Activity patterns of arboreal mammals that move using power lines in a Neotropical urban ecosystem - Isabela V. Conti; Remington J. Moll; Raul Costa-Pereira (Urban Ecosystems, 2026)
With the suppression of continuous tree canopies in cities, some arboreal mammals resort to using overhead power line networks to navigate urban landscapes. Surprisingly, although sightings of mammals moving on electrical wires are common in tropical and temperate cities, we still know very little about mammal activity patterns on these human-built structures. Importantly, electrocution is a significant cause of death for mammal species that travel along overhead wires and climb onto transformers. Here, we deployed arboreal camera traps to quantify spatial and temporal activity patterns of canopy-dwelling mammals moving on electric wires around one of the largest urban forests in Brazil. Also, we investigated seasonal variation in their temporal activity patterns across the austral dry and rainy seasons. We obtained 9,158 independent records of four species of arboreal or semi-arboreal mammals, with the Black capuchin monkey ( Sapajus nigritus ) accounting for most of the detections, followed by the Paraguayan hairy dwarf porcupine ( Coendou spinosus ). Overall, species-specific activity patterns remained consistent across seasons and aligned with those observed in natural habitats, indicating a convergent diel niche in urban and natural environments. Our results shed new light on the neglected ecology and natural history of mammals that use electric wires to navigate urban spaces, providing insights to attenuate human-wildlife conflicts and to inform the planning of more wildlife-friendly cities.

Unveiling “Mid-Pliocene Warm Period” dynamics through multiproxy stratigraphic analysis: The Valdelsa Basin in Northern Apennines – Italy as a key archive - L. Milaneschi; G. Cornamusini; P. Conti; I. Martini; J. Maffei; F. Cifelli; M. Mattei; S. Da Prato; M.C. Alçiçek; L.M. Foresi (Palaeogeography, Palaeoclimatology, Palaeoecology, 2026)

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Corrigendum to “Edaphobase 2.0: Advanced international data warehouse for collating and using soil biodiversity datasets” [Applied Soil Ecology 204 (2024) 105710] - D.J. Russell; E. Naudts; N.A. Soudzilovskaia; M.J.I. Briones; M. Çakır; E. Conti; J. Cortet; C. Fiera; D. Hackenberger Kutuzovic; M. Hedde; K. Hohberg; D. Indjic; et al. (Applied Soil Ecology, 2026)

Exploring light-effects of microalgal extract on zebrafish caudal fin cell regeneration for aquaculture applications - F. Conti; E. Frigato; E. Ruohisto; J. F. López-Olmeda; F. J. Sánchez-Vázquez; C. Baldisserotto; C. Bertolucci; S. Pancaldi (Aquaculture International, 2026)

Are environmental factors correlated with the diversity of Phytophthora in organically and conventionally managed citrus orchards in Sicily? Insights from metabarcoding and baiting - Sebastiano Conti Taguali; Federico La Spada; Antonella Pane; Peter J. A. Cock; Beatrix Keillor; David E. L. Cooke; Santa Olga Cacciola (Mycological Progress, 2025)
Phytophthora species pose a significant threat to citrus production in the Mediterranean, particularly in Sicily, a major citrus-producing region. This study explores the diversity and distribution of Phytophthora taxa in Sicilian citrus orchards, addressing the urgent need to tackle increasing agricultural challenges, such as climate change. Specifically, it aimed to evaluate how environmental factors, such as the type of management (organic vs. conventional) and geographical area influence the composition of Phytophthora communities in Sicilian citrus orchards, and whether these communities correlate with tree health. An additional objective was to compare the effectiveness of traditional baiting and high-throughput metabarcoding techniques (targeting the ITS1 region and RPS10 gene) in capturing this diversity, as well as to assess potential shifts in community structure resulting from climate change by comparing current data with historical records. Soil samples were collected from ten citrus-producing areas under two distinct agronomic management and tree health conditions. Traditional baiting recovered 556 isolates of three already described Phytophthora species, while ITS1 metabarcoding identified ten additional taxa, demonstrating higher specificity (99.5% of ITS1 reads classified as Phytophthora compared to 82.5% for RPS10 ). Our findings indicate that geographical location is a key driver of community composition. Although statistical analyses did not reveal significant differences in Phytophthora diversity between organic and conventional management systems, these results provide valuable insights into the factors shaping pathogen communities. These insights are crucial for developing targeted disease management strategies and for understanding how environmental stressors, including climate change, impact pathogen dynamics in Mediterranean citrus orchards. Graphical Abstract

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Edaphobase 2.0: Advanced international data warehouse for collating and using soil biodiversity datasets - D.J. Russell; E. Naudts; N.A. Soudzilovskaia; M.J.I. Briones; M. Çakır; E. Conti; J. Cortet; C. Fiera; D. Hackenberger Kutuzovic; M. Hedde; K. Hohberg; D. Indjic; et al. (Applied Soil Ecology, 2024)

Impact of data for forecasting on performance of model predictive control in buildings with smart energy storage - Max Langtry; Vijja Wichitwechkarn; Rebecca Ward; Chaoqun Zhuang; Monika J. Kreitmair; Nikolas Makasis; Zack Xuereb Conti; Ruchi Choudhary (Energy and Buildings, 2024)

Microstructural Characterization of Dry Powder Inhaler Formulations Using Orthogonal Analytical Techniques - Gonçalo Farias; William J. Ganley; Robert Price; Denise S. Conti; Sharad Mangal; Elizabeth Bielski; Bryan Newman; Jagdeep Shur (Pharmaceutical Research, 2024)
Purpose For locally-acting dry powder inhalers (DPIs), developing novel analytical tools that are able to evaluate the state of aggregation may provide a better understanding of the impact of material properties and processing parameters on the in vivo performance. This study explored the utility of the Morphologically-Directed Raman Spectroscopy (MDRS) and dissolution as orthogonal techniques to assess microstructural equivalence of the aerosolized dose of DPIs collected with an aerosol collection device. Methods Commercial DPIs containing different strengths of Fluticasone Propionate (FP) and Salmeterol Xinafoate (SX) as monotherapy and combination products were sourced from different regions. These inhalers were compared with aerodynamic particle size distribution (APSD), dissolution, and MDRS studies. Results APSD testing alone might not be able to explain differences reported elsewhere in in vivo studies of commercial FP/SX drug products with different Advair® strengths and/or batches. Dissolution studies demonstrated different dissolution rates between Seretide™ 100/50 and Advair® 100/50, whereas Flixotide™ 100 and Flovent® 100 had similar dissolution rates between each other. These differences in dissolution profiles were supported by MDRS results: the dissolution rate is increased if the fraction of FP associated with high soluble components is increased. Principle component analysis was used to identify the agglomerate classes that better discriminate different products. Conclusions MDRS and dissolution studies of the aerosolized dose of DPIs were successfully used as orthogonal techniques. This study highlights the importance of further assessing in vitro tools that are able to provide a bridge between material attributes or process parameters and in vivo performance.

CoMMa: A GIS geomorphometry toolbox to map and measure confined landforms - Riccardo Arosio; Joana Gafeira; Laurence H. De Clippele; Andrew J. Wheeler; Veerle A.I. Huvenne; Fabio Sacchetti; Luis A. Conti; Aaron Lim (Geomorphology, 2024)

The last cave lion of the late Upper Palaeolithic: The engraved feline of Grotta Romanelli (southern Italy) - D. Sigari; C. Bourdier; C. Conti; J. Conti; L. Forti; M. García-Diez; G. Lai; I. Mazzini; P. Pieruccini; R. Sardella (Quaternary Science Reviews, 2024)

Correction to: A1R–A2AR heteromers coupled to Gs and Gi/0 proteins modulate GABA transport into astrocytes - Sofia Cristóvão-Ferreira; Gemma Navarro; Marc Brugarolas; Kamil Pérez-Capote; Sandra H. Vaz; Giorgia Fattorini; Fiorenzo Conti; Carmen Lluis; Joaquim A. Ribeiro; Peter J. McCormick; Vicent Casadó; Rafael Franco; et al. (Purinergic Signalling, 2024)

Excess pancreatic cancer risk due to smoking and modifying effect of quitting smoking: The Multiethnic Cohort Study - David Bogumil; Daniel Stram; Dale L. Preston; Stephen J. Pandol; Anna H. Wu; Roberta McKean-Cowdin; David V. Conti; Veronica Wendy Setiawan (Cancer Causes & Control, 2024)
Purpose Risk factors for pancreatic cancer include racial/ethnic disparities and smoking. However, risk trajectories by smoking history and race/ethnicity are unknown. We examined the association of smoking with pancreatic cancer by race/ethnicity to generate age-specific incidence estimates by smoking history. Methods We modeled pancreatic cancer incidence by race/ethnicity, age, pack-years, and years-quit using an excess relative risk model for 182,011 Multiethnic Cohort participants. We tested heterogeneity of smoking variables and pancreatic cancer by race/ethnicity and predicted incidence by smoking history. Results We identified 1,831 incident pancreatic cancer cases over an average 19.3 years of follow-up. Associations of pack-years ( p interaction by race/ethnicity = 0.41) and years-quit ( p interaction = 0.83) with pancreatic cancer did not differ by race/ethnicity. Fifty pack-years smoked was associated with 91% increased risk (95% CI 54%, 127%) relative to never smokers in the combined sample. Every year quit corresponded to 9% decreased excess risk (95% CI 2%, 15%) from pack-years smoked. Differences in baseline pancreatic cancer risk across racial/ethnic groups ( p < 0.001) translated to large differences in risk for smokers at older ages across racial/ethnic groups (65–122 cases per 100,000 at age 70). Conclusion Smoking pack-years were positively associated with elevated pancreatic cancer risk. Predicted risk trajectories showed a high impact of smoking cessation at < 65 years. Although we did not identify significant heterogeneity in the association of pack-years or years quit with pancreatic cancer risk, current smoker risk varied greatly by race/ethnicity in later life due to large differences in baseline risk.

Investigating the potential of African land snail shells (Gastropoda: Achatininae) for amino acid geochronology - Chloë Baldreki; Andrew Burnham; Martina Conti; Lucy Wheeler; Michael J. Simms; Lawrence Barham; Tom S. White; Kirsty Penkman (Quaternary Geochronology, 2024)

Numerical modeling of the influence of reservoir management on the algal blooms of San Roque - J. Muchiut; M. I. Rodríguez; A. L. Ruibal Conti; M. Ruiz; A. Rodríguez (International Journal of Environmental Science and Technology, 2024)

Fully convolutional neural networks applied to large-scale marine morphology mapping - Riccardo Arosio; Brandon Hobley; Andrew J. Wheeler; Fabio Sacchetti; Luis A. Conti; Thomas Furey; Aaron Lim (Frontiers in Marine Science, 2023)
In this study we applied for the first time Fully Convolutional Neural Networks (FCNNs) to a marine bathymetric dataset to derive morphological classes over the entire Irish continental shelf. FCNNs are a set of algorithms within Deep Learning that produce pixel-wise classifications in order to create semantically segmented maps. While they have been extensively utilised on imagery for ecological mapping, their application on elevation data is still limited, especially in the marine geomorphology realm. We employed a high-resolution bathymetric dataset to create a set of normalised derivatives commonly utilised in seabed morphology and habitat mapping that include three bathymetric position indexes (BPIs), the vector ruggedness measurement (VRM), the aspect functions and three types of hillshades. The class domains cover ten or twelve semantically distinct surface textures and submarine landforms present on the shelf, with our definitions aiming for simplicity, prevalence and distinctiveness. Sets of 50 or 100 labelled samples for each class were used to train several U-Net architectures with ResNet-50 and VGG-13 encoders. Our results show a maximum model precision of 0.84 and recall of 0.85, with some classes reaching as high as 0.99 in both. A simple majority (modal) voting combining the ten best models produced an excellent map with overall F1 score of 0.96 and class precisions and recalls superior to 0.87. For target classes exhibiting high recall (proportion of positives identified), models also show high precision (proportion of correct identifications) in predictions which confirms that the underlying class boundary has been learnt. Derivative choice plays an important part in the performance of the networks, with hillshades combined with bathymetry providing the best results and aspect functions and VRM leading to an overall deterioration of prediction accuracies. The results show that FCNNs can be successfully applied to the seabed for a morphological exploration of the dataset and as a baseline for more in-depth habitat mapping studies. For example, prediction of semantically distinct classes as “submarine dune” and “bedrock outcrop” can be precise and reliable. Nonetheless, at present state FCNNs are not suitable for tasks that require more refined geomorphological classifications, as for the recognition of detailed morphogenetic processes.

Tumor and peritumoral adipose tissue crosstalk: De-differentiated adipocytes influence spread of colon carcinoma cells - G. Conti; L. Calderan; L.A. Quintero Sierra; A. Conti; R. Ossanna; F. Boschi; P. Marzola; F. Ferrarini; M. Governa; P.M.-J. Lievens; A. Sbarbati (Tissue and Cell, 2023)

Validation and Verification of High-Fidelity Simulations of Thoracic Stent-Graft Implantation - Anna Ramella; Francesco Migliavacca; Jose Felix Rodriguez Matas; Frederic Heim; Francesca Dedola; Stefania Marconi; Michele Conti; Sara Allievi; Tim J. Mandigers; Daniele Bissacco; Maurizio Domanin; Santi Trimarchi; et al. (Annals of Biomedical Engineering, 2022)
Thoracic Endovascular Aortic Repair (TEVAR) is the preferred treatment option for thoracic aortic pathologies and consists of inserting a self-expandable stent-graft into the pathological region to restore the lumen. Computational models play a significant role in procedural planning and must be reliable. For this reason, in this work, high-fidelity Finite Element (FE) simulations are developed to model thoracic stent-grafts. Experimental crimp/release tests are performed to calibrate stent-grafts material parameters. Stent pre-stress is included in the stent-graft model. A new methodology for replicating device insertion and deployment with explicit FE simulations is proposed. To validate this simulation, the stent-graft is experimentally released into a 3D rigid aortic phantom with physiological anatomy and inspected in a computed tomography (CT) scan at different time points during deployment with an ad-hoc set-up. A verification analysis of the adopted modeling features compared to the literature is performed. With the proposed methodology the error with respect to the CT is on average 0.92 ± 0.64%, while it is higher when literature models are adopted (on average 4.77 ± 1.83%). The presented FE tool is versatile and customizable for different commercial devices and applicable to patient-specific analyses.

3D Classification of Cold-Water Coral Reefs: A Comparison of Classification Techniques for 3D Reconstructions of Cold-Water Coral Reefs and Seabed - Larissa Macedo Cruz de Oliveira; Aaron Lim; Luis A. Conti; Andrew J. Wheeler (Frontiers in Marine Science, 2021)
Cold-water coral (CWC) reefs are complex structural habitats that are considered biodiversity “hotspots” in deep-sea environments and are subject to several climate and anthropogenic threats. As three-dimensional structural habitats, there is a need for robust and accessible technologies to enable more accurate reef assessments. Photogrammetry derived from remotely operated vehicle video data is an effective and non-destructive method that creates high-resolution reconstructions of CWC habitats. Here, three classification workflows [Multiscale Geometrical Classification (MGC), Colour and Geometrical Classification (CGC) and Object-Based Image Classification(OBIA)] are presented and applied to photogrammetric reconstructions of CWC habitats in the Porcupine Bank Canyon, NE Atlantic. In total, six point clouds, orthomosaics, and digital elevation models, generated from structure-from-motion photogrammetry, are used to evaluate each classification workflow. Our results show that 3D Multiscale Geometrical Classification outperforms the Colour and Geometrical Classification method. However, each method has advantages for specific applications pertinent to the wider marine scientific community. Results suggest that advancing from commonly employed 2D image analysis techniques to 3D photogrammetric classification methods is advantageous and provides a more realistic representation of CWC habitat composition.

Molecular fossils as a tool for tracking Holocene sea‐level change in the Loch of Stenness, Orkney - Martina L. G. Conti; Martin R. Bates; Richard C. Preece; Kirsty E. H. Penkman; Brendan J. Keely (Journal of Quaternary Science, 2020)
Sediments deposited in the Loch of Stenness (Orkney Islands, Scotland) during the Holocene transgression, previously dated to between ~5939–5612 bp , were analysed for molecular fossils – lipids and chlorophyll pigments from primary producers – that complement conventional microfossil and lithological approaches for studying past sea‐level change. While microfossil and lithological studies identified a transgression between 102 and 81 cm core depth, key molecular fossils fluctuate in occurrence and concentration between 118 and 85 cm, suggesting an earlier start to the transgression. Terrestrial lipid concentrations decreased and algal‐derived, short‐chain, n ‐alkanoic acid concentrations increased at 118 cm, indicating a disruption of the freshwater lake conditions associated with the early stages of the marine transgression. The lipid and pigment analyses provided information that complements and extends that from microfossil analysis, presenting a more complete record of Holocene sea‐level changes and local vegetation changes in the Loch of Stenness. The isostatic stability of Stenness during the Holocene points towards other factors to explain the transgression, such as regional factors and/or melting of the Antarctic ice sheet (which occurred up to 3 ka).

Correction to: Infectious mononucleosis, immune genotypes, and non-Hodgkin lymphoma (NHL): an InterLymph Consortium study - Niquelle Brown Wadé; Cindy M. Chang; David Conti; Joshua Millstein; Christine Skibola; Alexandra Nieters; Sophia S. Wang; Silvia De Sanjose; Eleanor Kane; John J. Spinelli; Paige Bracci; Yawei Zhang; et al. (Cancer Causes & Control, 2020)

Preservation of 34S-enriched sulfides in fossil sulfate-methane transition zones: new evidence from Miocene outcrops of the northern Apennines (Italy) - C. Argentino; J. E. Johnson; S. Conti; C. Fioroni; D. Fontana (Geo-Marine Letters, 2020)

Infectious mononucleosis, immune genotypes, and non-Hodgkin lymphoma (NHL): an InterLymph Consortium study - Niquelle Brown Wadé; Cindy M. Chang; David Conti; Joshua Millstein; Christine Skibola; Alexandra Nieters; Sophia S. Wang; Silvia De Sanjose; Eleanor Kane; John J. Spinelli; Paige Bracci; Yawei Zhang; et al. (Cancer Causes & Control, 2020)

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Correction to: Grotta Romanelli (Lecce, Southern Italy) Between Past and Future: New Studies and Perspectives for an Archaeo-geosite Symbol of the Palaeolithic in Europe - R. Sardella; D. A. Iurino; B. Mecozzi; D. Sigari; F. Bona; L. Bellucci; M. Coltorti; J. Conti; G. Lembo; B. Muttillo; I. Mazzini (Geoheritage, 2019)

Grotta Romanelli (Lecce, Southern Italy) Between Past and Future: New Studies and Perspectives for an Archaeo-geosite Symbol of the Palaeolithic in Europe - R. Sardella; D. A. Iurino; B. Mecozzi; D. Sigari; F. Bona; L. Bellucci; M. Coltorti; J. Conti; G. Lembo; B. Muttillo; I. Mazzini (Geoheritage, 2019)

Correction to: Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer - Stephanie A. Bien; Yu-Ru Su; David V. Conti; Tabitha A. Harrison; Conghui Qu; Xingyi Guo; Yingchang Lu; Demetrius Albanes; Paul L. Auer; Barbara L. Banbury; Sonja I. Berndt; Stéphane Bézieau; et al. (Human Genetics, 2019)

Developing allometric models to predict the individual aboveground biomass of shrubs worldwide - G. Conti; L. D. Gorné; S. R. Zeballos; M. L. Lipoma; G. Gatica; E. Kowaljow; J. I. Whitworth‐Hulse; A. Cuchietti; M. Poca; S. Pestoni; P. M. Fernandes (Global Ecology and Biogeography, 2019)
Aim Existing global models to predict standing biomass are based on trees characterized by a single principal stem, well developed in height. However, their use in open woodlands and shrublands, characterized by multistemmed species with substantial crown development, generates a high level of uncertainty in biomass estimates. This limitation led us to (a) develop global models of shrub individual aboveground biomass based on simple allometric variables, (b) to compare the fit of these models with existing global biomass models, and (c) to assess whether models fit change when bioclimatic variables are considered. Location Global. Time period Present. Major taxa studied 118 species of shrubs. Methods We compile a database of 3,243 individuals across 49 sites distributed worldwide. Including stem basal diameter, height and crown diameter as predictor variables, we built potential models and compared their fit using generalized least squares. We used mixed effects models to determine if bioclimatic variables improved the accuracy of biomass models. Results Although the most important variable in terms of predictive capacity was stem basal diameter, crown diameter significantly improved the models’ fit, followed by height. Four models were finally chosen, with the best model combining all these variables in the same equation [ R 2 = 0.930, root mean square error (RMSE) = 0.476]. Selected models performed as well as established global biomass models. Including the individual bioform significantly improved the models’ fit. Main conclusions Stem basal diameter, crown diameter and height measures could be combined to provide robust aboveground biomass (AGB) estimates of individual shrub species. Our study supplements well‐established models developed for trees, allowing more accurate biomass estimation of multistemmed woody individuals. We further provide tools for a methodological standardization of individual biomass quantification in these species. We expect these results contribute to improve the quality of biomass estimates across ecosystems, but also to generate methodological consensus on field biomass assessments in shrubs.

Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer - Stephanie A. Bien; Yu-Ru Su; David V. Conti; Tabitha A. Harrison; Conghui Qu; Xingyi Guo; Yingchang Lu; Demetrius Albanes; Paul L. Auer; Barbara L. Banbury; Sonja I. Berndt; Stéphane Bézieau; et al. (Human Genetics, 2019)

Whale Shark Tourism: Impacts on Coral Reefs in the Philippines - C. W. Martin Wong; Inga Conti-Jerpe; Laurie J. Raymundo; Caroline Dingle; Gonzalo Araujo; Alessandro Ponzo; David M. Baker (Environmental Management, 2019)

Effects of Formulation Variables on Lung Dosimetry of Albuterol Sulfate Suspension and Beclomethasone Dipropionate Solution Metered Dose Inhalers - Jeffry D. Schroeter; Poonam Sheth; Anthony J. Hickey; Bahman Asgharian; Owen T. Price; Jay T. Holt; Denise S. Conti; Bhawana Saluja (AAPS PharmSciTech, 2018)

Regional frequency analysis of extreme rainfall in Sicily (Italy) - Angelo Forestieri; Francesco Lo Conti; Stephen Blenkinsop; Marcella Cannarozzo; Hayley J. Fowler; Leonardo V. Noto (International Journal of Climatology, 2018)
Extreme rainfall events have large impacts on society and are likely to increase in intensity under climate change. For design and management decisions, particularly regarding hydraulic works, accurate estimates of precipitation magnitudes are needed at different durations. In this article, an objective approach of the regional frequency analysis (RFA) has been applied to precipitation data for the island of Sicily, Italy. Annual maximum series for rainfall with durations of 1, 3, 6, 12, and 24 h from about 130 rain gauges were used. The RFA has been implemented using principal component analysis (PCA) followed by a clustering analysis, through the k ‐means algorithm, to identify statistically homogeneous groups of stations for the derivation of regional growth curves. Three regional probability distributions were identified as appropriate from an initial wider selection of distributions and were compared – the three‐parameter log‐normal distribution (LN3), the generalized extreme value (GEV) distribution, and the two component extreme value (TCEV) distribution. The regional parameters of these distributions were estimated using L‐moments and considering a hierarchical approach. Finally, assessment of the accuracy of the growth curves was achieved by means of the relative bias and relative root‐mean‐square error (RMSE) using a simulation analysis of regional L‐moments. Results highlight that for the lower return periods, all distributions showed the same accuracy while for higher return periods the LN3 distribution provided the best result. The study provides an updated resource for the estimation of extreme precipitation quantiles for Sicily through the derivation of growth curves needed to obtain depth–duration–frequency (DDF) curves.

Influence of Formulation Factors on the Aerosol Performance of Suspension and Solution Metered Dose Inhalers: A Systematic Approach - Poonam Sheth; Dennis Sandell; Denise S. Conti; Jay T. Holt; Anthony J. Hickey; Bhawana Saluja (The AAPS Journal, 2017)

Erratum to: Immunoreactivity and avidity of IgG anti-β2-glycoprotein I antibodies from patients with autoimmune diseases to different peptide clusters of β2-glycoprotein I - A. Artenjak; I. Locatelli; H. Brelih; D. M. Simonič; Z. Ulcova-Gallova; J. Swadzba; J. Musial; T. Iwaniec; L. Stojanovich; F. Conti; G. Valesini; T. Avčin; et al. (Immunologic Research, 2015)

Immunoreactivity and avidity of IgG anti-β2-glycoprotein I antibodies from patients with autoimmune diseases to different peptide clusters of β2-glycoprotein I - A. Artenjak; I. Locatelli; H. Brelih; D. M. Simonič; Z. Ulcova-Gallova; J. Swadzba; J. Musial; T. Iwaniec; L. Stojanovich; F. Conti; G. Valesini; T. Avčin; et al. (Immunologic Research, 2015)

Islands as model systems in ecology and evolution: prospects fifty years after MacArthur‐Wilson - Ben H. Warren; Daniel Simberloff; Robert E. Ricklefs; Robin Aguilée; Fabien L. Condamine; Dominique Gravel; Hélène Morlon; Nicolas Mouquet; James Rosindell; Juliane Casquet; Elena Conti; Josselin Cornuault; et al. (Ecology Letters, 2015)
The study of islands as model systems has played an important role in the development of evolutionary and ecological theory. The 50th anniversary of MacArthur and Wilson's (December 1963) article, ‘An equilibrium theory of insular zoogeography’, was a recent milestone for this theme. Since 1963, island systems have provided new insights into the formation of ecological communities. Here, building on such developments, we highlight prospects for research on islands to improve our understanding of the ecology and evolution of communities in general. Throughout, we emphasise how attributes of islands combine to provide unusual research opportunities, the implications of which stretch far beyond islands. Molecular tools and increasing data acquisition now permit re‐assessment of some fundamental issues that interested MacArthur and Wilson. These include the formation of ecological networks, species abundance distributions, and the contribution of evolution to community assembly. We also extend our prospects to other fields of ecology and evolution – understanding ecosystem functioning, speciation and diversification – frequently employing assets of oceanic islands in inferring the geographic area within which evolution has occurred, and potential barriers to gene flow. Although island‐based theory is continually being enriched, incorporating non‐equilibrium dynamics is identified as a major challenge for the future.

A1R–A2AR heteromers coupled to Gs and Gi/0 proteins modulate GABA transport into astrocytes - Sofia Cristóvão-Ferreira; Gemma Navarro; Marc Brugarolas; Kamil Pérez-Capote; Sandra H. Vaz; Giorgia Fattorini; Fiorenzo Conti; Carmen Lluis; Joaquim A. Ribeiro; Peter J. McCormick; Vicent Casadó; Rafael Franco; et al. (Purinergic Signalling, 2013)

A study of NOAA particle flux sensitivity to solar activity and strategies to search for correlations among satellite data and earthquake phenomena - Cristiano Fidani; Roberto Battiston; William J. Burger; Livio Conti (International Journal of Remote Sensing, 2012)

Meta-analysis of new genome-wide association studies of colorectal cancer risk - Ulrike Peters; Carolyn M. Hutter; Li Hsu; Fredrick R. Schumacher; David V. Conti; Christopher S. Carlson; Christopher K. Edlund; Robert W. Haile; Steven Gallinger; Brent W. Zanke; Mathieu Lemire; Jagadish Rangrej; et al. (Human Genetics, 2012)

Variation in folate pathway genes and distal colorectal adenoma risk: a sigmoidoscopy-based case–control study - A. Joan Levine; Won Lee; Jane C. Figueiredo; David V. Conti; David J. Vandenberg; Brian D. Davis; Christopher K. Edlund; Susanne M. Henning; David Heber; Mariana C. Stern; Robert W. Haile (Cancer Causes & Control, 2011)

Genes involved with folate uptake and distribution and their association with colorectal cancer risk - Jane C. Figueiredo; A. Joan Levine; Won H. Lee; David V. Conti; Jenny N. Poynter; Peter T. Campbell; David Duggan; Juan Pablo Lewinger; Maria Elena Martinez; Cornelia M. Ulrich; Polly Newcomb; John Potter; et al. (Cancer Causes & Control, 2010)

Substance P Upregulates LTB4 in Rat Adherent Macrophages from Granuloma Induced by KMnO4 - M. L. Castellani; P. Conti; M. Felaco; J. Vecchiet; C. Ciampoli; G. Cerulli; P. Boscolo; T. C. Theoharides (Neurotoxicity Research, 2009)

Chemical Cues from Murgantia histrionica Eliciting Host Location and Recognition in the Egg Parasitoid Trissolcus brochymenae - Eric Conti; Gianandrea Salerno; Ferdinando Bin; Howard J. Williams; S. Bradleigh Vinson (Journal of Chemical Ecology, 2003)

The CD4 T cell-deficient mouse mutation nackt ( nkt ) involves a deletion in the cathepsin L ( Ctsl ) gene - Fernando Benavides; Ann Venables; Heather Poetschke Klug; Edward Glasscock; Natalia Martin Palenzuela; Claudio J. Conti; Alexander Rudensky; Marcela Gmez; Jean-Louis Gunet; Ellen R. Richie (Immunogenetics, 2001)

Influence of feeding precursors on tropane alkaloid production during an abiotic stress in Datura innoxia transformed roots - M. Boitel-Conti; J-C. Laberche; A. Lanoue; C. Ducrocq; B.S. Sangwan-Norreel (Plant Cell, Tissue and Organ Culture (PCTOC), 2000)

Factors influencing the expression in vitro of Candida albicans stress mannoproteins reactive with salivary secretory IgA - V. Vidotto; L. Polonelli; S. Conti; J. Pontón; I. Vieta (Mycopathologia, 1998)

Relationship of soil carbon light fraction, microbial activity, humic acid production and nitrogen fertilization in the decaying process of corn stubble - M. E. Conti; N. M. Arrigo; H. J. Marelli (Biology and Fertility of Soils, 1997)

Protective effects of melatonin in mice infected with encephalitis viruses - D. Ben-Nathan; G. J. M. Maestroni; S. Lustig; A. Conti (Archives of Virology, 1995)

Inhibition of rabies virus infection by a soluble membrane fraction from the rat central nervous system - C. Conti; B. Hauttecoeur; M. J. Morelec; B. Bizzini; N. Orsi; H. Tsiang (Archives of Virology, 1988)