246 research outputs found
Lowering β-Amyloid Levels Rescues Learning and Memory in a Down Syndrome Mouse Model
β-amyloid levels are elevated in Down syndrome (DS) patients throughout life and are believed to cause Alzheimer's disease (AD) in adult members of this population. However, it is not known if β-amyloid contributes to intellectual disability in younger individuals. We used a γ-secretase inhibitor to lower β-amyloid levels in young mice that model DS. This treatment corrected learning deficits characteristic of these mice, suggesting that β-amyloid-lowering therapies might improve cognitive function in young DS patients
Resource-sharing in multiple component working memory
Working memory research often focuses on measuring the capacity of the system and how it relates to other cognitive abilities. However, research into the structure of working memory is less concerned with an overall capacity measure but rather with the intricacies of underlying components and their contribution to different tasks. A number of models of working memory structure have been proposed, each with different assumptions and predictions, but none of which adequately accounts for the full range of data in the working memory literature. We report 2 experiments that investigated the effects of load manipulations on dual-task verbal temporary memory and spatial processing. Crucially, we manipulated cognitive load around the measured memory span of each individual participant. We report a clear effect of increasing memory load on processing accuracy, but only when memory load is increased above each participant’s measured memory span. However, increasing processing load did not affect memory performance. We argue that immediate verbal memory may rely both on a temporary phonological store and on activated traces in long-term memory, with the latter deployed to support memory performance for supraspan lists and when a high memory load is coupled with a processing task. We propose that future research should tailor the load manipulations to the capacities of individual participants and suggest that contrasts between models of working memory may be more apparent than real
Stochastic Gravity: Theory and Applications
Whereas semiclassical gravity is based on the semiclassical Einstein equation
with sources given by the expectation value of the stress-energy tensor of
quantum fields, stochastic semiclassical gravity is based on the
Einstein-Langevin equation, which has in addition sources due to the noise
kernel. In the first part, we describe the fundamentals of this new theory via
two approaches: the axiomatic and the functional. In the second part, we
describe three applications of stochastic gravity theory. First, we consider
metric perturbations in a Minkowski spacetime, compute the two-point
correlation functions of these perturbations and prove that Minkowski spacetime
is a stable solution of semiclassical gravity. Second, we discuss structure
formation from the stochastic gravity viewpoint. Third, we discuss the
backreaction of Hawking radiation in the gravitational background of a black
hole and describe the metric fluctuations near the event horizon of an
evaporating black holeComment: 100 pages, no figures; an update of the 2003 review in Living Reviews
in Relativity gr-qc/0307032 ; it includes new sections on the Validity of
Semiclassical Gravity, the Stability of Minkowski Spacetime, and the Metric
Fluctuations of an Evaporating Black Hol
Lymphatic vessel density and VEGF-C expression are significantly different among benign and malignant thyroid lesions
Thyroid cancer is the most frequent endocrine neoplasia worldwide. The route for metastasis and loco-regional invasion preferentially occurs by lymphatic vessels. For this reason, the assessment of lymphatic vessel density (LVD) is supposed to represent both a prognostic parameter and also a potential therapeutic target. In order to evaluate the value of LVD in benign and malignant thyroid lesions, we analyzed 110 thyroidectomy specimens using D2-40, a specific marker for lymphatic vessels and vascular endothelial growth factor C (VEGF-C), the most potent molecule of lymphatic proliferation. LVD was significantly different between papillary and follicular carcinomas in total (p = 0.045) and peritumoral area (p = 0.042). Follicular adenoma and follicular carcinoma showed an important difference of intra- (p = 0.019) and peritumoral (p = 0.033) LVD. VEGF-C was more markedly expressed in malignancies than in benign lesions (p = 0.0001). Almost all cancers with high positive VEGF-C expression also exhibited increased peritumoral LVD (p = 0.049) when compared with the benign lesions. Indeed, the high peritumoral LVD of malignant thyroid lesions is an important finding for surgery planning and supports the practice of total thyroidectomy in malignant thyroid neoplasm's since the lymphatic peritumoral vessels definitely are an escape path for tumor cells
Stochastic Gravity: Theory and Applications
Whereas semiclassical gravity is based on the semiclassical Einstein equation
with sources given by the expectation value of the stress-energy tensor of
quantum fields, stochastic semiclassical gravity is based on the
Einstein-Langevin equation, which has in addition sources due to the noise
kernel.In the first part, we describe the fundamentals of this new theory via
two approaches: the axiomatic and the functional. In the second part, we
describe three applications of stochastic gravity theory. First, we consider
metric perturbations in a Minkowski spacetime: we compute the two-point
correlation functions for the linearized Einstein tensor and for the metric
perturbations. Second, we discuss structure formation from the stochastic
gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in
the gravitational background of a quasi-static black hole.Comment: 75 pages, no figures, submitted to Living Reviews in Relativit
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A Schur complement approach to preconditioning sparse linear least-squares problems with some dense rows
The effectiveness of sparse matrix techniques for directly solving large-scale linear least-squares problems is severely limited if the system matrix A has one or more nearly dense rows. In this paper, we partition the rows of A into sparse rows and dense rows (A s and A d ) and apply the Schur complement approach. A potential difficulty is that the reduced normal matrix AsTA s is often rank-deficient, even if A is of full rank. To overcome this, we propose explicitly removing null columns of A s and then employing a regularization parameter and using the resulting Cholesky factors as a preconditioner for an iterative solver applied to the symmetric indefinite reduced augmented system. We consider complete factorizations as well as incomplete Cholesky factorizations of the shifted reduced normal matrix. Numerical experiments are performed on a range of large least-squares problems arising from practical applications. These demonstrate the effectiveness of the proposed approach when combined with either a sparse parallel direct solver or a robust incomplete Cholesky factorization algorithm
Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits
Background: In the analysis of complex traits, genetic effects can be confounded with non-genetic effects, especially when using full-sib families. Dominance and epistatic effects are typically confounded with additive genetic and non-genetic effects. This confounding may cause the estimated genetic variance components to be inaccurate and biased
Early experience of COVID-19 vaccination in adults with systemic rheumatic diseases: results from the COVID-19 Global Rheumatology Alliance Vaccine Survey.
Background: We describe the early experiences of adults with systemic rheumatic disease who received the COVID-19 vaccine.
Methods: From 2 April to 30 April 2021, we conducted an online, international survey of adults with systemic rheumatic disease who received COVID-19 vaccination. We collected patient-reported data on clinician communication, beliefs and intent about discontinuing disease-modifying antirheumatic drugs (DMARDs) around the time of vaccination, and patient-reported adverse events after vaccination.
Results: We analysed 2860 adults with systemic rheumatic diseases who received COVID-19 vaccination (mean age 55.3 years, 86.7% female, 86.3% white). Types of COVID-19 vaccines were Pfizer-BioNTech (53.2%), Oxford/AstraZeneca (22.6%), Moderna (21.3%), Janssen/Johnson & Johnson (1.7%) and others (1.2%). The most common rheumatic disease was rheumatoid arthritis (42.3%), and 81.2% of respondents were on a DMARD. The majority (81.9%) reported communicating with clinicians about vaccination. Most (66.9%) were willing to temporarily discontinue DMARDs to improve vaccine efficacy, although many (44.3%) were concerned about rheumatic disease flares. After vaccination, the most reported patient-reported adverse events were fatigue/somnolence (33.4%), headache (27.7%), muscle/joint pains (22.8%) and fever/chills (19.9%). Rheumatic disease flares that required medication changes occurred in 4.6%.
Conclusion: Among adults with systemic rheumatic disease who received COVID-19 vaccination, patient-reported adverse events were typical of those reported in the general population. Most patients were willing to temporarily discontinue DMARDs to improve vaccine efficacy. The relatively low frequency of rheumatic disease flare requiring medications was reassuring
Bupropion for the treatment of apathy in Huntington's disease:A multicenter, randomised, double-blind, placebo-controlled, prospective crossover trial
OBJECTIVE:To evaluate the efficacy and safety of bupropion in the treatment of apathy in Huntington's disease (HD). METHODS:In this phase 2b multicentre, double-blind, placebo-controlled crossover trial, individuals with HD and clinical signs of apathy according to the Structured Clinical Interview for Apathy-Dementia (SCIA-D), but not depression (n = 40) were randomized to receive either bupropion 150/300mg or placebo daily for 10 weeks. The primary outcome parameter was a significant change of the Apathy Evaluation Scale (AES) score after ten weeks of treatment as judged by an informant (AES-I) living in close proximity with the study participant. The secondary outcome parameters included changes of 1. AES scores determined by the patient (AES-S) or the clinical investigator (AES-C), 2. psychiatric symptoms (NPI, HADS-SIS, UHDRS-Behavior), 3. cognitive performance (SDMT, Stroop, VFT, MMSE), 4. motor symptoms (UHDRS-Motor), 5. activities of daily function (TFC, UHDRS-Function), and 6. caregiver distress (NPI-D). In addition, we investigated the effect of bupropion on brain structure as well as brain responses and functional connectivity during reward processing in a gambling task using magnetic resonance imaging (MRI). RESULTS:At baseline, there were no significant treatment group differences in the clinical primary and secondary outcome parameters. At endpoint, there was no statistically significant difference between treatment groups for all clinical primary and secondary outcome variables. Study participation, irrespective of the intervention, lessened symptoms of apathy according to the informant and the clinical investigator. CONCLUSION:Bupropion does not alleviate apathy in HD. However, study participation/placebo effects were observed, which document the need for carefully controlled trials when investigating therapeutic interventions for the neuropsychiatric symptoms of HD. TRIAL REGISTRATION:ClinicalTrials.gov 01914965
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