Notes

Uncommon reason behind simple reduced stomach hemorrhage: A case document.
Learning to associate a positive or negative experience with an unrelated cue after the presentation of a reward or a punishment defines associative learning. The ability to form associative memories has been reported in animal species as complex as humans and as simple as insects and sea slugs. Associative memory has even been reported in tardigrades [1], species that diverged from other animal phyla 500 million years ago. Understanding the mechanisms of memory formation is a fundamental goal of neuroscience research. In this article, we work on resolving the current contradictions between different Drosophila associative memory circuit models and propose an updated version of the circuit model that predicts known memory behaviors that current models do not. Finally, we propose a model for how dopamine may function as a reward prediction error signal in Drosophila, a dopamine function that is well-established in mammals but not in insects [2, 3].Remifentanil is widely used to control intraoperative pain. However, its analgesic effect is limited by the generation of postoperative hyperalgesia. In this study, we investigated whether the impairment of transmembrane protein 16C (TMEM16C)/Slack is required for α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic receptor (AMPAR) activation in remifentanil-induced postoperative hyperalgesia. Remifentanil anesthesia reduced the paw withdrawal threshold from 2 h to 48 h postoperatively, with a decrease in the expression of TMEM16C and Slack in the dorsal root ganglia (DRG) and spinal cord. Knockdown of TMEM16C in the DRG reduced the expression of Slack and elevated the basal peripheral sensitivity and AMPAR expression and function. Overexpression of TMEM16C in the DRG impaired remifentanil-induced ERK1/2 phosphorylation and behavioral hyperalgesia. AMPAR-mediated current and neuronal excitability were downregulated by TMEM16C overexpression in the spinal cord. Taken together, these findings suggest that TMEM16C/Slack regulation of excitatory synaptic plasticity via GluA1-containing AMPARs is critical in the pathogenesis of remifentanil-induced postoperative hyperalgesia in rats.Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder associated with both genetic and environmental risks. Neuroimaging approaches have been widely employed to parse the neurophysiological mechanisms underlying ASD, and provide critical insights into the anatomical, functional, and neurochemical changes. We reviewed recent advances in neuroimaging studies that focused on ASD by using magnetic resonance imaging (MRI), positron emission tomography (PET), or single-positron emission tomography (SPECT). Longitudinal structural MRI has delineated an abnormal developmental trajectory of ASD that is associated with cascading neurobiological processes, and functional MRI has pointed to disrupted functional neural networks. Vorapaxar Meanwhile, PET and SPECT imaging have revealed that metabolic and neurotransmitter abnormalities may contribute to shaping the aberrant neural circuits of ASD. Future large-scale, multi-center, multimodal investigations are essential to elucidate the neurophysiological underpinnings of ASD, and facilitate the development of novel diagnostic biomarkers and better-targeted therapy.Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses in silico and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by "computational model" is understood in many different ways by researchers in different fields of neuroscience and psychology, hindering communication and collaboration. In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level models, and behavior. On the one hand, computational models serve to investigate the mechanisms that generate brain activity, for example measured with EEG, such as the transient emergence of oscillations at different frequency bands and/or with different spatial topographies. On the other hand, computational models serve to design experiments and test hypotheses in silico. The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal. This is crucial for an accurate interpretation of EEG measurements that may ultimately serve in the development of novel clinical applications.
Achieving a higher chemotherapy completion rate is associated with better outcomes in breast cancer patients. We examined the role of exercise and health-related fitness variables in predicting chemotherapy completion in early stage breast cancer patients.

We pooled data from two large, multicenter, exercise trials that obtained baseline (pre-chemotherapy) measures of exercise and health-related fitness in 543 breast cancer patients initiating adjuvant chemotherapy. Assessments included body composition, cardiovascular fitness, muscular strength, patient-reported physical functioning, and self-reported exercise behavior. Chemotherapy completion was assessed as the average relative dose intensity (RDI) for the originally planned regimen. We used logistic regression analyses with a two-sided p value of < 0.05 to estimate the associations between the predictors and an RDI of ≥ 85%.

Overall, 432 of 543 (79.6%) breast cancer patients received an RDI of ≥ 85%. In logistic regression analyses adjusted for significant covariates, patients in the highest 20% vs. lowest 80% of absolute VO
were significantly more likely to complete ≥ 85% RDI (89.0% vs. 77.2%; OR
2.06, 95% CI 1.07-3.96, p = 0.031). Moreover, patients in the highest 80% vs. lowest 20% of absolute chest strength were significantly more likely to complete ≥ 85% RDI (81.5% vs. 71.4%; OR
1.80, 95% CI 1.09-2.98, p = 0.021).

In these exploratory analyses, higher baseline (pre-chemotherapy) cardiovascular fitness and muscular strength were associated with higher rates of chemotherapy completion in early stage breast cancer patients. Aerobic and/or strength training interventions that increase cardiovascular fitness and muscular strength prior to chemotherapy for breast cancer may improve treatment tolerability and outcomes.

START NCT00115713, June 24, 2005; CARE NCT00249015, November 7, 2005 ( http//clinicaltrials.gov ).
START NCT00115713, June 24, 2005; CARE NCT00249015, November 7, 2005 ( http//clinicaltrials.gov ).
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