An in vitro model for osteoarthritis using long-cultured inflammatory human macrophages repeatedly stimulated with TLR agonists.

Osteoarthritis (OA) is characterized by an abundance of inflammatory M1-like macrophages damaging local tissues. The search for new potential drugs for OA suffers from the lack of appropriate methods of long-lasting inflammation. Here we developed and characterized an in vitro protocol of long-lasting culture of primary human monocyte-derived macrophages differentiated with a combination of M-CSF+GM-CSF that optimally supported long-cultured macrophages (LC-Mϕs) for up to 15 days, unlike their single use. Macrophages repeatedly stimulated for 15 days with the TLR2 ligand Pam3CSK4 (LCS-Mϕs), showed sustained levels over time of IL-6, CCL2, and CXCL8, inflammatory mediators that were also detected in the synovial fluids of OA patients. Furthermore, macrophages isolated from the synovia of two OA patients showed an expression profile of inflammation-related genes similar to that of LCS-Mϕs, validating our protocol as a model of chronically activated inflammatory macrophages. Next, to confirm that these LCS-Mϕs could be modulated by anti-inflammatory compounds, we employed dexamethasone and/or celecoxib, two drugs widely used in OA treatment, that significantly inhibited the production of inflammatory mediators. This easy-to-use in vitro protocol of long-lasting inflammation with primary human macrophages could be useful for the screening of new compounds to improve the therapy of inflammatory disorders.

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.