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Intra-arterial chemotherapy (IAC) represents a mainstay in the treatment of retinoblastoma. In a minority of cases, the external carotid artery (ECA) serves as the dominant supply to the central retinal artery and is associated with prolonged fluoroscopy times and higher intraprocedural radiation doses. The aim of this study was to evaluate the utility of time-of-flight (TOF) magnetic resonance angiography (MRA) for prospective determination of internal (ICA) versus ECA dominance for procedural planning. Between April 2017 and December 2020 (44 months), staging MR prior to IAC for retinoblastoma included variant spatial saturation band position TOF angiography. Exams were then retrospectively reviewed for concordance of ICA versus ECA dominance between the two modalities. Eight consecutive patients were included in the study. Mean patient age at time of diagnosis was 20.3 ± 10.7 months (range: 2.7–33.2 months). Ten affected eyes were included (2 cases of bilateral disease), with stage D disease in eight eyes and stage B disease in two eyes. MRA techniques demonstrated antegrade ophthalmic artery (OA) flow in 9/10 (90%) of affected eyes. Subsequent catheter angiography confirmed ICA dominant supply in 9/9 (100%). For a single affected eye (10%), the OA was demonstrated as orthotopic by T2 flow void, nonvisualized on anterior saturation TOF sequences, and faintly visualized on posterior saturation TOF sequences. Aggregate MRA to catheter angiographic concordance was 10/10 (100%). Variant saturation TOF MRA predicts ICA versus ECA dominant supply to the central retinal artery in retinoblastoma.

Communication between intracellular organelles is essential for overall cellular function. How this communication occurs and under what circumstances alterations transpire are only the beginning to be elucidated. The pathways of calcium homeostasis, lipid transfer, mitochondrial dynamics, and mitophagy/apoptosis have been linked to the endoplasmic reticulum and tethering sites on the outer and/or inner mitochondrial membrane called mitochondria-associated endoplasmic reticulum membranes (MAM). Sensitive visualization by high-powered microscopy coupled with the advent of massive parallel sequencing has elaborated the structure, while patient’s diseases have uncovered the physiological function of these networks. Using specific patient examples from our pediatric mitochondrial center, we expand how specific genetic pathological variants in certain MAM structures induce disease. Genetic variants in MICU1, PASC-2, CYP2U1, SERAC1, and TANGO2 can induce early development abnormalities in the areas of cognition, motor, and central nervous system structures across multiple MAM pathways and implicate mitochondrial dysregulation.

Auriculocondylar syndrome 2 (ARCND2) is a rare autosomal dominant craniofacial malformation syndrome linked to multiple genetic variants in the coding sequence of phospholipase C β4 (PLCB4). PLCB4 is a direct signaling effector of the endothelin receptor type A (EDNRA)-Gq/11 pathway, which establishes the identity of neural crest cells (NCCs) that form lower jaw and middle ear structures. However, the functional consequences of PLCB4 variants on EDNRA signaling is not known. Here, we show, using multiple signaling reporter assays, that known PLCB4 variants resulting from missense mutations exert a dominant-negative interference over EDNRA signaling. In addition, using CRISPR/Cas9, we find that F0 mouse embryos modeling one PLCB4 variant have facial defects recapitulating those observed in hypomorphic Ednra mouse models, including a bone that we identify as an atavistic change in the posterior palate/oral cavity. Remarkably, we have identified a similar osseous phenotype in a child with ARCND2. Our results identify the disease mechanism of ARCND2, demonstrate that the PLCB4 variants cause craniofacial differences and illustrate how minor changes in signaling within NCCs may have driven evolutionary changes in jaw structure and function. This article has an associated First Person interview with the first author of the paper.

El objeto del presente trabajo es mostrar cuales son los márgenes de desbalance que aparecen y/o podrían aparecer en el sistema de distribución de la Argentina, sin violar la reglamentación nacional vigente al respecto, para compararlos con los recomendados por la normativa internacional vinculada con el tema. En tal sentido se determina el máximo valor posible que podría alcanzar la relación porcentual entre la componente de secuencia negativa y positiva (relación empleada por IEC e IEEE para evaluar el desbalance), utilizando como herramienta un algoritmo genético diseñado específicamente para cumplir con lo propuesto. Además se muestran una serie de mediciones de desbalance, obtenidas en distintos puntos del sistema de distribución eléctrica de baja tensión.

Primary intracranial choriocarcinoma (PICCC), a type of germ-cell tumor, is a very rare primary tumor of the central nervous system that generally arises in the pineal or suprasellar region. We present a case of a teenage boy with PICCC of the bilateral basal ganglia, an anatomic site for which we were unable to find the previous reports. We offer discussion of the differential diagnosis, imaging characteristics, and prognosis of PICCC and germ-cell tumors of the basal ganglia, in the hope that it will increase awareness and allow for early detection.

In an organization’s digital messaging environment, information is exchanged both internally and externally, resulting in a continuous evolution of the message stream at both the conceptual and feature levels. Feature-level changes occur due to the introduction of new attributes or the evolving meaning and relevance of existing features over time. Nevertheless, the prevailing approaches to addressing this issue frequently entail the initialization of a fixed set of parameters, which can be both intricate and expensive. Furthermore, maintaining these parameters in a fixed state over time may result in solutions becoming less adaptable, efficient, or effective as the message stream evolves. This paper introduces a goal-oriented, self-tuning solution for dynamic feature selection, based on approaches from the literature. The proposed solution is applied to the classification of messages within a multi-agent system. The approach employs the iStar modeling language to integrate proactive strategies and adaptive tuning plans, which are then operationalized through the multi-agent system. The effectiveness of the solution is evaluated through test cases and an experimental studies, comparing the results of the dynamic feature selection method from the literature with the variants introduced in this work. In spam detection, the proposed solution demonstrates improvements in several of the quality measures assessed. In news classification, the proposed solution was assessed, a variant was proposed and it demonstrated improved adaptability and effectiveness. This highlights the proposed solution potential for enhanced adaptability in dynamic messaging environments.

Abstract Cancer is a heterogeneous disease requiring costly genetic profiling for better understanding and management. Recent advances in deep learning have enabled cost-effective predictions of genetic alterations from whole slide images (WSIs). While transformers have driven significant progress in non-medical domains, their application to WSIs lags behind due to high model complexity and limited dataset sizes. Here, we introduce S E Q U O I A, a linearized transformer model that predicts cancer transcriptomic profiles from WSIs. S E Q U O I A is developed using 7584 tumor samples across 16 cancer types, with its generalization capacity validated on two independent cohorts comprising 1368 tumors. Accurately predicted genes are associated with key cancer processes, including inflammatory response, cell cycles and metabolism. Further, we demonstrate the value of S E Q U O I A in stratifying the risk of breast cancer recurrence and in resolving spatial gene expression at loco-regional levels. S E Q U O I A hence deciphers clinically relevant information from WSIs, opening avenues for personalized cancer management.

El objetivo del estudio fue describir y caracterizar las tendencias de la producción intelectual a nivel de rendimiento y desarrollo temático en artículos que abordan el constructo “cultura científica” en el contexto educativo en el periodo 1998-2022. Para este análisis bibliométrico se hizo una búsqueda en la base de datos Web of Science con los descriptores “scientific culture” y “education” lo cual arrojó un total de 100 artículos (n=100), tras el cribaje y estudio de idoneidad de los documentos, se consideró finalmente 87 artículos (n= 87). Para la visualización y análisis se empleó estadística descriptiva apoyada en las herramientas Excel 365, Biblioshine by Bibliométrix,y VOSviewer. Las variables abordadas fueron: producción anual, categorías WoS, revistas e impacto, autores, países y palabras clave. Los hallazgos muestran que entre los años 2017 y 2020 se ha dado la mayor producción de artículos. La categoría WoS que más aborda el tema es Education Educational Research (9,08%). La principal revista es de habla inglesa: Public Understanding of Science y en relación con los países, España, Brasil y Estados Unidos son los de mayor producción. Las palabras clave de mayor relevancia son epistemología, educación, educación científica, formación docente, aprendizaje. Se concluye que esta producción intelectual es interdisciplinaria estimándose que ha sido influenciada por políticas públicas, con una marcada influencia anglosajona y europea; y con una escasa relación con temas vinculados con la didáctica de las ciencias naturales.

There is uncertainty about the best approach to replacement treatment for kidney transplant recipients with chronic terminal graft dysfunction, since a retransplant could be performed before the resumption of dialysis, thus avoiding this treatment and the dilemma of whether or not to suspend immunosuppressive therapy. However, there is limited experience in pre-emptive repeat transplantations, and none from deceased donors. This study aims to assess the results of a pre-emptive retransplantation program with brain-dead deceased donors. We designed a retrospective matched cohort study, including 36 recipients in the pre-dialysis group and 36 controls who were already on dialysis, matched for donor age and transplant date, which could not differ by more than 7 days between pairs. The variables used to standardize the cohorts were donor and recipient age and sex, blood group, duration of the first graft, time on the waitlist to receive the second graft, cold ischemia time, induction and maintenance of immunosuppression, and HLA antibodies (-) prior to retransplantation. The efficacy variables were early graft loss, acute rejection, delay in graft function, renal function at the end of follow-up, survival time, and recipient and graft survival at 24 and 48 months’ follow-up. The pre-dialysis group presented a significantly shorter waitlist time, lower immunization status, and a significantly longer duration of the first graft than the control group. The percentage of recipients who presented early graft loss, delayed renal function, or acute rejection was similar between groups. No significant differences were observed in kidney function or in the survival of the recipient or graft. Retransplantation yields good outcomes in patients with terminal chronic dysfunction, helping to avoid recurrence to dialysis, shortening the time spent on the waitlist, reducing the risk of producing antibodies, and resolving the dilemma of whether or not to stop immunosuppression.

Background The COVID-19 pandemic, caused by the SARS-CoV-2, can be effectively managed with diagnostic tools such as RT-qPCR. However, it can produce false-negative results due to viral mutations and RNA secondary structures from the target gene sequence. Methods With High Performance Computing, the complete SARS-CoV-2 genome was obtained from the GenBank/GISAID to generate consensus sequences to design primers/probes for RT-qPCR. ORF8 gene was selected, meanwhile, E and N and RNAse P were according to CDC protocol. Nasopharyngeal swab samples were collected from patients diagnosed with SARS-CoV-2. Total RNA was purified according MagMAX kit, it was used in single, and multiplex RT-qPCR. To avoid templated secondary structures, compensate nucleotide proportions and improve Ct values, a solution composed of tetraethylammonium chloride and dimethyl sulfoxide and other with corresponding to dNTPs proportions in accordance SARS-CoV-2 genome were included. Sensitivity and specificity according to Ct values were determined with the Caret package in R software. Results 126,576 SARS-CoV-2 genomes from January to December 2020 comprised a database. From this, a region near of 5′ ORF8 gene showed three stem-loops was used for primers/FAM-probe. 49 samples were obtained, from them, 22 were positive to gene selected regions. Interestingly, samples from October to November 2020 were positive for all regions, however, in January 2021 different results were observed in ORF8. An improvement in Ct with the adjuvant solutions was determined in all samples with others SARS-CoV-2 primers/probes, for both single and multiplex RT-qPCR. The inclusion of the denaturing solution in single RT-qPCR increased its sensitivity with respect to the commercial method, while in multiplex the opposite was generated. Conclusions Including adjuvant solutions to prevent the formation of RNA secondary structures and the adjustment of the nucleotide ratios of SARS-CoV-2 improved single and multiplex RT-qPCR for viral identification, demonstrating its potential application in health public.

Data Science has emerged as a vital discipline applicable across numerous industry sectors. However, achieving reproducibility in this field remains a challenging and unresolved problem. Additionally, transitioning trained models from development to production environments often proves to be a non-trivial task. In this study, we propose SnapperML, a comprehensive framework designed to address these issues by enabling practitioners to establish structured workflows that facilitate result reproducibility. Leveraging DevOps techniques, SnapperML ensures seamless model deployment from the lab to production, mitigating the risks associated with compatibility issues and model selection errors. The framework enables meticulous tracking of every aspect of model training, including hyperparameter selection, tuning, and distributed training on a server. By offering a suite of tools for model tracking and optimization, SnapperML presents a promising solution to the reproducibility challenge in the field of data science.

Abstract Background Pancreatic ductal carcinoma patients have a really poor prognosis given its difficult early detection and the lack of early symptoms. Digital pathology is routinely used by pathologists to diagnose the disease. However, visually inspecting the tissue is a time-consuming task, which slows down the diagnostic procedure. With the advances occurred in the area of artificial intelligence, specifically with deep learning models, and the growing availability of public histology data, clinical decision support systems are being created. However, the generalization capabilities of these systems are not always tested, nor the integration of publicly available datasets for pancreatic ductal carcinoma detection (PDAC). Methods In this work, we explored the performace of two weakly-supervised deep learning models using the two more widely available datasets with pancreatic ductal carcinoma histology images, The Cancer Genome Atlas Project (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). In order to have sufficient training data, the TCGA dataset was integrated with the Genotype-Tissue Expression (GTEx) project dataset, which contains healthy pancreatic samples. Results We showed how the model trained on CPTAC generalizes better than the one trained on the integrated dataset, obtaining an inter-dataset accuracy of 90.62% ± 2.32 and an outer-dataset accuracy of 92.17% when evaluated on TCGA + GTEx. Furthermore, we tested the performance on another dataset formed by tissue micro-arrays, obtaining an accuracy of 98.59%. We showed how the features learned in an integrated dataset do not differentiate between the classes, but between the datasets, noticing that a stronger normalization might be needed when creating clinical decision support systems with datasets obtained from different sources. To mitigate this effect, we proposed to train on the three available datasets, improving the detection performance and generalization capabilities of a model trained only on TCGA + GTEx and achieving a similar performance to the model trained only on CPTAC. Conclusions The integration of datasets where both classes are present can mitigate the batch effect present when integrating datasets, improving the classification performance, and accurately detecting PDAC across different datasets.

The growing development of communication technologies has given rise to the Internet of Things, which has led to the emergence of new cities, smart grids, and smart buildings, and the development of energy generation using renewable sources, as well as the emergence of new electrical loads such as the electric car. These advances give rise to the need for new media devices with remote communication, and require a greater control and monitoring of the state of the electrical grid in order to verify its correct state, as well as the detection of faults or alterations that are occurring in it due to these new generation systems or new loads. These remote, unsupervised measurement devices require galvanic isolation to protect the measurement and communication system, so that even if there is a break in the isolation, the integrity of the measurement and communication system is maintained. In addition, as it is a device prepared for multipoint measurement, the cost of the probe must be contained. This article details the design, implementation, and validation of a low-cost remote isolated differential voltage probe. This probe is intended for monitoring at network supply points, as well as for the verification of the European standard EN 50160 as a means of detecting disturbances in network behaviour. Its characteristics as a differential and isolated probe provide it with the possibility of floating voltage averaging, guaranteeing the integrity of the electronics of the low-voltage probe, i.e., the digitalisation and communication system. The measurements collected are sent via an MQTT protocol, which makes the remote probe a device compatible with the Internet of Energy. For the validation of the probe, a full functional test is performed, including FFT spectral analysis to verify the compliance of the mains voltage with the aforementioned European standard EN 50160.

Oxidative stress, a physiological process that can damage cells, is known to affect various aspects of oral health. Oxidative stress can influence dental implant longevity and health. Assessing biomarkers of oxidative stress in saliva is beneficial for diagnosing and tracking the progression of oral diseases. A study is made of salivary oxidative stress in patients with dental implants with or without periodontitis. The study consisted of the following groups: Group1 (healthy without dental implants); Group 2 (subjects undergoing periodontal maintenance without dental implants); Group 3 (healthy patients with implants older than six months); and Group 4 (patients undergoing periodontal maintenance with implants older than six months). A complete examination of the oral cavity was made in each patient and a questionnaire was used to assess habits of hygiene, quality of life, and information about the implants. The following parameters were recorded in unstimulated whole saliva: ferric reducing antioxidant power (FRAP), Trolox equivalent antioxidant capacity (TEAC), cupric reducing antioxidant capacity (CUPRAC), advanced oxidation protein products (AOPP), and total proteins (TP). A total of 160 patients were studied, with 40 patients per group. The mean oxidative stress biomarker values obtained in the patients without implants and with implants were FRAP 0.590 ± 0.514 and 0.588 ± 0.334 mmol/L (p = 0.974); TEAC 0.320 ± 0.223 and 0.315 ± 0.172 mmol/L (p = 0.879); CUPRAC 0.286 ± 0.216 and 0.288 ± 0.151 mmol/L (p = 0.956); AOPP 456.04 ± 789.75 and 430.65 ± 752.05 µmol/L (p = 0.838); and TP 73.90 ± 50.83 and 70.36 ± 56.93 mg/dL (p = 0.684), respectively. No substantial variations were noted in the salivary oxidative stress biomarker levels between patients with controlled periodontal disease and/or dental implants compared to healthy individuals.

Incandescent pyroclasts of more than 64 mm in diameter erupted from active volcanoes are known as bombs and pose a significant hazard to life and infrastructure. Volcanic ballistic projectile hazard assessment normally considers fall as the main transport process, estimating its intensity from bomb location and impact cratering. We describe ballistically ejected bombs observed during the late October 2021 episode of eruption at La Palma (Canary Islands) that additionally travelled downhill by rolling and bouncing on the steep tephra-dominated cone. These bouncing bombs travelled for distances >1 km beyond their initial impact sites, increasing total travel distance by as much as 100%. They left multiple impact craters on their travel path and frequently spalled incandescent fragments on impact with substrate, leading to significant fire hazard for partially buried trees and structures far beyond the range of ballistic transport. We term these phenomena as bouncing spallation bombs. The official exclusion zone encompassed this hazard at La Palma, but elsewhere bouncing spallation bombs ought to be accounted for in risk assessment, necessitating awareness of an increased hazard footprint on steep-sided volcanoes with ballistic activity.

Voltage-lift is a widely used technique in DC–DC converters to step-up output voltage levels. Several traditional and advanced control techniques applicable to power electronic converters (PEC) have been reported and utilized for voltage-lift applications. Similarly, in recent years the implementation of fractional-order controllers (FOC) in PEC applications has gained interest, aiming to improve system performance, and has been validated in basic converter topologies. Following this trend, this work presents an FOC for a voltage-lift converter, requiring only output voltage feedback. A third-order non-minimal phase system is selected for experimentation to verify FOC implementations for more complex PEC configurations. A simple, straightforward design and approximation methodology for the FOC is proposed. Step-by-step development of the FOC, numerical and practical results on a 50 W voltage-lift converter are reported. The results show that PEC transient and steady-state responses can be enhanced using FOC controllers when compared with classical linear controllers. Extended applications of FOC for improved performance in power conversion is also discussed.

Abstract Eosinophils have widespread procoagulant effects. Eosinophilic cardiovascular toxicity mostly consists of endomyocardial damage or eosinophilic vasculitis, while reported cases of venous thrombosis (VT) are scarce. We aimed to report on the clinical features and treatment outcomes of patients with unexplained VT and eosinophilia, and to identify predictors of relapse. This retrospective, multicenter, observational study included patients aged over 15 years with VT, concomitant blood eosinophilia ≥ 1G/L and without any other moderate-to-strong contributing factors for VT. Fifty-four patients were included. VT was the initial manifestation of eosinophil-related disease in 29 (54%) patients and included pulmonary embolism (52%), deep venous thrombosis (37%), hepatic (11%) and portal vein (9%) thromboses. The median [IQR] absolute eosinophil count at VT onset was 3.3G/L [1.6–7.4]. Underlying eosinophil-related diseases included FIP1L1-PDGFRA-associated chronic myeloid neoplasm (n = 4), Eosinophilic Granulomatosis with Polyangiitis (n = 9), lymphocytic (n = 1) and idiopathic (n = 29) variants of hypereosinophilic syndrome. After a median [IQR] follow-up of 24 [10–62] months, 7 (13%) patients had a recurrence of VT. In multivariate analysis, persistent eosinophilia was the sole variable associated with a shorter time to VT relapse (HR 7.48; CI95% [1.94–29.47]; p = 0.015). Long-term normalization of eosinophil count could prevent the recurrence of VT in a subset of patients with unexplained VT and eosinophilia ≥ 1G/L.

Background: Recent estimates indicate that the COVID-19 pandemic, which is caused by the SARS-CoV-2 virus, could be effectively controlled via the development and implementation of diagnostic tools such as quantitative reverse transcription PCR (RT-qPCR). However, this reaction often generates false-negative results due to novel mutations and can also be affected by the secondary structure of the RNA transcripts that derive from the gene sequence used for diagnostic purposes. Methods: Using high-performance computing, we consolidated a global SARS-CoV-2 genome repository encompassing 19,317 genomes from the GenBank database and 107,259 from the GISAID database to generate monthly SARS-CoV-2 consensus sequences from January to December 2020. Results: These sequences were then used to create ORF8-specific primers and probes to validate single and multiplex RT-qPCR protocols both in silico and experimentally using genes E (Berlin protocol) and N (CDC protocol) as targets. Conclusions: Our findings demonstrated that RT-qPCR Ct values were improved by the inclusion of either a denaturing solution composed of tetraethylammonium chloride (TEA) and dimethyl sulfoxide (DMSO) and by adjusting nucleotide proportions based on the SARS-CoV-2 genome.

El nuevo perfil del docente universitario, más centrado en el aprendizaje y necesidades del alumnado, impulsa una nueva arquitectura de la tutoría universitaria. Este trabajo describe la validación de una escala de medida de las competencias tutoriales del profesorado desde la perspectiva del alumnado. Participaron 622 estudiantes de la Universidad de Murcia y se realizó un análisis factorial confirmatorio con los datos recabados. Los resultados muestran la adecuación del modelo teórico propuesto, constituido por cuatro dimensiones (Información y adaptación; Gestión y apoyo grupal; Orientación educativa y profesional; Seguimiento continuo del alumnado) así como una mayor percepción de importancia de estas competencias frente al desarrollo de las mismas por parte de los docentes (p < .05), lo que permite concluir con la importancia de profundizar en el conocimiento de este tipo de competencias en busca de una mejora continua de la tutoría universitaria.

In the last years, low pressure ozone UVC mercury germicidal lamps have been widely used to decontaminate air, surfaces, and water. This technology is mature, and it has been widely used during the pandemic as a measure against SARS-CoV-2, the coronavirus that causes COVID-19; because the exposure of this virus to the wavelength wave of 254 nm has been proven to be an effective way to eliminate it. However, the Minamata Convention in 2013 decided to limit mercury lamps by 2020; therefore, the development of new technology devices based on UVC-LEDs (short-wave ultraviolet, light-emitting diodes) are receiving a lot of attention. Today, this technology is commercially available from 265 to 300 nm peak wavelengths, and recently up to 254 nm. Notwithstanding, due to the characteristics of these LEDs, arrangements with a precisely dosed power supply are regularly required to provide effective decontamination. Thus, this article reports the design and implementation of a power electronic converter for an array of 254 nm UVC-LEDs, which can be used to decontaminate from SARS-CoV-2 in a safe way.