MAGUKs, scaffolding proteins at cell junctions, are substrates of different proteases during apoptosis

A major feature of apoptotic cell death is gross structural changes, one of which is the loss of cell–cell contacts. The caspases, executioners of apoptosis, were shown to cleave several proteins involved in the formation of cell junctions. The membrane-associated guanylate kinases (MAGUKs), which are typically associated with cell junctions, have a major role in the organization of protein–protein complexes at plasma membranes and are therefore potentially important caspase targets during apoptosis. We report here that MAGUKs are cleaved and/or degraded by executioner caspases, granzyme B and several cysteine cathepsins in vitro. When apoptosis was induced by UV-irradiation and staurosporine in different epithelial cell lines, caspases were found to efficiently cleave MAGUKs in these cell models, as the cleavages could be prevented by a pan-caspase inhibitor N-benzyloxycarbonyl-Val-Ala-Asp(OMe)fluoromethylketone. Using a selective lysosomal disrupting agent -leucyl--leucine methyl ester, which induces apoptosis through the lysosomal pathway, it was further shown that MAGUKs are also cleaved by the cathepsins in HaCaT and CaCo-2 cells. Immunohistological data showed rapid loss of MAGUKs at the sites of cell–cell contacts, preceding actual cell detachment, suggesting that cleavage of MAGUKs is an important step in fast and efficient cell detachment

Caspase deficiency alters the murine gut microbiome

Caspases are aspartate-specific cysteine proteases that have an essential role in apoptosis and inflammation, and contribute to the maintenance of homeostasis in the intestine. These facts, together with the knowledge that caspases are implicated in host-microbe crosstalk, prompted us to investigate the effect of caspase (Casp)1, -3 and -7 deficiency on the composition of the murine gut microbiota. We observed significant changes in the abundance of the Firmicutes and Bacteroidetes phyla, in particular the Lachnospiraceae, Porphyromonodaceae and Prevotellacea families, when comparing Casp-1, -7 and -3 knockout mice with wild-type mice. Our data point toward an intricate relationship between these caspases and the composition of the murine gut microflora

Features of diagnostics of parameters of the ionosphere at use of pair radioimpulses

В статье анализируется возможность измерения автокоррелляционной функции тепловых флюктуаций электронной концентрации ионосферы в случае, когда излучают посылку из двух линейно-поляризованных радиоимпульсов одинаковой длительности и частоты, фронты которых разделены интервалом времени. Прием, обработка отраженных от ионосферы сигналов осуществляется на два линейно-поляризованные ортогональные антенны с последующим квадратурным, синхронным детектированием. Предъявлены требования к временному интервалу, разделяющему фронты излученных радиоимпульсов.У статті аналізується можливість виміру автокоррелляційної функції теплових флуктуацій електронної концентрації іоносфери у випадку, коли випромінюють посилку з двох лінійно-поляризованих радіоімпульсів однакової тривалості та частоти, фронти яких розділені інтервалом часу. Прийом, обробка відбитих від іоносфери сигналів здійснюється на дві лінійно-поляризовані ортогональні антени з подальшим квадратурним, синхронним детектуванням. Пред'явлені вимоги до часового інтервалу, що розділяє фронти випромінених радіоімпульсів.In the article possibility of measuring of avtokorrellyacion function of thermal flyktuation of electronic concentration of ionosphere is analyses in the case when radiate a parcel from two linear-polarized radioimpu's of identical duration and frequency, fronts of which part a time domain. A reception, treatment of the signals reflected from an ionosphere, is carried out on two linear-polarized orthogonal aerials with subsequent quartered, synchronous detection. Requirements are produced to the temporal interval, to dividing fronts of radiated radioimpuls

Artificial intelligence for dementia prevention.

INTRODUCTION: A wide range of modifiable risk factors for dementia have been identified. Considerable debate remains about these risk factors, possible interactions between them or with genetic risk, and causality, and how they can help in clinical trial recruitment and drug development. Artificial intelligence (AI) and machine learning (ML) may refine understanding. METHODS: ML approaches are being developed in dementia prevention. We discuss exemplar uses and evaluate the current applications and limitations in the dementia prevention field. RESULTS: Risk-profiling tools may help identify high-risk populations for clinical trials; however, their performance needs improvement. New risk-profiling and trial-recruitment tools underpinned by ML models may be effective in reducing costs and improving future trials. ML can inform drug-repurposing efforts and prioritization of disease-modifying therapeutics. DISCUSSION: ML is not yet widely used but has considerable potential to enhance precision in dementia prevention. HIGHLIGHTS: Artificial intelligence (AI) is not widely used in the dementia prevention field. Risk-profiling tools are not used in clinical practice. Causal insights are needed to understand risk factors over the lifespan. AI will help personalize risk-management tools for dementia prevention. AI could target specific patient groups that will benefit most for clinical trials

Correction: MCC950/CRID3 potently targets the NACHT domain of wild-type NLRP3 but not disease-associated mutants for inflammasome inhibition.

[This corrects the article DOI: 10.1371/journal.pbio.3000354.]