Exposure to air pollution as an environmental determinant of how Sjögren's disease is expressed at diagnosis.

OBJECTIVES: To analyse how the potential exposure to air pollutants can influence the key components at the time of diagnosis of Sjögren's phenotype (epidemiological profile, sicca symptoms, and systemic disease). METHODS: For the present study, the following variables were selected for harmonization and refinement: age, sex, country, fulfilment of 2002/2016 criteria items, dry eyes, dry mouth, and overall ESSDAI score. Air pollution indexes per country were defined according to the OECD (1990-2021), including emission data of nitrogen and sulphur oxides (NO/SO), particulate matter (PM2.5 and 1.0), carbon monoxide (CO) and volatile organic compounds (VOC) calculated per unit of GDP, Kg per 1000 USD. RESULTS: The results of the chi-square tests of independence for each air pollutant with the frequency of dry eyes at diagnosis showed that, except for one, all variables exhibited p-values <0.0001. The most pronounced disparities emerged in the dry eye prevalence among individuals inhabiting countries with the highest NO/SO exposure, a surge of 4.61 percentage points compared to other countries, followed by CO (3.59 points), non-methane (3.32 points), PM2.5 (3.30 points), and PM1.0 (1.60 points) exposures. Concerning dry mouth, individuals residing in countries with worse NO/SO exposures exhibited a heightened frequency of dry mouth by 2.05 percentage points (p<0.0001), followed by non-methane exposure (1.21 percentage points increase, p=0.007). Individuals inhabiting countries with the worst NO/SO, CO, and PM2.5 pollution levels had a higher mean global ESSDAI score than those in lower-risk nations (all p-values <0.0001). When systemic disease was stratified according to DAS into low, moderate, and high systemic activity levels, a heightened proportion of individuals manifesting moderate/severe systemic activity was observed in countries with worse exposures to NO/SO, CO, and PM2.5 pollutant levels. CONCLUSIONS: For the first time, we suggest that pollution levels could influence how SjD appears at diagnosis in a large international cohort of patients. The most notable relationships were found between symptoms (dryness and general body symptoms) and NO/SO, CO, and PM2.5 levels.

Widespread effects of dMRI data quality on diffusion measures in children.

Diffusion magnetic resonance imaging (dMRI) datasets are susceptible to several confounding factors related to data quality, which is especially true in studies involving young children. With the recent trend of large-scale multicenter studies, it is more critical to be aware of the varied impacts of data quality on measures of interest. Here, we investigated data quality and its effect on different diffusion measures using a multicenter dataset. dMRI data were obtained from 691 participants (5-17 years of age) from six different centers. Six data quality metrics-contrast to noise ratio, outlier slices, and motion (absolute, relative, translation, and rotational)-and four diffusion measures-fractional anisotropy, mean diffusivity, tract density, and length-were computed for each of 36 major fiber tracts for all participants. The results indicated that four out of six data quality metrics (all except absolute and translation motion) differed significantly between centers. Associations between these data quality metrics and the diffusion measures differed significantly across the tracts and centers. Moreover, these effects remained significant after applying recently proposed harmonization algorithms that purport to remove unwanted between-site variation in diffusion data. These results demonstrate the widespread impact of dMRI data quality on diffusion measures. These tracts and measures have been routinely associated with individual differences as well as group-wide differences between neurotypical populations and individuals with neurological or developmental disorders. Accordingly, for analyses of individual differences or group effects (particularly in multisite dataset), we encourage the inclusion of data quality metrics in dMRI analysis.

Selecting the Most Relevant Brain Regions to Classify Children with Developmental Dyslexia and Typical Readers by Using Complex Magnocellular Stimuli and Multiple Kernel Learning.

Increasing evidence supports the presence of deficits in the visual magnocellular (M) system in developmental dyslexia (DD). The M system is related to the fronto-parietal attentional network. Previous neuroimaging studies have revealed reduced/absent activation within the visual M pathway in DD, but they have failed to characterize the extensive brain network activated by M stimuli. We performed a multivariate pattern analysis on a Region of Interest (ROI) level to differentiate between children with DD and age-matched typical readers (TRs) by combining full-field sinusoidal gratings, controlled for spatial and temporal frequencies and luminance contrast, and a coherent motion (CM) sensitivity task at 6%-CML6, 15%-CML15 and 40%-CML40. ROIs spanning the entire visual dorsal stream and ventral attention network (VAN) had higher discriminative weights and showed higher act1ivation in TRs than in children with DD. Of the two tasks, CM had the greatest weight when classifying TRs and children with DD in most of the ROIs spanning these streams. For the CML6, activation within the right superior parietal cortex positively correlated with reading skills. Our approach highlighted the dorsal stream and the VAN as highly discriminative areas between children with DD and TRs and allowed for a better characterization of the "dorsal stream vulnerability" underlying DD.

Barotrauma in mechanically ventilated patients with Coronavirus disease 2019: a survey of 38 hospitals in Lombardy, Italy.

BACKGROUND: The aim was to describe the incidence and risk factors of barotrauma in patients with the Coronavirus disease 2019 (COVID-19) on invasive mechanical ventilation, during the outbreak in our region (Lombardy, Italy). METHODS: The study was an electronic survey open from March 27th to May 2nd, 2020. Patients with COVID-19 who developed barotrauma while on invasive mechanical ventilation from 61 hospitals of the COVID-19 Lombardy Intensive Care Unit network were involved. RESULTS: The response rate was 38/61 (62%). The incidence of barotrauma was 145/2041 (7.1%; 95%-CI: 6.1-8.3%). Only a few cases occurred with ventilatory settings that may be considered non-protective such as a plateau airway pressure >35 cmH2O (2/113 [2%]), a driving airway pressure >15 cmH2O (30/113 [27%]), or a tidal volume >8 mL/kg of ideal body weight and a plateau airway pressure >30 cmH2O (12/134 [9%]). CONCLUSIONS: Within the limits of a survey, patients with COVID-19 might be at high risk for barotrauma during invasive (and allegedly lung-protective) mechanical ventilation.