Association between Air Pollution and Hemoptysis

Altres ajuts: The authors would like to thank the Service of Air Surveillance and Control (Servei de Vigilància i Control de l'Aire) of the Department of Environment of the Catalan Autonomous Government for the data provided.Background. The relationship between air pollution and exacerbation of respiratory diseases is well established. Nevertheless, its association with hemoptysis has been poorly investigated. This paper describes the relationship of air pollutants with severe hemoptysis. Methods. All consecutive subjects with severe hemoptysis during a 5-year period were included. The relationship between the contamination measurements and the frequency of embolizations was analyzed using Poisson regressions. In these regressions, the dependent variable was the monthly number of embolizations in a given month and the independent variable was either the concentration of an air contaminant during the same month, the concentration of the air contaminant during the previous month, or the difference between the two. Results. A higher total number of embolizations per month were observed over the months with increases in the concentration of NO. The number of embolizations was 2.0 in the 33 months with no increases in the concentration of NO, 2.1 in the 12 months with small increases, 2.2 in the 5 months with moderate increases, 2.5 in the 4 months with large increases, and 4.0 in the 5 months with very large increases. Conclusion. There is association between hemoptysis and increases in the concentration of atmospheric NO in Badalona (Spain)

Cortical gyrification morphology in individuals with ASD and ADHD across the lifespan: a systematic review and meta-analysis

Autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are common neurodevelopmental disorders (NDDs) that may impact brain maturation. A number of studies have examined cortical gyrification morphology in both NDDs. Here we review and when possible pool their results to better understand the shared and potentially disorder-specific gyrification features. We searched MEDLINE, PsycINFO, and EMBASE databases, and 24 and 10 studies met the criteria to be included in the systematic review and meta-analysis portions, respectively. Meta-analysis of local Gyrification Index (lGI) findings across ASD studies was conducted with SDM software adapted for surface-based morphometry studies. Meta-regressions were used to explore effects of age, sex, and sample size on gyrification differences. There were no significant differences in gyrification across groups. Qualitative synthesis of remaining ASD studies highlighted heterogeneity in findings. Large-scale ADHD studies reported no differences in gyrification between cases and controls suggesting that, similar to ASD, there is currently no evidence of differences in gyrification morphology compared with controls. Larger, longitudinal studies are needed to further clarify the effects of age, sex, and IQ on cortical gyrification in these NDDs.info:eu-repo/semantics/publishedVersio

Effectiveness of treatment with nebulized colistin in patients with COPD

To analyze whether the introduction of nebulized colistin in patients with chronic obstructive pulmonary disease (COPD) and infection with Pseudomonas aeruginosa (PA) is associated with a decrease of the number and duration of severe exacerbations. Thirty six patients with COPD and infection with PA treated with nebulized colistin attending a day hospital during a 5-year (January 2010-December 2014) period were prospectively included. Repeated-measures t -tests were used to assess whether the introduction of colistin was associated with changes in the number of exacerbations or the length of the hospitalizations, comparing for each patient the year prior to the introduction of colistin with the year after. After the introduction of colistin, the number of admissions decreased from 2.0 to 0.9 per individual year (P =0.0007), and hospitalizations were shorter (23.3 vs 10.9 days, P =0.00005). These results persisted when patients with and without bronchiectasis or with and without persistence of Pseudomonas were separately analyzed. No pre-post differences were detected in the number of exacerbations not requiring admission. Nebulized colistin seems associated with a strong decrease in the number and duration of hospitalizations due to exacerbation in patients with COPD and infection with PA. Clinical trials with a larger number of patients are needed in order to confirm these results

Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and spatial regularization

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on the methodology used to combine multichannel signals. Indeed, the two prevailing methods for multichannel signal combination lead to Rician and noncentral Chi noise distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in brain data

Neurocognitive Functioning in Individuals at Clinical High Risk for Psychosis

IMPORTANCE: Neurocognitive functioning is a potential biomarker to advance detection, prognosis, and preventive care for individuals at clinical high risk for psychosis (CHR-P). The current consistency and magnitude of neurocognitive functioning in individuals at CHR-P are undetermined. OBJECTIVE: To provide an updated synthesis of evidence on the consistency and magnitude of neurocognitive functioning in individuals at CHR-P. DATA SOURCES: Web of Science database, Cochrane Central Register of Reviews, and Ovid/PsycINFO and trial registries up to July 1, 2020. STUDY SELECTION: Multistep literature search compliant with Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology performed by independent researchers to identify original studies reporting on neurocognitive functioning in individuals at CHR-P. DATA EXTRACTION AND SYNTHESIS: Independent researchers extracted the data, clustering the neurocognitive tasks according to 7 Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) domains and 8 CHR-P domains. Random-effect model meta-analyses, assessment of publication biases and study quality, and meta-regressions were conducted. MAIN OUTCOMES AND MEASURES: The primary effect size measure was Hedges g of neurocognitive functioning in individuals at CHR-P (1) compared with healthy control (HC) individuals or (2) compared with individuals with first-episode psychosis (FEP) or (3) stratified for the longitudinal transition to psychosis. RESULTS: A total of 78 independent studies were included, consisting of 5162 individuals at CHR-P (mean [SD; range] age, 20.2 [3.3; 12.0-29.0] years; 2529 [49.0%] were female), 2865 HC individuals (mean [SD; range] age, 21.1 [3.6; 12.6-29.2] years; 1490 [52.0%] were female), and 486 individuals with FEP (mean [SD; range] age, 23.0 [2.0; 19.1-26.4] years; 267 [55.9%] were female). Compared with HC individuals, individuals at CHR-P showed medium to large deficits on the Stroop color word reading task (g = −1.17; 95% CI, −1.86 to −0.48), Hopkins Verbal Learning Test–Revised (g = −0.86; 95% CI, −1.43 to −0.28), digit symbol coding test (g = −0.74; 95% CI, −1.19 to −0.29), Brief Assessment of Cognition Scale Symbol Coding (g = −0.67; 95% CI, −0.95 to −0.39), University of Pennsylvania Smell Identification Test (g = −0.55; 95% CI, −0.97 to −0.12), Hinting Task (g = −0.53; 95% CI, −0.77 to −0.28), Rey Auditory Verbal Learning Test (g = −0.50; 95% CI, −0.78 to −0.21), California Verbal Learning Test (CVLT) (g = −0.50; 95% CI, −0.64 to −0.36), and National Adult Reading Test (g = −0.52; 95% CI, −1.01 to −0.03). Individuals at CHR-P were less impaired than individuals with FEP. Longitudinal transition to psychosis from a CHR-P state was associated with medium to large deficits in the CVLT task (g = −0.58; 95% CI, −1.12 to −0.05). Meta-regressions found significant effects for age and education on processing speed. CONCLUSIONS AND RELEVANCE: Findings from this meta-analysis support neurocognitive dysfunction as a potential detection and prognostic biomarker in individuals at CHR-P. These findings may advance clinical research and inform preventive approaches

Meta-analysis of cortical thickness abnormalities in medication-free patients with major depressive disorder

Alterations in cortical thickness have been identified in major depressive disorder (MDD), but findings have been variable and inconsistent. To date, no reliable tools have been available for the meta-analysis of surface-based morphometric (SBM) studies to effectively characterize what has been learned in previous studies, and drug treatments may have differentially impacted findings. We conducted a comprehensive meta-analysis of magnetic resonance imaging (MRI) studies that explored cortical thickness in medication-free patients with MDD, using a newly developed meta-analytic mask compatible with seed-based d mapping (SDM) meta-analytic software. We performed the meta-regression to explore the effects of demographics and clinical characteristics on variation in cortical thickness in MDD. Fifteen studies describing 529 patients and 586 healthy controls (HCs) were included. Medication-free patients with MDD, relative to HCs, showed a complex pattern of increased cortical thickness in some areas (posterior cingulate cortex, ventromedial prefrontal cortex, and anterior cingulate cortex) and decreased cortical thickness in others (gyrus rectus, orbital segment of the superior frontal gyrus, and middle temporal gyrus). Most findings in the whole sample analysis were confirmed in a meta-analysis of studies recruiting medication-naive patients. Using the new mask specifically developed for SBM studies, this SDM meta-analysis provides evidence for regional cortical thickness alterations in MDD, mainly involving increased cortical thickness in the default mode network and decreased cortical thickness in the orbitofrontal and temporal cortex

Removing the effects of the site in brain imaging machine-learning Measurement and extendable benchmark

Multisite machine-learning neuroimaging studies, such as those conducted by the ENIGMA Consortium, need to remove the differences between sites to avoid effects of the site (EoS) that may prevent or fraudulently help the creation of prediction models, leading to impoverished or inflated prediction accuracy. Unfortunately, we have shown earlier that current Methods Aiming to Remove the EoS (MAREoS, e.g., ComBat) cannot remove complex EoS (e.g., including interactions between regions). And complex EoS may bias the accuracy. To overcome this hurdle, groups worldwide are developing novel MAREoS. However, we cannot assess their effectiveness because EoS may either inflate or shrink the accuracy, and MAREoS may both remove the EoS and degrade the data. In this work, we propose a strategy to measure the effectiveness of a MAREoS in removing different types of EoS. FOR MAREOS DEVELOPERS, we provide two multisite MRI datasets with only simple true effects (i.e., detectable by most machine-learning algorithms) and two with only simple EoS (i.e., removable by most MAREoS). First, they should use these datasets to fit machine-learning algorithms after applying the MAREoS. Second, they should use the formulas we provide to calculate the relative accuracy change associated with the MAREoS in each dataset and derive an EoS-removal effectiveness statistic. We also offer similar datasets and formulas for complex true effects and EoS that include first-order interactions. FOR MACHINE-LEARNING RESEARCHERS, we provide an extendable benchmark website to show: a) the types of EoS they should remove for each given machine-learning algorithm and b) the effectiveness of each MAREoS for removing each type of EoS. Relevantly, a MAREoS only able to remove the simple EoS may suffice for simple machine-learning algorithms, whereas more complex algorithms need a MAREoS that can remove more complex EoS. For instance, ComBat removes all simple EoS as needed for predictions based on simple lasso algorithms, but it leaves residual complex EoS that may bias the predictions based on standard support vector machine algorithms

Amygdala where art thou?

The commentary of Morriss et al. on our recent meta-analysis of functional magnetic resonance imaging (fMRI) fear/threat extinction studies in humans (Fullana et al., 2018) raises some important issues for future research in the field. In essence, they argue that the lack of consistent evidence for amygdala and ventromedial prefrontal cortex (vmPFC) involvement in these studies, as summarized by meta-analysis, might be partly due to the fact that very few of these studies have provided appropriate analyses of time-varying neural responses, which Morriss et al. contend should be the gold standard

Meta-analysis of functional neuroimaging and cognitive control studies in schizophrenia: preliminary elucidation of a core dysfunctional timing network

Timing and other cognitive processes demanding cognitive control become interlinked when there is an increase in the level of difficulty or effort required. Both functions are interrelated and share neuroanatomical bases. A previous meta-analysis of neuroimaging studies found that people with schizophrenia had significantly lower activation, relative to normal controls, of most right hemisphere regions of the time circuit. This finding suggests that a pattern of disconnectivity of this circuit, particularly in the supplementary motor area, is a trait of this mental disease. We hypothesize that a dysfunctional temporal/cognitive control network underlies both cognitive and psychiatric symptoms of schizophrenia and that timing dysfunction is at the root of the cognitive deficits observed. The goal of our study was to look, in schizophrenia patients, for brain structures activated both by execution of cognitive tasks requiring increased effort and by performance of time perception tasks. We conducted a signed differential mapping (SDM) meta-analysis of functional neuroimaging studies in schizophrenia patients assessing the brain response to increasing levels of cognitive difficulty. Then, we performed a multimodal meta-analysis to identify common brain regions in the findings of that SDM meta-analysis and our previously-published activation likelihood estimate (ALE) meta-analysis of neuroimaging of time perception in schizophrenia patients. The current study supports the hypothesis that there exists an overlap between neural structures engaged by both timing tasks and non-temporal cognitive tasks of escalating difficulty in schizophrenia. The implication is that a deficit in timing can be considered as a trait marker of the schizophrenia cognitive profile