Cerebro-costo-mandibular syndrome: Report of two cases

AbstractCerebro-costo-mandibular syndrome (CCMS) is a rare syndrome that includes a constellation of mandibular hypoplasia and posterior rib defects as its basic features. Additional features can include hearing loss, tracheal cartilage abnormalities, scoliosis, elbow hypoplasia, and spina bifida. Here we report two cases of CCMS and discuss the reported long-term outcome of the disease

Verifying liquidity of recursive Bitcoin contracts

Smart contracts - computer protocols that regulate the exchange of crypto-assets in trustless environments - have become popular with the spread of blockchain technologies. A landmark security property of smart contracts is liquidity: in a non-liquid contract, it may happen that some assets remain frozen, i.e. not redeemable by anyone. The relevance of this issue is witnessed by recent liquidity attacks to Ethereum, which have frozen hundreds of USD millions. We address the problem of verifying liquidity on BitML, a DSL for smart contracts with a secure compiler to Bitcoin, featuring primitives for currency transfers, contract renegotiation and consensual recursion. Our main result is a verification technique for liquidity. We first transform the infinite-state semantics of BitML into a finite-state one, which focusses on the behaviour of a chosen set of contracts, abstracting from the moves of the context. With respect to the chosen contracts, this abstraction is sound, i.e. if the abstracted contract is liquid, then also the concrete one is such. We then verify liquidity by model-checking the finite-state abstraction. We implement a toolchain that automatically verifies liquidity of BitML contracts and compiles them to Bitcoin, and we assess it through a benchmark of representative contracts.Comment: arXiv admin note: text overlap with arXiv:2003.0029

A general framework for blockchain analytics

Modern cryptocurrencies exploit decentralised blockchains to record a public and unalterable history of transactions. Besides transactions, further information is stored for different, and often undisclosed, purposes, making the blockchains a rich and increasingly growing source of valuable information, in part of difficult interpretation. Many data analytics have been developed, mostly based on specifically designed and ad-hoc engineered approaches.We propose a general-purpose framework, seamlessly supporting data analytics on both Bitcoin and Ethereum — currently the two most prominent cryptocurrencies. Such a framework allows us to integrate relevant blockchain data with data from other sources, and to organise them in a database, either SQL or NoSQL. Our framework is released as an open-source Scala library. We illustrate the distinguishing features of our approach on a set of significant use cases, which allow us to empirically compare ours to other competing proposals, and evaluate the impact of the database choice on scalability

Verifying liquidity of recursive Bitcoin contracts

Smart contracts - computer protocols that regulate the exchange of crypto-assets in trustless environments - have become popular with the spread of blockchain technologies. A landmark security property of smart contracts is liquidity: in a non-liquid contract, it may happen that some assets remain frozen, i.e. not redeemable by anyone. The relevance of this issue is witnessed by recent liquidity attacks to Ethereum, which have frozen hundreds of USD millions. We address the problem of verifying liquidity on BitML, a DSL for smart contracts with a secure compiler to Bitcoin, featuring primitives for currency transfers, contract renegotiation and consensual recursion. Our main result is a verification technique for liquidity. We first transform the infinite-state semantics of BitML into a finite-state one, which focusses on the behaviour of a chosen set of contracts, abstracting from the moves of the context. With respect to the chosen contracts, this abstraction is sound, i.e. if the abstracted contract is liquid, then also the concrete one is such. We then verify liquidity by model-checking the finite-state abstraction. We implement a toolchain that automatically verifies liquidity of BitML contracts and compiles them to Bitcoin, and we assess it through a benchmark of representative contracts

Successful Treatment of Bloodstream Infection due to a KPC-Producing Klebsiella Pneumoniae Resistant to Imipenem/Relebactam in a Hematological Patient

Novel carbapenem-β-lactamase inhibitor combination, imipenem/relebactam (IMI-REL), has been recently approved for treatment of infections with limited or no alternative treatment options. In this study, we described the emergence of the IMI-REL-resistance in a KPC-producing Klebsiella pneumoniae (KPC-Kp) strain collected from a hematological patient with no evidence of prior colonization. Interestingly, IMI-REL-resistance was associated with meropenem/vaborbactam (MER-VAB) cross-resistance but was not associated with cross-resistance to ceftazidime/avibactam (CAZ-AVI). Although treatment with CAZ-AVI and gentamicin completely eradicated the infection due KPC-Kp cross-resistance to IMI-REL and MER-VAB, the patient became colonized subsequently by KPC-Kp strains susceptible to IMI-REL and MER-VAB. Whole-genome sequencing performed by hybrid approach using Illumina and Oxford Nanopore platforms demonstrated that all KPC-Kp strains isolated from hematological patient belonged to the ST512 and were clonally related. Analysis of antimicrobial and porins genes demonstrated that cross-resistance to IMI-REL and MER-VAB was associated with increased blaKPC-3 copy number and truncated OmpK35 and OmpK36 with GD134-135 insertion. Phylogenetic analysis demonstrated that KPC-Kp cross-resistance to IMI-REL and MER-VAB was clonally related to a KPC-Kp resistant to IMI-REL as previously described, demonstrating the spread of this multidrug resistant clone in the hematological unit. In conclusion, the results presented in this study reported the emergence of cross-resistance to MER-VAB and IMI-REL in a KPC-Kp strain isolated from a hematological patient and highlight the potential development and diffusion of new multidrug resistance traits

Gastrin-Releasing Peptide Receptor in Low Grade Prostate Cancer: Can It Be a Better Predictor Than Prostate-Specific Membrane Antigen?

The aim of the present study was to evaluate whether prostate cancer (PC) patients can be accurately classified on the bases of tissue expression of gastrin-releasing peptide receptor (GRPR) and prostate-specific membrane antigen (PSMA). This retrospective study included 28 patients with PC. Formalin-fixed paraffin-embedded samples were used for diagnosis. Immunohistochemistry staining techniques were used to evaluate PSMA and GRPR expression (both number of cells expressed and % of area stained). To assess the independent associations among selected variables, a multi-dimensional scaling (MDS) analysis was used. It was found that the PSMA expression was inversely correlated with GRPR expression. Only the number of cells expressing GRPR was significantly related to the Gleason score. Both the percentage of area expressing GRPR and the number of cells expressing PSMA were close to reaching significance at the 0.05 level. MDS provided a map of the overall, independent association confirming that GRPR and PSMA represent inversely correlated measures of the same dimension. In conclusion, our data showed that GRPR expression should be evaluated in prostate biopsy specimens to improve our ability to detect PC with low grades at the earliest phases of development. Considering that GRPRs appear to be directly involved in the mechanisms of tumor proliferation, advancements in nuclear medicine radiotherapy can focus on this receptor to improve the therapeutic approach to PC. Further studies in our laboratory will investigate the molecular mechanisms of activation based on GRPR