Quantitative measurements in 3-dimensional datasets of mouse lymph nodes resolve organ-wide functional dependencies

Deep tissue imaging has become state of the art in biology, but now the problem is to quantify spatial information in a global, organ-wide context. Although access to the raw data is no longer a limitation, the computational tools to extract biologically useful information out of these large data sets is still catching up. In many cases, to understand the mechanism behind a biological process, where molecules or cells interact with each other, it is mandatory to know their mutual positions. We illustrate this principle here with the immune system. Although the general functions of lymph nodes as immune sentinels are well described, many cellular and molecular details governing the interactions of lymphocytes and dendritic cells remain unclear to date and prevent an in-depth mechanistic understanding of the immune system. We imaged ex vivo lymph nodes isolated from both wild-type and transgenic mice lacking key factors for dendritic cell positioning and used software written in MATLAB to determine the spatial distances between the dendritic cells and the internal high endothelial vascular network. This allowed us to quantify the spatial localization of the dendritic cells in the lymph node, which is a critical parameter determining the effectiveness of an adaptive immune response.

Phyllotaxis — a new chapter in an old tale about beauty and magic numbers

Phyllotaxis, the regular arrangement of leaves and flowers around the stem, is one of the most fascinating patterning phenomena in biology. Numerous theoretical models, that are based on biochemical, biophysical and other principles, have been proposed to explain the development of the patterns. Recently, auxin has been identified as the inducer of organ formation. An emerging model for phyllotaxis states that polar auxin transport in the plant apex generates local peaks in auxin concentration that determine the site of organ formation and thereby the different phyllotactic patterns found in nature. The PIN proteins play a primary role in auxin transport. These proteins are localized in a polar fashion, reflecting the directionality of polar auxin transport. Recent evidence shows that most aspects of phyllotaxis can be explained by the expression pattern and the dynamic subcellular localization of PIN1.

Automated detection of the osseous acetabular rim using three-dimensional models of the pelvis

An automated algorithm for detection of the acetabular rim was developed. Accuracy of the algorithm was validated in a sawbone study and compared against manually conducted digitization attempts, which were established as the ground truth. The latter proved to be reliable and reproducible, demonstrated by almost perfect intra- and interobserver reliability. Validation of the automated algorithm showed no significant difference compared to the manually acquired data in terms of detected version and inclination. Automated detection of the acetabular rim contour and the spatial orientation of the acetabular opening plane can be accurately achieved with this algorithm.

Cartilage tissue engineering for degenerative joint disease

Pain in the joint is often due to cartilage degeneration and represents a serious medical problem affecting people of all ages. Although many, mostly surgical techniques, are currently employed to treat cartilage lesions, none has given satisfactory results in the long term. Recent advances in biology and material science have brought tissue engineering to the forefront of new cartilage repair techniques. The combination of autologous cells, specifically designed scaffolds, bioreactors, mechanical stimulations and growth factors together with the knowledge that underlies the principles of cell biology offers promising avenues for cartilage tissue regeneration. The present review explores basic biology mechanisms for cartilage reconstruction and summarizes the advances in the tissue engineering approaches. Furthermore, the limits of the new methods and their potential application in the osteoarthritic conditions are discussed.

Real-time observation of the charge-transfer-to-solvent dynamics

Intermolecular electron-transfer reactions have a crucial role in biology, solution chemistry and electrochemistry. The first step of such reactions is the expulsion of the electron to the solvent, whose mechanism is determined by the structure and dynamical response of the latter. Here we visualize the electron transfer to water using ultrafast fluorescence spectroscopy with polychromatic detection from the ultraviolet to the visible region, upon photo-excitation of the so-called charge transfer to solvent states of aqueous iodide. The initial emission is short lived (~60 fs) and it relaxes to a broad distribution of lower-energy charge transfer to solvent states upon rearrangement of the solvent cage. This distribution reflects the inhomogeneous character of the solvent cage around iodide. Electron ejection occurs from the relaxed charge transfer to solvent states with lifetimes of 100–400 fs that increase with decreasing emission energy.

Standardised animal models of host microbial mutualism.

An appreciation of the importance of interactions between microbes and multicellular organisms is currently driving research in biology and biomedicine. Many human diseases involve interactions between the host and the microbiota, so investigating the mechanisms involved is important for human health. Although microbial ecology measurements capture considerable diversity of the communities between individuals, this diversity is highly problematic for reproducible experimental animal models that seek to establish the mechanistic basis for interactions within the overall host-microbial superorganism. Conflicting experimental results may be explained away through unknown differences in the microbiota composition between vivaria or between the microenvironment of different isolated cages. In this position paper, we propose standardised criteria for stabilised and defined experimental animal microbiotas to generate reproducible models of human disease that are suitable for systematic experimentation and are reproducible across different institutions.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Towards tailored radiopeptide therapy.

PURPOSE Somatostatin receptor-targeted radiopeptide therapy is commonly performed using single radioisotopes. We evaluated the benefits and harms of combining radioisotopes in radiopeptide therapy in patients with neuroendocrine tumor. METHODS Using multivariable-adjusted survival analyses and competing risk analyses we evaluated outcomes in patients with neuroendocrine tumor receiving (90)Y-DOTATOC, (177)Lu-DOTATOC or their combination. RESULTS (90)Y-DOTATOC plus (177)Lu-DOTATOC treatment was associated with longer survival than (90)Y-DOTATOC (66.1 vs. 47.5 months; n = 1,358; p < 0.001) or (177)Lu-DOTATOC alone (66.1 vs. 45.5 months; n = 390; p < 0.001). (177)Lu-DOTATOC was associated with longer survival than (90)Y-DOTATOC in patients with solitary lesions (HR 0.3, range 0.1 - 0.7; n = 153; p = 0.005), extrahepatic metastases (HR 0.5, range 0.3 - 0.9; n = 256; p = 0.029) and metastases with low uptake (HR 0.1, range 0.05 - 0.4; n = 113; p = 0.001). (90)Y-DOTATOC induced higher hematotoxicity rates than combined treatment (9.5% vs. 4.0%, p = 0.005) or (177)Lu-DOTATOC (9.5 vs. 1.4%, p = 0.002). Renal toxicity was similar among the treatments. CONCLUSIONS Using (90)Y and (177)Lu might facilitate tailoring radiopeptide therapy and improve survival in patients with neuroendocrine tumors.

Morphomechanical Innovation Drives Explosive Seed Dispersal

How mechanical and biological processes are coordinated across cells, tissues, and organs to produce complex traits is a key question in biology. Cardamine hirsuta, a relative of Arabidopsis thaliana, uses an explosive mechanism to disperse its seeds. We show that this trait evolved through morphomechanical innovations at different spatial scales. At the organ scale, tension within the fruit wall generates the elastic energy required for explosion. This tension is produced by differential contraction of fruit wall tissues through an active mechanism involving turgor pressure, cell geometry, and wall properties of the epidermis. Explosive release of this tension is controlled at the cellular scale by asymmetric lignin deposition within endocarp b cells-a striking pattern that is strictly associated with explosive pod shatter across the Brassicaceae plant family. By bridging these different scales, we present an integrated mechanism for explosive seed dispersal that links evolutionary novelty with complex trait innovation.

Molecular subtype analysis determines the association of advanced breast cancer in Egypt with favorable biology

Background Prognostic markers and molecular breast cancer subtypes reflect underlying biological tumor behavior and are important for patient management. Compared to Western countries, women in North Africa are less likely to be prognosticated and treated based on well-characterized markers such as the estrogen receptor (ER), progesterone receptor (PR) and Her2. We conducted this study to determine the prevalence of breast cancer molecular subtypes in the North African country of Egypt as a measure of underlying biological characteristics driving tumor manifestations. Methods To determine molecular subtypes we characterized over 200 tumor specimens obtained from Egypt by performing ER, PR, Her2, CK5/6, EGFR and Ki67 immunohistochemistry. Results Our study demonstrated that the Luminal A subtype, associated with favorable prognosis, was found in nearly 45% of cases examined. However, the basal-like subtype, associated with poor prognosis, was found in 11% of cases. These findings are in sharp contrast to other parts of Africa in which the basal-like subtype is over-represented. Conclusions Egyptians appear to have favorable underlying biology, albeit having advanced disease at diagnosis. These data suggest that Egyptians would largely profit from early detection of their disease. Intervention at the public health level, including education on the benefits of early detection is necessary and would likely have tremendous impact on breast cancer outcome in Egypt.