Bayesian hierarchical EMAX model for doseâ response in early phase efficacy clinical trials

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149669/1/sim8167_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149669/2/sim8167.pd

Latin American Trans-ancestry INitiative for OCD genomics (LATINO): Study protocol

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but \u3e95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity

Language Impairment in Children Perinatally Infected with HIV Compared to Children Who Were HIV-Exposed and Uninfected

Objective - To investigate risk for language impairment in children perinatally infected or exposed to HIV. Methods - We evaluated the prevalence of language impairment (LI) in 7–16 year old children with perinatal HIV infection (HIV+) compared to children HIV-exposed and uninfected (HEU), using a comprehensive standardized language test (CELF-4). LI was classified as primary LI (Pri-LI) (monolingual English exposure and no cognitive or hearing impairment), concurrent LI (Con-LI) (cognitive or hearing impairment), or no LI. Associations of demographic, caregiver, HIV disease and antiretroviral treatment (ART) factors with LI category were evaluated using univariate and multivariable logistic regression models. Results - Of 468 children with language assessments, 184 (39%) had LI. No difference was observed by HIV infection status for overall LI or for Pri-LI or Con-LI; mean (SD) CELF-4 scores were 88.5 (18.4) for HIV+ vs 87.5 (17.9) for HEU. After adjustment, Black children had higher odds of Pri-LI vs no LI (aOR=2.43, p=0.03). Children who were Black, Hispanic, had a caregiver with low education or low IQ, or a non-biological parent as caregiver had higher odds of Con-LI vs no LI. Among HIV+ children, viral load \u3e400 copies/ml (aOR=3.04, pp=0.02) and ART initiation (aOR=2.12, p=0.02) were associated with higher odds of Con-LI vs. no LI. Conclusions - Children perinatally exposed to HIV are at high risk for LI, but such risk was not increased for youth with HIV. Risk factors differed for Pri-LI and Con-LI

Language Impairment in Children Perinatally Infected with HIV Compared to Children Who Were HIV-Exposed and Uninfected

OBJECTIVE: To investigate risk for language impairment in children perinatally infected or exposed to HIV. METHOD: We evaluated the prevalence of language impairment (LI) in 7–16 year old children with perinatal HIV infection (HIV+) compared to children HIV-exposed and uninfected (HEU), using a comprehensive standardized language test (CELF-4). LI was classified as primary LI (Pri-LI) (monolingual English exposure and no cognitive or hearing impairment), concurrent LI (Con-LI) (cognitive or hearing impairment), or no LI. Associations of demographic, caregiver, HIV disease and antiretroviral treatment (ART) factors with LI category were evaluated using univariate and multivariable logistic regression models. RESULTS: Of 468 children with language assessments, 184 (39%) had LI. No difference was observed by HIV infection status for overall LI or for Pri-LI or Con-LI; mean (SD) CELF-4 scores were 88.5 (18.4) for HIV+ vs 87.5 (17.9) for HEU. After adjustment, Black children had higher odds of Pri-LI vs no LI (aOR=2.43, p=0.03). Children who were Black, Hispanic, had a caregiver with low education or low IQ, or a non-biological parent as caregiver had higher odds of Con-LI vs no LI. Among HIV+ children, viral load >400 copies/ml (aOR=3.04, p<0.001), CDC Class C (aOR=2.19, p=0.02) and ART initiation <6 months of age (aOR=2.12, p=0.02) were associated with higher odds of Con-LI vs. no LI. CONCLUSIONS: Children perinatally exposed to HIV are at high risk for LI, but such risk was not increased for youth with HIV. Risk factors differed for Pri-LI and Con-LI

NICER Detects a Soft X-Ray Kilohertz Quasi-periodic Oscillation in 4U 0614+09

We report on the detection of a kilohertz quasi-periodic oscillation (QPO) with the Neutron Star Interior Composition Explorer (NICER). Analyzing approximately 165 ks of NICER exposure on the X-ray burster 4U 0614+09, we detect multiple instances of a single-peak upper kHz QPO, with centroid frequencies that range from 400 to 750 Hz. We resolve the kHz QPO as a function of energy, and measure, for the first time, the QPO amplitude below 2 keV. We find the fractional amplitude at 1 keV is on the order of 2% rms, and discuss the implications for the QPO emission process in the context of Comptonization models. Key words: accretion, accretion disks – stars: neutron – X-rays: binaries – X-rays: individual (4U 0614+0

A NICER look at the Aql X-1 hard state

We report on a spectral-timing analysis of the neutron star low-mass X-ray binary (LMXB) Aql X-1 with the Neutron Star Interior Composition Explorer (NICER) on the International Space Station (ISS). Aql X-1 was observed with NICER during a dim outburst in 2017 July, collecting approximately 50 ks of good exposure. The spectral and timing properties of the source correspond to that of a (hard) extreme island state in the atoll classification. We find that the fractional amplitude of the low-frequency (<0.3 Hz) band-limited noise shows a dramatic turnover as a function of energy: it peaks at 0.5 keV with nearly 25% rms, drops to 12% rms at 2 keV, and rises to 15% rms at 10 keV. Through the analysis of covariance spectra, we demonstrate that band-limited noise exists in both the soft thermal emission and the power-law emission. Additionally, we measure hard time lags, indicating the thermal emission at 0.5 keV leads the power-law emission at 10 keV on a timescale of ∼100 ms at 0.3 Hz to ∼10 ms at 3 Hz. Our results demonstrate that the thermal emission in the hard state is intrinsically variable, and is driving the modulation of the higher energy power-law. Interpreting the thermal spectrum as disk emission, we find that our results are consistent with the disk propagation model proposed for accretion onto black holes.United States. National Aeronautics and Space Administration. Neutron Star Interior Composition ExplorerUnited States. National Aeronautics and Space Administration. Astrophysics Research and Analysis Progra

A cancer drug atlas enables synergistic targeting of independent drug vulnerabilities.

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value

Electric dipole moments and the search for new physics

Static electric dipole moments of nondegenerate systems probe mass scales for physics beyond the Standard Model well beyond those reached directly at high energy colliders. Discrimination between different physics models, however, requires complementary searches in atomic-molecular-and-optical, nuclear and particle physics. In this report, we discuss the current status and prospects in the near future for a compelling suite of such experiments, along with developments needed in the encompassing theoretical framework.Comment: Contribution to Snowmass 2021; updated with community edits and endorsement

PaLM 2 Technical Report

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of objectives. Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more efficient inference compared to PaLM. This improved efficiency enables broader deployment while also allowing the model to respond faster, for a more natural pace of interaction. PaLM 2 demonstrates robust reasoning capabilities exemplified by large improvements over PaLM on BIG-Bench and other reasoning tasks. PaLM 2 exhibits stable performance on a suite of responsible AI evaluations, and enables inference-time control over toxicity without additional overhead or impact on other capabilities. Overall, PaLM 2 achieves state-of-the-art performance across a diverse set of tasks and capabilities. When discussing the PaLM 2 family, it is important to distinguish between pre-trained models (of various sizes), fine-tuned variants of these models, and the user-facing products that use these models. In particular, user-facing products typically include additional pre- and post-processing steps. Additionally, the underlying models may evolve over time. Therefore, one should not expect the performance of user-facing products to exactly match the results reported in this report