Membrane dynamics shape TCR-generated signaling

Despite intensive investigation, the mechanisms of T cell receptor (TCR)-mediated signal generation remain poorly understood. Here we review various dynamic processes at the cell membrane that might critically control this signaling. Firstly, we summarize recent reports providing new information on the sensitivity of TCR/ligand interaction to the membrane environment and particularly to applied forces. Secondly, we review recent evidence that forces and displacements are continuously generated at cell surfaces. Thirdly, we summarize recent experimental evidence demonstrating the capacity of forces to generate signals. Lastly, we provide a quantitative model to exemplify the capacity of dynamic processes to modulate TCR properties such as specificity that were previously difficult to explain with conventional models. It is concluded that the described dynamic processes must be integrated into current models of TCR signaling

voxel2vec: A Natural Language Processing Approach to Learning Distributed Representations for Scientific Data

Relationships in scientific data, such as the numerical and spatial distribution relations of features in univariate data, the scalar-value combinations' relations in multivariate data, and the association of volumes in time-varying and ensemble data, are intricate and complex. This paper presents voxel2vec, a novel unsupervised representation learning model, which is used to learn distributed representations of scalar values/scalar-value combinations in a low-dimensional vector space. Its basic assumption is that if two scalar values/scalar-value combinations have similar contexts, they usually have high similarity in terms of features. By representing scalar values/scalar-value combinations as symbols, voxel2vec learns the similarity between them in the context of spatial distribution and then allows us to explore the overall association between volumes by transfer prediction. We demonstrate the usefulness and effectiveness of voxel2vec by comparing it with the isosurface similarity map of univariate data and applying the learned distributed representations to feature classification for multivariate data and to association analysis for time-varying and ensemble data.Comment: Accepted by IEEE Transaction on Visualization and Computer Graphics (TVCG

One-stitch anastomosis through the skin with bicanalicular intubation:a modified approach for repair of bicanalicular laceration

<b>AIM:</b> To evaluate the efficacy and safety of one-stitch anastomosis through the skin with bicanalicular silicone tube intubation in repairing of bicanalicular laceration.<b>METHODS:</b>The clinical data of 15 consecutive patients with both superior and inferior canalicular laceration in one eye who underwent surgical repair using one-stitch anastomosis through the skin and bicanalicular stent were retrospective studied. All the operations were performed under surgical microscope, 5-0 silk sutures were used and were with bicanalicular silicone tube (diameter was 8mm) intubation, for one lacerated canaliculi one-stitch anastomosis through the skin. The stents were left in place for 3 months postoperatively and then removed. The follow-up period was 3 - 36 months (average 14 months).<b>RESULTS:</b>In 15 patients, 13 patients were cured entirely, 1 patient was meliorated, 1 patient with no effects. All patients had got good recovery of eyelid laceration with no traumatic deformity in eyelid and canthus. Complication was seen in one case, for not followed the doctor’s guidance to come back to hospital to had the suture removed on the 7^th day after operation, when he came at the 15^th day, the inferior canalicular wall and eyelid skin were corroded by the suture caused 2mm wound, and the inside silicone tube was exposed, a promptly repair with 10-0 nylon suture was done, the wound healed in a week. There were no early tube protrusions and punctal slits in the patients.<b>CONCLUSION:</b>One-stitch anastomosis through the skin with bicanalicular silicone tube intubation is a good method in repair of bicanalicular laceration in one eye, the cut ends can be anastomosed directly, and with excellent cosmetic results, it is acceptable for the patients. For there is no suture remained in the wound permanently, so there is no suture-related granuloma which may cause obstruction or stenosis of canaliculi. It is simple, economical, effective and safe

Plasma Concentrations of Trace Elements Selenium and Cobalt During and After Coronary Artery Bypass Grafting Surgery

Trace elements selenium (Se) and cobalt (Co) are essential in the human body, and a correlation between Se and cardiac surgery has been suggested. We investigated the plasma concentrations of Se and Co during and after coronary artery bypass grafting (CABG) surgery under cardiopulmonary bypass (CPB). From December 2019 to January 2020, preoperative plasma samples from isolated first-time CABG patients (n=20; 10 males, 10 females) were prospectively collected post-anesthesia and before CPB (T1), 45 min after CPB started (T2), 90 min after CPB started (T3), and postoperative days 1 (T4), and day 4 (T5). The plasma concentrations of Se and Co were measured. The Se concentration was significantly decreased at T2 (105.24±4.08 vs. 68.56±2.42 μg/L, p<0.001) and T3 (105.24±4.08 vs. 80.41±3.40 μg/L, p<0.001). The Co concentration was significantly decreased at T4 (0.35±0.19 vs. 0.26±0.13 μg/L, p<0.01) and T5 (0.35±0.19 vs. 0.23±0.11 μg/L, p<0.001). Five patients developed atrial fibrillation (AF); there was no other operative mortality or major morbidity. This is the first report of alterations of plasma Se and Co concentrations during and after CABG surgery. Our results may indicate that Se supplementation before or during CABG and Co supplementation after CABG may become necessary for patients undergoing CABG

MSFormer: A Skeleton-multiview Fusion Method For Tooth Instance Segmentation

Recently, deep learning-based tooth segmentation methods have been limited by the expensive and time-consuming processes of data collection and labeling. Achieving high-precision segmentation with limited datasets is critical. A viable solution to this entails fine-tuning pre-trained multiview-based models, thereby enhancing performance with limited data. However, relying solely on two-dimensional (2D) images for three-dimensional (3D) tooth segmentation can produce suboptimal outcomes because of occlusion and deformation, i.e., incomplete and distorted shape perception. To improve this fine-tuning-based solution, this paper advocates 2D-3D joint perception. The fundamental challenge in employing 2D-3D joint perception with limited data is that the 3D-related inputs and modules must follow a lightweight policy instead of using huge 3D data and parameter-rich modules that require extensive training data. Following this lightweight policy, this paper selects skeletons as the 3D inputs and introduces MSFormer, a novel method for tooth segmentation. MSFormer incorporates two lightweight modules into existing multiview-based models: a 3D-skeleton perception module to extract 3D perception from skeletons and a skeleton-image contrastive learning module to obtain the 2D-3D joint perception by fusing both multiview and skeleton perceptions. The experimental results reveal that MSFormer paired with large pre-trained multiview models achieves state-of-the-art performance, requiring only 100 training meshes. Furthermore, the segmentation accuracy is improved by 2.4%-5.5% with the increasing volume of training data.Comment: Under revie

Ethyl 2-diethyl­amino-4-oxo-3,5-diphenyl-4,5-dihydro-3H-pyrrolo­[3,2-d]pyrimidine-7-carboxyl­ate

In the title compound, C25H26N4O3, the two fused pyrrolo­[3,2-d]pyrimidine rings form a dihedral angle of 3.7 (2)°. The two substituent phenyl rings are twisted with respect to the pyrrole and pyrimidine rings, making dihedral angles of 57.2 (2) and 69.0 (2)°, respectively. The ethyl and eth­oxy groups are disordered over two positions; the site occupancies are 0.53 (1) and 0.47 (1) for ethyl, and 0.63 (1) and 0.37 (1) for eth­oxy. The crystal packing features C—H⋯O hydrogen bonds