Kumarreeves4464
The purpose of this study was to investigate pharmacodynamic effects of drugs targeting cortical excitability using transcranial magnetic stimulation (TMS) combined with electromyography (EMG) and electroencephalography (EEG) in healthy subjects, to further develop TMS outcomes as biomarkers for proof-of-mechanism in early-phase clinical drug development. Antiepileptic drugs presumably modulate cortical excitability. Therefore, we studied effects of levetiracetam, valproic acid and lorazepam on cortical excitability in a double-blind, placebo-controlled, 4-way cross-over study.
In 16 healthy male subjects, single- and paired-pulse TMS-EMG-EEG measurements were performed predose and 1.5, 7 and 24 hours postdose. Treatment effects on motor-evoked potential, short and long intracortical inhibition and TMS-evoked potential amplitudes, were analysed using a mixed model ANCOVA and cluster-based permutation analysis.
We show that motor-evoked potential amplitudes decreased after administration of levetiracetaming TMS-EMG-EEG in healthy subjects. These findings provide support for the use of TMS excitability measures as biomarkers to demonstrate pharmacodynamic effects of drugs that influence cortical excitability.Cancer is heterogeneous, and for seemingly similar cancer patients, the associations between an outcome/phenotype and covariates can be different. To describe such differences, finite mixture of regression (FMR) and other modeling techniques have been developed. "Classic" FMR analysis has usually been based on clinical, demographic, and molecular variables. More recently, histopathological imaging data-which is a byproduct of biopsy and enjoys broader data availability and higher cost-effectiveness-has been increasingly used in cancer modeling, although it is noted that its application to cancer FMR analysis still remains limited. In this article, we further advance cancer FMR analysis based on histopathological imaging data. Significantly advancing from the existing analyses under heterogeneity and homogeneity, our goal is to simultaneously use two types of histopathological imaging features, which are extracted based on domain-specific biomedical knowledge and using automated signal processing software, respectively. A significant modeling/methodological advancement is that, to reflect the "increased resolution" of the second type of imaging features over the first type, we impose a hierarchy in the mixture structures. An effective and flexible Bayesian approach is proposed. Simulation shows its competitiveness over several alternatives. The TCGA lung cancer data is analyzed, and interesting heterogeneous structures different from using the alternatives are found. Overall, this study provides a new venue for FMR analysis for cancer and other complex diseases.
To reduce the likelihood of errors in organ delineations used for radiotherapy treatment planning, a knowledge-based quality control (KBQC) system, which discriminates between valid and anomalous delineations isdeveloped.
The KBQC is comprised of a group-wise inference system and anomaly detection modules trained using historical priors from 296 locally advanced lung and prostate cancer patient computational tomographies (CTs). The inference system discriminates different organs based on shape, relational, and intensity features. For a given delineated image set, the inference system solves a combinatorial optimization problem that results in an organ group whose relational features follow those of the training set considering the posterior probabilities obtained from support vector machine (SVM), discriminant subspace ensemble (DSE), and artificial neural network (ANN) classifiers. These classifiers are trained on nonrelational features with a 10-fold cross-validation scheme. The anomaly detection moduleations compared to each individual classifier and a fused classifier that used the average posterior probability of all classifiers. For 15 independent locally advanced lung patients, the system detected
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79% of the anomalous ROIs. For 1320 auto-segmented abdominopelvic organs, the anomaly detection system identified anomalous delineations, which also had low Dice similarity coefficient values with respect to manually delineated organs in the training dataset.
The KBQC system detected anomalous delineations with superior accuracy compared to classification methods that judge only based on posterior probabilities.
The KBQC system detected anomalous delineations with superior accuracy compared to classification methods that judge only based on posterior probabilities.Herbivore population dynamics are strongly influenced by the interactions established through their shared host. Such plant-mediated interactions can occur between different herbivore species and different life developmental stages of the same herbivore. However, whether these interactions occur between leaf-feeding herbivores and their soil-dwelling pupae is unknown. We studied whether tomato (Solanum lycopersicum) leaf herbivory by the American serpentine leafminer Liriomyza trifolii affects the performance of conspecific pupae exposed to the soil headspace of the plant. To gain mechanistic insights, we performed insect bioassays with the jasmonate-deficient tomato mutant def-1 and its wild-type, along with phytohormones, gene expression and root volatiles analyses. Belowground volatiles accelerated leafminer metamorphosis when wild-type plants were attacked aboveground by conspecifics. The opposite pattern was observed for def-1 plants, in which aboveground herbivory slowed metamorphosis. Leafminer attack induced jasmonate and abscisic acid accumulation and modulated volatile production in tomato roots in a def-1-dependent manner. Our results demonstrate that aboveground herbivory triggers changes in root defence signalling and expression, which can directly or indirectly via changes in soil or microbial volatiles, alter pupal development time. This finding expands the repertoire of plant-herbivore interactions to herbivory-induced modulation of metamorphosis, with potential consequences for plant and herbivore community dynamics.At present, the global COVID-19 epidemic has not been completely controlled, and epidemic prevention and control still face severe challenges. As there is no specific treatment for COVID-19, promoting roll-out vaccinations and building herd immunity are still the most effective and economic measures to control the COVID-19 pandemic. https://www.selleckchem.com/products/srt2104-gsk2245840.html However, the neutralizing antibody level in the recipients decreases with time, and the vaccine's protective efficacy gradually weakens. It is still inconclusive whether it is necessary to carry out booster vaccination to strengthen the immune barrier to infection. In this paper, we combined the existing data on the effectiveness and persistence of COVID-19 vaccines. We found that it is necessary to carry out a booster vaccination strategy. However, not all subjects need to receive one more dose of vaccine 6 months after the initial immunization. Priority should be given to the high-risk groups, such as the elderly and people with immunodeficiency. A heterologous booster can induce higher immune responses and enhance immune protection than homologous vaccinations. However, more scientific data and clinical studies are needed to verify the safety of heterologous vaccination strategies.
The purpose of this scoping review was to map clinical-related critical incidents and their implications on undergraduate nursing students.
The unpredictability inherent in the clinical learning environment places nursing students at risk of a critical incident that may lead to long-term consequences.
A scoping review was conducted using the Joanna Briggs Institute framework.
A search for primary research sources and dissertations was conducted using the CINAHL, PubMed, Dissertation and Thesis Global, and MEDLINE databases. Eligibility criteria included primary research related to undergraduate nursing students who had experienced critical incidents in the clinical setting.
From a total of 66 identified articles, only one met the inclusion criteria. Overall, it was identified that the term "stress" was inconsistently defined. Researchers have primarily focused on general stress from academic and experiential learning rather than sudden and unexpected critical incidents underpinned by clinical experiences.
The scoping review results identify a significant gap in the research relative to clinical-related critical incidents and the associated implications experienced by undergraduate nursing students.
Further research is needed so that crisis interventions can be prioritized and strategies to enhance resilience can be addressed before graduation.
Further research is needed so that crisis interventions can be prioritized and strategies to enhance resilience can be addressed before graduation.
The noise power spectrum (NPS) plays a key role in image quality (IQ) evaluation as it can be used for predicting detection performance or calculating detective quantum efficiency (DQE). Traditionally, the NPS is estimated by ensemble averaging multiple realizations of noise-only images. However, the estimation error increases when there are a limited number of images. Since the estimation error directly affects the image quality (IQ) index, an accurate NPS estimation method is required. Recent works have proposed NPS estimation methods using the radial one-dimensional (1D) NPS as the basis; however, when sharp kernels are used during image reconstruction, these methods cannot accurately estimate the amplitude of each angular spoke of the 2D NPS composed of different cutoff frequencies determined from the complementary projection magnification factors for different spatial regions. In this work, we propose a 2D NPS estimation method that reflects the accurate amplitude of each angular spoke for fan-beam CTictions achieved better estimation performance compared with the method using the radial 1D NPS as the basis.
In this work, we propose a 2D NPS estimation method that reflects the accurate amplitude of each angular spoke for fan-beam CT images using two basis functions. We observed that the proposed 2D NPS estimation method using two basis functions achieved better estimation performance compared with the method using the radial 1D NPS as the basis.Resource-use strategies are hypothesized to evolve along climatic gradients. However, our understanding of the environmental factors driving divergent evolution of resource-use strategies and the relationship between trait genetic variation and phenotypic plasticity is far from complete. Using the Mediterranean tree Quercus faginea as study system, we tested the hypothesis that a conservative resource-use strategy with increased drought tolerance and reduced phenotypic plasticity has evolved in areas with longer and more severe dry seasons. We conducted a glasshouse experiment in which we measured leaf morphological, physiological, growth and allocation traits in seedlings from 10 range-wide climatically contrasting populations, grown under two different watering treatments. Both univariate and multivariate analyses revealed a genetic gradient of resource-use strategies and phenotypic plasticity associated with provenance climate. In particular, populations from harsher (drier and colder) environments had more sclerophyllous leaves, lower growth rates, better physiological performance under dry conditions and reduced multi-trait phenotypic plasticity compared to populations from more mesic and milder environments.
