Quick sections of neurophysiological activity enable personal distinction

G protein-coupled receptors (GPCRs) constitute the largest class of membrane proteins that transduce signals across the plasma membrane and orchestrate a multitude of physiological processes within cells. The serotonin1A receptor is a crucial neurotransmitter receptor in the GPCR family involved in a multitude of neurological, behavioral and cognitive functions. We have previously shown, using a combination of experimental and simulation approaches, that membrane cholesterol acts as a key regulator of organization, dynamics, signaling and endocytosis of the serotonin1A receptor. In addition, we showed that membrane cholesterol stabilizes the serotonin1A receptor against thermal deactivation. In the present work, we explored the molecular basis of cholesterol-induced thermal stability of the serotonin1A receptor. For this, we explored the possible role of the K101 residue in a cholesterol recognition/interaction amino acid consensus (CRAC) motif in transmembrane helix 2 in conferring the thermal stability of the serotonin1A receptor. Our results show that a mutation in the K101 residue leads to loss in thermal stability of the serotonin1A receptor imparted by cholesterol, independent of membrane cholesterol content. We envision that our results could have potential implications in structural biological advancements of GPCRs and design of thermally stabilized receptors for drug development.Aquaporins constitute a family of transmembrane proteins that function to transport water and other small solutes across the cell membrane. selleck kinase inhibitor Aquaporins family members are found in diverse life forms. Aquaporins share the common structural fold consisting of six transmembrane alpha helices with a central water-transporting channel. Four such monomers assemble together to form tetramers as their biological unit. Initially, aquaporins were discovered as water-transporting channels, but several studies supported their involvement in mediating the facilitated diffusion of different solutes. The so-called water channel is able to transport a variety of substrates ranging from a neutral molecule to a charged molecule or a small molecule to a bulky molecule or even a gas molecule. This article gives an overview of a diverse range of substrates conducted by aquaporin family members. Prime focus is on human aquaporins where aquaporins show a wide tissue distribution and substrate specificity leading to various physiological functions. This review also highlights the structural mechanisms leading to the transport of water and glycerol. More research is needed to understand how one common fold enables the aquaporins to transport an array of solutes.
To develop diagnostic radiomic model-based algorithm for pancreatic ductal adenocarcinoma (PDAC) grade prediction.
Ninety-one patients with histologically confirmed PDAC and preoperative CT were divided into subgroups based on tumor grade. Two histology-blinded radiologists independently segmented lesions for quantitative texture analysis in all contrast enhancement phases. The ratio of densities of PDAC and unchanged pancreatic tissue, and relative tumor enhancement (RTE) in arterial, portal venous, and delayed phases of the examination were calculated. Principal component analysis was used for multivariate predictor analysis. The selection of predictors in the binary logistic model was carried out in 2 stages (1) using one-factor logistic models (selection criterion was p < 0.1); (2) using regularization (LASSO regression after standardization of variables). Predictors were included in proportional odds models without interactions.
There were significant differences in 4, 16, and 8 texture featurestic accuracy using CT texture analysis presented in this study.
• A diagnostic algorithm based on CT texture features for preoperative PDAC grade prediction was developed. • The assumption that the scanning protocol can influence the results of texture analysis was confirmed and assessed. • Our results show that tumor differentiation grade can be assessed with sufficient diagnostic accuracy using CT texture analysis presented in this study.
Photon-counting detector computed tomography (PCD-CT) is a promising new technique for CT imaging. The aim of the present study was the in vitro comparison of coil-related artifacts in PCD-CT and conventional energy-integrating detector CT (EID-CT) using a comparable standard brain imaging protocol before and after metal artifact reduction (MAR).
A nidus-shaped rubber latex, resembling an aneurysm of the cerebral arteries, was filled with neurovascular platinum coils and inserted into a brain imaging phantom. Image acquisition and reconstruction were repeatedly performed for PCD-CT and EID-CT (n = 10, respectively) using a standard brain imaging protocol. Moreover, linear interpolation MAR was performed for PCD-CT and EID-CT images. The degree of artifacts was analyzed quantitatively (standard deviation in a donut-shaped region of interest) and qualitatively (5-point scale analysis).
Quantitative and qualitative analysis demonstrated a lower degree of metal artifacts in the EID-CT images compared to thetro study.
• Photon-counting detector CT produces more artifacts compared to energy-integrating detector CT without metal artifact reduction in cerebral in vitro imaging after neurovascular coil-embolization. • Spectral information of PCD-CT provides the potential for new post-processing techniques, since the coil-related artifacts were lower in PCD-CT images compared to EID-CT images after linear interpolation metal artifact reduction in this in vitro study.
To explore radiologists' opinions regarding the shift from in-person oncologic multidisciplinary team meetings (MDTMs) to online MDTMs. To assess the perceived impact of online MDTMs, and to evaluate clinical and technical aspects of online meetings.
An online questionnaire including 24 questions was e-mailed to all European Society of Oncologic Imaging (ESOI) members. Questions targeted the structure and efficacy of online MDTMs, including benefits and limitations.
A total of 204 radiologists responded to the survey. Responses were evaluated using descriptive statistical analysis. The majority (157/204; 77%) reported a shift to online MDTMs at the start of the pandemic. For the most part, this transition had a positive effect on maintaining and improving attendance. The majority of participants reported that online MDTMs provide the same clinical standard as in-person meetings, and that interdisciplinary discussion and review of imaging data were not hindered. Seventy three of 204 (35.8%) participants ovide the same clinical standard as in-person meetings. • Most would favour the return to in-person MDTMs but would also accept the continued use of online MDTMs following the end of the current pandemic.
• Majority of surveyed radiologists reported shift from in-person to online oncologic MDT meetings during the COVID-19 pandemic. • The shift to online MDTMs was feasible and generally accepted by the radiologists surveyed with the majority reporting that online MDTMs provide the same clinical standard as in-person meetings. • Most would favour the return to in-person MDTMs but would also accept the continued use of online MDTMs following the end of the current pandemic.
Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC.
Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1-10, 11-100, 101-400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers).
Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strong computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis.
• Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)-based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis.
To compare the delineation of mandibular cancer by 3D T1 turbo field echo with compressed SENSE (CS-3D-T1TFE) images and MDCT images, and to compare both sets of images with histopathological findings, as the gold standard, to validate the accuracy and clinical usefulness of CS-3D-T1TFE reconstruction.
Twenty-four patients with mandibular squamous cell carcinoma (SCC) who underwent MRI including CS-3D-T1TFE and MDCT examinations before surgery were retrospectively included. For both examinations, 0.5-mm-thick coronal plane images and 0.5-mm-thick plane images perpendicular and parallel to the dentition were constructed. Two radiologists rated bone invasion in three categories indexed by cortical bone, cancellous bone, and mandibular canal (MC), and inter-rater agreement was assessed by weighted kappa statistics. In 20 of the 24 patients who underwent surgery, the correlation of bone invasion with the histopathological evaluation by pathologists was assessed using Pearson's correlation coefficient. Soft-tiroblem of overestimation of the tumor extent, which has been associated with MRI in the past.
• Reconstructed CS-3D-T1TFE images were useful for the diagnosis of mandibular cancer. • CS-3D-T1TFE images showed higher inter-rater agreement than MDCT and high correlation with pathological findings. • CS-3D-T1TFE images may solve the problem of overestimation of the tumor extent, which has been associated with MRI in the past.
Increasing evidence suggests a role for epicardial fat in the development of coronary artery disease in the general population. Heart transplantation patients are at increased risk of developing a specific form of coronary artery disease, cardiac allograft vasculopathy (CAV), which has far-reaching consequences in terms of morbidity and mortality. Until now, the role of epicardial fat volume (EFV) in the development of CAV remains unknown. Hence, we investigated the relationship between EFV and CAV as well as the influence of donor/recipient sex on EFV.
Adult heart transplant patients who underwent coronary computed tomography angiography (CCTA) for CAV screening who were four or more years post-HT were included. Using the CT examinations, we quantified the EFV and the degree of CAV. Ordinal and linear regression models were used to assess the association of EFV with CAV.
In total, 149 (median age 44.5 years, 36% women) patients were included. The median time between HT and the CT scan was 11.0 (7.3-16.