Uncertain identification

Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which can lead to a mix of point- and set- identified models. We propose performing inference in the presence of such uncertainty by generalizing Bayesian model averaging. The method considers multiple posteriors for the set-identified models and combines them with a single posterior for models that are either point-identified or that impose non-dogmatic assumptions. The output is a set of posteriors (post-averaging ambiguous belief ), which can be summarized by reporting the set of posterior means and the associated credible region. We clarify when the prior model probabilities are updated and characterize the asymptotic behavior of the posterior model probabilities. The method provides a formal framework for conducting sensitivity analysis of empirical findings to the choice of identifying assumptions. For example, we find that in a standard monetary model one would need to attach a prior probability greater than 0.28 to the validity of the assumption that prices do not react contemporaneously to a monetary policy shock, in order to obtain a negative response of output to the shock

Uncertain identification

Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which, in general, leads to a mix of point- and set-identified models. We propose performing inference in the presence of such uncertainty by generalizing Bayesian model averaging. The method considers multiple posteriors for the set-identified models and combines them with a single posterior for models that are either point-identified or that impose non-dogmatic assumptions. The output is a set of posteriors (post-averaging ambiguous belief) that are mixtures of the single posterior and any element of the class of multiple posteriors, with weights equal to the posterior model probabilities. We suggest reporting the range of posterior means and the associated credible region in practice, and provide a simple algorithm to compute them. We establish that the prior model probabilities are updated when the models are "distinguishable" and/or they specify different priors for reduced-form parameters, and characterize the asymptotic behavior of the posterior model probabilities. The method provides a formal framework for conducting sensitivity analysis of empirical findings to the choice of identifying assumptions. In a standard monetary model, for example, we show that, in order to support a negative response of output to a contractionary monetary policy shock, one would need to attach a prior probability greater than 0.32 to the validity of the assumption that prices do not react contemporaneously to such a shock. The method is general and allows for dogmatic and non-dogmatic identifying assumptions, multiple point-identified models, multiple set-identified models, and nested or non-nested models

The role of non-coding RNAs as prognostic factor, predictor of drug response or resistance and pharmacological targets, in the cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma (CSCC) is the most common keratinocyte-derived skin cancer in the Caucasian population. Exposure to UV radiations (UVRs) represents the main risk carcinogenesis, causing a considerable accumulation of DNA damage in epidermal keratinocytes with an uncontrolled hyperproliferation and tumor development. The limited and rarely durable response of CSCC to the current therapeutic options has led researchers to look for new therapeutic strategies. Recently, the multi-omics approaches have contributed to the identification and prediction ofthe key role of non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), circularRNAs (circRNAs) and long non-coding RNAs (lncRNAs) in the regulation of several cellular processes in different tumor types, including CSCC. ncRNAs can modulate transcriptional and post-transcriptional events by interacting either with each other or with DNAand proteins, such as transcription factors and RNA-binding proteins.In this review, the implication of ncRNAs in tumorigenesis and their potential role as diagnostic biomarkers and therapeutic targets in human CSCC are reported

Identification of an Amylomaltase from the Halophilic Archaeon Haloquadratum walsbyi by Functional Metagenomics: Structural and Functional Insights

Amylomaltases are prokaryotic 4-α-glucanotransferases of the GH77 family. Thanks to the ability to modify starch, they constitute a group of enzymes of great interest for biotechnological applications. In this work we report the identification, by means of a functional metagenomics screening of the crystallization waters of the saltern of Margherita di Savoia (Italy), of an amylomaltase gene from the halophilic archaeon Haloquadratum walsbyi, and its expression in Escherichia coli cells. Sequence analysis indicated that the gene has specific insertions yet unknown in homologous genes in prokaryotes, and present only in amylomaltase genes identified in the genomes of other H. walsbyi strains. The gene is not part of any operon involved in the metabolism of maltooligosaccharides or glycogen, as it has been found in bacteria, making it impossible currently to assign a precise role to the encoded enzyme. Sequence analysis of the H. walsbyi amylomaltase and 3D modelling showed a common structure with homologous enzymes characterized in mesophilic and thermophilic bacteria. The recombinant H. walsbyi enzyme showed starch transglycosylation activity over a wide range of NaCl concentrations, with maltotriose as the best acceptor substrate compared to other maltooligosaccharides. This is the first study of an amylomaltase from a halophilic microorganism

Plant Health and Rhizosphere Microbiome: Effects of the Bionematicide Aphanocladium album in Tomato Plants Infested by Meloidogyne javanica

The artificial introduction in the soil of antagonistic microorganisms can be a successful strategy, alternative to agrochemicals, for the control of the root-knot nematodes (Meloidogyne spp.) and for preserving plant health. On the other hand, plant roots and the associated rhizosphere constitute a complex system in which the contribution of microbial community is fundamental to plant health and development, since microbes may convert organic and inorganic substances into available plant nutrients. In the present study, the potential nematicidal activity of the biopesticide Aphanocladium album (A. album strain MX-95) against the root-knot nematode Meloidogyne javanica in infected tomato plants was investigated. Specifically, the effect of the A. album treatment on plant fitness was evaluated observing the plant morphological traits and also considering the nematode propagation parameters, the A. album MX-95 vitality and population density. In addition, the treatment effects on the rhizosphere microbiome were analysed by a metabarcoding procedure. Treatments with A. album isolate MX-95 significantly decreased root gall severity index and soil nematode population. The treatment also resulted in increased rhizosphere microbial populations. A. album MX-95 can be favourably considered as a new bionematicide to control M. javanica infestation

Identification and characterization of the sucrose synthase 2 gene (Sus2) in durum wheat

Sucrose transport is the central system for the allocation of carbon resources in vascular plants. Sucrose synthase (SUS), which reversibly catalyzes sucrose synthesis and cleavage, represents a key enzyme in the control of the flow of carbon into starch biosynthesis. In the present study the genomic identification and characterization of the Sus2-2A and Sus2-2B genes coding for SUS in durum wheat (cultivars Ciccio and Svevo) is reported. The genes were analyzed for their expression in different tissues and at different seed maturation stages, in four tetraploid wheat genotypes (Svevo, Ciccio, Primadur, and 5-BIL42). The activity of the encoded proteins was evaluated by specific activity assays on endosperm extracts and their structure established by modeling approaches. The combined results of sucrose synthase 2 expression and activity levels were then considered in the light of their possible involvement in starch yield

Modeling SARS-CoV-2 spike/ACE2 protein–protein interactions for predicting the binding affinity of new spike variants for ACE2, and novel ACE2 structurally related human protein targets, for COVID-19 handling in the 3PM context

Aims The rapid spread of new SARS-CoV-2 variants has highlighted the crucial role played in the infection by mutations occurring at the SARS-CoV-2 spike receptor binding domain (RBD) in the interactions with the human ACE2 receptor. In this context, it urgently needs to develop new rapid tools for quickly predicting the affinity of ACE2 for the SARS-CoV-2 spike RBD protein variants to be used with the ongoing SARS-CoV-2 genomic sequencing activities in the clinics, aiming to gain clues about the transmissibility and virulence of new variants, to prevent new outbreaks and to quickly estimate the severity of the disease in the context of the 3PM. Methods In our study, we used a computational pipeline for calculating the interaction energies at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface for a selected group of characterized infectious variants of concern/interest (VoC/ VoI). By using our pipeline, we built 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for the VoC B.1.1.7-United Kingdom (carrying the mutations of concern/interest N501Y, S494P, E484K at the RBD), P.1- Japan/Brazil (RBD mutations: K417T, E484K, N501Y), B.1.351-South Africa (RBD mutations: K417N, E484K, N501Y), B.1.427/B.1.429-California (RBD mutations: L452R), the B.1.141 (RBD mutations: N439K), and the recent B.1.617.1- India (RBD mutations: L452R; E484Q) and the B.1.620 (RBD mutations: S477N; E484K). Then, we used the obtained 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for predicting the interaction energies at the protein–protein interface. Results Along SARS-CoV-2 mutation database screening and mutation localization analysis, it was ascertained that the most dangerous mutations at VoC/VoI spike proteins are located mainly at three regions of the SARS-CoV-2 spike “boat-shaped” receptor binding motif, on the RBD domain. Notably, the P.1 Japan/Brazil variant present three mutations, K417T, E484K, N501Y, located along the entire receptor binding motif, which apparently determines the highest interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, among those calculated. Conversely, it was also observed that the replacement of a single acidic/hydrophilic residue with a basic residue (E484K or N439K) at the “stern” or “bow” regions, of the boat-shaped receptor binding motif on the RBD, appears to determine an interaction energy with ACE2 receptor higher than that observed with single mutations occurring at the “hull” region or with other multiple mutants. In addition, our pipeline allowed searching for ACE2 structurally related proteins, i.e., THOP1 and NLN, which deserve to be investigated for their possible involvement in interactions with the SARS-CoV-2 spike protein, in those tissues showing a low expression of ACE2, or as a novel receptor for future spike variants. A freely available web-tool for the in silico calculation of the interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, starting from the sequences of the investigated spike and/or ACE2 variants, was made available for the scientific community at: https:// www. mitoa irm. it/ covid 19aff​initi es. Conclusion In the context of the PPPM/3PM, the employment of the described pipeline through the provided webservice, together with the ongoing SARS-CoV-2 genomic sequencing, would help to predict the transmissibility of new variants sequenced from future patients, depending on SARS-CoV-2 genomic sequencing activities and on the specific amino acid replacement and/or on its location on the SARS-CoV-2 spike RBD, to put in play all the possible counteractions for preventing the most deleterious scenarios of new outbreaks, taking into consideration that a greater transmissibility has not to be necessarily related to a more severe manifestation of the disease

Identification and characterisation of tomato torrado virus, a new plant picorna-like virus from tomato

A new virus was isolated from tomato plants from the Murcia region in Spain which showed symptoms of ‘torrado disease’ very distinct necrotic, almost burn-like symptoms on leaves of infected plants. The virus particles are isometric with a diameter of approximately 28 nm. The viral genome consists of two (+)ssRNA molecules of 7793 (RNA1) and 5389 nts (RNA2). RNA1 contains one open reading frame (ORF) encoding a predicted polyprotein of 241 kDa that shows conserved regions with motifs typical for a protease-cofactor, a helicase, a protease and an RNA-dependent RNA polymerase. RNA2 contains two, partially overlapping ORFs potentially encoding proteins of 20 and 134 kDa. These viral RNAs are encapsidated by three proteins with estimated sizes of 35, 26 and 23 kDa. Direct protein sequencing mapped these coat proteins to ORF2 on RNA2. Phylogenetic analyses of nucleotide and derived amino acid sequences showed that the virus is related to but distinct from viruses belonging to the genera Sequivirus, Sadwavirus and Cheravirus. This new virus, for which the name tomato torrado virus is proposed, most likely represents a member of a new plant virus genus

Cervical cancer benefits from trabectedin combination with the β-blocker propranolol: in vitro and ex vivo evaluations in patient-derived organoids

Background: Cervical cancer (CC) is characterized by genomic alterations in DNA repair genes, which could favor treatment with agents causing DNA double-strand breaks (DSBs), such as trabectedin. Hence, we evaluated the capability of trabectedin to inhibit CC viability and used ovarian cancer (OC) models as a reference. Since chronic stress may promote gynecological cancer and may hinder the efficacy of therapy, we investigated the potential of targeting β-adrenergic receptors with propranolol to enhance trabectedin efficacy and change tumor immunogenicity.Methods: OC cell lines, Caov-3 and SK-OV-3, CC cell lines, HeLa and OV2008, and patient-derived organoids were used as study models. MTT and 3D cell viability assays were used for drug(s) IC50 determination. The analysis of apoptosis, JC-1 mitochondrial membrane depolarization, cell cycle, and protein expression was performed by flow cytometry. Cell target modulation analyses were carried out by gene expression, Western blotting, immunofluorescence, and immunocytochemistry.Results: Trabectedin reduced the proliferation of both CC and OC cell lines and notably of CC patient-derived organoids. Mechanistically, trabectedin caused DNA DSBs and S-phase cell cycle arrest. Despite DNA DSBs, cells failed the formation of nuclear RAD51 foci and underwent apoptosis. Under norepinephrine stimulation, propranolol enhanced trabectedin efficacy, further inducing apoptosis through the involvement of mitochondria, Erk1/2 activation, and the increase of inducible COX-2. Notably, trabectedin and propranolol affected the expression of PD1 in both CC and OC cell lines.Conclusion: Overall, our results show that CC is responsive to trabectedin and provide translational evidence that could benefit CC treatment options. Our study pointed out that combined treatment offset trabectedin resistance caused by β-adrenergic receptor activation in both ovarian and cervical cancer models

Transcriptomic analysis of nickel exposure in Sphingobium sp. ba1 cells using RNA-seq

Nickel acts as cofactor for a number of enzymes of many bacteria species. Its homeostasis is ensured by proteins working as ion efflux or accumulation systems. These mechanisms are also generally adopted to counteract life-threatening high extra-cellular Ni2+concentrations. Little is known regarding nickel tolerance in the genus Sphingobium. We studied the response of the novel Sphingobium sp. ba1 strain, able to adapt to high Ni2+concentrations. Differential gene expression in cells cultured in 10 mM Ni2+, investigated by RNA-seq analysis, identified 118 differentially expressed genes. Among the 90 up-regulated genes, a cluster including genes coding for nickel and other metal ion efflux systems (similar to either cnrCBA, nccCBA or cznABC) and for a NreB-like permease was found. Comparative analyses among thirty genomes of Sphingobium species show that this cluster is conserved only in two cases, while in the other genomes it is partially present or even absent. The differential expression of genes encoding proteins which could also work as Ni2+-accumulators (HupE/UreJ-like protein, NreA and components of TonB-associated transport and copper-homeostasis systems) was also detected. The identification of Sphingobium sp. ba1 strain adaptive mechanisms to nickel ions, can foster its possible use for biodegradation of poly-aromatic compounds in metal-rich environments