Gouldmcclain2577

The regulatory (neuro)peptide galanin and its three receptors (GAL1-3R) are involved in immunity and inflammation. Galanin alleviated inflammatory bowel disease (IBD) in rats. However, studies on the galanin receptors involved are lacking. We aimed to determine galanin receptor expression in IBD patients and to evaluate if GAL2R and GAL3R contribute to murine colitis. Immunohistochemical analysis revealed that granulocytes in colon specimens of IBD patients (Crohn's disease and ulcerative colitis) expressed GAL2R and GAL3R but not GAL1R. After colitis induction with 2% dextran sulfate sodium (DSS) for 7 days, mice lacking GAL3R (GAL3R-KO) lost more body weight, exhibited more severe colonic inflammation and aggravated histologic damage, with increased infiltration of neutrophils compared to wild-type animals. Loss of GAL3R resulted in higher local and systemic inflammatory cytokine/chemokine levels. Remarkably, colitis-associated changes to the intestinal microbiota, as assessed by quantitative culture-independent techniques, were most pronounced in GAL3R-KO mice, characterized by elevated numbers of enterobacteria and bifidobacteria. In contrast, GAL2R deletion did not influence the course of colitis. In conclusion, granulocyte GAL2R and GAL3R expression is related to IBD activity in humans, and DSS-induced colitis in mice is strongly affected by GAL3R loss. Consequently, GAL3R poses a novel therapeutic target for IBD.This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of [Formula see text] ion flows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling [Formula see text] signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the [Formula see text] activated level and time slot of input signals [Formula see text] into the gate. read more This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the effectiveness of the reinforced learning platform, a [Formula see text] signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the [Formula see text] activated level and time slot of input signals [Formula see text] is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural-Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants.The usefulness of local collagenase in therapeutic approaches to solid tumors has been tested recently. In this study, we evaluate the safety and efficacy of intraperitoneal collagenase associated or not to mitomycin for treatment of colorectal peritoneal metastases in an experimental rat model. Using a fixed-dose procedure, we found that a dose of collagenase of 37 IU/mL administered for 15 min with a hyperthermia pump at 37.5 °C, both in isolation or associated to sequential treatment with intraperitoneal mitomycin, led to a macroscopic decrease in tumor volume as evaluated by the modified peritoneal cancer index (mPCI). Concerning the safety of the procedure, the animals showed no physiological or behavioral disorders during 8 weeks of follow-up. Local treatment for peritoneal metastases of colorectal origin with intraperitoneal collagenase has proved safe and effective in an experimental murine model. Therefore, the stroma-first approach by enzymatic breakdown of collagen from the tumor's extracellular matrix provides a new therapeutic target for colorectal peritoneal metastases.Bamboo-shaped multi-walled carbon nanotubes (BS-MWCNTs) have compartmented structures inherently obtained during their catalytic growth, and the curvature of the compartmented structure is known to be determined by the morphology of the metal catalysts. In this study, the inside curvature of the BS-MWCNTs was directly measured through scanning probe microscopy (SPM). The surface of the compartment structures of BS-MWCNTs has discontinuous graphene layers and different frictional force levels depending on the curvature direction. That of the inside curvature can be directly observed through tribological analysis by adding and subtracting the lateral force microscopy images obtained on opposite sides along the axial direction of the BS-MWCNT (diameter of 500 nm). This tells us the direction of the inside curvature of the BS-MWCNT, which was also confirmed by identifying the growth direction of the BS-MWCNTs via scanning electron microscopy. Our demonstration implies that SPM can give the same insight into the structural characterization of nanomaterials that is relatively inexpensive and more user-friendly than currently used methods.Cognitive abilities are impaired by sleep deprivation and can be recovered when sufficient sleep is obtained. Changes in alpha-band oscillations are considered to be closely related to sleep deprivation. In this study, power spectrum, source localization and functional connectivity analyses were used to investigate the changes in resting-state alpha-band activity after normal sleep, sleep deprivation and recovery sleep. The results showed that the global alpha power spectrum decreased and source activation was notably reduced in the precuneus, posterior cingulate cortex, cingulate gyrus, and paracentral lobule after sleep deprivation. Functional connectivity analysis after sleep deprivation showed a weakened functional connectivity pattern in a widespread network with the precuneus and posterior cingulate cortex as the key nodes. Furthermore, the changes caused by sleep deprivation were reversed to a certain extent but not significantly after one night of sleep recovery, which may be due to inadequate time for recovery sleep. In conclusion, large-scale resting-state alpha-band activation and functional connectivity were weakened after sleep deprivation, and the inhibition of default mode network function with the precuneus and posterior cingulate cortex as the pivotal nodes may be an important cause of cognitive impairment. These findings provide new insight into the physiological response to sleep deprivation and determine how sleep deprivation disrupts brain alpha-band oscillations.A precise determination of the cantilever spring constant is the critical point of all colloidal probe experiments. Existing methods are based on approximations considering only cantilever geometry and do not take into account properties of any object or substance attached to the cantilever. Neglecting the influence of the colloidal sphere on the cantilever characteristics introduces significant uncertainty in a spring constant determination and affects all further considerations. In this work we propose a new method of spring constant calibration for 'colloidal probe' type cantilevers based on the direct measurement of force constant. The Optical Tweezers based calibration method will help to increase the accuracy and repeatability of the AFM colloidal probe experiments.Scratching is one of the most important behaviours in experimental animals because it can reflect itching and/or psychological stress. Here, we aimed to establish a novel method to detect scratching using deep neural network. Scratching was elicited by injecting a chemical pruritogen lysophosphatidic acid to the back of a mouse, and behaviour was recorded using a standard handy camera. Images showing differences between two consecutive frames in each video were generated, and each frame was manually labelled as showing scratching behaviour or not. Next, a convolutional recurrent neural network (CRNN), composed of sequential convolution, recurrent, and fully connected blocks, was constructed. The CRNN was trained using the manually labelled images and then evaluated for accuracy using a first-look dataset. Sensitivity and positive predictive rates reached 81.6% and 87.9%, respectively. The predicted number and durations of scratching events correlated with those of the human observation. The trained CRNN could also successfully detect scratching in the hapten-induced atopic dermatitis mouse model (sensitivity, 94.8%; positive predictive rate, 82.1%). In conclusion, we established a novel scratching detection method using CRNN and showed that it can be used to study disease models.Many of the characteristics ascribed to cancer-associated fibroblasts (CAFs) are shared by activated, autophagic and senescent fibroblasts. Whilst most oral squamous cell carcinomas (OSCCs) are genetically unstable (GU-OSCC), genetically stable variants (GS-OSCC) have been described and, notably, CAF activation (myofibroblast differentiation) and senescence are characteristics particularly associated with GU-OSCCs. However, it is not known whether autophagy is disrupted in these cells or whether autophagy regulates the development of the myofibroblast and senescent phenotypes. In this study, we show that senescent CAFs from GU-OSCCs contained more autophagosomes than normal human oral fibroblasts (NHOFs) and CAFs from GS-OSCCs possibly due to autophagic impairment. Further, we show that deregulation of autophagy in normal fibroblasts, either by inhibition with autophagy inhibitor, SAR405, or activation with TGF-β1, induced fibroblast activation and senescence In response to TGF-β1, autophagy was induced prior to the development of the activated and senescent phenotypes. Lastly, we show that both SAR405- and TGF-β1-treated NHOFs enhance OSCC cell migration but only TGF-β1-treated cells increase OSCC invasion through Matrigel, indicating that TGF-β1 has additional effects that are independent of fibroblast activation/senescence. These results suggest a functional role for autophagy in the development of myofibroblast and CAF phenotypes.Collapsibility determination in loess area is expensive, and it also requires a large amount of experimentation. This paper aims to find the association rules between physical parameters and collapsibility of the loess in Xining through the method of data mining, so to help researchers predict the collapsibility of loess. Related physical parameters of loess collapsibility, collected from 1039 samples, involve 13 potential influence factors. According to Grey Relational Analysis, the key influence factors that lead to collapsing are identified from these potential influence factors. Subsequently, take the key influence factors, δs (coefficient of collapsibility) and δzs (coefficient of collapsibility under overburden pressure) as input items, and use the Apriori algorithm to find multiple association rules between them. Then, through analysing the results of association rules between these key influence factors and collapsibility, the evaluation criteria for collapsibility in this area is proposed, which can be used to simplify the workload of determining collapsibility. Finally, based on these research results, recommendations for projects construction were made to ensure the safety of construction in the area.