Historical antisemitism, ethnic specialization, and financial development

Historically, European Jews have specialized in financial services while being the victims of antisemitism. We find that the present-day demand for finance is lower in German counties where historical antisemitism was higher, compared to otherwise similar counties. Households in counties with high historical antisemitism have similar saving rates but invest less in stocks, hold lower saving deposits, and are less likely to get a mortgage to finance homeownership after controlling for wealth and a rich set of current and historical covariates. Present-day antisemitism and supply-side forces do not fully explain the results. Households in counties where historical antisemitism was higher distrust the financial sector more—a potential cultural externality of historical antisemitism that reduces wealth accumulation in the long run

Telecracy: Testing for Channels of Persuasion

We consider the long-lived slant towards Berlusconi in political information on Italian television (TV ). We exploit a shock to the slanted exposure of viewers: idiosyncratic deadlines to switch to digital TV from 2008 to 2012, which increased the number of freeview channels tenfold. The switch caused a drop in the vote share of Berlusconi’s coalition by between 5.5 and 7.5 percentage points. The effect was stronger in towns with older and less educated voters. At least 20 percent of digital users changed their voting behavior after the introduction of digital TV. Our evidence is consistent with the existence of persuasion- biased viewers

A chemical screen identifies the chemotherapeutic drug topotecan as a specific inhibitor of the B-MYB/MYCN axis in neuroblastoma

The transcription factor MycN is the prototypical neuroblastoma oncogene and a potential therapeutic target. However, its strong expression caused by gene amplification in about 30% of neuroblastoma patients is a considerable obstacle to the development of therapeutic approaches aiming at eliminating its tumourigenic activity. We have previously reported that B-Myb is essentially required for transcription of the MYCN amplicon and have also shown that B-MYB and MYCN are engaged in a feed forward loop promoting the survival/proliferation of neuroblastoma cells. We postulated that pharmacological strategies breaking the B-MYB/MYCN axis should result in clinically desirable effects. Thus, we implemented a high throughput chemical screen, using a curated library of ~1500 compounds from the National Cancer Institute, whose endpoint was the identification of small molecules that inhibited B-Myb. At the end of the screening, we found that the compounds pinafide, ellipticine and camptothecin inhibited B-Myb transcriptional activity in luciferase assays. One of the compounds, the topoisomerase-1 inhibitor camptothecin, is of considerable clinical interest since its derivatives topotecan and irinotecan are currently used as first and second line treatment agents for various types of cancer, including neuroblastoma. We found that neuroblastoma cells with amplification of MYCN are more sensitive than MYCN negative cells to camptothecin and topotecan killing. Campothecin and topotecan caused selective down-regulation of B-Myb and MycN expression in neuroblastoma cells. Notably, forced overexpression of B-Myb could antagonize the killing effect of topotecan and camptothecin, demonstrating that the transcription factor is a key target of the drugs. These results suggest that camptothecin and its analogues should be more effective in patients whose tumours feature amplification of MYCN and/or overexpression of B-MYB

Learning Multi-Frequency Partial Correlation Graphs

Despite the large research effort devoted to learning dependencies between time series, the state of the art still faces a major limitation: existing methods learn partial correlations but fail to discriminate across distinct frequency bands. Motivated by many applications in which this differentiation is pivotal, we overcome this limitation by learning a block-sparse, frequency-dependent, partial correlation graph, in which layers correspond to different frequency bands, and partial correlations can occur over just a few layers. To this aim, we formulate and solve two nonconvex learning problems: the first has a closed-form solution and is suitable when there is prior knowledge about the number of partial correlations; the second hinges on an iterative solution based on successive convex approximation, and is effective for the general case where no prior knowledge is available. Numerical results on synthetic data show that the proposed methods outperform the current state of the art. Finally, the analysis of financial time series confirms that partial correlations exist only within a few frequency bands, underscoring how our methods enable the gaining of valuable insights that would be undetected without discriminating along the frequency domain

Bringing social interaction at the core of organizational neuroscience

Organizations are composed of individuals working together for achieving specific goals, and interpersonal dynamics do exert a strong influence on workplace behaviour. Nevertheless, the dual and multiple perspective of interactions has been scarcely considered by Organizational Neuroscience (ON), the emerging field of study that aims at incorporating findings from cognitive and brain sciences into the investigation of organizational behaviour. This perspective article aims to highlight the potential benefits of adopting experimental settings involving two or more participants (the so-called "second person" approach) for studying the neural bases of organizational behaviour. Specifically, we stress the idea that moving beyond the individual perspective and capturing the dynamical relationships occurring within dyads or groups (e.g., leaders and followers, salespersons and clients, teams) might bring novel insights into the rising field of ON. In addition, designing research paradigms that reliably recreate real work and life situations might increase the generalizability and ecological validity of its results. We start with a brief overview of the current state of ON research and we continue by describing the second-person approach to social neuroscience. In the last paragraph, we try and outline how this approach could be extended to ON. To this end, we focus on leadership, group processes and emotional contagion as potential targets of interpersonal ON research

COVID-eVax, an electroporated DNA vaccine candidate encoding the SARS-CoV-2 RBD, elicits protective responses in animal models

The COVID-19 pandemic caused by SARS-CoV-2 has made the development of safe and effective vaccines a critical priority. To date, four vaccines have been approved by European and American authorities for preventing COVID-19, but the development of additional vaccine platforms with improved supply and logistics profiles remains a pressing need. Here we report the preclinical evaluation of a novel COVID-19 vaccine candidate based on the electroporation of engineered, synthetic cDNA encoding a viral antigen in the skeletal muscle. We constructed a set of prototype DNA vaccines expressing various forms of the SARS-CoV-2 spike (S) protein and assessed their immunogenicity in animal models. Among them, COVID-eVax—a DNA plasmid encoding a secreted monomeric form of SARS-CoV-2 S protein receptor-binding domain (RBD)—induced the most potent anti-SARS-CoV-2 neutralizing antibody responses (including against the current most common variants of concern) and a robust T cell response. Upon challenge with SARS-CoV-2, immunized K18-hACE2 transgenic mice showed reduced weight loss, improved pulmonary function, and lower viral replication in the lungs and brain. COVID-eVax conferred significant protection to ferrets upon SARS-CoV-2 challenge. In summary, this study identifies COVID-eVax as an ideal COVID-19 vaccine candidate suitable for clinical development. Accordingly, a combined phase I-II trial has recently started