9 research outputs found

    Neuropathic Pain Phenotype Does Not Involve the NLRP3 Inflammasome and Its End Product Interleukin-1β in the Mice Spared Nerve Injury Model.

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    The NACHT, LRR and PYD domains-containing protein 3 (NLRP3) inflammasome is one of the main sources of interleukin-1β (IL-1β) and is involved in several inflammatory-related pathologies. To date, its relationship with pain has not been studied in depth. The aim of our study was to elucidate the role of NLRP3 inflammasome and IL-1β production on neuropathic pain. Results showed that basal pain sensitivity is unaltered in NLRP3-/- mice as well as responses to formalin test. Spared nerve injury (SNI) surgery induced the development of mechanical allodynia and thermal hyperalgesia in a similar way in both genotypes and did not modify mRNA levels of the NLRP3 inflammasome components in the spinal cord. Intrathecal lipopolysaccharide (LPS) injection increases apoptosis-associated speck like protein (ASC), caspase-1 and IL-1β expression in both wildtype and NLRP3-/- mice. Those data suggest that NLRP3 is not involved in neuropathic pain and also that other sources of IL-1β are implicated in neuroinflammatory responses induced by LPS

    STRengthening analytical thinking for observational studies: The STRATOS initiative

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    The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests.In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved
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