Cutaneous T-cell lymphomas (CTCLs) are non-Hodgkin lymphomas caused by malignant T cells which migrate to the skin and lead to rash-like lesions which can be difficult to distinguish from inflammatory skin conditions like atopic dermatitis (AD) and psoriasis (PSO). To characterize CTCL in comparison to these differential diagnoses, we carried out multi-antigen imaging on 69 skin tissue samples (21 CTCL, 23 AD, 25 PSO). The resulting protein abundance maps were then analyzed via scoring functions to quantify the heterogeneity of the individual cells’ neighborhoods within spatial graphs inferred from the cells’ positions in the tissue samples. Our analyses reveal characteristic patterns of skin tissue organization in CTCL as compared to AD and PSO, including a combination of increased local entropy and egophily in T-cell neighborhoods. These results could not only pave the way for high-precision diagnosis of CTCL, but may also facilitate further insights into cellular disease mechanisms.

Emerging techniques in imaging-based spatial proteomics (ISP) enable in-depth insights into the architecture and protein abundance of tissue(s). Explainable machine learning (xML) models promise to yield substantial advances in ISP data-based diagnosis and prognosis. However, a clinical application of these new possibilities predicting the course of a tumor has not been suggested yet. Here, we use a few-shot learning workflow on histological multi-antigen images to predict 5-year progression-free survival (PFS) in melanoma. We address the problem of a relatively small cohort (n = 22), by utilizing a pre-trained convolutional neural network (CNN) model, which we further pre-train on a proxy task for which more samples were available (n = 39) before fine-tuning for PFS prediction. Our approach yielded a model achieving an accuracy of more than 90%, outperforming baseline models trained on clinical data by around 10%. Using an xML technique, we identified immune infiltration and proteins associated with tumor progression as crucial predictors. This indicated that our models' PFS predictions are not only highly accurate but also grounded in a relevant biological background. ### Competing Interest Statement D.B.B. consults for BioVariance GmbH. All other authors declare no competing interests.

A long-term objective of network medicine is to replace our current, mainly phenotype-based disease definitions by subtypes of health conditions corresponding to distinct pathomechanisms. For this, molecular and health data are modeled as networks and are mined for pathomechanisms. However, many such studies rely on large-scale disease association data where diseases are annotated using the very phenotype-based disease definitions the network medicine field aims to overcome. This raises the question to which extent the biases mechanistically inadequate disease annotations introduce in disease association data distort the results of studies which use such data for pathomechanism mining. We address this question using global- and local-scale analyses of networks constructed from disease association data of various types. Our results indicate that large-scale disease association data should be used with care for pathomechanism mining and that analyses of such data should be accompanied by close-up analyses of molecular data for well-characterized patient cohorts.

A method to create stratified structures with static mixing elements initially developed for the plastic polymer industry is investigated here as a new route for structuring food dispersions. Food dispersions of different viscosities were structured with static mixing elements to investigate the potential of the method for foods. Differently coloured chocolates were used as the model products. The viscosity of the chocolate was controlled through the addition of pea fibre. The first step was the formation of 2-8 layers, with the two differently coloured chocolates. Then, the chocolate dispersions were layered into 256 layers with an approximate layer thickness of 60 mu m. Layer formation was facilitated when using similar paste viscosity and when slip was induced through wall coating with vegetable oil. Uniaxial cutting tests of the layered chocolate indicated that layering resulted in different mechanical properties, parallel and perpendicular to the layers. Fibre orientation in the direction of flow was observed, resulting in the potential to induce anisotropy, additional to the layers. The higher viscous dispersions, wheat dough and melt cheese, could also be structured into layers, although the force constraints of the experimental set-up were reached. Mid-stream additions were added to produce strand structures instead of layers, resulting in higher hierarchy structures but less uniformity.

We report on the effect of processing, particularly heating, on the digestion dynamics of pea proteins using the standardised semi-dynamic in vitro digestion method. Fractions with native proteins were obtained by mild aqueous fractionation of pea flour. A commercial pea protein isolate was chosen as a benchmark. Heating dispersions of pea flour and mild protein fractions reduced the trypsin inhibitory activity to levels similar to that of the protein isolate. Protein-rich and non-soluble protein fractions were up to 18% better hydrolysed after being thermally denatured, particularly for proteins emptied later in the gastric phase. The degree of hydrolysis throughout the digestion was similar for these heated fractions and the conventional isolate. Further heating of the protein isolate reduced its digestibility as much as 9%. Protein solubility enhances the digestibility of native proteins, while heating aggregates the proteins, which ultimately reduces the achieved extent of hydrolysis from gastro-small intestinal enzymes.

Currently, food industries typically favour formulation of food products using highly refined techno-functional ingredients of high purity. However, there is a growing interest in less pure techno-functional ingredients with a lower degree of refining as they deliver the same functional properties with reduced environmental impact. We propose that instead of selecting formulations based on purity, they should be selected based on their techno-functional properties. This article illustrates that the shift in perspective may increase the sustainability of food production. The functionality-driven product formulation is explored through a case study in which yellow pea ingredients are selected to increase the viscosity of a salad dressing. The relation between the ingredients (in terms of composition; protein, starch fibre, and a residual fraction) and the final viscosity was quantified and validated using multiple linear regression. The model described the observations well: the final viscosity is mostly dominated by the starch content; protein content has only a marginal impact; and dietary fibre contributes to viscosity with an antagonistic effect with starch. Based on the multiple linear regression model and further formulation optimisation, we identified various combinations of ingredients (with either a high or low degree of refining) that would result in the target final viscosity. An evaluation of the global warming potential of all blends showed that the desired viscosity could be achieved using only isolates, as well as by using only mildly refined fractions. The latter is associated with a global warming potential that is 80% lower than the one based on isolates. This case study demonstrates the proof of concept for this approach, showing it can aid in identifying alternative product formulations with similar techno-functional properties but with a higher sustainability.

Techno-functional properties of multi-component blends and ingredients are determined by the contribution of each ingredient and the water distribution between those ingredients in the blends. However, ingredients can consist of multiple components, which should be considered to better understand the properties of ingredients and blends thereof. Recently, empirical models were used to describe the viscosity of mildly refined ingredient blends. While many compositions were described well by the empirical models, blends with high fiber contents were not predicted sufficiently well. Therefore, in this research, the multi-component blends of commercial pea protein, pea starch, and pea fiber isolates were investigated on their rheological properties as a function of dry matter content. The same properties were then measured for blends of two of these isolates mixed in different ratios. From the rheological experiments, estimations of the water distribution were made with the polymer blending law. The results were compared with CLSM images. A quantitative analysis of the CLSM images mostly confirmed the model outcomes. The isolate ratio could describe the isolate blends sufficiently well, meaning that it was not necessary to know the exact compositions of the ingredients. It was concluded that changes in meso-structure of the blends, for example a phase transition at high fiber contents, caused the lower predictability by the recently published empirical viscosity models. This study demonstrates that the water distribution in multi-component blends plays a crucial role for their viscoelastic properties and the contribution of the individual isolates and components. Moreover, these polymer blending laws that include water distribution provide extra mechanical insights into the fraction behavior in multi-component blends.

To meet the consumer demand for minimally processed foods and clean labels, the potential of processes where chemicals are omitted and only water is used needs to be explored. Mild wet fractionation of yellow pea, a water-only process, is investigated on maximum separation and efficient water use. By only using water, starch and protein from pea could be successfully separated, resulting in fractions high in yield and purity. Multiple washing steps of both the starch and the non-soluble protein fraction were performed to enhance separation. As a result of starch- and non-soluble protein pellet washing, the starch fraction was further depleted in protein and the protein solubility in the non-soluble protein fraction decreased. Ultrafiltration of the soluble protein fraction served to concentrate and the extracted water has potential to be reused in the process. Small solutes were concurrently extracted, which resulted in a higher protein purity in the soluble protein concentrate of 75%. The presented method has potential for upscale use in industry to produce protein fractions comparable to protein isolates obtained through conventional fractionation.

Mild wet fractionation can separate pea proteins into a soluble and a non-soluble fraction. Soluble proteins and solutes are extracted into the soluble protein fraction, insoluble proteins are collected in the non-soluble protein fraction. The protein composition in the respective fractions was investigated by further fractionating the protein fractions with isoelectric precipitation. The molecular mass of the proteins in the fractions was determined by SDS-PAGE and size exclusion chromatography. The protein fractions' solubility was determined in excess water, and the gelation properties were investigated at the same protein concentration. With mild wet fractionation, compared to conventional wet fractionation, both globulins and albumins are extracted. The protein fractions were mixtures of both proteins, although the non-soluble protein fraction contained mainly globulins. Solubility and gelation properties varied with protein type, composition and protein state; isoelectric precipitation decreased the gelation capacity of the protein fractions.

The relation between the structure of yellow pea and its optimal fractionation process was investigated using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). Different fractionations obtained by milling and various methods were investigated and compared to pea flour. Milling resulted in structure break-up and a distinction of particles in shape and size. Different particles were identified using the mapping of the elements (EDS), carbon, oxygen and nitrogen, indicating the presence of starch, protein and other carbohydrates, in the form of protein bodies, starch granules and cell wall fragments. It was further observed that not only protein bodies contained protein, but also particles that were presumed to be cell wall material contained protein, although in considerably lower concentrations. With both fractionation methods protein and starch could be partly separated, but wet fractionation resulted in a higher purity in both the soluble and nonsoluble protein fractions.

Making use of crops structural break-up during pearling and subsequent fractionation into starch or protein enriched fractions was investigated using stepwise pearling as a method. In first instance, pearling resulted in separation of pea testa and embryonic axis from the cotyledon. Further around 20% of the yellow pea cotyledon was pearled off and collected separately from the inner kernel. All four fractions were finely ground and their composition analysed. Due to the di-cotyledon structure of the pea, solely pearling the outer kernel couldn't be guaranteed. Therefore, the process was repeated by hand-dissection, to ensure only separation of the outer 20% cotyledon. Pearling resulted in size reduction and separation of testa, embryonic axis and the outer and inner part of the cotyledon. Although, no considerable enrichment was achieved in protein or starch content in the pearled fraction of the outer and inner cotyledon, pearling gave the opportunity to obtain the testa fraction, which according to literature is rich in dietary fibre. Moreover, the protein-rich embryonic axis was separated and collected. The testa fraction accounts for 7–8% of the whole pea and contains little protein and starch, which makes it a promising dietary fibre rich ingredient in food application.

Pluripotency can be induced in vitro from adult somatic mammalian cells by enforced expression of defined transcription factors regulating and initiating the pluripotency network. Despite the substantial advances over the last decade to improve the efficiency of direct reprogramming, exact mechanisms underlying the conversion into the pluripotent stem cell state are still vaguely understood. Several studies suggested that induced pluripotency follows reversed embryonic development. For somatic cells of mesodermal and endodermal origin that would require the transition through a Primitive streak-like state, which would necessarily require an Eomesodermin ( Eomes ) expressing intermediate. We analyzed reprogramming in human and mouse cells of mesodermal as well as ectodermal origin by thorough marker gene analyses in combination with genetic reporters, conditional loss of function and stable fate-labeling for the broad primitive streak marker Eomes . We unambiguously demonstrate that induced pluripotency is not dependent on a transient primitive streak-like stage and thus does not represent reversal of mesendodermal development in vivo .

Abrasive milling: A method to pre-fractionate testa and embryonic axis from yellow pea