FiPhA: an open-source platform for fiber photometry analysis.

Significance: Fiber photometry (FP) is a widely used technique in modern behavioral neuroscience, employing genetically encoded fluorescent sensors to monitor neural activity and neurotransmitter release in awake-behaving animals. However, analyzing photometry data can be both laborious and time-consuming. Aim: We propose the fiber photometry analysis (FiPhA) app, which is a general-purpose FP analysis application. The goal is to develop a pipeline suitable for a wide range of photometry approaches, including spectrally resolved, camera-based, and lock-in demodulation. Approach: FiPhA was developed using the R Shiny framework and offers interactive visualization, quality control, and batch processing functionalities in a user-friendly interface. Results: This application simplifies and streamlines the analysis process, thereby reducing labor and time requirements. It offers interactive visualizations, event-triggered average processing, powerful tools for filtering behavioral events, and quality control features. Conclusions: FiPhA is a valuable tool for behavioral neuroscientists working with discrete, event-based FP data. It addresses the challenges associated with analyzing and investigating such data, offering a robust and user-friendly solution without the complexity of having to hand-design custom analysis pipelines. This application thus helps standardize an approach to FP analysis.

FiPhA: An Open-Source Platform for Fiber Photometry Analysis.

Significance: Fiber photometry is a widely used technique in modern behavioral neuroscience, employing genetically encoded fluorescent sensors to monitor neural activity and neurotransmitter release in awake-behaving animals, However, analyzing photometry data can be both laborious and time-consuming. Aim: We propose the FiPhA (Fiber Photometry Analysis) app, which is a general-purpose fiber photometry analysis application. The goal is to develop a pipeline suitable for a wide range of photometry approaches, including spectrally resolved, camera-based, and lock-in demodulation. Approach: FiPhA was developed using the R Shiny framework and offers interactive visualization, quality control, and batch processing functionalities in a user-friendly interface. Results: This application simplifies and streamlines the analysis process, thereby reducing labor and time requirements. It offers interactive visualizations, event-triggered average processing, powerful tools for filtering behavioral events and quality control features. Conclusions: FiPhA is a valuable tool for behavioral neuroscientists working with discrete, event-based fiber photometry data. It addresses the challenges associated with analyzing and investigating such data, offering a robust and user-friendly solution without the complexity of having to hand-design custom analysis pipelines. This application thus helps standardize an approach to fiber photometry analysis.

Nicotine exposure decreases likelihood of SARS-CoV-2 RNA expression and neuropathology in the hACE2 mouse brain but not moribundity.

Individuals infected by SARS-CoV-2 are at risk of developing neurological-related post-acute disorders. Disputed epidemiological data indicated nicotine may reduce the severity of infection. Here we find exposure to nicotine in drinking water does not alter the moribundity of hACE2 mice. However, pre-exposure to nicotine decreased the likelihood of SARS-CoV-2 RNA expression and pathology in the brain. These results suggest mechanisms involving targets of nicotine could be leveraged to prevent the neurovirulence of SARS-CoV-2.

Nicotine exposure decreases likelihood of SARS-CoV-2 RNA expression and neuropathology in the hACE2 mouse brain but not moribundity.

Individuals infected by SARS-CoV-2 are at risk of developing neurological-related post-acute disorders. Disputed epidemiological data indicated nicotine may reduce the severity of infection. Here we find exposure to nicotine in drinking water does not alter the moribundity of hACE2 mice. However, pre-exposure to nicotine decreased the likelihood of SARS-CoV-2 RNA expression and pathology in the brain. These results suggest mechanisms involving targets of nicotine could be leveraged to prevent the neurovirulence of SARS-CoV-2.

Validation of Questionnaire-based Case Definitions for Chronic Obstructive Pulmonary Disease.

BACKGROUND: Various questionnaire-based definitions of chronic obstructive pulmonary disease (COPD) have been applied using the US representative National Health and Nutrition Examination Survey (NHANES), but few have been validated against objective lung function data. We validated two prior definitions that incorporated self-reported physician diagnosis, respiratory symptoms, and/or smoking. We also validated a new definition that we developed empirically using gradient boosting, an ensemble machine learning method. METHODS: Data came from 7,996 individuals 40-79 years who participated in NHANES 2007-2012 and underwent spirometry. We considered participants "true" COPD cases if their ratio of postbronchodilator forced expiratory volume in 1 second to forced vital capacity was below 0.7 or the lower limit of normal. We stratified all analyses by smoking history. We developed a gradient boosting model for smokers only; predictors assessed (25 total) included sociodemographics, inhalant exposures, clinical variables, and respiratory symptoms. RESULTS: The spirometry-based COPD prevalence was 26% for smokers and 8% for never smokers. Among smokers, using questionnaire-based definitions resulted in a COPD prevalence ranging from 11% to 16%, sensitivity ranging from 18% to 35%, and specificity ranging from 88% to 92%. The new definition classified participants based on age, bronchodilator use, body mass index (BMI), smoking pack-years, and occupational organic dust exposure, and resulted in the highest sensitivity (35%) and specificity (92%) among smokers. Among never smokers, the COPD prevalence ranged from 4% to 5%, and we attained good specificity (96%) at the expense of sensitivity (9-10%). CONCLUSION: Our results can be used to parametrize misclassification assumptions for quantitative bias analysis when pulmonary function data are unavailable.

Editor's Highlight: Comparative Toxicity of Organophosphate Flame Retardants and Polybrominated Diphenyl Ethers to Caenorhabditis elegans.

With the phasing-out of the polybrominated diphenyl ether (PBDE) flame retardants due to concerns regarding their potential developmental toxicity, the use of replacement compounds such as organophosphate flame retardants (OPFRs) has increased. Limited toxicity data are currently available to estimate the potential adverse health effects of the OPFRs. The toxicological effects of 4 brominated flame retardants, including 3 PBDEs and 3,3',5,5'-tetrabromobisphenol A, were compared with 6 aromatic OPFRs and 2 aliphatic OPFRs. The effects of these chemicals were determined using 3 biological endpoints in the nematode Caenorhabditis elegans (feeding, larval development, and reproduction). Because C. elegans development was previously reported to be sensitive to mitochondrial function, results were compared with those from an in vitro mitochondrial membrane permeabilization (MMP) assay. Overall 11 of the 12 flame retardants were active in 1 or more C. elegans biological endpoints, with only tris(2-chloroethyl) phosphate inactive across all endpoints including the in vitro MMP assay. For 2 of the C. elegans endpoints, at least 1 OPFR had similar toxicity to the PBDEs: triphenyl phosphate (TPHP) inhibited larval development at levels comparable to the 3 PBDEs; whereas TPHP and isopropylated phenol phosphate (IPP) affected C. elegans reproduction at levels similar to the PBDE commercial mixture, DE-71. The PBDEs reduced C. elegans feeding at lower concentrations than any OPFR. In addition, 9 of the 11 chemicals that inhibited C. elegans larval development also caused significant mitochondrial toxicity. These results suggest that some of the replacement aromatic OPFRs may have levels of toxicity comparable to PBDEs.