Motor deficits and brain pathology in the Parkinson's disease mouse model hA53Ttg.

Background: Parkinson's disease (PD) is a debilitating neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons and the accumulation of α-synuclein (α-syn) aggregates. The A53T missense point mutation occurs in autosomal dominant familial PD and has been found to promote the aggregation of α-syn. To investigate the role of the A53T mutation in PD, researchers have developed various mouse models with this mutation.

Effect of astaxanthin in type-2 diabetes -induced APPxhQC transgenic and NTG mice.

Objectives: Aggregation and misfolding of amyloid beta (Aβ) and tau proteins, suggested to arise from post-translational modification processes, are thought to be the main cause of Alzheimer's disease (AD). Additionally, a plethora of evidence exists that links metabolic dysfunctions such as obesity, type 2 diabetes (T2D), and dyslipidemia to the pathogenesis of AD. We thus investigated the combinatory effect of T2D and human glutaminyl cyclase activity (pyroglutamylation), on the pathology of AD and whether astaxanthin (ASX) treatment ameliorates accompanying pathophysiological manifestations.

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals.

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials.

Longitudinal progression of blood biomarkers reveals a key role of astrocyte reactivity in preclinical Alzheimer's disease.

Defining the progression of blood biomarkers of Alzheimer's disease (AD) is essential for targeting treatments in patients most likely to benefit from early intervention. We delineated the temporal ordering of blood biomarkers a decade prior to the onset of AD symptoms in participants in the Baltimore Longitudinal Study of Aging. We show that increased astrocyte reactivity, assessed by elevated glial fibrillary acidic protein (GFAP) levels is an early event in the progression of blood biomarker changes in preclinical AD.

Correction: Accelerating copolymer inverse design using monte carlo tree search.

Correction for 'Accelerating copolymer inverse design using monte carlo tree search' by Tarak K. Patra , , 2020, , 23653-23662, https://doi.org/10.

Posterior Wall Acetabular Fracture After Low-Energy Trauma Masquerading as Infection: A Case Report.

Case: A 12-year-old adolescent boy presented after a low-energy fall with groin pain, inability to bear weight, painful passive range of motion, fever, elevated inflammatory markers, and upper respiratory symptoms. Initial radiographs did not demonstrate any abnormality, and magnetic resonance imaging suggested infection. Posterior wall acetabular fracture was not diagnosed until a computed tomography-guided biopsy was performed.

Hydroxychloroquine lowers Alzheimer's disease and related dementias risk and rescues molecular phenotypes related to Alzheimer's disease.

We recently nominated cytokine signaling through the Janus-kinase-signal transducer and activator of transcription (JAK/STAT) pathway as a potential AD drug target. As hydroxychloroquine (HCQ) has recently been shown to inactivate STAT3, we hypothesized that it may impact AD pathogenesis and risk. Among 109,124 rheumatoid arthritis patients from routine clinical care, HCQ initiation was associated with a lower risk of incident AD compared to methotrexate initiation across 4 alternative analyses schemes addressing specific types of biases including informative censoring, reverse causality, and outcome misclassification (hazard ratio [95% confidence interval] of 0.

No association between initiation of phosphodiesterase-5 inhibitors and risk of incident Alzheimer's disease and related dementia: results from the Drug Repurposing for Effective Alzheimer's Medicines study.

We evaluated the hypothesis that phosphodiesterase-5 inhibitors, including sildenafil and tadalafil, may be associated with reduced incidence of Alzheimer's disease and related dementia using a patient-level cohort study of Medicare claims and cell culture-based phenotypic assays. We compared incidence of Alzheimer's disease and related dementia after phosphodiesterase-5 inhibitor initiation versus endothelin receptor antagonist initiation among patients with pulmonary hypertension after controlling for 76 confounding variables through propensity score matching. Across four separate analytic approaches designed to address specific types of biases including informative censoring, reverse causality, and outcome misclassification, we observed no evidence for a reduced risk of Alzheimer's disease and related dementia with phosphodiesterase-5 inhibitors;hazard ratio (95% confidence interval): 0.

Machine learning overcomes human bias in the discovery of self-assembling peptides.

Peptide materials have a wide array of functions, from tissue engineering and surface coatings to catalysis and sensing. Tuning the sequence of amino acids that comprise the peptide modulates peptide functionality, but a small increase in sequence length leads to a dramatic increase in the number of peptide candidates. Traditionally, peptide design is guided by human expertise and intuition and typically yields fewer than ten peptides per study, but these approaches are not easily scalable and are susceptible to human bias.

Machine learning the metastable phase diagram of covalently bonded carbon.

Conventional phase diagram generation involves experimentation to provide an initial estimate of the set of thermodynamically accessible phases and their boundaries, followed by use of phenomenological models to interpolate between the available experimental data points and extrapolate to experimentally inaccessible regions. Such an approach, combined with high throughput first-principles calculations and data-mining techniques, has led to exhaustive thermodynamic databases (e.g.

Advancing Chemical Separations: Unraveling the Structure and Dynamics of Phase Splitting in Liquid-Liquid Extraction.

Liquid-liquid extraction (LLE), the go-to process for a variety of chemical separations, is limited by spontaneous organic phase splitting upon sufficient solute loading, called third phase formation. In this study we explore the applicability of critical phenomena theory to gain insight into this deleterious phase behavior with the goal of improving separations efficiency and minimizing waste. A series of samples representative of rare earth purification were constructed to include each of one light and one heavy lanthanide (cerium and lutetium) paired with one of two common malonamide extractants (DMDOHEMA and DMDBTDMA).

Multi-reward Reinforcement Learning Based Bond-Order Potential to Study Strain-Assisted Phase Transitions in Phosphorene.

We introduce a multi-reward reinforcement learning (RL) approach to train a flexible bond-order potential (BOP) for 2D phosphorene based on ab initio training data sets. Our approach is based on a continuous action space Monte Carlo tree search algorithm that is general and scalable and presents an efficient multiobjective optimization scheme for high-dimensional materials design problems. As a proof-of-concept, we deploy this scheme to parametrize multiple structural and dynamical properties of 2D phosphorene polymorphs.

Learning in continuous action space for developing high dimensional potential energy models.

Reinforcement learning (RL) approaches that combine a tree search with deep learning have found remarkable success in searching exorbitantly large, albeit discrete action spaces, as in chess, Shogi and Go. Many real-world materials discovery and design applications, however, involve multi-dimensional search problems and learning domains that have continuous action spaces. Exploring high-dimensional potential energy models of materials is an example.

A brain proteomic signature of incipient Alzheimer's disease in young ε4 carriers identifies novel drug targets.

Aptamer-based proteomics revealed differentially abundant proteins in Alzheimer’s disease (AD) brains in the Baltimore Longitudinal Study of Aging and Religious Orders Study (mean age, 89 ± 9 years). A subset of these proteins was also differentially abundant in the brains of young ε4 carriers relative to noncarriers (mean age, 39 ± 6 years). Several of these proteins represent targets of approved and experimental drugs for other indications and were validated using orthogonal methods in independent human brain tissue samples as well as in transgenic AD models.

Learning with Delayed Rewards-A Case Study on Inverse Defect Design in 2D Materials.

Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects-their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches.

Homozygosity of BACHD rats not only causes strong behavioral deficits in young female rats but also a reduced breeding success.

Huntington's disease is known to be a purely genetic disease based on an expansion of a CAG base triplet repeat in the coding region of the Huntingtin gene. Some years ago, researchers were able to introduce the extensive full-length gene sequence of the mutant huntingtin gene into a rodent model. The resulting BACHD rat is already well characterized for behavioral deficits.

Metabolic, Phenotypic, and Neuropathological Characterization of the Tg4-42 Mouse Model for Alzheimer's Disease.

Background: Preclinical Alzheimer's disease (AD) research strongly depends on transgenic mouse models that display major symptoms of the disease. Although several AD mouse models have been developed representing relevant pathologies, only a fraction of available mouse models, like the Tg4-42 mouse model, display hippocampal atrophy caused by the death of neurons as the key feature of AD. The Tg4-42 mouse model is therefore very valuable for use in preclinical research.

Accelerating copolymer inverse design using monte carlo tree search.

There exists a broad class of sequencing problems in soft materials such as proteins and polymers that can be formulated as a heuristic search that involves decision making akin to a computer game. AI gaming algorithms such as Monte Carlo tree search (MCTS) gained prominence after their exemplary performance in the computer Go game and are decision trees aimed at identifying the path (moves) that should be taken by the policy to reach the final winning or optimal solution. Major challenges in inverse sequencing problems are that the materials search space is extremely vast and property evaluation for each sequence is computationally demanding.

Nanoscale Critical Phenomena in a Complex Fluid Studied by X-Ray Photon Correlation Spectroscopy.

The advent of high-speed x-ray photon correlation spectroscopy now allows the study of critical phenomena in fluids to much smaller length scales and over a wider range of temperatures than is possible with dynamic light scattering. We present an x-ray photon correlation spectroscopy study of critical fluctuation dynamics in a complex fluid typical of those used in liquid-liquid extraction (LLE) of ions, dodecane-DMDBTDMA with extracted aqueous Ce(NO_{3})_{3}. We observe good agreement with both static and dynamic scaling without the need for significant noncritical background corrections.

Constant Levels of Tau Phosphorylation in the Brain of htau Mice.

Excessive tau phosphorylation is the hallmark of tauopathies. Today's research thus focusses on the development of drugs targeting this pathological feature. To test new drugs in preclinical studies, animal models are needed that properly mimic this pathological hallmark.