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We develop a quantitative single cell-based mathematical model for multi-cellular tumor spheroids (MCTS) of SK-MES-1 cells, a non-small cell lung cancer (NSCLC) cell line, growing under various nutrient conditions: we confront the simulations performed with this model with data on the growth kinetics and spatial labeling patterns for cell proliferation, extracellular matrix (ECM), cell distribution and cell death. We start with a simple model capturing part of the experimental observations. We then show, by performing a sensitivity analysis at each development stage of the model that its complexity needs to be stepwise increased to account for further experimental growth conditions. We thus ultimately arrive at a model that mimics the MCTS growth under multiple conditions to a great extent. Interestingly, the final model, is a minimal model capable of explaining all data simultaneously in the sense, that the number of mechanisms it contains is sufficient to explain the data and missing out any of its mechanisms did not permit fit between all data and the model within physiological parameter ranges. Nevertheless, compared to earlier models it is quite complex i.e., it includes a wide range of mechanisms discussed in biological literature. In this model, the cells lacking oxygen switch from aerobe to anaerobe glycolysis and produce lactate. Too high concentrations of lactate or too low concentrations of ATP promote cell death. Only if the extracellular matrix density overcomes a certain threshold, cells are able to enter the cell cycle. Dying cells produce a diffusive growth inhibitor. Missing out the spatial information would not permit to infer the mechanisms at work. Our findings suggest that this iterative data integration together with intermediate model sensitivity analysis at each model development stage, provide a promising strategy to infer predictive yet minimal (in the above sense) quantitative models of tumor growth, as prospectively of other tissue organization processes. Importantly, calibrating the model with two nutriment-rich growth conditions, the outcome for two nutriment-poor growth conditions could be predicted. As the final model is however quite complex, incorporating many mechanisms, space, time, and stochastic processes, parameter identification is a challenge. This calls for more efficient strategies of imaging and image analysis, as well as of parameter identification in stochastic agent-based simulations.

Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG. 28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings. Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001). Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90). Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile). Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52). ICU stay, mechanical and patient clinical complexity level score (PCCL) predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001). We suggest considering psychiatric diagnosis, admission as an emergency case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses.

This paper presents a cost-effective approach for automated surface quality measurement in reamed bores. The study involved drilling 4000 holes into 42CrMo S4V steel, of which 3600 underwent subsequent reaming. Utilizing a CNC-controlled gantry coupled with a mobile roughness measurement device through a compliant mechanism, surface data of every bore were efficiently gathered and processed. Additionally, analytical methods are presented that extend beyond standardized, aggregated metrics. We propose the evaluation of retraction grooves by using autocovariance. In addition, the correlation between the phase position of the waviness profile and the positional deviation of the bore is analyzed. The position deviation is also associated with bending moments that occur during reaming using a sensory tool holder. Furthermore, a 360-degree surface scan is presented to visually inspect the retraction groove. This approach aims to enhance understanding of the reaming process, ultimately improving bore quality, reducing component rejects, and extending tool lifespan.

We report on direct, real-space imaging of the stray magnetic field above a micro-scale disc of a thin film of the high-temperature superconductor YBa2Cu3O7−δ (YBCO) using scanning single spin magnetometry. Our experiments yield a direct measurement of the sample’s London penetration depth and allow for a quantitative reconstruction of the supercurrents flowing in the sample as a result of Meissner screening. These results show the potential of scanning single spin magnetometry for studies of the nanoscale magnetic properties of thin-film superconductors, which could be readily extended to elevated temperatures or magnetic fields.

Novel recycled fertilizers could help close environmental nutrient cycles in the circular economy. To better understand their performance and residual value, commercially available biobased nitrogen (N) and phosphorus (P) fertilizers (BBFs) were tested in a two-year crop cycle of winter wheat and ryegrass. The N fertilizer replacement value of N-BBFs ranged from 47 to 80% in the main crop. Not all BBFs led to a similarly high N concentration as the mineral reference in the wheat straw. However, full and early fertilization with incorporation could make the fertilizing effect of N-BBFs more reliable. The P fertilizer replacement value ranged between 105 and 161% for the crop cycle. We assume that the N contained in biobased phosphorus fertilizers can be seen as unproblematic for losses during winter and can serve as a starter fertilizer already present in the soil for the succeeding crop in spring. In general, biobased P fertilizers had a higher residual value than biobased N fertilizers. However, these residual values were comparable to those of mineral fertilizer references. While P-BBFs proved to be a sustainable and reliable nutrient source for a crop cycle, the N-BBFs used as the main crop fertilizer were found to be more prone to environmental influences.

Cardiovascular diseases (CVDs) account for a high fatality rate worldwide. Heart murmurs can be detected from phonocardiograms (PCGs) and may indicate CVDs. Still, they are often overlooked as their detection and correct clinical interpretation require expert skills. In this work, we aim to predict the presence of murmurs and clinical outcomes from multiple PCG recordings employing an explainable multitask model. Our approach consists of a two-stage multitask model. In the first stage, we predict the murmur presence in single PCGs using a multiple instance learning (MIL) framework. MIL also allows us to derive sample-wise classifications (i.e. murmur locations) while only needing one annotation per recording (\"weak label\") during training. In the second stage, we fuse explainable hand-crafted features with features from a pooling-based artificial neural network (PANN) derived from the MIL framework. Finally, we predict the presence of murmurs and the clinical outcome for a single patient based on multiple recordings using a simple feed-forward neural network. We show qualitatively and quantitatively that the MIL approach yields useful features and can be used to detect murmurs on multiple time instances and may thus guide a practitioner through PCGs. We analyze the second stage of the model in terms of murmur classification and clinical outcome. We achieved a weighted accuracy of 0.714 and an outcome cost of 13612 when using the PANN model and demographic features on the CirCor dataset (hidden test set of the George B. Moody PhysioNet challenge 2022, team \"Heart2Beat\", rank 12 / 40). To the best of our knowledge, we are the first to demonstrate the usefulness of MIL in PCG classification. Also, we showcase how the explainability of the model can be analyzed quantitatively, thus avoiding confirmation bias inherent to many post-hoc methods. Finally, our overall results demonstrate the merit of employing MIL combined with handcrafted features for the generation of explainable features as well as for a competitive classification performance.

Plants encode a unique group of papain-type cysteine endopeptidases (CysEP) characterized by a C-terminal KDEL endoplasmic reticulum retention signal (KDEL-CysEP) and an unusually broad substrate specificity. The three Arabidopsis KDEL-CysEPs (AtCEP1, AtCEP2, and AtCEP3) are differentially expressed in vegetative and generative tissues undergoing programmed cell death (PCD). While KDEL-CysEPs have been shown to be implicated in the collapse of tissues during PCD, roles of these peptidases in processes other than PCD are unknown. Using mCherry-AtCEP2 and EGFP-AtCEP1 reporter proteins in wild type versus atcep2 or atcep1 mutant plants, we explored the participation of AtCEP in young root development. Loss of AtCEP2, but not AtCEP1 resulted in shorter primary roots due to a decrease in cell length in the lateral root (LR) cap, and impairs extension of primary root epidermis cells such as trichoblasts in the elongation zone. AtCEP2 was localized to root cap corpses adherent to epidermal cells in the rapid elongation zone. AtCEP1 and AtCEP2 are expressed in root epidermis cells that are separated for LR emergence. Loss of AtCEP1 or AtCEP2 caused delayed emergence of LR primordia. KDEL-CysEPs might be involved in developmental tissue remodeling by supporting cell wall elongation and cell separation.

Micro forming can be used for a highly efficient manufacturing of small parts like screws or caps. Because of the small dimensions of the structures, high stresses and forming forces occur, especially in the case of micro bulk forming. In addition, the influence of friction is significantly higher compared to macro forming processes. A typical example of small structures are micro channels. An approach for the reduction of the necessary forming force to obtain lower loads on the tool consists in a vibration-assisted micro forming process. As vibration source, a piezo power module is placed directly in the force axis of the forming press. For the investigations, micro channels with a depth of more than 300 μm and a width of 300 μm are formed into 1.5 mm thick AlMg4.5Mn0.7 aluminium alloy sheets. The focus of the research lies in the influence of the process parameters like frequency and oscillation amplitude onto the material flow and the achieved channel depths. To investigate a possible influence on the friction conditions due to the vibration assistance, different lubrication conditions are applied. First results show a channel depth increase of 12 % compared to samples formed without vibration assistance.

Virulence in the ubiquitous intracellular protozoon Toxoplasma gondii for its natural intermediate host, the mouse, appears paradoxical from an evolutionary standpoint because death of the mouse before encystment interrupts the parasite life cycle. Virulent T. gondii strains secrete kinases and pseudokinases that inactivate the immunity-related GTPases (IRG proteins) responsible for mouse resistance to avirulent strains. Such considerations stimulated a search for IRG alleles unknown in laboratory mice that might confer resistance to virulent strains of T. gondii. We report that the mouse IRG system shows extraordinary polymorphic complexity in the wild. We describe an IRG haplotype from a wild-derived mouse strain that confers resistance against virulent parasites by interference with the virulent kinase complex. In such hosts virulent strains can encyst, hinting at an explanation for the evolution of virulence polymorphism in T. gondii. The parasite Toxoplasma gondii is one of the most common parasites worldwide and is known for its unusual life cycle. It reproduces sexually inside its primary host—the cat—and produces eggs that are released in faeces. Other animals, most often rodents, can then become infected when they unknowingly eat the eggs while foraging. Once inside its new host, the parasite reproduces asexually until the rodent’s immune system begins to fight back. It then becomes semi-dormant and forms cysts within the brain and muscle cells of its host. In an added twist, the parasite also causes rodents to lose their fear of cats. This increases their chances of being caught and eaten, thereby helping the parasite to return to its primary host and complete its life cycle. Previous work has shown that virulent strains of T. gondii can evade the host immune system in mice by secreting enzymes that inactivate immune-related proteins called IRG proteins. This prevents the infection being cleared and leads to death of the host within a few days. The existence of these virulent strains is intriguing because parasites that kill their host, and thus prevent their own reproduction, should be eliminated from the population. The fact that they are fairly common suggests that there must be a hitherto unknown mechanism that allows rodents to survive these virulent strains. Lilue et al. now report the existence of such a mechanism in strains of mice found in the wild. In contrast to laboratory mice, wild mice produce IRG proteins that inhibit the enzymes secreted by the virulent strains of T. gondii. Moreover, the IRG genes in wild mice are highly variable, whereas laboratory mice all have virtually identical IRG genes. By uncovering the complexity and variability of IRG genes in wild mice—complexity that has been lost from laboratory strains—Lilue et al. solve the conundrum of how highly virulent T. gondii strains can persist in the mouse population, and offer an explanation for the evolution of parasitic strains with differing levels of virulence.

Root-root interactions are much more sophisticated than previously thought, yet the mechanisms of belowground neighbor perception remain largely obscure. Genome-wide transcriptome analyses allow detailed insight into plant reactions to environmental cues. A root interaction trial was set up to explore both morphological and whole genome transcriptional responses in roots of Arabidopsis thaliana in the presence or absence of an inferior competitor, Hieracium pilosella. Neighbor perception was indicated by Arabidopsis roots predominantly growing away from the neighbor (segregation), while solitary plants placed more roots toward the middle of the pot. Total biomass remained unaffected. Database comparisons in transcriptome analysis revealed considerable similarity between Arabidopsis root reactions to neighbors and reactions to pathogens. Detailed analyses of the functional category \"biotic stress\" using MapMan tools found the sub-category \"pathogenesis-related proteins\" highly significantly induced. A comparison to a study on intraspecific competition brought forward a core of genes consistently involved in reactions to neighbor roots. We conclude that beyond resource depletion roots perceive neighboring roots or their associated microorganisms by a relatively uniform mechanism that involves the strong induction of pathogenesis-related proteins. In an ecological context the findings reveal that belowground neighbor detection may occur independently of resource depletion, allowing for a time advantage for the root to prepare for potential interactions.