Heterozygosity for Neuronal Ceroid Lipofuscinosis predisposes to Bipolar Disorder

Objective: Bipolar Disorder (BD) is an heritable chronic mental disorder causing psychosocial impairment, affecting patients with depressive/manic episodes. The familial transmission of BD does not follow any of the simple Mendelian patterns of inheritance. The aim of this study is to describe a new large family with twelve affected BD members: WES was performed in eight of them, three of which were diagnosed for BD, and one was reported as a "borderline" individual. Material and methods: WES data allowed us to select variants in common between the affected subjects, once including and once excluding a "borderline" subject with moderate anxiety and traits of obsessive-compulsive disorder. Results: Results were in favor of new predisposing BD genes, electing a heterozygous missense variant in CLN6 resulting in a "borderline" phenotype that if combined with a heterozygous missense variant in ZNF92 is responsible for the more severe BD phenotype. Both rare missense changes are predicted to disrupt the protein function. Conclusions: Loss of both alleles in CLN6 causes Neuronal Ceroid Lipofuscinosis, a severe progressive neurological disorder of childhood. Our results indicate that heterozygous CLN6 carriers, previously reported as healthy, may be susceptible to bipolar disorder late in life if associated with additional variants in ZNF92

Growth, electronic and electrical characterization of Ge-Rich Ge-Sb-Te alloy

In this study, we deposit a Ge-rich Ge-Sb-Te alloy by physical vapor deposition (PVD) in the amorphous phase on silicon substrates. We study in-situ, by X-ray and ultraviolet photoemission spectroscopies (XPS and UPS), the electronic properties and carefully ascertain the alloy composition to be GST 29 20 28. Subsequently, Raman spectroscopy is employed to corroborate the results from the photoemission study. X-ray diffraction is used upon annealing to study the crystallization of such an alloy and identify the effects of phase separation and segregation of crystalline Ge with the formation of grains along the [111] direction, as expected for such Ge-rich Ge-Sb-Te alloys. In addition, we report on the electrical characterization of single memory cells containing the Ge-rich Ge-Sb-Te alloy, including I-V characteristic curves, programming curves, and SET and RESET operation performance, as well as upon annealing temperature. A fair alignment of the electrical parameters with the current state-of-the-art of conventional (GeTe)n-(Sb2Te3)m alloys, deposited by PVD, is found, but with enhanced thermal stability, which allows for data retention up to 230 °C

PIK3R1W624R Is an Actionable Mutation in High Grade Serous Ovarian Carcinoma.

Identifying cancer drivers and actionable mutations is critical for precision oncology. In epithelial ovarian cancer (EOC) the majority of mutations lack biological or clinical validation. We fully characterized 43 lines of Patient-Derived Xenografts (PDXs) and performed copy number analysis and whole exome sequencing of 12 lines derived from naïve, high grade EOCs. Pyrosequencing allowed quantifying mutations in the source tumours. Drug response was assayed on PDX Derived Tumour Cells (PDTCs) and in vivo on PDXs. We identified a PIK3R1W624R variant in PDXs from a high grade serous EOC. Allele frequencies of PIK3R1W624R in all the passaged PDXs and in samples of the source tumour suggested that it was truncal and thus possibly a driver mutation. After inconclusive results in silico analyses, PDTCs and PDXs allowed the showing actionability of PIK3R1W624R and addiction of PIK3R1W624R carrying cells to inhibitors of the PI3K/AKT/mTOR pathway. It is noteworthy that PIK3R1 encodes the p85α regulatory subunit of PI3K, that is very rarely mutated in EOC. The PIK3R1W624R mutation is located in the cSH2 domain of the p85α that has never been involved in oncogenesis. These data show that patient-derived models are irreplaceable in their role of unveiling unpredicted driver and actionable variants in advanced ovarian cancer

Pathogen-sugar interactions revealed by universal saturation transfer analysis

Many pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an “end-on” manner. uSTA-guided modeling and a high-resolution cryo–electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis

Combined fit to the spectrum and composition data measured by the Pierre Auger Observatory including magnetic horizon effects

The measurements by the Pierre Auger Observatory of the energy spectrum and mass composition of cosmic rays can be interpreted assuming the presence of two extragalactic source populations, one dominating the flux at energies above a few EeV and the other below. To fit the data ignoring magnetic field effects, the high-energy population needs to accelerate a mixture of nuclei with very hard spectra, at odds with the approximate E$^{-2}$ shape expected from diffusive shock acceleration. The presence of turbulent extragalactic magnetic fields in the region between the closest sources and the Earth can significantly modify the observed CR spectrum with respect to that emitted by the sources, reducing the flux of low-rigidity particles that reach the Earth. We here take into account this magnetic horizon effect in the combined fit of the spectrum and shower depth distributions, exploring the possibility that a spectrum for the high-energy population sources with a shape closer to E$^{-2}$ be able to explain the observations

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration