the frequency, distribution, and heritability of abnormal white matter and its association with hypertension in 395 middle-aged male twins (61.9 ± 2.6 years) from the Vietnam Era Twin Study of Aging, 67% of whom were hypertensive. A multi-channel segmentation approach estimated abnormal regions within the white matter. Using multivariable regression models, we characterized the frequency distribution of abnormal white matter in midlife and investigated associations with hypertension and Apolipoprotein E-ε4 status and the impact of duration and control of hypertension. Then, using the classical twin design, we estimated abnormal white matter heritability and the extent of shared genetic overlap with blood pressure. Abnormal white matter was predominantly located in periventricular and deep parietal and frontal regions; associated with age (t = 1.9, p = 0.05) and hypertension (t = 2.9, p = 0.004), but not Apolipoprotein ε4 status; and was greater in those with uncontrolled hypertension relative to controlled (t = 3.0, p = 0.003) and normotensive (t = 4.0, p = 0.0001) groups, suggesting that abnormal white matter may reflect currently active cerebrovascular effects. Abnormal white matter was highly heritable (a² = 0.81) and shared some genetic influences with systolic blood pressure (r_A = 0.26), although there was evidence for distinct genetic contributions and unique environmental influences. Future longitudinal research will shed light on factors impacting white matter disease presentation, progression, and potential recovery.

Objective: Abnormal white matter (AWM) on magnetic resonance imaging is associated with cognitive performance in older adults. We explored cognitive associations with AWM during late-midlife. Method: Participants were community-dwelling men (n = 242; M = 61.90 years; range = 56-66). Linear-mixed effects regression models examined associations of total, periventricular, and deep AWM with cognitive performance, controlling for multiple comparisons. Models considering specific cognitive domains controlled for current general cognitive ability (GCA). We hypothesized that total AWM would be associated with worse processing speed, executive function, and current GCA; deep AWM would correlate with GCA and periventricular AWM would relate to specific cognitive abilities. We also assessed the potential influence of cognitive reserve by examining a moderation effect of early life (mean age of 20) cognition. Results: Greater total and deep AWM were associated with poorer current GCA. Periventricular AWM was associated with worse executive function, working memory, and episodic memory. When periventricular and deep AWM were modeled simultaneously, both retained their respective significant associations with cognitive performance. Cognitive reserve did not moderate associations. Conclusions: Our findings suggest that AWM contributes to poorer cognitive function in late-midlife. Examining only total AWM may obscure the potential differential impact of regional AWM. Separating total AWM into subtypes while controlling for current GCA revealed a dissociation in relationships with cognitive performance; deep AWM was associated with nonspecific cognitive ability whereas periventricular AWM was associated with specific frontal-related abilities and memory. Management of vascular or other risk factors that may increase the risk of AWM should begin during or before early late-midlife. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Despite the widening use of combination antiretroviral therapy (ART), neurocognitive impairment remains common among HIV-infected (HIV+) individuals. Associations between HIV-related neuromedical variables and magnetic resonance imaging indices of brain structural integrity may provide insight into the neural bases for these symptoms. A diverse HIV+ sample (n = 251) was studied through the CNS HIV Antiretroviral Therapy Effects Research initiative. Multi-channel image analysis produced volumes of ventricular and sulcal cerebrospinal fluid (CSF), cortical and subcortical gray matter, total cerebral white matter, and abnormal white matter. Cross-sectional analyses employed a series of multiple linear regressions to model each structural volume as a function of severity of prior immunosuppression (CD4 nadir), current CD4 count, presence of detectable CSF HIV RNA, and presence of HCV antibodies; secondary analyses examined plasma HIV RNA, estimated duration of HIV infection, and cumulative exposure to ART. Lower CD4 nadir was related to most measures of the structural brain damage. Higher current CD4, unexpectedly, correlated with lower white and subcortical gray and increased CSF. Detectable CSF HIV RNA was related to less total white matter. HCV coinfection was associated with more abnormal white matter. Longer exposure to ART was associated with lower white matter and higher sulcal CSF. HIV neuromedical factors, including lower nadir, higher current CD4 levels, and detectable HIV RNA, were associated with white matter damage and variability in subcortical volumes. Brain structural integrity in HIV likely reflects dynamic effects of current immune status and HIV replication, superimposed on residual effects associated with severe prior immunosuppression.

MRI alterations in the cerebral white (WM) and gray matter (GM) are common in HIV infection, even during successful combination antiretroviral therapy (CART), and their pathophysiology and clinical significance are unclear. We evaluated the association of these alterations with recovery of CD4+ T cells. Seventy-five HIV-infected (HIV+) volunteers in the CNS HIV Anti-Retroviral Therapy Effects Research study underwent brain MRI at two visits. Multi-channel morphometry yielded volumes of total cerebral WM, abnormal WM, cortical and subcortical GM, and ventricular and sulcal CSF. Multivariable linear regressions were used to predict volumetric changes with change in current CD4 and detectable HIV RNA. On average, the cohort (79 % initially on CART) demonstrated loss of total cerebral WM alongside increases in abnormal WM and ventricular volumes. A greater extent of CD4 recovery was associated with increases in abnormal WM and subcortical GM volumes. Virologic suppression was associated with increased subcortical GM volume, independent of CD4 recovery. These findings suggest a possible link between brain alterations and immune recovery, distinct from the influence of virologic suppression. The association of increasing abnormal WM and subcortical GM volumes with CD4+ T cell recovery suggests that neuroinflammation may be one mechanism in CNS pathogenesis.

Despite modern antiretroviral therapy, HIV-associated sensory neuropathy affects over 50 % of HIV patients. The clinical expression of HIV neuropathy is highly variable: many individuals report few symptoms, but about half report distal neuropathic pain (DNP), making it one of the most prevalent, disabling, and treatment-resistant complications of HIV disease. The presence and intensity of pain is not fully explained by the degree of peripheral nerve damage, making it unclear why some patients do, and others do not, report pain. To better understand central nervous system contributions to HIV DNP, we performed a cross-sectional analysis of structural magnetic resonance imaging volumes in 241 HIV-infected participants from an observational multi-site cohort study at five US sites (CNS HIV Anti-Retroviral Treatment Effects Research Study, CHARTER). The association between DNP and the structural imaging outcomes was investigated using both linear and nonlinear (Gaussian Kernel support vector) multivariable regression, controlling for key demographic and clinical variables. Severity of DNP symptoms was correlated with smaller total cerebral cortical gray matter volume (r = -0.24; p = 0.004). Understanding the mechanisms for this association between smaller total cortical volumes and DNP may provide insight into HIV DNP chronicity and treatment-resistance.