Neurotrophins are well-characterized neurologically active molecules in the central nervous system. The regulation of these signaling molecules, which are involved in cell growth, differentiation, ...and survival, is critical for normal brain function. Among the different types of neurotrophins, brain-derived neurotrophic factor (BDNF) is involved in various brain functions, including memory consolidation, synaptic plasticity, and adult neurogenesis, and is therefore a key molecule for understanding comprehensive brain function and neurodevelopmental and psychiatric diseases. The concentration of BDNF in body fluid is highly related to several neurodevelopmental and psychiatric diseases, including Alzheimer's diseases, depression, schizophrenia, and bipolar disorder. In the present review, the mechanisms by which BDNF is released from secretory vesicles are reviewed, with a particular focus on the recently described glycan-mediated release. In addition, the impact of glycan-mediated BDNF release on psychiatric disorders is also discussed.
Sialic acids (Sia) are involved in many biological activities and frequently exist as monosialyl residues at the non-reducing terminal end of glycoconjugates. Occasionally, polymerized structures in ...the form of disialic acid (diSia), oligosialic acid (oligoSia) and polysialic acid (polySia) are also found in glycoconjugates. In particular, polySia, which is an evolutionarily conserved epitope from sea urchin to humans, is one of the most biologically important glycotopes in vertebrates. The biological functions of polySia, especially on neural cell adhesion molecules, have been well studied and an in-depth body of knowledge concerning polySia has been accumulated. However, considerably less attention has been paid to glycoproteins containing di- and oligoSia groups. However, advances in analytical methods for detecting oligo/polymerized structures have allowed the identification and characterization of an increasing number of glycoproteins containing di/oligo/polySia chains in nature. In addition, sophisticated genetic techniques have also helped to elucidate the underlying mechanisms of polySia-mediated activities. In this review, recent advances in the study of the chemical properties, distribution and functions of di-, oligo- and polySia residues on glycoproteins are described.
Aims/hypothesis Glucagon-like peptide-1 (GLP-1) has various extra-pancreatic actions, in addition to its enhancement of insulin secretion from pancreatic beta cells. The GLP-1 receptor is produced in ...kidney tissue. However, the direct effect of GLP-1 on diabetic nephropathy remains unclear. Here we demonstrate that a GLP-1 receptor agonist, exendin-4, exerts renoprotective effects through its anti-inflammatory action via the GLP-1 receptor without lowering blood glucose. Methods We administered exendin-4 at 10 μg/kg body weight daily for 8 weeks to a streptozotocin-induced rat model of type 1 diabetes and evaluated their urinary albumin excretion, metabolic data, histology and morphometry. We also examined the direct effects of exendin-4 on glomerular endothelial cells and macrophages in vitro. Results Exendin-4 ameliorated albuminuria, glomerular hyperfiltration, glomerular hypertrophy and mesangial matrix expansion in the diabetic rats without changing blood pressure or body weight. Exendin-4 also prevented macrophage infiltration, and decreased protein levels of intercellular adhesion molecule-1 (ICAM-1) and type IV collagen, as well as decreasing oxidative stress and nuclear factor-κB activation in kidney tissue. In addition, we found that the GLP-1 receptor was produced on monocytes/macrophages and glomerular endothelial cells. We demonstrated that in vitro exendin-4 acted directly on the GLP-1 receptor, and attenuated release of pro-inflammatory cytokines from macrophages and ICAM-1 production on glomerular endothelial cells. Conclusions/interpretation These results indicate that GLP-1 receptor agonists may prevent disease progression in the early stage of diabetic nephropathy through direct effects on the GLP-1 receptor in kidney tissue.
Context
Habitat loss and fragmentation can interact with other threats, including altered fire regimes, and responses to these effects can be mediated by functional traits.
Objectives
To determine ...how richness and abundance of reptile trait groups respond to habitat fragmentation, patch isolation and fire.
Methods
We surveyed reptiles in 30 sites over 3 years. Sites in remnant patches in farmland were adjacent to a conservation park with either recently burnt or long-unburnt habitat. The remnant patches were stratified by distance from the reserve. Sites were spatially paired, and we experimentally burnt one of each pair in farmland. Trait groups included size, reproduction, habitat position, diet, and activity period.
Results
None of the trait groups benefited from experimental burns, while the burns reduced abundance of viviparous, small, and above-ground species. Species richness was lower in isolated sites than in sites close to the conservation park, while generalist trait groups appeared unaffected by patch isolation. Large-sized reptiles had higher abundance in remnants. There was not more rapid colonisation of burnt sites near recently burnt conservation park. Instead, low initial abundance may have been caused by fire in combination with drought, with high rainfall during the study allowing recovery and spill-over into adjacent remnants.
Conclusions
Landscape structure appears to interact with natural fires, restoration burns and longer-term climatic trends to influence the abundance and distribution of reptiles. Traits mediate responses, enabling us to formulate a set of testable mechanistic hypotheses, which illustrates a pathway to generalisation and prediction.
Adhesive joining technology is important for reducing the weight of an automobile body. As joints can be defective, it is necessary to accurately assess the risk of defects. Dumbbell-shaped bulk ...specimens were prepared using an epoxy adhesive. A semi-circular artificial crack was introduced in the center of the specimen to conduct the fatigue tests. As a result, it was found that defects smaller than a certain size did not reduce the strength. Using the defect inspection and fatigue test results, a method was proposed to guarantee the strength of the adhesive joints. The test material was extremely sensitive to a crack; however, the linear cumulative damage rule did not hold. Furthermore, the creep life was considerably longer than the fatigue life due to the relaxation effect.
•Cracks in dumbbell-shaped bulk adhesive between 0.1mm and 0.2 mm do not affect the strength.•The creep life was considerably longer than the fatigue life due to the relaxation effect.•A reliability guarantee procedure could be suggested.
Surface contamination of an adherend has an influence on its adhesive bonding properties. To investigate this phenomenon, various contaminants, including silicone oil, mineral oil, a fluorine release ...agent, and surfactants, were quantitatively applied to an aluminium plate (6061) using a spray apparatus. The contaminated adherends were bonded with acrylic and epoxy adhesives, and their adhesion strengths were examined using single lap-shear tests. Mineral oil did not affect the adhesion strength, but silicone oil and surfactant agents were found to significantly affect the adhesion strength. Atomic force microscopy observations and Fourier transform infrared spectroscopy of these surfaces revealed a specific interaction between silicone oil and aluminium.
A convergent synthesis of the ABC ring of antitumor natural product paclitaxel (Taxol) is described. SmI2-mediated reductive cyclization of an allylic benzoate possessing an aldehyde function, ...synthesized from tri-O-acetyl-d-glucal and 1,3-cyclohexanedione, smoothly afforded the highly strained 6–8–6 tricarbocyclic structure in 66% yield.
Stress concentration in adhesively bonded joints, which is considered a major factor affecting their strength, can be avoided by tailoring the material properties of the adhesives using a ...functionally graded adhesive (FGA). The material properties of second-generation acrylic (SGA) adhesives can be simply changed by changing the mixing ratio of the agents. However, the superiority of FGA joints using SGA adhesives has not been experimentally clarified yet. Therefore, in this study, a shear strength test and a constant load low-cycle shear test were conducted on single lap joint (SLJ) specimens tailoring the adhesive layer stepwise. The FGA specimen was compared with the non-tailored specimens using stiff or flexible adhesives. The SLJ test results showed 16% improvement in the joint strength by stepwise tailoring of the adhesive layer. Additionally, the difference in the strain distributions among the different adhesive layers was investigated via a digital image correlation (DIC) method, and the shear strain at the edge of the FGA specimen was more than 40% decreased compared to the non-tailored specimen using the flexible adhesive. The low-cycle test results also showed the superiority of the FGA specimen to the other specimens. The FGA specimen held up more than 4 times the number of cycle of other specimens with an applied load of 18 kN or more. This was attributed to the suppressed plastic deformation at the edges of the adhesive layer owing to the introduction of FGAs.
To investigate the effect of deep learning on the diagnostic performance of radiologists and radiology residents in detecting breast cancers on computed tomography (CT).
In this retrospective study, ...patients undergoing contrast-enhanced chest CT between January 2010 and December 2020 using equipment from two vendors were included. Patients with confirmed breast cancer were categorised as the training (n=201) and validation (n=26) group and the testing group (n=30) using processed CT images from either vendor. The trained deep-learning model was applied to test group patients with (30 females; mean age = 59.2 ± 15.8 years) and without (19 males, 21 females; mean age = 64 ± 15.9 years) breast cancer. Image-based diagnostic performance of the deep-learning model was evaluated with the area under the receiver operating characteristic curve (AUC). Two radiologists and three radiology residents were asked to detect malignant lesions by recording a four-point diagnostic confidence score before and after referring to the result from the deep-learning model, and their diagnostic performance was evaluated using jackknife alternative free-response receiver operating characteristic analysis by calculating the figure of merit (FOM).
The AUCs of the trained deep-learning model on the validation and test data were 0.976 and 0.967, respectively. After referencing with the result of the deep learning model, the FOMs of readers significantly improved (reader 1/2/3/4/5: from 0.933/0.962/0.883/0.944/0.867 to 0.958/0.968/0.917/0.947/0.900; p=0.038).
Deep learning can help radiologists and radiology residents detect breast cancer on CT.
PDF
