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Background: Hippocampal disturbances are important in the pathophysiology of both schizophrenia and major depressive disorder (MDD). Imaging studies have shown selective volume deficits across hippocampal subfields in both disorders. We aimed to investigate whether these volumetric alterations in hippocampal subfields are shared or divergent across disorders. Methods: We searched PubMed and Embase from database inception to May 8, 2021. We identified MRI studies in patients with schizophrenia, MDD or both, in which hippocampal subfield volumes were measured. We excluded nonoriginal, animal or postmortem studies, and studies that used other imaging modalities or overlapping data. We conducted a network meta-analysis to estimate and contrast alterations in subfield volumes in the 2 disorders. Results: We identified 45 studies that met the initial criteria for systematic review, of which 15 were eligible for network metaanalysis. Compared to healthy controls, patients with schizophrenia had reduced volumes in the bilateral cornu ammonis (CA) 1, granule cell layer of the dentate gyrus, subiculum, parasubiculum, molecular layer, hippocampal tail and hippocampus- amygdala transition area (HATA); in the left CA4 and presubiculum; and in the right fimbria. Patients with MDD had decreased volumes in the left CA3 and CA4 and increased volumes in the right HATA compared to healthy controls. The bilateral parasubiculum and right HATA were smaller in patients with schizophrenia than in patients with MDD. Limitations: We did not investigate medication effects because of limited information. Study heterogeneity was noteworthy in direct comparisons between patients with MDD and healthy controls. Conclusion: The volumes of multiple hippocampal subfields are selectively altered in patients with schizophrenia and MDD, with overlap and differentiation in subfield alterations across disorders. Rigorous head-to-head studies are needed to validate our findings., Introduction Schizophrenia and major depressive disorder (MDD) are common psychiatric illnesses with overlaps in pathogenesis, symptom presentation and neurobiological features. Epidemiological evidence suggests that both disorders are associated with prenatal [...]

In this research, a new computational method was proposed for describing the mechanical behavior of super-elastic-plastic foams under inhomogeneous compressive impacts. The method regarded the foam material as composed of two typical mechanical properties superimposed multiple times: one was the hyper-elastic layer, and the other was the elastoplastic layer. The hyper-elastic layer and the elastoplastic layer were interwoven and overlapped, divided into double-layer, four-layer, and six-layer configurations to characterize the foam material. After the equivalent layering of the foam, by comparing the results of the four-layer and six-layer divisions, it was found that when the layering reached four layers, the foam performance curve had already converged. The study utilized the HYPERFOAM model and Mullins effect in the ABAQUS software to establish the constitutive relationship of the hyper-elastic layer. It adopted the Crushable foam model to develop the constitutive relationship of the elastoplastic layer. Under uniaxial compression conditions, quasi-static and intermediate strain rate compression tests were performed on polyethylene (PE) foam materials with three different densities. Based on the experimental results, the parameter values of the hyper-elastic-plastic foam model in the ABAQUS code were determined. By comparing the computational results and the experimental results, the established finite element (FE) model was validated using the mechanical behavior of indentation and compression tests. The results showed that this method could effectively describe the complex mechanical behavior and residual deformation of hyper-elastic-plastic foam packaging materials under non-uniform compression, and the experimental and simulation results agreed well, proving the reliability of this method. [ABSTRACT FROM AUTHOR]

With higher standards in terms of diet and leisure enjoyment, spices and essential oils of aromatic plants (APEOs) are no longer confined to the food industry. The essential oils (EOs) produced from them are the active ingredients that contribute to different flavors. The multiple odor sensory properties and their taste characteristics of APEOs are responsible for their widespread use. The research on the flavor of APEOs is an evolving process attracting the attention among scientists in the past decades. For APEOs, which are used for a long time in the catering and leisure industries, it is necessary to analyze the components associated with the aromas and the tastes. It is important to identify the volatile components and assure quality of APEOs in order to expand their application. It is worth celebrating the different means by which the loss of flavor of APEOs can be retarded in practice. Unfortunately, relatively little research has been done on the structure and flavor mechanisms of APEOs. This also points the way to future research on APEOs.Therefore, this paper reviews the principles of flavor, identification of components and sensory pathways in humans for APEOs. Moreover, the article outlines the means of increasing the efficiency of using of APEOs. Finally, with respect to the sensory applications of APEOs, the review focuses on the practical application of APEOs in food sector and in aromatherapy. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence technology, explosive research on the recognition of retina diseases with artificial intelligence was published worldwide, among which, diabetic retinopathy attracted most attention. However, evaluation of different artificial intelligence software remains a problem. The Department of Ophthalmology, Peking Union Medical College Hospital published the first standard well-annotated color photo database of diabetic retinopathy for artificial intelligence research in China. We herein present the procedures for the establishment of the database and aim to provide reference for the future development of similar databases.

Studying and understanding the complexity and interactions of different factors influencing stream sediment quality is necessary for the development of successful water quality management strategies. This study aims to evaluate the level of contamination by potentially toxic elements (PTEs) (As, Co, Cr, Cu, Mn, Ni, Pb, V, Zn) of the stream sediments of the Nile River. During the spring of 2019, river sediments were sampled at 23 sites along the Nile River. For each sample, one aliquot was digested in aqua regia and analyzed by ICP-MS for pseudo-total concentration, while for another aliquot, sequential extraction procedures were applied to determine chemical speciation. Compositional data analysis (CoDa) and k-means were applied to recognize the contribution of natural and anthropogenic sources, while pollution indices (EF, RAC) and sediment quality guidelines (SQGs) were applied to assess the ecological risk to biotic species. The results reveal that elements such as Cr, Mn, V and Fe, found in high concentrations in almost all samples (Cr up to 739 mg/kg, Mn up to 1942 mg/kg, V up to 507 mg/kg, Fe up to 98,519 mg/kg), have a natural origin, while the concentrations of Cu (up to 69 mg/kg), Ni (up to 88 mg/kg), Co (up to 42 mg/kg) and As (up to 9.8 mg/kg) are linked to both natural and anthropogenic processes. Sequential extraction shows that Mn, Co, Ni and, in some sites, Cu and Zn, are the most bioavailable elements. These elements present a high risk of toxicity, while the remaining elements imply a low-to-moderate risk.