Geometric Deep Learning of the Human Connectome Project Multimodal Cortical Parcellation

Understanding the topographic heterogeneity of cortical organisation is an essential step towards precision modelling of neuropsychiatric disorders. While many cortical parcellation schemes have been proposed, few attempt to model inter-subject variability. For those that do, most have been proposed for high-resolution research quality data, without exploration of how well they generalise to clinical quality scans. In this paper, we benchmark and ensemble four different geometric deep learning models on the task of learning the Human Connectome Project (HCP) multimodal cortical parcellation. We employ Monte Carlo dropout to investigate model uncertainty with a view to propagate these labels to new datasets. Models achieved an overall Dice overlap ratio of >0.85 ± 0.02. Regions with the highest mean and lowest variance included V1 and areas within the parietal lobe, and regions with the lowest mean and highest variance included areas within the medial frontal lobe, lateral occipital pole and insula. Qualitatively, our results suggest that more work is needed before geometric deep learning methods are capable of fully capturing atypical cortical topographies such as those seen in area 55b. However, information about topographic variability between participants was encoded in vertex-wise uncertainty maps, suggesting a potential avenue for projection of this multimodal parcellation to new datasets with limited functional MRI, such as the UK Biobank.

Characteristics of the Soil Microbial Communities in Different Slope Positions along an Inverted Stone Slope in a Degraded Karst Tiankeng

The underground forests developed on inverted stone slopes in degraded karst tiankengs are important areas for biodiversity conservation, but the microbial community profiles have not been sufficiently characterized. Thus, we investigated the soil microbial communities at four sites (at the bottom of the slope (BS), in the middle of the slope (MS), in the upper part of the slope (US) and outside the tiankeng (OT)) in the Shenxiantang tiankeng. The dominant phyla in the inverted stone slope were Proteobacteria, Actinobacteria, and Acidobacteria, and the relative abundance were different in different slope positions. The Shannon–Wiener diversity index of the microbial community was significantly greater for the US site than for the MS or BS sites. The metabolism functional pathways (including C/N cycle) were more abundant at the BS site. Total nitrogen and pH were the dominant factors in determining the distribution of the microbial community along an inverted stone slope. These results suggest that topographic heterogeneity can influence the variations in the soil microbial structure, diversity, and function in degraded karst tiankengs and emphasized the ecological value of inverted stone slopes within karst tiankengs.

Topographic heterogeneity of lung microbiota in end-stage idiopathic pulmonary fibrosis: the Microbiome in Lung Explants-2 (MiLEs-2) study

BackgroundLung microbiota profiles in patients with early idiopathic pulmonary fibrosis (IPF) have been associated with disease progression; however, the topographic heterogeneity of lung microbiota and their roles in advanced IPF are unknown.MethodsWe performed a retrospective, case-control study of explanted lung tissue obtained at the time of lung transplantation or rapid autopsy from patients with IPF and other chronic lung diseases (connective tissue disease-associated interstitial lung disease (CTD-ILD), cystic fibrosis (CF), COPD and donor lungs unsuitable for transplant from Center for Organ Recovery and Education (CORE)). We sampled subpleural tissue and airway-based specimens (bronchial washings and airway tissue) and quantified bacterial load and profiled communities by amplification and sequencing of the 16S rRNA gene.FindingsExplants from 62 patients with IPF, 15 patients with CTD-ILD, 20 patients with CF, 20 patients with COPD and 20 CORE patients were included. Airway-based samples had higher bacterial load compared with distal parenchymal tissue. IPF basilar tissue had much lower bacterial load compared with CF and CORE lungs (p<0.001). No microbial community differences were found between parenchymal tissue samples from different IPF lobes. Dirichlet multinomial models revealed an IPF cluster (29%) with distinct composition, high bacterial load and low alpha diversity, exhibiting higher odds for acute exacerbation or death.InterpretationIPF explants had low biomass in the distal parenchyma of all three lobes with higher bacterial load in the airways. The discovery of a distinct subgroup of patients with IPF with higher bacterial load and worse clinical outcomes supports investigation of personalised medicine approaches for microbiome-targeted interventions.

Topographic heterogeneity of intrinsic excitability in mouse hippocampal CA3 pyramidal neurons

Area CA3 is a major hippocampal region that is classically thought to act as a homogeneous neural network vital for spatial navigation and episodic memories. Here, we report that CA3 pyramidal neurons exhibit marked heterogeneity of somatodendritic morphology and cellular electrical properties along both proximodistal and dorsoventral axes. These new results uncover a complex, yet orderly, pattern of topographic organization of CA3 neuronal features that may contribute to its in vivo functional diversity.

Plant richness, turnover, and evolutionary diversity track gradients of stability and ecological opportunity in a megadiversity center

Research on global patterns of diversity has been dominated by studies seeking explanations for the equator-to-poles decline in richness of most groups of organisms, namely the latitudinal diversity gradient. A problem with this gradient is that it conflates two key explanations, namely biome stability (age and area) and productivity (ecological opportunity). Investigating longitudinal gradients in diversity can overcome this problem. Here we investigate a longitudinal gradient in plant diversity in the megadiverse Cape Floristic Region (CFR). We test predictions of the age and area and ecological opportunity hypotheses using metrics for both taxonomic and phylogenetic diversity and turnover. Our plant dataset includes modeled occurrences for 4,813 species and dated molecular phylogenies for 21 clades endemic to the CFR. Climate and biome stability were quantified over the past 140,000 y for testing the age and area hypothesis, and measures of topographic diversity, rainfall seasonality, and productivity were used to test the ecological opportunity hypothesis. Results from our spatial regression models showed biome stability, rainfall seasonality, and topographic heterogeneity were the strongest predictors of taxonomic diversity. Biome stability alone was the strongest predictor of all diversity metrics, and productivity played only a marginal role. We argue that age and area in conjunction with non–productivity-based measures of ecological opportunity explain the CFR’s longitudinal diversity gradient. We suggest that this model may possibly be a general explanation for global diversity patterns, unconstrained as it is by the collinearities underpinning the latitudinal diversity gradient.

Lichen Distribution Patterns in the Ecoregions of Italy

An outline of the main distribution patterns of lichens in the ecoregions of Italy, accounting for their climatic, geographic, and environmental features, is still missing. On the basis of a GIS-based analysis, we summarized: (1) the main features (e.g., surface, climate, landscape, topographic heterogeneity, bedrock, eutrophication) of the 9 ecoregions adopted in ITALIC, the information system on Italian lichens, and (2) the patterns of richness, functional traits, and ecological requirements of lichens in the ecoregions. Our GIS-based analysis describes for the first time the main features of the 9 ecoregions adopted in ITALIC, highlighting differences which could explain the main lichen patterns. Overall, the exploration of the Italian lichen biota is still a work in progress, some regions being still underexplored, especially in the South, with new taxa being reported every year. Our research could provide a baseline for further advancements in the understanding of species richness and community composition of Italian lichens, at a regional scale.

LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest

Accurate canopy base height (CBH) information is essential for forest and fire managers since it constitutes a key indicator of seedling growth, wood quality and forest health as well as a necessary input in fire behavior prediction systems such as FARSITE, FlamMap and BEHAVE. The present study focused on the potential of airborne LiDAR data analysis to estimate plot-level CBH in a dense uneven-aged structured forest on complex terrain. A comparative study of two widely employed methods was performed, namely the voxel-based approach and regression analysis, which revealed a clear outperformance of the latter. More specifically, the voxel-based CBH estimates were found to lack correlation with the reference data ( R 2 = 0.15 , r R M S E = 42.36 % ) while most CBH values were overestimated resulting in an r b i a s of − 17.52 % . On the contrary, cross-validation of the developed regression model showcased an R 2 , r R M S E and r b i a s of 0 . 61 , 18.19 % and − 0.09 % respectively. Overall analysis of the results proved the voxel-based approach incapable of accurately estimating plot-level CBH due to vegetation and topographic heterogeneity of the forest environment, which however didn’t affect the regression analysis performance.

Topographic Heterogeneity of Lung Microbiota in End-Stage Idiopathic Pulmonary Fibrosis: The Microbiome in Lung Explants-2 (MiLEs-2) Study

BackgroundLung microbiota profiles in patients with early idiopathic pulmonary fibrosis (IPF) have been associated with disease progression; however, the topographic heterogeneity of lung microbiota and their roles in advanced IPF are unknown.MethodsWe sampled subpleural tissue from up to three lobes as well as airway-based specimens (bronchial washings and airway tissue) in patients with IPF, connective tissue disease-associated interstitial lung disease (CTD-ILD), cystic fibrosis (CF), and chronic obstructive pulmonary disease (COPD) and donor lungs deemed unsuitable for transplant (controls). We quantified bacterial load and profiled communities by polymerase chain reaction (PCR) amplification and sequencing of the 16S rRNA gene.FindingsExplants from 62 IPF, 15 CTD-ILD, 20 CF, 20 COPD and 20 control patients were included. Airway-based samples had higher bacterial load compared to distal parenchymal tissue across all patient groups. IPF basilar tissue had much lower bacterial load compared to CF and control lungs (p<0.001). Among patients with IPF, no differences in microbial community profiles were found between parenchymal tissue samples from different lobes. With Dirichlet multinomial models, a cluster of IPF patients (29%) with distinct composition, high bacterial load and low alpha diversity was identified, exhibiting higher odds for acute exacerbation of IPF or death.InterpretationIPF explants exhibited low biomass in the distal parenchyma of all three lobes with higher bacterial load in the airways. The discovery of a distinct subgroup of IPF patients with higher bacterial load and worse clinical outcomes supports investigation of personalized medicine approaches for microbiome-targeted interventions.Key MessagesWhat is the key question?Bronchoalveolar lavage microbiome profiles in early idiopathic pulmonary fibrosis (IPF) have been associated with disease progression, but the regional heterogeneity of resident microbiota in end-stage IPF has not been defined.What is the bottom line?IPF explants demonstrate higher bacterial load in airway compared to parenchymal samples, but no differences in between apical or basilar parenchymal samples. A subgroup of patients with higher bacterial load and respiratory pathogen abundance was associated with worse clinical outcomes.Why read on?Patient-specific heterogeneity in the lung microbiome of IPF supports the need for personalized microbiome-targeted interventions in IPF.