Smallpox vaccination-elicited antibodies cross-neutralize 2022-Monkeypox virus Clade II

Since early May 2022, some monkeypox virus (MPXV) infections have been reported from countries where the disease is not endemic. Within 2 months, the number of patients has increased extensively, becoming the most considerable MPXV outbreak described. Smallpox vaccines demonstrated high efficacy against MPXVs in the past and are considered a crucial outbreak control measure. However, viruses isolated during the current outbreak carry distinct genetic variations, and the cross-neutralizing capability of antibodies remains to be assessed. Here we report that serum antibodies elicited by first-generation smallpox vaccines can neutralize the current MPXV more than 40 years after vaccine administration

Potential impact of a microarray-based nucleic acid assay for rapid detection of gram-negative bacteria and resistance markers in positive blood cultures

We evaluated the Verigene Gram-negative blood culture (BC-GN) test, a microarray that detects Gram-negative bacteria and several resistance genes. A total of 102 positive blood cultures were tested, and the BC-GN test correctly identified 97.9% of the isolates within its panel. Resistance genes (CTX-M, KPC, VIM, and OXA genes) were detected in 29.8% of the isolates, with positive predictive values of 95.8% (95% confidence interval [CI], 87.7% to 98.9%) in Enterobacteriaceae and 100% (95% CI, 75.9% to 100%) in Pseudomonas aeruginosa and negative predictive values of 100% (95% CI, 93.9% to 100%) and 78.6% (95% CI, 51.0% to 93.6%), respectively

Lower Bounds for Structuring Unreliable Radio Networks

In this paper, we study lower bounds for randomized solutions to the maximal independent set (MIS) and connected dominating set (CDS) problems in the dual graph model of radio networks---a generalization of the standard graph-based model that now includes unreliable links controlled by an adversary. We begin by proving that a natural geographic constraint on the network topology is required to solve these problems efficiently (i.e., in time polylogarthmic in the network size). We then prove the importance of the assumption that nodes are provided advance knowledge of their reliable neighbors (i.e, neighbors connected by reliable links). Combined, these results answer an open question by proving that the efficient MIS and CDS algorithms from [Censor-Hillel, PODC 2011] are optimal with respect to their dual graph model assumptions. They also provide insight into what properties of an unreliable network enable efficient local computation.Comment: An extended abstract of this work appears in the 2014 proceedings of the International Symposium on Distributed Computing (DISC

Comparative fragility methods for seismic assessment of masonry buildings located in Muccia (Italy)

The current paper focuses on a sector of the historic centre of Muccia, in the district of Macerata (Italy), affected by the seismic sequence that involved Central Italy in 2016. The main goal is comparison, in terms of fragility curves, among two vulnerability assessment methodologies (empirical and mechanical). The study area has been structurally and typologically identified according to the Building Typology Matrix (BTM). Physical vulnerability analysis of the urban-sector was performed through application of an index-based method, specifically for masonry building aggregates. An isolated masonry building, damaged after the seismic sequences, has been selected as a case study. For the assessed building, empirical fragility curves are presented according to Guagenti & Petrini’s correlation law. Furthermore, a numerical model has been set up by using the macro-element approach, which has allowed to perform non-linear static analyses. Mechanical properties of masonry were defined according to the New Technical Codes for Constructions (NTC18), assuming a limited knowledge level (LC1). Refined mechanical fragility functions have been derived and compared to the empirical ones. Analysis results have shown that the empirical method tends to overestimate by 5% and 10% the expected damage for slight and moderate thresholds. For PGA values greater than 0,3 g the damage levels decreased by 30% and 20%, with reference to the near collapse and collapse conditions, respectively

Impact of ART Use on Labour Force Participation among PLWHA Using ART in Southern Highlands HIV/AIDS Program in Tanzania

This is the retrospective cohort study which was conducted to analyse the impact of ART on labour force participation by 2829 PLWHA using ART at in Tanzania from 2005 to 2011. Quantitative method of research was applied and review of patients’ record was used to collect data. The results revealed that 92.4% of PLWHA registered on ART belong to working age group i.e. 15 – 65 years old (t-statistical value = 4.9 and p - value = 0.0002). There were 92.0% PLWHA who were able to work before ART, but labour force increased to 99.5% after PLWHA initiated on ART (correlation coefficient, r = 0.999, p-value < 0.001). The researcher concluded that majority of PLWHA using ART belongs to the working age group, and ART increases PLWHA labour force participation .The researcher therefore recommended that ART is worth continuing on with the universal population coverage. The study has some limitations as it assessed only one benefits of ART that is labour force participation of PLWHA. Key words: PLWHA, Antiretroviral therapy, labour force participation, resource limited settin

Naringenin is a powerful inhibitor of SARS-CoV-2 infection in vitro

Recently, an interesting review appeared in Pharmacological Research presented a list of candidate drugs against SARS-CoV-2 and COVID-19 [1]. In the present insight, we highlight novel experimental evidence that the flavanone Naringenin, targeting the endo-lysosomal Two-Pore Channels (TPCs), could be added to the list of potential weapons against SARS-CoV-2 infection and COVID-19 disease

Discontinuous vs continuous approaches for the nonlinear dynamics of an historic masonry tower

The present paper investigates, from an advanced numerical point of view, the progressive damage of the Amatrice (Rieti, Italy) civic clock tower, after a long sequence of strong earthquakes that struck Central Italy in 2016. Two advanced numerical models are here used to provide an insight into the modalities of progressive damage and the behaviour of the structure under strong dynamic excitations, namely a Discrete Element Method (DEM), the Non-Smooth Contact Dynamics (NSCD) method, and a FE Concrete Damage Plasticity (CDP) model. In both cases, a full 3D detailed discretization is adopted. From the numerical results, the role played by both the actual geometries and the insufficient resistance of the constituent materials are envisaged, showing a good match with actual crack patterns observed after the seismic sequence

Clinical characterization and whole genome sequence-based typing of two cases of endophthalmitis due to Listeria monocytogenes

Endophthalmitis due to Listeria monocytogenes is a rare form of listeriosis. Here, we report two cases that occurred in patients with different medical history, a 46-years-old woman with no comorbidities and an elderly man with several comorbidities. There was no history of trauma or surgery in either patient suggesting an endogenous origin. Despite antibiotic treatment, both patients showed poor visual acuity outcomes. Subtyping clinical isolates using whole genome sequencing could allow to characterise Listeria monocytogenes strains involved in rare clinical manifestation, such as in unusual anatomical sites, even in immunocompetent patients

Dual-domain reporter approach for multiplex identification of major SARS-CoV-2 variants of concern in a microarray-based assay

: Since the emergence of the COVID-19 pandemic in December 2019, the SARS-CoV-2 virus continues to evolve into many variants emerging around the world. To enable regular surveillance and timely adjustments in public health interventions, it is of the utmost importance to accurately monitor and track the distribution of variants as rapidly as possible. Genome sequencing is the gold standard for monitoring the evolution of the virus, but it is not cost-effective, rapid and easily accessible. We have developed a microarray-based assay that can distinguish known viral variants present in clinical samples by simultaneously detecting mutations in the Spike protein gene. In this method, the viral nucleic acid, extracted from nasopharyngeal swabs, after RT-PCR, hybridizes in solution with specific dual-domain oligonucleotide reporters. The domains complementary to the Spike protein gene sequence encompassing the mutation form hybrids in solution that are directed by the second domain ("barcode" domain) at specific locations on coated silicon chips. The method utilizes characteristic fluorescence signatures to unequivocally differentiate, in a single assay, different known SARS-CoV-2 variants. In the nasopharyngeal swabs of patients, this multiplex system was able to genotype the variants which have caused waves of infections worldwide, reported by the WHO as being of concern (VOCs), namely Alpha, Beta, Gamma, Delta and Omicron variants

Random walks on randomly evolving graphs

A random walk is a basic stochastic process on graphs and a key primitive in the design of distributed algorithms. One of the most important features of random walks is that, under mild conditions, they converge to a stationary distribution in time that is at most polynomial in the size of the graph. This fundamental property, however, only holds if the graph does not change over time; on the other hand, many distributed networks are inherently dynamic, and their topology is subjected to potentially drastic changes. In this work we study the mixing (i.e., convergence) properties of random walks on graphs subjected to random changes over time. Specifically, we consider the edge-Markovian random graph model: for each edge slot, there is a two-state Markov chain with transition probabilities p (add a non-existing edge) and q (remove an existing edge). We derive several positive and negative results that depend on both the density of the graph and the speed by which the graph changes