Structure, shape and dynamics of biological membranes.

Cells use membranes as their boundary, shielding their inside from the outside world, and to create internal structure. The different membranes in a cell have large variations in chemical composition, elasticity, shape and function. In contrast with the standard static picture often shown in cartoons, membranes are moreover one of the most dynamic components of the cell. Based on a detailed study of the structure and shape of various membranes we have developed techniques to measure the relevant physical parameters. Using these, we can directly couple the structure and shape to the function of the membrane. Combining these studies with studies of the membrane dynamics we find that membranes can spontaneously demix in different domains, which can interact with each other by forces mediated by the membrane itself. This interaction results in a sorting of the domains by size. Introducing an active element, molecular motors, into the system, we find that new structures are formed. An example of such a structure is a long membrane tube. These tubes also exhibit rich dynamics, and oscillating growth and shrink patters, which makes them suitable length and shape regulators in living cells.LEI Universiteit LeidenStichting voor Fundamenteel Onderzoek der Materie (FOM).Theoretical Physic

Lipid membrane-mediated attraction between curvature inducing objects

The interplay of membrane proteins is vital for many biological processes, such as cellular transport, cell division, and signal transduction between nerve cells. Theoretical considerations have led to the idea that the membrane itself mediates protein self-organization in these processes through minimization of membrane curvature energy. Here, we present a combined experimental and numerical study in which we quantify these interactions directly for the first time. In our experimental model system we control the deformation of a lipid membrane by adhering colloidal particles. Using confocal microscopy, we establish that these membrane deformations cause an attractive interaction force leading to reversible binding. The attraction extends over 2.5 times the particle diameter and has a strength of three times the thermal energy (−3.3 kBT). Coarse-grained Monte-Carlo simulations of the system are in excellent agreement with the experimental results and prove that the measured interaction is independent of length scale. Our combined experimental and numerical results reveal membrane curvature as a common physical origin for interactions between any membrane-deforming objects, from nanometre-sized proteins to micrometre-sized particles

Mechanics of epithelial tissue formation

A key process in the life of any multicellular organism is its development from a single egg into a full grown adult. The first step in this process often consists of forming a tissue layer out of randomly placed cells on the surface of the egg. We present a model for generating such a tissue, based on mechanical interactions between the cells, and find that the resulting cellular pattern corresponds to the Voronoi tessellation of the nuclei of the cells. Experimentally, we obtain the same result in both fruit flies and flour beetles, with a distribution of cell shapes that matches that of the model, without any adjustable parameters. Finally, we show that this pattern is broken when the cells grow at different rates.Animal science

Lipid membrane-mediated attraction between curvature inducing objects

Biological and Soft Matter Physic

A gastruloid model of the interaction between embryonic and extra-embryonic cell types

Biological and Soft Matter Physic

Both clinical trial register and electronic bibliographic database searches were needed to identify randomized clinical trials for systematic reviews: an evaluation study

OBJECTIVES: To determine whether clinical trial register (CTR) searches can accurately identify a greater number of completed randomized clinical trials (RCTs) than electronic bibliographic database (EBD) searches for systematic reviews of interventions, and to quantify the number of eligible ongoing trials. STUDY DESIGN AND SETTING: We performed an evaluation study and based our search for RCTs on the eligibility criteria of a systematic review that focused on the underrepresentation of people with chronic kidney disease in cardiovascular RCTs. We conducted a combined search of ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform through the Cochrane Central Register of Controlled Trials to identify eligible RCTs registered up to June 1, 2023. We searched Cochrane Central Register of Controlled Trials, EMBASE, and MEDLINE for publications of eligible RCTs published up to June 5, 2023. Finally, we compared the search results to determine the extent to which the two sources identified the same RCTs. RESULTS: We included 92 completed RCTs. Of these, 81 had results available. Sixty-six completed RCTs with available results were identified by both sources (81% agreement [95% CI: 71-88]). We identified seven completed RCTs with results exclusively by CTR search (9% [95% CI: 4-17]) and eight exclusively by EBD search (10% [95% CI: 5-18]). Eleven RCTs were completed but lacked results (four identified by both sources (36% [95% CI: 15-65]), one exclusively by EBD search (9% [95% CI: 1-38]), and six exclusively by CTR search (55% [95% CI: 28-79])). Also, we identified 42 eligible ongoing RCTs: 16 by both sources (38% [95% CI: 25-53]) and 26 exclusively by CTR search (62% [95% CI: 47-75]). Lastly, we identified four RCTs of unknown status by both sources. CONCLUSION: CTR searches identify a greater number of completed RCTs than EBD searches. Both searches missed some included RCTs. Based on our case study, researchers (eg, information specialists, systematic reviewers) aiming to identify all available RCTs should continue to search both sources. Once the barriers to performing CTR searches alone are targeted, CTR searches may be a suitable alternative

Oxidative stress and inflammation in a spectrum of epileptogenic cortical malformations: molecular insights into their interdependence

Oxidative stress (OS) occurs in brains of patients with epilepsy and coincides with brain inflammation, and both phenomena contribute to seizure generation in animal models. We investigated whether expression of OS and brain inflammation markers co-occurred also in resected brain tissue of patients with epileptogenic cortical malformations: hemimegalencephaly (HME), focal cortical dysplasia (FCD) and cortical tubers in tuberous sclerosis complex (TSC). Moreover, we studied molecular mechanisms linking OS and inflammation in an in vitro model of neuronal function. Untangling interdependency and underlying molecular mechanisms might pose new therapeutic strategies for treating patients with drug-resistant epilepsy of different etiologies. Immunohistochemistry was performed for specific OS markers xCT and iNOS and brain inflammation markers TLR4, COX-2 and NF-κB in cortical tissue derived from patients with HME, FCD IIa, IIb and TSC. Additionally, we studied gene expression of these markers using the human neuronal cell line SH-SY5Y in which OS was induced using H 2 O 2 . OS markers were higher in dysmorphic neurons and balloon/giant cells in cortex of patients with FCD IIb or TSC. Expression of OS markers was positively correlated to expression of brain inflammation markers. In vitro, 100 µM, but not 50 µM, of H 2 O 2 increased expression of TLR4, IL-1β and COX-2. We found that NF-κB signaling was activated only upon stimulation with 100 µM H 2 O 2 leading to upregulation of TLR4 signaling and IL-1β. The NF-κB inhibitor TPCA-1 completely reversed this effect. Our results show that OS positively correlates with neuroinflammation and is particularly evident in brain tissue of patients with FCD IIb and TSC. In vitro, NF-κB is involved in the switch to an inflammatory state after OS. We propose that the extent of OS can predict the neuroinflammatory state of the brain. Additionally, antioxidant treatments may prevent the switch to inflammation in neurons thus targeting multiple epileptogenic processes at once

Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks

Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection