Multimodal nonlinear microscopy: A powerful label-free method for supporting standard diagnostics on biological tissues

The large use of nonlinear laser scanning microscopy in the past decade paved the way for potential clinical application of this imaging technique. Modern nonlinear microscopy techniques offer promising label-free solutions to improve diagnostic performances on tissues. In particular, the combination of multiple nonlinear imaging techniques in the same microscope allows integrating morphological with functional information in a morpho-functional scheme. Such approach provides a high-resolution label-free alternative to both histological and immunohistochemical examination of tissues and is becoming increasingly popular among the clinical community. Nevertheless, several technical improvements, including automatic scanning and image analysis, are required before the technique represents a standard diagnostic method. In this review paper, we highlight the capabilities of multimodal nonlinear microscopy for tissue imaging, by providing various examples on colon, arterial and skin tissues. The comparison between images acquired using multimodal nonlinear microscopy and histology shows a good agreement between the two methods. The results demonstrate that multimodal nonlinear microscopy is a powerful label-free alternative to standard histopathological methods and has the potential to find a stable place in the clinical setting in the near future

Evidence suggests that issues may have mattered more than expected in the 2016 US presidential elections

In the lead up to the 2016 election, many commentators argued that Donald Trump’s personality and actions would encourage many voters to cross party lines or to stay home. That was emphatically not the case, with Republicans generally voting for Trump as they would any other GOP candidate. Using data from a Voting Advice Application, Diego Garzia and Lorenzo Cicchi write that while partisanship was important in the election, their initial results show that policy issues – such as the repeal of Obamacare – were important to voters as well

The Health–Economy Divide: A Structural Analysis of Sectoral Affectedness and Covid-19 Policy Preferences in Europe

The Covid-19 health emergency and the resulting economic crisis hit European societies asymmetrically, which led to divergent preferences over the policies addressing the emergency. This paper analyses how different economic sectors were affected based on the “essentiality” and “physicality” of their activities, and how the level of affectedness--job losses, furloughs, decreased working hours and salaries--opposed the interests in favour of reopening the economy against the lockdowns dictated by health concerns. We combine a structural approach with an examination of the impact of party identification on citizens’ preferences, and posit that the parties that mobilise groups negatively affected by previous crises take positions toward the economic end of the continuum, in line with the preferences of an electorate that has been negatively affected by the pandemic. Our explanatory models integrate other structural (age, education) and political (trust, attitudes on expertise) factors in an effort to assess if the health–economy divide reordered the European cleavage structure towards material, rather than cultural and post-material, concerns

A new 3,4-dihydroxypyrrolidine-based material for molecular recognition

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Few Shot Learning in Histopathological Images:Reducing the Need of Labeled Data on Biological Datasets

Although deep learning pathology diagnostic algorithms are proving comparable results with human experts in a wide variety of tasks, they still require a huge amount of well annotated data for training. Generating such extensive and well labelled datasets is time consuming and is not feasible for certain tasks and so, most of the medical datasets available are scarce in images and therefore, not enough for training. In this work we validate that the use of few shot learning techniques can transfer knowledge from a well defined source domain from Colon tissue into a more generic domain composed by Colon, Lung and Breast tissue by using very few training images. Our results show that our few-shot approach is able to obtain a balanced accuracy (BAC) of 90% with just 60 training images, even for the Lung and Breast tissues that were not present on the training set. This outperforms the finetune transfer learning approach that obtains 73% BAC with 60 images and requires 600 images to get up to 81% BAC.This study has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 732111 (PICCOLO project)

Novel synthetic approach to heteroatom doped polycyclic aromatic hydrocarbons: Optimizing the bottom-up approach to atomically precise doped nanographenes

The success of the rational bottom-up approach to nanostructured carbon materials and the discovery of the importance of their doping with heteroatoms puts under the spotlight all synthetic organic approaches to polycyclic aromatic hydrocarbons. The construction of atomically precise heteroatom doped nanographenes has evidenced the importance of controlling its geometry and the position of the doping heteroatoms, since these parameters influence their chemical–physical properties and their applications. The growing interest towards this research topic is testified by the large number of works published in this area, which have transformed a once “fundamental research” into applied research at the cutting edge of technology. This review analyzes the most recent synthetic approaches to this class of compounds

(3R,4S)-3,4-Isopropyl­idenedioxy-3,4-dihydro-2H-pyrrole 1-oxide

The title compound C7H11NO3 was prepared by intra­molecular nucleophilic displacement of 2,3-O-iso-propyl­idene-d-erythronolactol. There are two mol­ecules in the asymmetric unit, which are related by a pseudo-inversion centre. The crystal structure determination confirms unequivocally the configuration of the chiral centres as 3S,4R. In the crystal structure, inter­molecular C—H⋯O inter­actions link the mol­ecules (into infinite zigzag chains along the a axis