Dynamics of ColicinE2 production and release determine the competitive success of a toxin-producing bacterial population

The release of toxins is one mechanism used by bacterial species to establish dominance over competitors, but how the dynamics of toxin expression determine the competitive success of a toxin-producing population is largely unknown. Here, we investigate how the expression dynamics of ColicinE2 - a toxic bacteriocin - affect competition between toxin-producing and toxin-sensitive strains of Escherichia coli. We demonstrate that, in addition to genetic modifications in the toxin expression system, alterations of the growth medium can be used to modulate the timing of toxin production and the amount of toxin released. Thus cells that release the toxin at later times can accumulate more colicin. In experiments, we found that delaying toxin release does not significantly alter competition outcome. However, our theoretical analysis allowed us to assess the relative contributions of release time and toxin level to the competitive success of the producer strain, that might counteract each other in experiments. The results reveal that the importance of delaying toxin release lies in increasing the toxin amount. This is a more effective strategy for the toxin-producing strain than prompt discharge of the colicin. In summary, our study shows how the toxin release dynamics influence the competitive success of the toxin-producing bacterial population

Predictive Factors Associated with Declining Psycho-Oncological Support in Patients with Cancer

(1) Background: International cancer treatment guidelines recommend low-threshold psycho-oncological support based on nurses’ routine distress screening (e.g., via the distress thermometer and problem list). This study aims to explore factors which are associated with declining psycho-oncological support in order to increase nurses’ efficiency in screening patients for psycho-oncological support needs. (2) Methods: Using machine learning, routinely recorded clinical data from 4064 patients was analyzed for predictors of patients declining psycho-oncological support. Cross validation and nested resampling were used to guard against model overfitting. (3) Results: The developed model detects patients who decline psycho-oncological support with a sensitivity of 89% (area under the cure of 79%, accuracy of 68.5%). Overall, older patients, patients with a lower score on the distress thermometer, fewer comorbidities, few physical problems, and those who do not feel sad, afraid, or worried refused psycho-oncological support. (4) Conclusions: Thus, current screening procedures seem worthy to be part of daily nursing routines in oncology, but nurses may need more time and training to rule out misconceptions of patients on psycho-oncological support

Metabolomic Abnormalities in Serum from Untreated and Treated Dogs with Hyper- and Hypoadrenocorticism

The adrenal glands play a major role in metabolic processes, and both excess and insufficient serum cortisol concentrations can lead to serious metabolic consequences. Hyper- and hypoadrenocorticism represent a diagnostic and therapeutic challenge. Serum samples from dogs with untreated hyperadrenocorticism (n = 27), hyperadrenocorticism undergoing treatment (n = 28), as well as with untreated (n = 35) and treated hypoadrenocorticism (n = 23) were analyzed and compared to apparently healthy dogs (n = 40). A validated targeted proton nuclear magnetic resonance (H-1 NMR) platform was used to quantify 123 parameters. Principal component analysis separated the untreated endocrinopathies. The serum samples of dogs with untreated endocrinopathies showed various metabolic abnormalities with often contrasting results particularly in serum concentrations of fatty acids, and high- and low-density lipoproteins and their constituents, which were predominantly increased in hyperadrenocorticism and decreased in hypoadrenocorticism, while amino acid concentrations changed in various directions. Many observed serum metabolic abnormalities tended to normalize with medical treatment, but normalization was incomplete when compared to levels in apparently healthy dogs. Application of machine learning models based on the metabolomics data showed good classification, with misclassifications primarily observed in treated groups. Characterization of metabolic changes enhances our understanding of these endocrinopathies. Further assessment of the recognized incomplete reversal of metabolic alterations during medical treatment may improve disease management.Peer reviewe

Insights into mitochondrial dysfunction: aging, amyloid-β, and tau-A deleterious trio

Significance: Alzheimer's disease (AD) is an age-related progressive neurodegenerative disorder mainly affecting elderly individuals. The pathology of AD is characterized by amyloid plaques (aggregates of amyloid-β [Aβ]) and neurofibrillary tangles (aggregates of tau), but the mechanisms underlying this dysfunction are still partially unclear. Recent Advances: A growing body of evidence supports mitochondrial dysfunction as a prominent and early, chronic oxidative stress-associated event that contributes to synaptic abnormalities and, ultimately, selective neuronal degeneration in AD. Critical Issues: In this review, we discuss on the one hand whether mitochondrial decline observed in brain aging is a determinant event in the onset of AD and on the other hand the close interrelationship of this organelle with Aβ and tau in the pathogenic process underlying AD. Moreover, we summarize evidence from aging and Alzheimer models showing that the harmful trio "aging, Aβ, and tau protein" triggers mitochondrial dysfunction through a number of pathways, such as impairment of oxidative phosphorylation (OXPHOS), elevation of reactive oxygen species production, and interaction with mitochondrial proteins, contributing to the development and progression of the disease. Future Directions: The aging process may weaken the mitochondrial OXPHOS system in a more general way over many years providing a basis for the specific and destructive effects of Aβ and tau. Establishing strategies involving efforts to protect cells at the mitochondrial level by stabilizing or restoring mitochondrial function and energy homeostasis appears to be challenging, but very promising route on the horizon

A Computational Workflow for Interdisciplinary Deep Learning Projects utilizing bwHPC Infrastructure

Deep neural networks have the capability to solve complex tasks through accurate function approximation. The process from submitting domain data and defining process requirements to analyzed data consists of multiple steps, disallowing a simplistic straightforward procedure. It follows that one of the core questions is: how does an application development process facilitating interaction between data scientists and domain experts look like? Practically, two connected challenges need to be addressed. Firstly, it requires a solution for handling large amounts of domain-specific data. Secondly, when dealing with complex deep neural networks, it is essential to find a concept of how model training can be designed in an computationally efficient manner. While tailored solutions for addressing these challenges in interdisciplinary deep learning projects exist, a comprehensive and structured approach is missing. Hence, we present a computational workflow to enhance these kinds of projects concerning data handling, integration of cluster computing resources such as bwHPC infrastructure, and development processes. We exemplify our proposal by means of a biomedical image analysis project

Clinically Significant Distress and Physical Problems Detected on a Distress Thermometer are Associated With Survival Among Lung Cancer Patients

Objective: The distress thermometer (DT) is a well-established screening tool to detect clinically significant distress in cancer patients. It is often administered in combination with the problem list (PL), differentiating further between various (e.g., physical and emotional) sources of distress. The present study aimed to extend previous research on the association between distress and overall survival. Further exploratory analysis aimed to evaluate the predictive value of the PL for overall survival. Methods: Patients (n=323) with newly diagnosed lung cancer were recruited from a large cancer center. Patients were split into two groups, those with (DT score ≥5) and those without significant distress. Overall survival time was illustrated by a Kaplan Meier curve and compared with a log rank test. Univariable Cox proportional hazard models were built to control the association of distress with overall survival for age, gender, disease stage,comorbidity and their interaction terms. A multiple linear regression was used to investigate the association of the items from the problem list with survival time. Results: Patients with significant distress had a shorter survival time compared to patients without significant distress (25 vs. 43 months). Regression analysis revealed more problems with both "bathing and dressing" and "eating", as well as absence of "diarrhea" and increased "nervousness" to negatively impact overall survival time. Conclusion: Our results show that estimation of the survival function using cancer-related distress is possible. However, when using Cox regression, distress shows no significant value for survival as a predictor. Moreover, our study did not reveal an interaction effect between disease stage, comorbidity, and distress. Overall, results suggest that physical and emotional problems that arise from lung cancer may be useful to identify patients at risk for poor prognosis. Keywords: cancer-related distress; distress thermometer; lung-cancer; problem list; psycho-oncology; survival

Effects of stochasticity and division of labor in toxin production on two-strain bacterial competition in Escherichia coli

In phenotypically heterogeneous microbial populations, the decision to adopt one or another phenotype is often stochastically regulated. However, how this stochasticity affects interactions between competing microbes in mixed communities is difficult to assess. One example of such an interaction system is the competition of an Escherichia coli strain C, which performs division of labor between reproducers and self-sacrificing toxin producers, with a toxin-sensitive strain S. The decision between reproduction or toxin production within a single C cell is inherently stochastic. Here, combining experimental and theoretical approaches, we demonstrate that this stochasticity in the initial phase of colony formation is the crucial determinant for the competition outcome. In the initial phase (t < 12h), stochasticity influences the formation of viable C clusters at the colony edge. In the subsequent phase, the effective fitness differences (set primarily by the degree of division of labor in the C strain population) dictate the deterministic population dynamics and consequently competition outcome. In particular, we observe that competitive success of the C strain is only found if (i) a C edge cluster has formed at the end of the initial competition phase and (ii) the beneficial and detrimental effects of toxin production are balanced, which is the case at intermediate toxin producer fractions. Our findings highlight the importance of stochastic processes during the initial phase of colony formation, which might be highly relevant for other microbial community interactions in which the random choice between phenotypes can have long-lasting consequences for community fate

Staphylococcal Peptidoglycan Co-Localizes with Nod2 and TLR2 and Activates Innate Immune Response via Both Receptors in Primary Murine Keratinocytes

In mammalian host cells staphylococcal peptidoglycan (PGN) is recognized by Nod2. Whether PGN is also recognized by TLR2 is disputed. Here we carried out PGN co-localization and stimulation studies with TLR2 and Nod2 in wild type and mutant host cells. To exclude contamination with lipoproteins, polymeric staphylococcal PGN (PGNpol) was isolated from Staphylococcus aureus Δlgt (lacking lipidated prelipoproteins). PGNpol was biotinylated (PGN-Bio) for fluorescence monitoring with specific antibodies. Keratinocytes from murine oral epithelium (MK) readily internalized PGN-Bio in an endocytosis-like process. In wt MK, PGNpol induced intracellular accumulation of Nod2 and TLR2 and co-localized with Nod2 and TLR2, but not with TLR4. In TLR2-deficient MK Nod2 and in Nod2-deficient MK TLR2 was induced, indicating that PGNpol recognition by Nod2 is independent of TLR2 and vice versa. In both mutants IL-6 and IL-1B release was decreased by approximately 50% compared to wt MK, suggesting that the immune responses induced by Nod2 and TLR2 are comparable and that the two receptors act additively in MK. In TLR2-tranfected HEK293 cells PGNpol induced NFkB-promoter fused luciferase expression. To support the data, co-localization and signaling studies were carried out with SHL-PGN, a lipase protein covalently tethered to PGN-fragments of varying sizes at its C-terminus. SHL-PGN also co-localized with Nod2 or TLR2 and induced their accumulation, while SHL without PGN did not. The results show that staphylococcal PGN not only co-localizes with Nod2 but also with TLR2. PGN is able to stimulate the immune system via both receptors