Mitochondrial sAC-cAMP-PKA Axis Modulates the ΔΨm-Dependent Control Coefficients of the Respiratory Chain Complexes: Evidence of Respirasome Plasticity.

The current view of the mitochondrial respiratory chain complexes I, III and IV foresees the occurrence of their assembly in supercomplexes, providing additional functional properties when compared with randomly colliding isolated complexes. According to the plasticity model, the two structural states of the respiratory chain may interconvert, influenced by the intracellular prevailing conditions. In previous studies, we suggested the mitochondrial membrane potential as a factor for controlling their dynamic balance. Here, we investigated if and how the cAMP/PKA-mediated signalling influences the aggregation state of the respiratory complexes. An analysis of the inhibitory titration profiles of the endogenous oxygen consumption rates in intact HepG2 cells with specific inhibitors of the respiratory complexes was performed to quantify, in the framework of the metabolic flux theory, the corresponding control coefficients. The attained results, pharmacologically inhibiting either PKA or sAC, indicated that the reversible phosphorylation of the respiratory chain complexes/supercomplexes influenced their assembly state in response to the membrane potential. This conclusion was supported by the scrutiny of the available structure of the CI/CIII2/CIV respirasome, enabling us to map several PKA-targeted serine residues exposed to the matrix side of the complexes I, III and IV at the contact interfaces of the three complexes.

A PCR-based method for the diagnosis of Enterobius vermicularis in stool samples, specifically designed for clinical application.

Background: Enterobius vermicularis (E. vermicularis) is a nematode that infects up to 200 million people worldwide, despite effective medications being available. Conventional diagnostic tests are hindered by low sensitivity and poor patient compliance. Furthermore, no biomolecular techniques are available for clinical application. The aim of this study was to develop a procedure specifically designed for clinical application to detect E. vermicularis by means of PCR. Materials and methods: Two subject groups were taken into account: a group of 27 infected patients and a control group of 27 healthy subjects. A nested-PCR was performed on fecal samples to detect E. vermicularis. Due to the intrinsic difficulties of the fecal matrix, several countermeasures were adopted to ensure the efficient performance of the method: (a) a large amount of feces for the extraction process (20 g instead of 200 mg); (b) a combination of chemical and physical treatments to grind the fecal matrix; (c) an additional purification process for the negative samples after the first nested-PCR; and (d) the selection of a very specific target region for the PCR. Results: Due to the lack of overlap with other organisms, a sequence of the 5S ribosomal DNA (rDNA) spacer region including the tract SL1 was chosen to design appropriate external and internal primers. The first nested-PCR detected E.vermicularis in 19/27 samples from infected patients. After further purification, 5/8 of the negative samples resulted positive at the second PCR. Conversely, all the samples from healthy controls resulted negative to both PCRs. Sensitivity and specificity of the method were, respectively, 88.9% and 100%. Conclusion: The results prove the high diagnostic accuracy of the proposed method, addressing and overcoming the challenges posed by both conventional tests and PCR-based approaches. Therefore, the method can be proposed for clinical application.

Structural equation modeling to shed light on the controversial role of climate on the spread of SARS-CoV-2.

Climate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation among COVID-19, population density, and climate, a theoretical path diagram was hypothesized and tested using structural equation modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of COVID-19 (p < 0.001 and p < 0.01, respectively). Overall, climate outweighs population density (path coefficients: climate vs. incidence = 0.18, climate vs. prevalence = 0.11, population density vs. incidence = 0.04, population density vs. prevalence = 0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of - 0.77, followed by temperature (- 0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p < 0.001. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect the transmission, and their influence may overcome the protective effect of climate, where favourable.