Einstein's Local Realism and the Realistic Interpretation of the Wave Function

We review the different kinds of realism debates in philosophy and particularly in philosophy of science, then discussing in which ways they may be empirically significant, and analyzing criteria for a (non sharp nor absolute) demarcation between science and philosophy. We then outline two main realistic approaches in the foundations of quantum mechanics, de Broglie’s and Bohm’s “wave existential realism”, and Einstein, Podolski and Rosen’s “properties independence realism”. Both appear quite appealing, but neither has been completely successful. We then draw inspiration from them to propose a complementarity experiment, whereby the reality of quantum waves turns out to be grounded on “non local” properties of quantum systems. In this frame, empirical evidence appears to be relevant both to philosophy and science

Evaluation of the residual carrying capacity of a large-scale model bridge through frequency shifts

Structural systems are often subjected to degradation processes due to different kinds of phenomena like unexpected loadings, ageing of the materials, and fatigue cycles. This is true, especially for bridges, in which their safety evaluation is crucial for planning maintenance activities. This paper discusses the experimental evaluation of the residual carrying capacity from frequency changes due to distributed damage scenarios. For this purpose, in the laboratory of the University of Bologna, an experimental reinforced concrete model bridge was built and loaded. The applied forces produced bending moments causing up to three increasing levels of damage severity, namely early and diffused concrete cracking, and finally rebar yielding. By processing the acceleration signals recorded during the dynamic tests on the model bridge, the main natural frequencies of the bridge were obtained and the remaining bearing capacity was estimated based on the damage state. The opening and closure of cracks during a dynamic excitation produced a biased estimation of natural frequencies related to each damaged condition. The frequency decay predicted by the theory of breathing cracks applied to the performed experiments properly estimated the losses in the carrying capacity

P-glycoprotein (ABCB1) and oxidative stress: Focus on Alzheimer's disease

ATP-binding cassette (ABC) transporters, in particular P-glycoprotein (encoded by ABCB1), are important and selective elements of the blood-brain barrier (BBB), and they actively contribute to brain homeostasis. Changes in ABCB1 expression and/or function at the BBB may not only alter the expression and function of other molecules at the BBB but also affect brain environment. Over the last decade, a number of reports have shown that ABCB1 actively mediates the transport of beta amyloid (A\u3b2) peptide. This finding has opened up an entirely new line of research in the field of Alzheimer's disease (AD). Indeed, despite intense research efforts, AD remains an unsolved pathology and effective therapies are still unavailable. Here, we review the crucial role of ABCB1 in the A\u3b2 transport and how oxidative stress may interfere with this process. A detailed understanding of ABCB1 regulation can provide the basis for improved neuroprotection in AD and also enhanced therapeutic drug delivery to the brain

Induction of Labor According to Medical Indications: A Critical Evaluation through a Prospective Study

Background: The induction of labor (IOL) is a common obstetric intervention, steadily increasing (one out four pregnancies) in the last years. This procedure should be considered only when there is a medical indication, and when the benefits outweigh the maternal and/or fetal risks of waiting for spontaneous onset of labor. Therefore, this study aims to compare the efficacy of the IOL in terms of induction to delivery time, mode of delivery, and neonatal well-being among different evidence-based and non-evidence-based indications. Methods: This prospective study was conducted at the University Hospital of Modena, between January and December 2020. We included singleton pregnant women undergoing IOL, at the term. Intrauterine deaths, small for gestational age fetuses <5th centile as well women with hypertensive disorders were excluded. Women have been subdivided into 3 groups based on the indication to IOL: premature rupture of membranes (PROM), post-date pregnancy (>41 weeks + 3 days), and non-evidence-based indications (NEBI). The primary outcome is the time occurring between IOL and delivery (TIME), analyzing separately by parity. Moreover, mode of delivery and neonatal wellbeing were evaluated. Results: A total of 585 women underwent IOL in the study period. Overall, the median TIME between IOL and delivery was 19 hours, and the mean cesarean section CS rate was 15.5% (91/585). Pregnancies induced for postdate and non-evidencebased indications registered respectively a significantly higher mean time (p < 0.001), compared with women induced for PROM. This occurred both in nulliparous and multiparous women. Moreover, at multivariate analysis, the IOL TIME ≥24 hours was significantly influenced by Bishop score (p = 0.000) and NEBI (p = 0.02) in nulliparous and by gestational age (p = 0.000) and NEBI (p = 0.02) in multiparous. Moreover, CS rate was significantly influenced by Bishop score (p = 0.003) in nulliparous and by gestational age (p = 0.01) in multiparous. Finally, neonatal intensive care unit (NICU) admission resulted significantly influenced only by gestational age (p = 0.002) in multiparous. Conclusions: Our study confirms that IOL in non-evidence-based indications, leads to an increase in induction to delivery time comparing with women induced for PROM, both in nulliparous and multiparous women, thus it should be justified and carefully evaluated. Further randomized controlled trials (RCT) conducted in European/Italian settings are needed to determine the perinatal outcomes of IOL in non-evidence-based indications

Esculetin provides neuroprotection against mutant huntingtin-induced toxicity in huntington’s disease models

Huntington’s disease (HD) is a neurodegenerative disorder caused by an abnormal CAG trinucleotide repeat expansion within exon 1 of the huntingtin (HTT) gene. This mutation leads to the production of mutant HTT (mHTT) protein which triggers neuronal death through several mechanisms. Here, we investigated the neuroprotective effects of esculetin (ESC), a bioactive phenolic compound, in an inducible PC12 model and a transgenic Drosophila melanogaster model of HD, both of which express mHTT fragments. ESC partially inhibited the progression of mHTT aggregation and reduced neuronal death through its ability to counteract the oxidative stress and mitochondria impairment elicited by mHTT in the PC12 model. The ability of ESC to counteract neuronal death was also confirmed in the transgenic Drosophila model. Although ESC did not modify the lifespan of the transgenic Drosophila, it still seemed to have a positive impact on the HD phenotype of this model. Based on our findings, ESC may be further studied as a potential neuroprotective agent in a rodent transgenic model of HD

Identification of recurrent genetic patterns from targeted sequencing panels with advanced data science: a case-study on sporadic and genetic neurodegenerative diseases

open8noThis work is funded by the University of Bologna, the IRCCS Institute of Neurological sciences of Bologna, and by the European Grants H2020 GenoMed4All [AM1] (Grant N. 101017549) and H2020 MSCA-ITN IMforFUTURE (Grant N. 721815).Background Targeted Next Generation Sequencing is a common and powerful approach used in both clinical and research settings. However, at present, a large fraction of the acquired genetic information is not used since pathogenicity cannot be assessed for most variants. Further complicating this scenario is the increasingly frequent description of a poli/oligogenic pattern of inheritance showing the contribution of multiple variants in increasing disease risk. We present an approach in which the entire genetic information provided by target sequencing is transformed into binary data on which we performed statistical, machine learning, and network analyses to extract all valuable information from the entire genetic profile. To test this approach and unbiasedly explore the presence of recurrent genetic patterns, we studied a cohort of 112 patients affected either by genetic Creutzfeldt–Jakob (CJD) disease caused by two mutations in the PRNP gene (p.E200K and p.V210I) with different penetrance or by sporadic Alzheimer disease (sAD). Results Unsupervised methods can identify functionally relevant sources of variation in the data, like haplogroups and polymorphisms that do not follow Hardy–Weinberg equilibrium, such as the NOTCH3 rs11670823 (c.3837 + 21 T > A). Supervised classifiers can recognize clinical phenotypes with high accuracy based on the mutational profile of patients. In addition, we found a similar alteration of allele frequencies compared the European population in sporadic patients and in V210I-CJD, a poorly penetrant PRNP mutation, and sAD, suggesting shared oligogenic patterns in different types of dementia. Pathway enrichment and protein–protein interaction network revealed different altered pathways between the two PRNP mutations. Conclusions We propose this workflow as a possible approach to gain deeper insights into the genetic information derived from target sequencing, to identify recurrent genetic patterns and improve the understanding of complex diseases. This work could also represent a possible starting point of a predictive tool for personalized medicine and advanced diagnostic applications.openTarozzi, M.; Bartoletti-Stella, A.; Dall’Olio, D.; Matteuzzi, T.; Baiardi, S.; Parchi, P.; Castellani, G.; Capellari, S.Tarozzi, M.; Bartoletti-Stella, A.; Dall’Olio, D.; Matteuzzi, T.; Baiardi, S.; Parchi, P.; Castellani, G.; Capellari, S