Search

BackgroundStaging of melanoma and follow up after melanoma diagnosis aims at predicting risk and detecting progression or recurrence at early stage, respectively in order to timely start and/or change treatment. Tumor thickness according to Breslow, status of the sentinel node and value of the lactate dehydrogenase (LDH) are well-established prognostic markers for metastatic risk, but reliable biomarkers identifying early recurrence or candidates who may benefit best from medical treatment are still warranted. Liquid biopsy has emerged to be a suitable method for identifying biomarkers for early cancer diagnosis, prognosis, therapeutic response prediction, and patient follow-up. Liquid biopsy is a blood-based non-invasive procedure that allows analyzing circulating analytes, including extracellular vesicles.MethodsIn this study we have explored the use of 7 miRNAs, namely hsa-miR-149-3p, hsa-miR-150-5p, hsa-miR-21-5p, hsa-miR-200c-3p, hsa-miR-134-5p, hsa-miR-144-3p and hsa-miR-221-3p in plasma exosomes to discriminate melanoma patients from controls without melanoma in a cohort of 92 individuals.Results and discussionOur results showed that three out seven miRNAs, namely hsa-miR-200c-3p, hsa-miR-144-3p and hsa-miR-221-3p were differentially expressed in plasma-derived exosomes from melanoma patients and controls. Furthermore, the expression of the three miRNAs may be a promising ancillary tool as a melanoma biomarker, even for discriminating between nevi and melanoma.

Granuloma faciale (GF) is a rare benign chronic inflammatory dermatosis often difficult to distinguish clinically from other diseases, both inflammatory and neoplastic. Dermoscopy can be a helpful diagnostic tool and indeed several dermoscopic criteria observed in GF have been described in literature. We present two patients affected by GF in which we have observed rosettes.

Particle acceleration is a fundamental process arising in many astrophysical objects, including active galactic nuclei, black holes, neutron stars, gamma-ray bursts, accretion disks, solar and stellar coronae, and planetary magnetospheres. Its ubiquity means energetic particles permeate the Universe and influence the conditions for the emergence and continuation of life. In our solar system, the Sun is the most energetic particle accelerator, and its proximity makes it a unique laboratory in which to explore astrophysical particle acceleration. However, despite its importance, the physics underlying solar particle acceleration remain poorly understood. The SPARK mission will reveal new discoveries about particle acceleration through a uniquely powerful and complete combination of γ-ray, X-ray, and EUV imaging and spectroscopy at high spectral, spatial, and temporal resolutions. SPARK’s instruments will provide a step change in observational capability, enabling fundamental breakthroughs in our understanding of solar particle acceleration and the phenomena associated with it, such as the evolution of solar eruptive events. By providing essential diagnostics of the processes that drive the onset and evolution of solar flares and coronal mass ejections, SPARK will elucidate the underlying physics of space weather events that can damage satellites and power grids, disrupt telecommunications and GPS navigation, and endanger astronauts in space. The prediction of such events and the mitigation of their potential impacts are crucial in protecting our terrestrial and space-based infrastructure.

Models of particle acceleration in solar eruptive events suggest that roughly equal energy may go into accelerating electrons and ions. However, while previous solar X-ray spectroscopic imagers have transformed our understanding of electron acceleration, only one resolved image of γ-ray emission from solar accelerated ions has ever been produced. This paper outlines a new satellite instrument concept—the large imaging spectrometer for solar accelerated nuclei (LISSAN)—with the capability not only to observe hundreds of events over its lifetime, but also to capture multiple images per event, thereby imaging the dynamics of solar accelerated ions for the first time. LISSAN provides spectroscopic imaging at photon energies of 40 keV–100 MeV on timescales of ≲10 s with greater sensitivity and imaging capability than its predecessors. This is achieved by deploying high-resolution scintillator detectors and indirect Fourier imaging techniques. LISSAN is suitable for inclusion in a multi-instrument platform such as an ESA M-class mission or as a smaller standalone mission. Without the observations that LISSAN can provide, our understanding of solar particle acceleration, and hence the space weather events with which it is often associated, cannot be complete.

In recent years, targeted (biological) therapies have become available also for primary cutaneous T-cell lymphomas (PCTCLs) including anti-CD30 (brentuximab vedotin) in mycosis fungoides, primary cutaneous anaplastic large T-cell lymphoma, lymphomatoid papulosis; anti-CCR4 (mogamulizumab) in Sezary syndrome; anti-CD123 (tagraxofusp) in blastic plasmocytoid cell neoplasm. Moreover, anti-PD1 (nivolumab), anti-PDL1 (pembrolizumab, atezolizumab), anti-CD52 (alemtuzumab), anti-KIR3DL2-CD158k (lacutamab), and anti-CD70 (cusatuzumab) have been tested or are under investigations in phase II trials. The expression of these epitopes on neoplastic cells in skin biopsies or blood samples plays a central role in the management of PCTCL patients. This narrative review aims to provide readers with an update on the latest advances in the newest therapeutic options for PCTCLs.

Abstract Reinforced concrete structural walls (RCSWs) are one of the most efficient lateral force-resisting systems used in buildings, providing sufficient strength, stiffness, and deformation capacities to withstand the forces generated during earthquake ground motions. Identifying the failure mode of the RCSWs is a critical task that can assist engineers and designers in choosing appropriate retrofitting solutions. This study evaluates the efficiency of three ensemble deep neural network models, including the model averaging ensemble, weighted average ensemble, and integrated stacking ensemble for predicting the failure mode of the RCSWs. The ensemble deep neural network models are compared against previous studies that used traditional well-known ensemble models (AdaBoost, XGBoost, LightGBM, CatBoost) and traditional machine learning methods (Naïve Bayes, K-Nearest Neighbors, Decision Tree, and Random Forest). The weighted average ensemble model is proposed as the best-suited prediction model for identifying the failure mode since it has the highest accuracy, precision, and recall among the alternative models. In addition, since complex and advanced machine learning-based models are commonly referred to as black-box, the SHapley Additive exPlanation method is also used to interpret the model workflow and illustrate the importance and contribution of the components that impact determining the failure mode of the RCSWs.

In September 2021 on the platform of the Italian Association of Hospital Dermatologists (ADOI; https://www.adoi.it/) a monthly on-line live session of teledermatopathology was started involving collegial discussion among experienced Italian pathologists about challenging melanocytic tumors using the virtual microscope [...].

Background: Multicomponent interventions based on a comprehensive geriatric assessment (CGA) could promote active aging and improve health status in older people with Noncommunicable Chronic Diseases (NCDs), but conflicting evidences are available. Aim: To evaluate the efficacy of a CGA-based multicomponent personalized preventive program (PPP) in reducing unplanned hospitalization rates during 12-month follow-up in community-dwelling older people with NCDs. Materials and methods: In this randomized clinical trial (RCT), 1216 older adults recruited by 33 general practitioners (GPs) will be randomly allocated to intervention group (IG) or usual care control group (CG). The IG will receive a multicomponent PPP developed on the findings of the CGA-based Multidimensional Prognostic Index short-form (Brief-MPI), including structured interventions to improve functional, physical, cognitive, and nutritional status, to monitor NCDs and vaccinations, and to prevent social isolation. Participants in the CG will receive usual care. Brief-MPI, resilience, and health-related quality of life will be assessed after 6 and 12 months. Moreover, saliva samples will be collected at baseline in IG to measure biomarkers of oxidative stress, inflammatory cytokines, and oral microbiome. Expected results: The CGA-based PPP might reduce unplanned hospitalization rates and potentially institutionalization rates, emergency department (ED) and unplanned GP visits, and mortality. Further outcomes explored in the IG will be the adherence to PPP, resilience, health-related quality of life, and multidimensional frailty as assessed by the Brief-MPI. Conclusions: Results will suggest whether the CGA-based multicomponent PPP is able to improve specific outcomes in a primary care setting. Trial registration: ClinicalTrials.gov; identifier: NCT06224556; Registered January 25, 2024. [ABSTRACT FROM AUTHOR]

This Letter reports the first observational estimate of the heating rate in the slowly expanding solar corona. The analysis exploits the simultaneous remote and local observations of the same coronal plasma volume, with the Solar Orbiter/Metis and the Parker Solar Probe instruments, respectively, and relies on the basic solar wind magnetohydrodynamic equations. As expected, energy losses are a minor fraction of the solar wind energy flux, since most of the energy dissipation that feeds the heating and acceleration of the coronal flow occurs much closer to the Sun than the heights probed in the present study, which range from 6.3 to 13.3 R _⊙ . The energy deposited to the supersonic wind is then used to explain the observed slight residual wind acceleration and to maintain the plasma in a nonadiabatic state. As derived in the Wentzel–Kramers–Brillouin limit, the present energy transfer rate estimates provide a lower limit, which can be very useful in refining the turbulence-based modeling of coronal heating and subsequent solar wind acceleration.

This case was presented at the on-line telepathology meeting on the ADOI platform held on October 19th 2022 by Dr Luongo.

Here, we present a set of algorithms using the Python programming language, that will allow using a routine for object detection and tracking in experimental videos. We developed a script, under the fundamentals of background subtraction and image thresholding (using the OpenCV package), that makes it possible to track a wide spectrum of animals under different conditions. We have validated this script through testing on semi-terrestrial and aquatic crustacean species and under different experimental scenarios (laboratory and field sampling and using video created under nocturnal and diurnal conditions). The open-source nature of the script allows for flexibility and scalability, so it can be easily customized and is thus transferable to other species/experiments in the context of behavioral ecology. The tracking script is easy customizable and free alternative to commercial video tracking systems and therefore, applicable to a wide variety of both educational and research programs.

ABSTRACT Firewood is still a major source of household energy in most parts of the world, including Brazil. This study establishes baseline fuelwood consumption for domestic cooking by rural families in Bahia, Brazil, as part of a socioenvironmental project centered on stove substitution. The project, titled “Fogão do Mar” (Seaside Stove), engaged families in adopting more efficient stoves to replace the traditional open-air, rudimentary models. The study involved household visits and interviews with 103 low-income rural families to estimate firewood consumption for domestic cooking. The results showed that all households have liquid petroleum gas (LPG) stove, but most of the families prefer to use a firewood stove for cooking. The annual per capita consumption of firewood was estimated to be 1,297±952 kg, which is higher than estimate by governmental data (560 kg), as well as other rural regions. Therefore, the consumption of firewood is regionalized. Economic factors are decisive in the choice of fuel for cooking.