High-resolution quantitative T mapping of the human brain at 7 T using a multi-echo spin-echo sequence and dictionary-based modeling.

Quantitative mapping offers a unique contrast for detailed brain imaging. At ultra-high field strengths (7 T), the higher signal-to-noise ratio (SNR) enables higher spatial resolution and the delineation of smaller structures. The translation of multi-echo spin-echo-based acquisitions to higher field strength, however, is complicated by inhomogeneities in the radio frequency (RF) transmit field resulting in stronger stimulated echoes and multi-echo refocusing pathways.

deepFPlearn +: enhancing toxicity prediction across the chemical universe using graph neural networks.

Summary: Sophisticated approaches for the in silico prediction of toxicity are required to support the risk assessment of chemicals. The number of chemicals on the global chemical market and the speed of chemical innovation stand in massive contrast to the capacity for regularizing chemical use. We recently proved our ready-to-use application deepFPlearn as a suitable approach for this task.

Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity.

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R and R, proton density PD, and magnetization transfer saturation MT) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g.

AI for predicting chemical-effect associations at the chemical universe level-deepFPlearn.

Many chemicals are present in our environment, and all living species are exposed to them. However, numerous chemicals pose risks, such as developing severe diseases, if they occur at the wrong time in the wrong place. For the majority of the chemicals, these risks are not known.

Transforming Growth Factor Beta 3-Loaded Decellularized Equine Tendon Matrix for Orthopedic Tissue Engineering.

Transforming growth factor beta 3 (TGFβ3) promotes tenogenic differentiation and may enhance tendon regeneration in vivo. This study aimed to apply TGFβ3 absorbed in decellularized equine superficial digital flexor tendon scaffolds, and to investigate the bioactivity of scaffold-associated TGFβ3 in an in vitro model. TGFβ3 could effectively be loaded onto tendon scaffolds so that at least 88% of the applied TGFβ3 were not detected in the rinsing fluid of the TGFβ3-loaded scaffolds.

Growth Factor-Mediated Tenogenic Induction of Multipotent Mesenchymal Stromal Cells Is Altered by the Microenvironment of Tendon Matrix.

Age-related degenerative changes in tendon tissue represent a common cause for acute tendon pathologies. Although the regenerative potential of multipotent mesenchymal stromal cells (MSC) was reported to restore functionality in injured tendon tissue, cellular mechanisms of action remain partly unclear. Potential tenogenic differentiation of applied MSC is affected by various intrinsic and extrinsic factors.

Tenogenic Properties of Mesenchymal Progenitor Cells Are Compromised in an Inflammatory Environment.

Transplantation of multipotent mesenchymal progenitor cells is a valuable option for treating tendon disease. Tenogenic differentiation leading to cell replacement and subsequent matrix modulation may contribute to the regenerative effects of these cells, but it is unclear whether this occurs in the inflammatory environment of acute tendon disease. Equine adipose-derived stromal cells (ASC) were cultured as monolayers or on decellularized tendon scaffolds in static or dynamic conditions, the latter represented by cyclic stretching.

Automated detection of the choroid boundary within OCT image data using quadratic measure filters.

A novel method for the automated detection of the outer choroid boundary within spectral-domain optical coherence tomography image data, based on an image model within the space of functions of bounded variation and the application of quadratic measure filters, is presented. The same method is used for the segmentation of retinal layer boundaries and proves to be suitable even for data generated without special imaging modes and moderate line averaging. Based on the segmentations, an automated determination of the central fovea region and choroidal thickness measurements for this and two adjacent 1-mm regions are provided.

Analysis of foveal characteristics and their asymmetries in the normal population.

The advance of optical coherence tomography (OCT) enables a detailed examination of the human retina in-vivo for clinical routine and experimental eye research. Only few investigations to date captured human foveal morphology in a large subject group on the basis of a detailed analysis employing mathematical models. However, even for important foveal characteristics unified terminology and clear definitions were not implemented so far.

Local Variability of Parameters for Characterization of the Corneal Subbasal Nerve Plexus.

Purpose: The corneal subbasal nerve plexus (SNP) offers high potential for early diagnosis of diabetic peripheral neuropathy. Changes in subbasal nerve fibers can be assessed in vivo by confocal laser scanning microscopy (CLSM) and quantified using specific parameters. While current study results agree regarding parameter tendency, there are considerable differences in terms of absolute values.

Parametric model for the 3D reconstruction of individual fovea shape from OCT data.

As revealed by optical coherence tomography (OCT), the shape of the fovea may vary greatly among individuals. However, none of the hitherto available mathematical descriptions comprehensively reproduces all individual characteristics such as foveal depth, slope, naso-temporal asymmetry, and others. Here, a novel mathematical approach is presented to obtain a very accurate model of the complete 3D foveal surface of an individual, by utilizing recent developments in OCT.

Nanostructured self-assembling peptides as a defined extracellular matrix for long-term functional maintenance of primary hepatocytes in a bioartificial liver modular device.

Much effort has been directed towards the optimization of the capture of in vivo hepatocytes from their microenvironment. Some methods of capture include an ex vivo cellular model in a bioreactor based liver module, a micropatterned module, a microfluidic 3D chip, coated plates, and other innovative approaches for the functional maintenance of primary hepatocytes. However, none of the above methods meet US Food and Drug Administration (FDA) guidelines, which recommend and encourage that the duration of a toxicity assay of a drug should be a minimum of 14 days, to a maximum of 90 days for a general toxicity assay.

Quantitative analysis of astrogliosis in drug-dependent humans.

Drug addiction is a chronic, relapsing disease caused by neurochemical and molecular changes in the brain. In this human autopsy study qualitative and quantitative changes of glial fibrillary acidic protein (GFAP)-positive astrocytes in the hippocampus of 26 lethally intoxicated drug addicts and 35 matched controls are described. The morphological characterization of these cells reflected alterations representative for astrogliosis.

Classifying prostate cancer malignancy by quantitative histomorphometry.

Purpose: Prostate cancer is routinely graded according to the Gleason grading scheme. This scheme is predominantly based on the textural appearance of aberrant glandular structures. Gleason grade is difficult to standardize and often leads to discussion due to interrater and intrarater disagreement.

Langmuir-Blodgett films of fluorinated glycolipids and polymerizable lipids and their phase separating behavior.

This paper describes the phase separating behavior of Langmuir monolayers from mixtures of different lipids that (i) either carry already a glycopeptide recognition site or can be easily modified to carry one and (ii) polymerizable lipids. To ensure demixing during compression, we used fluorinated lipids for the biological headgroups and hydrocarbon based lipids as polymerizable lipids. As a representative for a lipid monomer, which can be polymerized in the hydrophilic headgroup, a methacrylic monomer was used.

Image-processing chain for a three-dimensional reconstruction of basal cell carcinomas.

Basal cell carcinoma (BCC) is the most common malignant skin cancer. For a deeper insight into the specific growth patterns of the tumorous tissue in BCC, we have focused on the development of a novel automated image-processing chain for 3D reconstruction of BCC using histopathological serial sections. For fully automatic delineation of the tumor within the tissue, we apply a fuzzy c-means segmentation method.

Langmuir-Blodgett films of biocompatible poly(HPMA)-block-poly(lauryl methacrylate) and poly(HPMA)-random-poly(lauryl methacrylate): influence of polymer structure on membrane formation and stability.

Membranes based on functional biocompatible polymers can be regarded as a useful model system to study biological interactions, e.g. antibody-antigen interactions or protein polymer interactions.

Diagnosis of rheumatoid arthritis using light: correction of motion artefacts and color visualization of multispectral images.

State-of-the-art image-processing methods offer new possibilities for diagnosing diseases using scattered light. The optical diagnosis of rheumatism is taken as an example to show that the diagnostic sensitivity can be improved using overlapped pseudocolored images of different wavelengths, provided that multispectral images are recorded to compensate for any motion-related artefacts that occur during examination.