In-vivo two-photon imaging of the honey bee antennal lobe

Due to the honey bee's importance as a simple neural model, there is a great need for new functional imaging modalities. Herein we report on the use of two-photon microscopy for in-vivo functional and morphological imaging of the honey bee's olfactory system focusing on its primary centers, the antennal lobes (ALs). Our imaging platform allows for simultaneously obtaining both morphological measurements of the AL and in-vivo calcium recording of neural activities. By applying external odor stimuli to the bee's antennas, we were able to record the characteristic odor response maps. Compared to previous works where conventional fluorescence microscopy is used, our approach offers all the typical advantages of multi-photon imaging, providing substantial enhancement in both spatial and temporal resolutions while minimizing photo-damages and autofluorescence contribution with a four-fold improvement in the functional signal. Moreover, the multi-photon associated extended penetration depth allows for functional imaging within profound glomeruli.Comment: 3 pages, 3 figure

Dependence of sub-micron vaterite container release properties on pH and ionic strength of the surrounding solution

We report on the synthesis and characterization of porous monodisperse vaterite containers with controllable average sizes from 400 nm to 10 mu m. Possible release strategies of enclosed substances via recrystallization or by pH-change are presented. As a model experiment, a fluorescent marker was encapsulated and imaged by two-photon microscopy to monitor the dye release. The release process was found to be controllable via the immersion medium's properties. Release times can be further tuned by covering the containers with additional polymer layers, creating a flexible system with promising perspectives for pharmaceutical applications

Second-harmonic generation sensitivity to transmembrane potential in normal and tumor cells.

Second-harmonic generation (SHG) is emerging as a powerful tool for the optical measurement of transmembrane potential in live cells with high sensitivity and temporal resolution. Using a patch clamp, we characterize the sensitivity of the SHG signal to transmembrane potential for the RH 237 dye in various normal and tumor cell types. SHG sensitivity shows a significant dependence on the type of cell, ranging from 10 to 17% per 100 mV. Furthermore, in the samples studied, tumor cell lines display a higher sensitivity compared to normal cells. In particular, the SHG sensitivity increases in the cell line Balb/c3T3 by the transformation induced with SV40 infection of the cells. We also demonstrate that fluorescent labeling of the membrane with RH 237 at the concentration used for SHG measurements does not induce any measurable alteration in the electrophysiological properties of the cells investigated. Therefore, SHG is suitable for the investigation of outstanding questions in electrophysiology and neurobiology

A multimodal approach for tracing lateralization along the olfactory pathway in the honeybee through electrophysiological recordings, morpho-functional imaging, and behavioural studies

Recent studies have revealed asymmetries between the left and right sides of the brain in invertebrate species. Here we present a review of a series of recent studies from our labs, aimed at tracing asymmetries at different stages along the honeybee's (Apis mellifera) olfactory pathway. These include estimates of the number of sensilla present on the two antennae, obtained by scanning electron microscopy, as well as electroantennography recordings of the left and right antennal responses to odorants. We describe investigative studies of the antennal lobes, where multi-photon microscopy is used to search for possible morphological asymmetries between the two brain sides. Moreover, we report on recently published results obtained by two-photon calcium imaging for functional mapping of the antennal lobe aimed at comparing patterns of activity evoked by different odours. Finally, possible links to the results of behavioural tests, measuring asymmetries in single-sided olfactory memory recall, are discussed.Comment: 28 pages, 8 figure

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes

Carriers of single pathogenic variants of the CFTR (cystic fibrosis transmembrane conductance regulator) gene have a higher risk of severe COVID-19 and 14-day death. The machine learning post-Mendelian model pinpointed CFTR as a bidirectional modulator of COVID-19 outcomes. Here, we demonstrate that the rare complex allele [G576V;R668C] is associated with a milder disease via a gain-of-function mechanism. Conversely, CFTR ultra-rare alleles with reduced function are associated with disease severity either alone (dominant disorder) or with another hypomorphic allele in the second chromosome (recessive disorder) with a global residual CFTR activity between 50 to 91%. Furthermore, we characterized novel CFTR complex alleles, including [A238V;F508del], [R74W;D1270N;V201M], [I1027T;F508del], [I506V;D1168G], and simple alleles, including R347C, F1052V, Y625N, I328V, K68E, A309D, A252T, G542*, V562I, R1066H, I506V, I807M, which lead to a reduced CFTR function and thus, to more severe COVID-19. In conclusion, CFTR genetic analysis is an important tool in identifying patients at risk of severe COVID-19

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

: The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity.. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores (IPGSph1 and IPGSph2). By applying a logistic regression with both IPGS, (IPGSph2 (or indifferently IPGSph1) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%