Monte Carlo and experimental evaluation of a Timepix4 compact gamma camera for coded aperture nuclear medicine imaging with depth resolution

Purpose: We designed a prototype compact gamma camera (MediPROBE4) for nuclear medicine tasks, including radio-guided surgery and sentinel lymph node imaging with a 99mTc radiotracer. We performed Monte Carlo (MC) simulations for image performance assessment, and first spectroscopic imaging tests with a 300 μm thick silicon detector. Methods: The hand-held camera (1 kg weight) is based on a Timepix4 readout circuit for photon-counting, energy-sensitive, hybrid pixel detectors (24.6 × 28.2 mm2 sensitive area, 55 μm pixel pitch), developed by the Medipix4 Collaboration. The camera design adopts a CdTe detector (1 or 2 mm thick) bump-bonded to a Timepix4 readout chip and a coded aperture collimator with 0.25 mm diameter round holes made of 3D printed 1-mm thick tungsten. Image reconstruction is performed via autocorrelation deconvolution. Results: Geant4 MC simulations showed that, for a 99mTc source in air, at 50 mm source-collimator distance, the estimated collimator sensitivity (4 × 10-4) is 292 times larger than that of a single hole in the mask; the system sensitivity is 0.22 cps/kBq (2 mm CdTe); the lateral spatial resolution is 1.7 mm FWHM. The estimated axial longitudinal resolution is 8.2 mm FWHM at 40 mm distance. First experimental tests with a 300 μm thick Silicon pixel detector bump-bonded to a Timepix4 chip and a high-resolution coded aperture collimator showed time-over-threshold and time-of-arrival capabilities with 241Am and 133Ba gamma-ray sources. Conclusions: MC simulations and validation lab tests showed the expected performance of the MediPROBE4 compact gamma camera for gamma-ray 3D imaging

Enterocyte Proliferation and Signaling Are Constitutively Altered in Celiac Disease

Celiac disease (CD) occurs frequently, and is caused by ingestion of prolamins from cereals in subjects with a genetic predisposition. The small intestinal damage depends on an intestinal stress/innate immune response to certain gliadin peptides (e.g., A-gliadin P31-43) in association with an adaptive immune response to other gliadin peptides (e.g., A-gliadin P57-68). Gliadin and peptide P31-43 affect epithelial growth factor receptor (EGFR) signaling and CD enterocyte proliferation. The reason why the stress/innate immune and proliferative responses to certain gliadin peptides are present in CD and not in control intestine is so far unknown. The aim of this work is to investigate if, in CD, a constitutive alteration of enterocyte proliferation and signaling exists that may represent a predisposing condition to the damaging effects of gliadin. Immunofluorescence and immunohistochemistry were used to study signaling in CD fibroblasts and intestinal biopsies. Western blot (WB) analysis, immunoprecipitation, and quantitative PCR were also used. We found in CD enterocytes enhancement of both proliferation and Epidermal Growth Factor Receptor (EGFR)/ligand system. In CD enterocytes and fibroblasts we found increase of the phosphorylated downstream signaling molecule Extracellular Signal Regulated Kinase (ERK); block of the ERK activation normalizes enterocytes proliferation in CD mucosa. In conclusion the same pathway, which gliadin and gliadin peptide P31-43 can interfere with, is constitutively altered in CD cells. This observation potentially explains the specificity of the damaging effects of certain gliadin peptides on CD intestine.</p

Caratterizzazione della dinamica produttiva di pascoli naturali italiani

This work studies herbage production and its seasonal distribution in indigenous pastures, and analyses the relationship between the environmental factors (soil, clima, vegetation) and the productivity of these resources. The investigations have been carried on during the period 1983-90 by the joint activity of 10 different University Istitutions in 23 different environments distributed along the Italian peninsula and the main islands. For each environment, pasture production has been measured with the Corrall and Fenlon method, analysing the more important vegetational and ecological conditions; altogether the total yearly production and the seasonal pattern of herbage production have been detected on 104 pastures. The total herbage yield is not significantly influenced by the latitudinal gradient, and the overall regional (alps, central Appenine, south Apennine and islands) production is about 2.3 t ha-1 year-1 The wide range (0.5-6.3 t ha-1 year-1) of herbage production, on small or medium scale, seems to be due to evident changeof environmental or management factors. Five types of seasonal distribution of herbage growth are evidenced with multivariate analysis methods, based on the growing season and the amplitude of the growth. With mean temperature above 12°C and total rainfall below 800 mm, herbage distribution shows a standstill during summer period and an evident regrowth in autumn. On the contrary, for the 4 other distribution types, the winter standstill become important, and the types are distinct by summer growth amplitude and by the growing season lenght. With cluster analysis method, for each type of herbage distribution, have been pointed out under-types characterized by interannual herbage production variation. Among the environmental factors, vegetation characheristics, expressed as Pasture Value following Daget and Poissonet seems to be strictly correlated with total production. The comparative poor role played by the soil and climatic factor, may be due to the strong past and present antropic influence, related with management and utilization techniques. Il presente lavoro ha come scopo l'approfondimento delle conoscenze sulla produzione e sulla distribuzione stagionale della crescita dell'erba dei pascoli naturali, nonché l'analisi delle interazioni tra i fattori ambientali, pedo-climatici e vegetazionali, e la risposta produttiva di queste risorse. La ricerca è stata condotta nel periodo 1983-90 da 10 diverse Istituzioni Universitarie, in 23 ambienti differenti, distribuiti lungo tutta la penisola e le isole maggiori. Per ogni ambiente, con il metodo di rilievo di Corrall e Fenlon, è stata saggiata la risposta produttiva di pascoli rappresentativi delle principali situazioni vegetazionali e di giacitura; complessivamente sono state rilevate la produzione totale annua e la curva di produttività media pluriennale di 104 pascoli. Riguardo la produzione annua complessiva si è osservato che essa non presenta variazioni significative lungo il gradiente latitudinale, collocandosi tra le diverse regioni (alpina, centro appenninica, suq, appenninica e insulare) attorno a 2.3 t ha-1 anno-1. La fitomassa raccolta è soggetta invece a variazioni sensibili (0.5-6.3 t ha-1 anno-1) riconducibili a fattori ambientali e gestionali che si esprimono su piccola e media scala. Con metodi di analisi multivariata si sono individuate 5 tipologie distributive della crescita dell'erba, in rapporto alla stagione vegetativa e alle variazioni dell'intensità di crescita nel corso della stagione stessa. Con temperature medie e precipitazioni annue rispettivamente maggiori di 12°C e minori di 800 mm, risulta evidente la stasi vegetativa nel trimestre estivo e la ripresa vegetativa autunnale. Nel caso opposto la stasi è invernale e le 4 tipologie afferenti a questo modello, sono distinguibili dall'entità della crescita nei mesi estivi e dalla durata della stagione vegetativa. Per ogni tipologia produttiva, sono state evidenziate, tramite l'analisi cluster, sotto-tipologie distinte per la variabilità produttiva interannuale. Tra i fattori ambientali, la vegetazione, espressa attraverso l'indice del valore pastorale di Daget e Poissonet, presenta una buona capacità predittiva nei confronti del livello produttivo dei pascoli. Il contributo comparativamente modesto offerto dai fattori pedoclimatici sembra attribuibile alla forte influenza antropica, pregressa e attuale, attraverso le cure colturali e l'utilizzazione

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

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