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Thus, ELF-EF suppresses the stress response that causes an increase in the GC level and slightly promotes GC production in the absence of stress. Moreover, the suppressive effect of ELF-EF on induced stress response might be involved in stress-induced tissue damage or inflammation in immobilised mice. Overall, the model and the data help explore the biological effect of ELF-EF and explain the stress-relieving effect of EF. They would be useful in determining the medical applications of EF in humans and animals.Sustained disturbances are relevant for environmental biotechnology as they can lead to alternative stable states in a system that may not be reversible. Here, we tested the effect of a sustained organic loading alteration (food-to-biomass ratio, FM, and carbon-to-nitrogen ratio, CN) on activated sludge bioreactors, focusing on the stability of nitrification and nitrifiers. Two sets of replicate 5-L sequencing batch reactors were operated at different, low and high, FM (0.19-0.36 mg COD/mg TSS/d) and CN (3.5-6.3 mg COD/mg TKN) conditions for a period of 74 days, following 53 days of sludge acclimation. Recovery and resilience were tested during the last 14 days by operating all reactors at low FM and CN (henceforth termed FM-CN). Stable nitrite accumulation (77%) was achieved through high FM-CN loading with a concurrent reduction in the abundance of Nitrospira. Subsequently, only two of the three reactors experiencing a switch back from high to low FM-CN recovered the nitrite oxidation function, with an increase in Nitrobacter as the predominant NOB, without a recovery of Nitrospira. The AOB community was more diverse, resistant and resilient than the NOB community. We showed that functional recovery and resilience can vary across replicate reactors, and that nitrification recovery need not coincide with a return to the initial nitrifying community structure.As a leading cause of death and morbidity, heart failure (HF) is responsible for a large portion of healthcare and disability costs worldwide. Current approaches to define specific HF subpopulations may fail to account for the diversity of etiologies, comorbidities, and factors driving disease progression, and therefore have limited value for clinical decision making and development of novel therapies. ZnC3 Here we present a novel and data-driven approach to understand and characterize the real-world manifestation of HF by clustering disease and symptom-related clinical concepts (complaints) captured from unstructured electronic health record clinical notes. We used natural language processing to construct vectorized representations of patient complaints followed by clustering to group HF patients by similarity of complaint vectors. We then identified complaints that were significantly enriched within each cluster using statistical testing. Breaking the HF population into groups of similar patients revealed a clinically interpretable hierarchy of subgroups characterized by similar HF manifestation. Importantly, our methodology revealed well-known etiologies, risk factors, and comorbid conditions of HF (including ischemic heart disease, aortic valve disease, atrial fibrillation, congenital heart disease, various cardiomyopathies, obesity, hypertension, diabetes, and chronic kidney disease) and yielded additional insights into the details of each HF subgroup's clinical manifestation of HF. Our approach is entirely hypothesis free and can therefore be readily applied for discovery of novel insights in alternative diseases or patient populations.Understanding the inner behaviour of multilayer perceptrons during and after training is a goal of paramount importance for many researchers worldwide. This article experimentally shows that relevant patterns emerge upon training, which are typically related to the underlying problem difficulty. The occurrence of these patterns is highlighted by means of [Formula see text] diagrams, a 2D graphical tool originally devised to support the work of researchers on classifier performance evaluation and on feature assessment. The underlying assumption being that multilayer perceptrons are powerful engines for feature encoding, hidden layers have been inspected as they were in fact hosting new input features. Interestingly, there are problems that appear difficult if dealt with using a single hidden layer, whereas they turn out to be easier upon the addition of further layers. The experimental findings reported in this article give further support to the standpoint according to which implementing neural architectures with multiple layers may help to boost their generalisation ability. A generic training strategy inspired by some relevant recommendations of deep learning has also been devised. A basic implementation of this strategy has been thoroughly used during the experiments aimed at identifying relevant patterns inside multilayer perceptrons. Further experiments performed in a comparative setting have shown that it could be adopted as viable alternative to the classical backpropagation algorithm.Stimulator of interferon genes (STING) controlled innate immune pathway is essential for host defense against pathogenic infection and effective anti-tumor adaptive immunity initiation. Although macrophages transformed across diverse phenotypes play crucial roles in anti-tumor immune response, events determining this transformation and the host-intrinsic role of STING in this process remain controversial. Here we report how STING signaling acts as a key switch to dominate the gene expression patterns of macrophage transformation for promoting priming and releasing immunosuppression. Furthermore, polyphyllin VII, a potential STING agonist, exerts anti-tumor efficacy upon macrophages priming and subsequent cytotoxic T lymphocytes intratumoral infiltration. Meanwhile, the simultaneous PD-L1 amplification on macrophages in response to PP VII is also ruled by STING, thus PP VII may benefit immune-checkpoint blockade therapy for combining. Moreover, PP VII suppresses carcinogenesis upon restraining the immunosuppressed macrophage transformation. This is due to the boosted STING that negatively regulates a STAT3 propagated crosstalk between immune cells and tumor cells. Overall, PP VII-stimulated STING in macrophages provides a paradigm for anti-tumor, and if possible, anti-infection immunotherapy.