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Effect sizes for significant differences were medium to large (Cohen's d 0.26-0.67).

Alcohol- and cannabis-involved sexual activity tend to be overreported on retrospective surveys, and preliminary findings suggest that these recall biases may vary by gender. Researchers interested in the co-occurrence of substance use and sexual activity should be aware of this potential random error and consider how to reduce recall biases based on method of data collection.

Alcohol- and cannabis-involved sexual activity tend to be overreported on retrospective surveys, and preliminary findings suggest that these recall biases may vary by gender. Researchers interested in the co-occurrence of substance use and sexual activity should be aware of this potential random error and consider how to reduce recall biases based on method of data collection.Increased nutrient loading has led to eutrophication of coastal shelf waters which has resulted in increased prevalence of persistent hypoxic zones - areas in which the dissolved oxygen content of the water drops below 2 mg/L. The northern Gulf of Mexico, fed primarily by the Mississippi River watershed, undergoes annual establishment of one of the largest hypoxic zones in the world. Exposure to hypoxia can induce physiological impacts in fish cardiac systems that include bradycardia, changes in stroke volume, and altered cardiovascular vessel development. While these impacts have been addressed at the functional level, there is little information regarding the molecular basis for these changes. This study used transcriptomic analysis techniques to interrogate the effects of hypoxia exposure on the developing cardiovascular system in newly hatched larvae of two estuarine species that occupy the same ecological niche - the sheepshead minnow (Cyprinodon variegatus) and the Gulf killifish (Fundulus grandis). Results suggest that while differential gene expression is largely distinct between the two species, downstream impacts on pathways and functional responses such as reduced cardiac hypertrophy, modulation of blood pressure, and increased incidence of apoptosis appear to be conserved. Further, differences in the magnitude of these conserved responses may suggest that the length of embryonic development could impart a level of resiliency to hypoxic perturbation in early life stage fish.Nanostructures generated by self-assembly of peptides yield nanomaterials that have many therapeutic applications, including drug delivery and biomedical engineering, due to their low cytotoxicity and higher uptake by targeted cells owing to their high affinity and specificity towards cell surface receptors. Despite the promising implications of this rapidly expanding field, there is no dedicated resource to study peptide nanostructures. This study endeavours to create a repository of short peptides, which may prove to be the best models to study ordered nanostructures formed by peptide self-assembly. SAPdb has a repertoire of 1049 entries of experimentally validated nanostructures formed by the self-assembly of small peptides. It consists of 328 tripeptides, 701 dipeptides, and 20 single amino acids with some conjugate partners. Each entry encompasses comprehensive information about the peptide, such as chemical modifications, the type of nanostructure formed, experimental conditions like pH, temperature, solvent required for the self-assembly, etc. Our analysis indicates that peptides containing aromatic amino acids favour the formation of self-assembling nanostructures. Additionally, we observed that these peptides form different nanostructures under different experimental conditions. SAPdb provides this comprehensive information in a hassle-free tabulated manner at a glance. User-friendly browsing, searching, and analysis modules have been integrated for easy data retrieval, data comparison, and examination of properties. learn more We anticipate SAPdb to be a valuable repository for researchers engaged in the burgeoning arena of nanobiotechnology. It is freely available at https//webs.iiitd.edu.in/raghava/sapdb.At present, the global pandemic as it relates to novel coronavirus pneumonia is still a very difficult situation. Due to the recent outbreak of novel coronavirus pneumonia, novel chest X-ray (CXR) images that can be used for deep learning analysis are very rare. To solve this problem, we propose a deep learning framework that integrates a convolutional neural network and a capsule network. DenseCapsNet, a new deep learning framework, is formed by the fusion of a dense convolutional network (DenseNet) and the capsule neural network (CapsNet), leveraging their respective advantages and reducing the dependence of convolutional neural networks on a large amount of data. Using 750 CXR images of lungs of healthy patients as well as those of patients with other pneumonia and novel coronavirus pneumonia, the method can obtain an accuracy of 90.7% and an F1 score of 90.9%, and the sensitivity for detecting COVID-19 can reach 96%. These results show that the deep fusion neural network DenseCapsNet has good performance in novel coronavirus pneumonia CXR radiography detection.Despite that fluorescence spectroscopy coupled with Parallel Factor Analysis (PARAFAC) has been widely used in the investigation of Fluorescent Dissolved Organic Matter (FDOM) in aquatic systems, the proper performance of PARAFAC analysis on datasets originating from various sources is not to be taken for granted. In this study, we examine the impact of the co-analysis of datasets from various natural water systems located in the same geographical region in the Eastern Mediterranean Sea. For this purpose three datasets were formed representative of open sea waters (SW), rivers and streams (RV) and lagoons (LG). The Excitation Emission Matrices (EEMs) derived from fluorescence analysis were subjected to individual PARAFAC analysis per dataset as well as combined analyses i.e. SWRV, SWLG, RVLG, ALL (SW-RV-LG). We evaluated the reliability of the components that were validated in the combined models through the investigation of model's residuals and components correlation. We also assessed the similarity of the common identified components among models in regards of (a) spectral position, by calculating the Tucker congruence coefficient (TCC) of the excitation and emission loadings of the PARAFAC components, and (b) fluorescence intensity, through regression analysis of Fmax, among models.

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