RESUMO
The process of inference reflects the structure of propositions with assigned truth values, either true or false. Modus ponens is a fundamental form of inference that involves affirming the antecedent to affirm the consequent. Inspired by the quantum computer, the superposition of true and false is used for the parallel processing. In this work, we propose a quantum version of modus ponens. Additionally, we introduce two generations of quantum modus ponens: quantum modus ponens inference chain and multidimensional quantum modus ponens. Finally, a simple implementation of quantum modus ponens on the OriginQ quantum computing cloud platform is demonstrated.
RESUMO
Hyperthyroidism is becoming increasingly important as an independent risk factor for cardiovascular disease, eventually resulting in cardiac hypertrophy and heart failure. The 14-3-3 protein family subtypes regulate many cellular processes in eukaryotes by interacting with a diverse array of client proteins. Considering that the 14-3-3η protein protects cardiomyocytes by affecting mitochondrial function, exploring the biological influence and molecular mechanisms by which 14-3-3η alleviates the cardiac hypertrophy of hyperthyroidism is imperative. In vivo and in vitro, RT-PCR, Western blot, and Mitochondrial tracking assay were performed to understand the molecular mechanism of thyroxine-induced cardiomyocyte hypertrophy. HE staining, transmission electron microscopy, and immunofluorescence were used to observe intuitively changes of hearts and cardiomyocytes. The in vivo and in vitro results indicated that overexpression of the 14-3-3η ameliorated thyroxine-induced cardiomyocyte hypertrophy, whereas knockdown of the 14-3-3η protein aggravated thyroxine-induced cardiomyocyte hypertrophy. Additionally, overexpression of the 14-3-3η protein reduces thyroxine-induced mitochondrial damage and mitophagy in cardiomyocytes. Overexpression of 14-3-3η protein improves excessive mitophagy in the myocardium caused by thyroxine and thus prevents cardiac hypertrophy.
Assuntos
Proteínas 14-3-3 , Cardiomegalia , Mitofagia , Miócitos Cardíacos , Tiroxina , Animais , Masculino , Camundongos , Ratos , Proteínas 14-3-3/metabolismo , Proteínas 14-3-3/genética , Cardiomegalia/metabolismo , Cardiomegalia/patologia , Cardiomegalia/genética , Camundongos Endogâmicos C57BL , Mitocôndrias/metabolismo , Mitocôndrias/efeitos dos fármacos , Mitocôndrias/ultraestrutura , Mitofagia/efeitos dos fármacos , Miócitos Cardíacos/metabolismo , Miócitos Cardíacos/efeitos dos fármacos , Miócitos Cardíacos/patologia , Miócitos Cardíacos/ultraestrutura , Tiroxina/farmacologiaRESUMO
Cancer is characterized by uncontrolled cell proliferation, leading to cellular damage or death. Acute lymphoblastic leukemia (ALL), a kind of blood cancer, that affects lymphoid cells and is a challenging malignancy to treat. The Fermatean fuzzy set (FFS) theory is highly effective at capturing imprecision due to its capacity to incorporate extensive problem descriptions that are unclear and periodic. Within the framework of this study, two innovative aggregation operators: The Fermatean fuzzy Dynamic Weighted Averaging (FFDWA) operator and the Fermatean fuzzy Dynamic Weighted Geometric (FFDWG) operator are presented. The important attributes of these operators, providing a comprehensive elucidation of their significant special cases has been discussed in details. Moreover, these operators are utilized in the development of a systematic approach for addressing scenarios involving multiple attribute decision-making (MADM) problems with Fermatean fuzzy (FF) data. A numerical example concerning on finding the optimal treatment approach for ALL using the proposed operators, is provided. At the end, the validity and merits of the new method to illustrate by comparing it with the existing methods.