Search

Background: Pediatric high-grade gliomas (pHGGs) are the leading cause of mortality in pediatric neuro-oncology, displaying frequent resistance to standard therapies. Profiling DNA repair and cell cycle gene expression has recently been proposed as a strategy to classify adult glioblastomas. To improve our understanding of the DNA damage response pathways that operate in pHGGs and the vulnerabilities that these pathways might expose, we sought to identify and characterize a specific DNA repair and cell-cycle gene expression signature of pHGGs. Methods: Transcriptomic analyses were performed to identify a DNA repair and cell-cycle gene expression signature able to discriminate pHGGs (n = 6) from low-grade gliomas (n = 10). This signature was compared to related signatures already established. We used the pHGG signature to explore already transcriptomic datasets of DIPGs and sus-tentorial pHGGs. Finally, we examined the expression of key proteins of the pHGG signature in 21 pHGG diagnostic samples and nine paired relapses. Functional inhibition of one DNA repair factor was carried out in four patients who derived H3.3 K27M mutant cell lines. Results: We identified a 28-gene expression signature of DNA repair and cell cycle that clustered pHGGs cohorts, in particular sus-tentorial locations, in two groups. Differential protein expression levels of PARP1 and XRCC1 were associated to TP53 mutations and TOP2A amplification and linked significantly to the more radioresistant pHGGs displaying the worst outcome. Using patient-derived cell lines, we showed that the PARP-1/XRCC1 expression balance might be correlated with resistance to PARP1 inhibition. Conclusion: We provide evidence that PARP1 overexpression, associated to XRCC1 expression, TP53 mutations, and TOP2A amplification, is a new theranostic and potential therapeutic target.

Aims: This review aims to analyze the multiple factors affecting the staging of the orthodontic tooth movement during clear aligner treatment and to provide an efficient work methodology in this regard during digital treatment planning. Materials and Methods: A literature search was conducted on electronic databases (Pubmed, Scopus, Google Scholar and CNKI). The results of the present study have been divided into several sections: (1) definition and concept of staging, (2) basic principles of clear aligners, (3) macro-staging, (4) micro-staging, and (5) limitations. Results: The terminology of macro-staging and micro-staging proposed in this paper aims to be a first step towards a more detailed analysis of staging. The macro-staging constitutes the general biomechanics of movements that need to be prioritized to meet the objectives of the treatment plan. It provides a comprehensive view of the movements occurring in each dental arch. The micro-staging constitutes the biomechanics of movements for each individual tooth. This involves studying the movements in the different planes of space in which each tooth is programmed, deciding if they are compatible, and having strategies to create space to avoid lack of expression. Conclusions: Further studies should focus on exploring different staging approaches to address similar malocclusions to determine which are the most effective and applicable to clinical practice.

Infant meningitis remains a severe burden on global health, particularly for young infants. Traditional ultrasound imaging techniques are limited in spatial resolution to visualize white blood cells (WBCs) in the cerebrospinal fluid (CSF), which is considered a well-established marker for meningitis detection. This work presents a novel platform that uses high-resolution ultrasound to detect the backscatter signals from microscopic CSF WBCs through the anterior fontanelle of neonates and young infants. The whole system was built around a custom probe that allows for a 20 MHz focused transducer to be mechanically controlled to map the area of interest in the CSF. Data processing can be performed internally in the device without the need to extract the images for further analysis. The in vitro feasibility of the proposed solution was evaluated in imaging 7 μm particle suspensions at different concentrations relevant to meningitis diagnosis ranging from 7- to 646-particles (pp)/μL. The experimental tests were conducted from a simple setup using a sample container to a more realistic setup based on an anatomical phantom of the neonatal head. The results show high-quality images, where 7 μm particles can be resolved for the different concentrations.

The Internet of Medical Things (IoMT) extends the concept of eHealth and mHealth for patients with continuous monitoring requirements. This research concentrates on the use of wearable devices based on the use of inertial measurement units (IMUs) that account for a gait analysis for its use in three health cases, equilibrium evaluation, fall prevention and surgery recovery, that impact a large elderly population. We also analyze two different scenarios for data capture: supervised by clinicians and unsupervised during activities of daily life (ADLs). The continuous monitoring of patients produces large amounts of data that are analyzed in specific IoMT platforms that must be connected to the health system platforms containing the health records of the patients. The aim of this study is to evaluate the factors that impact the cost of the deployment of such an IoMT solution. We use population data from Catalonia together with an IoMT deployment model for costs from the current deployment of connected devices for monitoring diabetic patients. Our study reveals the critical dependencies of the proposed IoMT platforms: from the devices and cloud cost, the size of the population using these services and the savings from the current model under key parameters such as fall reduction or rehabilitation duration. Future research should investigate the benefit of continuous monitoring in improving the quality of life of patients.

In the field of embedded systems, energy efficiency is a critical requirement, particularly for battery-powered devices. RISC-V processors have gained popularity due to their flexibility and open-source nature, making them an attractive choice for embedded applications. However, not all RISC-V processors are equally energy-efficient, and evaluating their performance in specific use cases is essential. This paper presents RisCO2, an RISC-V implementation optimized for energy efficiency. It evaluates its performance compared to other RISC-V processors in terms of resource utilization and energy consumption in a signal processing application for nondispersive infrared (NDIR) CO2 sensors.The processors were implemented in the PULPino SoC and synthesized using Vivado IDE. RisCO2 is based on the RV32E_Zfinx instruction set and was designed from scratch by the authors specifically for low-power signal demodulation in CO2 NDIR sensors. The other processors are Ri5cy, Micro-riscy, and Zero-riscy, developed by the PULP team, and CV32E40P (derived from Ri5cy) from the OpenHW Group, all of them widely used in the RISC-V community. Our experiments showed that RisCO2 had the lowest energy consumption among the five processors, with a 53.5% reduction in energy consumption compared to CV32E40P and a 94.8% reduction compared to Micro-riscy. Additionally, RisCO2 had the lowest FPGA resource utilization compared to the best-performing processors, CV32E40P and Ri5cy, with a 46.1% and a 59% reduction in LUTs, respectively. Our findings suggest that RisCO2 is a highly energy-efficient RISC-V processor for NDIR CO2 sensors that require signal demodulation to enhance the accuracy of the measurements. The results also highlight the importance of evaluating processors in specific use cases to identify the most energy-efficient option. This paper provides valuable insights for designers of energy-efficient embedded systems using RISC-V processors.

The world is moving towards a low-carbon economy through renewable energy sources. In this context, concentrating solar power (CSP) technologies can exploit the rich solar resource in Brazil, diversifying the national electricity mix. The aim of this paper is to support the insertion of CSP generation in the Brazilian bottom-up model MATRIZ by analyzing the environmental performance of three CSP technologies: (i) solar tower power (STP) with a thermal storage system (TSS) of 7.5 h; (ii) solar thermal parabolic trough (STPT) with a TSS of 6 h; and (iii) STPT without TSS. From a life cycle perspective, their freshwater consumption and greenhouse gas (GHG) emissions are addressed by employing the software SimaPro, the Ecoinvent database, and the ReCiPe 2016 method, as well as information from the system advisory model (SAM) and the literature. As a result, STP is the most environmentally sound CSP alternative, presenting lower GHG emissions and water consumption than the two STPT technologies. In general, CSP generation proves to be more environmentally attractive than some fossil-fired power plants and renewable energy sources. Moreover, moving the manufacturing of CSP technologies to Brazil has the potential to reduce GHG emissions from the upstream processes of their value chain.

The aim of this audit was to evaluate the usefulness and serviceability of testing for pathogenic mutations in BRCA1 or BRCA2 (BRCA1/2) genes in ovarian cancer (OC) patients. One hundred and thirty-five patients with more common histological sub-types of OC were retrospectively identified between 2011 and 2019. The fail rate of the molecular analysis was 7.4% (10/135). One hundred and twenty-five records were evaluated: 99 (79.2%) patients had wild-type BRCA (both somatic and germline); tumour BRCA1/2 (tBRCA1/2) pathogenic mutations were found in 20 (16%) patients with distribution between BRCA1 and BRCA2 being 40% and 60%, respectively; 13 (10.4%) patients with pathogenic variants had germline mutations; and tBRCA1/2 with variant of unknown significance (VUS), in the absence of pathogenic BRCA1 or BRCA2 variants, was detected in 6 (4.8%) patients. Our data show that expanding the molecular service to the routine first-tumour testing for patients with OC will potentially increase the detection rate of BRCA mutations, thereby providing early benefits of PARP inhibitors therapy. The tumour testing service should continue to be offered to newly diagnosed patients with high-grade epithelial cancers, including high-grade serous carcinoma, but also with carcinosarcomas and poorly-differentiated metastatic adenocarcinomas of unknown origin.

Augmented reality is showing a continuous evolution due to the increasing number of smart glasses that are being used for different applications (e.g. training, marketing, industry, risk avoidance, etc.). In this paper, we present an implementation that uses augmented reality (AR) for emergency situations in smart buildings by means of indoor localization through the use of sub-GHz beacons. This also includes the mapping of emergency elements in the three-dimensional building, together with some example cases.

Pedestrian detection is one of the key problems in the emerging self-driving car industry. In addition, the Histogram of Gradients (HOG) algorithm proved to provide good accuracy for pedestrian detection. Many research works focused on accelerating HOG algorithm on FPGA (Field-Programmable Gate Array) due to its low-power and high-throughput characteristics. In this paper, we present an energy-efficient HOG-based implementation for pedestrian detection system on a low-cost FPGA system-on-chip platform. The hardware accelerator implements the HOG computation and the Support Vector Machine classifier, the rest of the algorithm is mapped to software in the embedded processor. The hardware runs at 50 Mhz (lower frequency than previous works), thus achieving the best pixels processed per clock and the lower power design.