Multimodal Non-Extensive Frequency-Magnitude Distributions and Their Relationship to Multi-Source Seismicity.

We investigate multimodal seismicity by analyzing it as the result of multiple seismic sources. We examine three case studies: the Redoubt and Spurr regions in Alaska, where volcanic and subduction-related seismicity occur, and the Kii Peninsula in Japan, where shallow and deep earthquakes are clearly separated. To understand this phenomenon, we perform spatial, temporal, and magnitude analyses.

Specialist training in infectious diseases in Europe.

Objectives: The objectives were to determine the structure of training programmes and assessment of physicians training to become infectious disease (ID) specialists in Europe in early 2024, and to document the provision of specialists, trainees and training centres in each country.

Methods: Delegates to the ID Section and Board of the European Union of Medical Specialists (UEMS) entered national data on a web-based survey tool in late 2023-early 2024. Results were compared to UEMS recommendations on the structure and content of postgraduate training in ID in Europe (2018), and to results of a similar survey in early 2021.

Mal'aria in the Republic of Ireland; A retrospective review of the clinical epidemiology of mal'aria between 2016 and 2020.

Objectives: Mal'aria is a parasitic infection that continues to present significant morbidity and mortality figures throughout the world. In the Republic of Ireland (Ireland), mal'aria is an imported infection linked most frequently to travel routes from West Africa. There is a paucity of data on the clinical epidemiology and hospital service utilization of mal'aria in non-endemic setting to inform physician practice.

Robust and persistent B-cell responses following SARS-CoV-2 vaccine determine protection from SARS-CoV-2 infection.

Introduction: A clear immune correlate of protection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been defined. We explored antibody, B-cell, and T-cell responses to the third-dose vaccine and relationship to incident SARS-CoV-2 infection.

Methods: Adults in a prospective cohort provided blood samples at day 0, day 14, and 10 months after the third-dose SARS-CoV-2 vaccine.

Early inflammatory profiles predict maximal disease severity in COVID-19: An unsupervised cluster analysis.

Background: The inflammatory changes that underlie the heterogeneous presentations of COVID-19 remain incompletely understood. In this study we aimed to identify inflammatory profiles that precede the development of severe COVID-19, that could serve as targets for optimised delivery of immunomodulatory therapies and provide insights for the development of new therapies.

Methods: We included individuals sampled <10 days from COVID-19 symptom onset, recruited from both inpatient and outpatient settings.

Misidentification of as species: potential pitfalls in the diagnosis of brucellosis.

We describe a case of brucellosis in a man in his 20s, who presented to the emergency department with a 1-month history of fevers, dry cough and knee pain. Blood cultures were positive after 55 hours and was identified on matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometry. spp are Gram-negative organisms that are phylogenetically related to spp but commercially available MALDI-TOF libraries cannot distinguish between the two genera.

A Multinational Case Series Describing Successful Treatment of Persistent Severe Acute Respiratory Syndrome Coronavirus 2 Infection Caused by Omicron Sublineages With Prolonged Courses of Nirmatrelvir/Ritonavir.

The optimum treatment for persistent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is not known. Our case series, across 5 hospitals in 3 countries, describes 11 cases where persistent SARS-CoV-2 infection was successfully treated with prolonged courses (median, 10 days [range, 10-18 days]) of nirmatrelvir/ritonavir (Paxlovid). Most cases (9/11) had hematological malignancy and 10 (10/11) had received CD20-depleting therapy.

Development of a novel medium throughput flow-cytometry based micro-neutralisation test for SARS-CoV-2 with applications in clinical vaccine trials and antibody screening.

Quantifying neutralising capacity of circulating SARS-COV-2 antibodies is critical in evaluating protective humoral immune responses generated post-infection/post-vaccination. Here we describe a novel medium-throughput flow cytometry-based micro-neutralisation test to evaluate Neutralising Antibody (NAb) responses against live SARS-CoV-2 Wild Type and Variants of Concern (VOC) in convalescent/vaccinated populations. Flow Cytometry-Based Micro-Neutralisation Test (Micro-NT) was performed in 96-well plates using clinical isolates WT-B, WT-B.

Associations between host microbiome and inflammation suggest role for host microbiome in driving COVID-19 disease severity.

Systemic inflammation and innate immune activation are associated with COVID-19 disease severity. Knowledge gaps remain in the relationships between microbiome, inflammation and COVID-19 disease severity. To better characterise these associations, we performed 16SrDNA analysis of stool samples in COVID-19 subjects to explore diversity and taxanomic composition.

Distinct receptor binding domain IgG thresholds predict protective host immunity across SARS-CoV-2 variants and time.

SARS-CoV-2 neutralising antibodies provide protection against COVID-19. Evidence from early vaccine trials suggested binding antibody thresholds could serve as surrogate markers of neutralising capacity, but whether these thresholds predict sufficient neutralising capacity against variants of concern (VOCs), and whether this is impacted by vaccine or infection history remains unclear. Here we analyse individuals recovered from, vaccinated or with hybrid immunity against SARS-CoV-2.

A Graph-Space Optimal Transport Approach Based on Kaniadakis -Gaussian Distribution for Inverse Problems Related to Wave Propagation.

Data-centric inverse problems are a process of inferring physical attributes from indirect measurements. Full-waveform inversion (FWI) is a non-linear inverse problem that attempts to obtain a quantitative physical model by comparing the wave equation solution with observed data, optimizing an objective function. However, the FWI is strenuously dependent on a robust objective function, especially for dealing with cycle-skipping issues and non-Gaussian noises in the dataset.

Dysregulated early transcriptional signatures linked to mast cell and interferon responses are implicated in COVID-19 severity.

Background: Dysregulated immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are thought to underlie the progression of coronavirus disease 2019 (COVID-19) to severe disease. We sought to determine whether early host immune-related gene expression could predict clinical progression to severe disease.

Methods: We analysed the expression of 579 immunological genes in peripheral blood mononuclear cells taken early after symptom onset using the NanoString nCounter and compared SARS-CoV-2 negative controls with SARS-CoV-2 positive subjects with mild (SARS+ Mild) and Moderate/Severe disease to evaluate disease outcomes.

A soil fungus confers plant resistance against a phytophagous insect by disrupting the symbiotic role of its gut microbiota.

Plants generate energy flows through natural food webs, driven by competition for resources among organisms, which are part of a complex network of multitrophic interactions. Here, we demonstrate that the interaction between tomato plants and a phytophagous insect is driven by a hidden interplay between their respective microbiotas. Tomato plants colonized by the soil fungus , a beneficial microorganism widely used in agriculture as a biocontrol agent, negatively affects the development and survival of the lepidopteran pest by altering the larval gut microbiota and its nutritional support to the host.

Full-waveform inversion based on generalized Rényi entropy using patched Green's function techniques.

The estimation of physical parameters from data analyses is a crucial process for the description and modeling of many complex systems. Based on Rényi α-Gaussian distribution and patched Green's function (PGF) techniques, we propose a robust framework for data inversion using a wave-equation based methodology named full-waveform inversion (FWI). From the assumption that the residual seismic data (the difference between the modeled and observed data) obeys the Rényi α-Gaussian probability distribution, we introduce an outlier-resistant criterion to deal with erratic measures in the FWI context, in which the classical FWI based on l2-norm is a particular case.

Educational Data Virtual Lab: Connecting the Dots Between Data Visualization and Analysis.

Educational Data Virtual Lab (EDVL) is an open-source platform for data exploration and analysis that combines the power of a coding environment, the convenience of an interactive visualization engine, and the infrastructure needed to handle the complete data lifecycle. Based on the building blocks of the FIWARE European platform and Apache Zeppelin, this tool allows domain experts to become acquainted with data science methods using the data available within their own organization, ensuring that the skills they acquire are relevant to their field and driven by their own professional goals. We used EDVL in a pilot study in which we carried out a focus group within a multinational company to gain insight into potential users' perceptions of EDVL, both from the educational and operational points of view.

Ending tuberculosis: the cost of missing the World Health Organization target in a low-incidence country.

Background: Ending tuberculosis (TB) is a global priority and targets for doing so are outlined in the World Health Organization (WHO) End TB Strategy. For low-incidence countries, eliminating TB requires high levels of wealth, low levels of income inequality and effective TB programmes and services that can meet the needs of people who have not benefited from these and are still at risk of TB. In Ireland, numerous reports have noted a need for more funding for TB prevention and control.

Performance and validation of an adaptable multiplex assay for detection of serologic response to SARS-CoV-2 infection or vaccination.

Measurement of quantitative antibody responses are increasingly important in evaluating the immune response to infection and vaccination. In this study we describe the validation of a quantitative, multiplex serologic assay utilising an electrochemiluminescence platform, which measures IgG against the receptor binding domain (RBD), spike S1 and S2 subunits and nucleocapsid antigens of SARS-CoV-2. The assay displayed a sensitivity ranging from 73 to 91% and specificity from 90 to 96% in detecting previous infection with SARS-CoV-2 depending on antigenic target and time since infection, and this assay highly correlated with commercially available assays.

Isavuconazole Treatment of Spinal Cord Invasive Aspergillosis Guided by Cerebrospinal Fluid (1,3)-β-d-Glucan Levels in a Patient with Low Interferon-Gamma and Ulcerative Colitis.

This case highlights the use of (1,3)-beta-d glucan to direct treatment of a cervical spinal cord Aspergillus fumigatus infection in a 22-year-old woman immunocompromised due to steroid and anti-TNF therapy in the context of ulcerative colitis and interferon gamma deficiency. A 4-year treatment course requiring neurosurgical intervention on four occasions and prolonged antifungal therapy, including isavuconazole, resulted in clinical cure with a corresponding decrease in CSF beta-d-glucan to <30 pg/mL. Serum and CSF galactomannan levels were not elevated at any point during the clinical course.

Not Only Systemin: Prosystemin Harbors Other Active Regions Able to Protect Tomato Plants.

Prosystemin is a 200-amino acid precursor expressed in Solanaceae plants which releases at the C-terminal part a peptidic hormone called Systemin in response to wounding and herbivore attack. We recently showed that Prosystemin is not only a mere scaffold of Systemin but, even when deprived of Systemin, is biologically active. These results, combined with recent discoveries that Prosystemin is an intrinsically disordered protein containing disordered regions within its sequence, prompted us to investigate the N-terminal portions of the precursor, which contribute to the greatest disorder within the sequence.

Antimicrobial neurotoxicity: an under-recognised cause of delirium.

Antimicrobial associated encephalopathy (AAE) is a well-documented, though under recognised, adverse event associated with antimicrobial use. Clinical manifestations of AAE are varied, ranging from myoclonus and seizure to an encephalopathy with cerebellar signs. The phenotypic presentation of the encephalopathy syndrome is, in general, governed by the antimicrobial in question.

Statistical Modeling of the Seismic Moments via Mathai Distribution.

Mathai's pathway model is playing an increasingly prominent role in statistical distributions. As a generalization of a great variety of distributions, the pathway model allows the studying of several non-linear dynamics of complex systems. Here, we construct a model, called the Pareto-Mathai distribution, using the fact that the earthquakes' magnitudes of full catalogues are well-modeled by a Mathai distribution.

Delayed Tuberculosis Treatment and Cost of Care in a Low-Incidence Country.

Background: Tuberculosis (TB) elimination requires high-quality, timely care. In countries with a low incidence of TB, such as Ireland, delayed diagnosis is common. This evaluation aimed to determine the factors that predict patient-related and health care provider-related delays in TB management and to establish how TB care cost is affected by care delays.

Identification of Distinct Long COVID Clinical Phenotypes Through Cluster Analysis of Self-Reported Symptoms.

Background: We aimed to describe the clinical presentation of individuals presenting with prolonged recovery from coronavirus disease 2019 (COVID-19), known as long COVID.

Methods: This was an analysis within a multicenter, prospective cohort study of individuals with a confirmed diagnosis of COVID-19 and persistent symptoms >4 weeks from onset of acute symptoms. We performed a multiple correspondence analysis (MCA) on the most common self-reported symptoms and hierarchical clustering on the results of the MCA to identify symptom clusters.