Berberine regulates endocrine function in mice with polycystic ovary syndrome through PI3K/Akt/GSK-3β insulin signaling pathway

Purpose: To study the influence of berberine on endocrine status in mice with polycystic ovary syndrome (PCOS), and the underlying mechanism of action. Methods: A total of 80 mice were used in this research. Sixteen mice were randomly selected to serve as control. The remaining 64 mice were subcutaneously given dehydroepiandrosterone (DHEA) injection to establish a mouse model of PCOS. The PCOS mice were randomly divided into model group, and low-dose-, medium-dose and high-dose berberine groups. Oral glucose tolerance test (OGTT) and expression levels of PI3K/Akt/GSK-3 signaling pathway related proteins (PI3K 85, Akt2, p-GSK-3 Tyr216, p-GSK-3β Ser9, and GSK-3) were evaluated. Results: At 60 and 120 min, OGTT blood glucose level of model group was significantly higher than that of blank control group, but it was significantly lower in the berberine dose groups than in model group (p < 0.05). There were significantly higher protein expression levels of pi3k85, AKT2 and p-GSK-3β tyr116 in berberine dose groups than in model mice, but the protein levels of p-GSK-3β ser9 in berberine dose groups were significantly lower than that in model mice. Conclusion: Berberine improved endocrine function in PCOS mice through a mechanism involving regulation of the key proteins of PI3K/Akt/GSK-3 β insulin signaling pathway. Thus, berberine may potentially play a similar role in humans with PCOS functions. However, clinical trials need to be carried out first

p-sylowizers and p-nilpotency of finite groups

In this paper, we investigate the structure of finite group G by assuming that the intersections between p-sylowizers of some p-subgroups of G and $O^p(G)$ are S-permutable in G. We obtain some criterions for p-nilpotency of a finite group

Efficient Structure Slimming for Spiking Neural Networks

Spiking neural networks (SNNs) are deeply inspired by biological neural information systems. Compared to convolutional neural networks (CNNs), SNNs are low power consumption because of their spike based information processing mechanism. However, most of the current structures of SNNs are fully-connected or converted from deep CNNs which poses redundancy connections. While the structure and topology in human brain systems are sparse and efficient. This paper aims at taking full advantage of sparse structure and low power consumption which lie in human brain and proposed efficient structure slimming methods. Inspired by the development of biological neural network structures, this paper designed types of structure slimming methods including neuron pruning and channel pruning. In addition to pruning, this paper also considers the growth and development of the nervous system. Through iterative application of the proposed neural pruning and rewiring algorithms, experimental evaluations on CIFAR-10, CIFAR-100, and DVS-Gesture datasets demonstrate the effectiveness of the structure slimming methods. When the parameter count is reduced to only about 10% of the original, the performance decreases by less than 1%

Composition of Turmeric Oil and Preparation, Characterization, Bioactivity and in Vitro Digestion of Its Microemulsion

The active components of turmeric oil (TO) were analyzed using gas chromatography-mass spectrometry (GC-MS), gas chromatography-ion mobility spectrometry (GC-IMS), and electronic nose. The major components of TO were found to be ar-curcumone (23.09%), curcumone (21.36%), and β-curcumone (14.93%). In order to maximize the stability of TO and to mask its irritating substances, a microemulsion encapsulating it (TO-ME) was constructed by the water titration method. Based on the pseudo ternary phase diagram constructed, the optimal process parameters were determined as follows: TO as the oil phase, Tween-80 as the surfactant, propylene glycol as the co-surfactant, deionized water as the aqueous phase, a mass ratio of surfactant to co-surfactant of 4:1, a mass ratio of mixed surfactant to oil phase of 8:2, and a water content of 70% in the microemulsion. The largest area of the microemulsion region was formed under these conditions. The resultant microemulsion had a pH of 6.81 ± 0.02, a density of (1.053 ± 0.001) g/mL, a polydispersity index (PDI) of 0.27 ± 0.11, and an average particle size of (32.81 ± 14.54) nm. The microemulsion was characterized as an oil-in-water (O/W) type microemulsion, with spherical or ellipsoidal droplets. The prepared TO-ME exhibited good centrifugal stability, storage stability, and resistance to oral and gastric digestion, and could be released and utilized in the intestine. The microemulsion system significantly improved the scavenging capacity of TO against 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) cation radical. In conclusion, microemulsion encapsulation significantly improved the stability and antioxidant activity of TO while effectively facilitating its release and digestion in the intestine. Our research results provide a theoretical basis for the high-value development and utilization of TO

Improving the Brain-Computer Interface Learning Process with Gamification in Motor Imagery: A Review

Brain-computer-interface-based motor imagery (MI-BCI), a control method for transferring the imagination of motor behavior to computer-based commands, could positively impact neural functions. With the safety guaranteed by non-invasive BCI devices, this method has the potential to enhance rehabilitation and physical outcomes. Therefore, this MI-BCI control strategy has been highly researched. However, applying a non-invasive MI-BCI to real life is still not ideal. One of the main reasons is the monotonous training procedure. Although researchers have reviewed optimized signal processing methods, no suggestion is found in training feedback design. The authors believe that enhancing the engagement interface via gamification presents a potential method that could increase the MI-BCI outcome. After analyzing 2524 articles (from 2001 to 2020), 28 pieces of research are finally used to evaluate the feasibility of using gamified MI-BCI system for training. This paper claims that gamification is feasible for MI-BCI training with an average accuracy of 74.35% among 111 individuals and positive reports from 26 out of 28 studies. Furthermore, this literature review suggests more emphasis should be on immersive and humanoid design for a gaming system, which could support relieving distraction, stimulate correct MI and improve learning outcomes. Interruptive training issues such as disturbing graphical interface design and potential solutions have also been presented for further research

The roles and mechanisms of gut microbiome and metabolome in patients with cerebral infarction

As the most common type of stroke, ischemic stroke, also known as cerebral infarction (CI), with its high mortality and disability rate, has placed a huge burden on social economy and public health. Treatment methods for CI mainly include thrombectomy, thrombolysis, drug therapy, and so on. However, these treatments have certain timeliness and different side effects. In recent years, the gut-brain axis has become a hot topic, and its role in nervous system diseases has been confirmed by increasing evidences. The intestinal microbiota, as an important part of the gut-brain axis, has a non-negligible impact on the progression of CI through mechanisms such as inflammatory response and damage-associated molecular patterns, and changes in the composition of intestinal microbiota can also serve as the basis for predicting CI. At the same time, the diagnosis of CI requires more high-throughput techniques, and the analysis method of metabolomics just fits this demand. This paper reviewed the changes of intestinal microbiota in patients within CI and the effects of the intestinal microbiota on the course of CI, and summarized the therapeutic methods of the intervention with the intestinal microbiota. Furthermore, metabolic changes of CI patients were also discussed to reveal the molecular characteristics of CI and to elucidate the potential pathologic pathway of its interference

Structural Performance of a Hybrid FRP-Aluminum Modular Triangular Truss System Subjected to Various Loading Conditions

A novel hybrid FRP-aluminum truss system has been employed in a two-rut modular bridge superstructure composed of twin inverted triangular trusses. The actual flexural behavior of a one-rut truss has been previously investigated under the on-axis loading test; however, the structural performance of the one-rut truss subjected to an off-axis load is still not fully understood. In this paper, a geometrical linear finite element model is introduced and validated by the on-axis loading test; the structural performance of the one-rut truss subjected to off-axis load was numerically obtained; the dissimilarities of the structural performance between the two different loading cases are investigated in detail. The results indicated that (1) the structural behavior of the off-axis load differs from that of the on-axis load, and the off-axis load is the critical loading condition controlling the structural performance of the triangular truss; (2) under the off-axis load, the FRP trussed members and connectors bear certain out-of-plane bending moments and are subjected to a complicated stress state; and (3) the stress state of these members does not match that of the initial design, and optimization for the redesign of these members is needed, especially for the pretightened teeth connectors

Experimental study on friction pressure drop and circumferential heat transfer characteristics in helical tubes

Helical tubes are widely used in nuclear plants, heat recovery process, and refrigeration technology. The fluid is influenced by centrifugal force flow through the helical tube, accompanied by secondary flow which is conducive to the enhancement of heat transfer. However, the uneven circumferential heat transfer caused by the secondary flow was seldom reported, while the pressure drops and heat transfer characteristics of helical tubes under single-phase and two-phase flow conditions need to be supplemented. This paper investigated the friction pressure drop and circumferential heat transfer characteristics based on the experiments on helical tubes with the coil diameter to the tube diameter varying from 28.5 to 128.5 and lift angle varying from 3° to 10°. The results showed that the coil diameter was the key parameter affecting the pressure drop and non-uniform circumferential heat transfer, compared with the lift angle. At the same cross section, the heat transfer coefficient at the outside tube wall was the highest, which was more obvious under small coil diameter conditions. Correlations of flow resistance and heat transfer were proposed for the single-phase and saturated boiling two-phase flow, respectively, and the predicted values were improved compared with the prediction results of correlations in the existing literature