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Abstract Background The EU Patient-cEntric clinicAl tRial pLatforms (EU-PEARL) project (IMI2-853966) aimed to develop tools to establish integrated research platforms (IRP) for conducting adaptive-design trials in various diseases, including metabolic-dysfunction associated steatohepatitis (MASH). One essential component of a successful MASH IRP is a robust and reliable Clinical Research Network (CRN). Herein, we outline the required elements and anticipated steps to set-up such a CRN. Methods We identified European clinical research sites that could potentially serve as the foundation for MASH IRP and a CRN. A survey was sent to sites to assess their interest in joining a CRN, their familiarity with platform trials, and their capacity to participate in a future MASH IRP. Results A total of 141 investigators were invited to participate in the survey, and 40% responded. More than half of the answers (52%) identify MASH with advanced fibrosis (F3-4) as the subpopulation with the greatest unmet need. Regarding the difficulty in identifying candidates for trials, 65% find it is moderately difficult and 30% very difficult. Most respondents (94%) believe that a platform trial could offer substantial benefits to patients. Nearly all researchers express interest in participating in a platform trial (78%), with 22% indicating their interest would be contingent on initial industry funding. Conclusion While preliminary, our findings on responding sites are encouraging for the potential establishment of a CRN for a MASH IRP. However, funding schemes and sustainability strategies to provide proof-of-platform in MASH seem key in the short-term scenario.

Abstract Background During the COVID-19 pandemic, decentralised clinical trials incorporated self-monitoring, self-reporting, and telenursing tools to address health literacy and health empowerment of patients enrolled in clinical trials. We aimed to determine the impact of an educational intervention using telenursing consultations on health literacy, health empowerment, and health-related quality of life in cancer patients enrolled in clinical trials by measuring the level of satisfaction with the care received and assessing the views of healthcare professionals concerning the advanced practice nurse (APN) role in oncology clinical trials. Methods In this pilot analytical, descriptive, longitudinal, quasi-experimental, and pre-post test study, an educational intervention was conducted by 5 visits with an APN using synchronous teleconsultation in patients starting cancer treatment for the first time in a clinical trial (n = 60), and health professionals working with the APN (n = 31). A descriptive analysis of the samples and questionnaires were utilised along with statistical comparisons. Results After the intervention, patients' health literacy (31.7%), health empowerment (18.3%), and health-related quality of life (33.3%) increased (p

Objective. To analyze trends in mortality caused by cardiovascular diseases (CVD) in Chile during the period 2000–2020. Methods. Data on age-adjusted mortality rates (AAMR) from CVD per 100 000 population in Chile for 2000–2020 were extracted from the World Health Organization Mortality Database. Joinpoint regression was used to analyze the trends and compute the average annual percent change (AAPC) in Chile. In addition, analyses were conducted by sex and type of CVD. Results. Between 2000 and 2020, the AAMR from CVD decreased in Chile from 159.5 to 94.6 per 100 000 population, with a statistically significant decrease in the AAPC of 2.6% (95% CI [–2.8, –2.4]). No joinpoints were identified. The AAMR from CVD decreased annually by 2.6% (95% CI [–2.8, –2.4]) and 2.8% (95% CI [–3.5, –2.6]) in men and women, respectively. The AAMR from ischemic heart disease reduced annually by 3.6% (95% CI [–4.6, –2.7]) with two joinpoints in 2011 and 2015. In the case of stroke, the mortality rate decreased annually by 3.7% (95% CI [–4.5, –3.0]), with two joinpoints in 2008 and 2011. Conclusions. Cardiovascular disease mortality rates have decreased significantly in Chile, in both sexes, especially in women. This decrease could be explained mainly by a significant reduction in the case fatality in recent decades. These results could be a reference for developing primary prevention and acute management of CVD policies focused on populations with higher mortality.

This study evaluates the efficacy of [131I]I-ERIC1 in targeting and inhibiting the growth of SCLC tumors in mice, focusing on tumor accumulation and regression and potential side effects. NCAM-positive NCI-H69 SCLC cells were implanted in CB 17 SCID mice, and [131I]I-ERIC1 biokinetics were measured in organs and tissues at four post-injection time points (24, 72, 96, and 120 h). The experimental series compared tumor growth, survival, and changes in blood counts among three treatment groups (1, 2, or 3 MBq) and a control group, with treatments initiated either two or five days post implantation. [131I]I-ERIC1 was synthesized with >95% radiochemical purity and a specific activity of 15 TBq/mmol. Tumor activity peaked at 31.5 ± 6.6% ID/g after four days, demonstrating significant antitumor efficacy, which resulted in sustained remission and extended survival. Hematological toxicity was observed, with the optimal dose identified as 2 MBq per animal administered two days post implantation. [131I]I-ERIC1 shows promise as a theranostic agent for personalized cancer treatment by effectively targeting SCLC tumors with manageable side effects. However, further studies are required to optimize dosing strategies and minimize toxicity.

Objective: Pompe disease (PD) is caused by deficiency of the lysosomal enzyme acid α-glucosidase (GAA), leading to progressive glycogen accumulation and severe myopathy with progressive muscle weakness. In the Infantile-Onset PD (IOPD), death generally occurs

Summary: During genome duplication, replication forks (RFs) can be stalled by different obstacles or by depletion of replication factors or nucleotides. A limited number of histone post-translational modifications at stalled RFs are involved in RF protection and restart. Provided the recent observation that the SIN3A histone deacetylase complex reduces transcription-replication conflicts, we explore the role of the SIN3A complex in protecting RFs under stressed conditions. We observe that Sin3A protein is enriched at replicating DNA in the presence of hydroxyurea. In this situation, Sin3A-depleted cells show increased RF stalling, H3 acetylation, and DNA breaks at stalled RFs. Under Sin3A depletion, RF recovery is impaired, and DNA damage accumulates. Importantly, these effects are partially dependent on the MUS81 endonuclease, which promotes DNA breaks and MRE11-dependent DNA degradation of such breaks. We propose that chromatin deacetylation triggered by the SIN3A complex limits MUS81 cleavage of stalled RFs, promoting genome stability when DNA replication is challenged.

This paper presents a deep learning approach for predicting rail corrugation based on on-board rolling-stock vertical acceleration and forward velocity measurements using One-Dimensional Convolutional Neural Networks (CNN-1D). The model’s performance is examined in a 1:10 scale railway system at two different forward velocities. During both the training and test stages, the CNN-1D produced results with mean absolute percentage errors of less than 5% for both forward velocities, confirming its ability to reproduce the corrugation profile based on real-time acceleration and forward velocity measurements. Moreover, by using a Gradient-weighted Class Activation Mapping (Grad-CAM) technique, it is shown that the CNN-1D can distinguish various regions, including the transition from damaged to undamaged regions and one-sided or two-sided corrugated regions, while predicting corrugation. In summary, the results of this study reveal the potential of data-driven techniques such as CNN-1D in predicting rails’ corrugation using online data from the dynamics of the rolling-stock, which can lead to more reliable and efficient maintenance and repair of railways.

Abstract Obesity and type 2 diabetes are two closely related diseases representing a serious threat worldwide. An increase in metabolic rate through enhancement of non-shivering thermogenesis in adipose tissue may represent a potential therapeutic strategy. Nevertheless, a better understanding of thermogenesis transcriptional regulation is needed to allow the development of new effective treatments. Here, we aimed to characterize the specific transcriptomic response of white and brown adipose tissues after thermogenic induction. Using cold exposure to induce thermogenesis in mice, we identified mRNAs and miRNAs that were differentially expressed in several adipose depots. In addition, integration of transcriptomic data in regulatory networks of miRNAs and transcription factors allowed the identification of key nodes likely controlling metabolism and immune response. Moreover, we identified the putative role of the transcription factor PU.1 in the regulation of PPARγ-mediated thermogenic response of subcutaneous white adipose tissue. Therefore, the present study provides new insights into the molecular mechanisms that regulate non-shivering thermogenesis.

BackgroundHealth literacy has a direct impact on the health of populations. It is related to education, capacity for self-care, and management of health resources. The Health Literacy Survey Questionnaire HLS-Q12 is one of the reference instruments but has not yet been adapted to Spanish. The aims of the study were to cross-culturally adapt and evaluate the psychometric properties of the Spanish version of the HLS-Q12.MethodsData was collected from June 2020 to March 2022. The sample consisted of 60 patients who initiated cancer treatment for the first time within a clinical trial. Double direct translation, back-translation, cognitive debriefing with a 10-patient sample, and an expert committee were used for cross-cultural adaptation. For validation of the HLS-Q12, a psychometric analysis was performed to assess feasibility, reliability, sensitivity to change and construct validity with other measures such as health-related quality of life, empowerment, and health needs.ResultsThe HLS-Q12 is equivalent at the semantic, conceptual, and content level to the original version and its psychometric properties demonstrated good internal consistency with a Cronbach's alpha of 0.88 and a McDonald´s omega of 0.91, a high degree of fit for the confirmatory factor analysis, and a statistically significant sensitivity to change (p = 0.025).ConclusionsBased on robust psychometric values, the Spanish version of HLS-Q12 was found to be a good cross-culturally adapted tool for collecting correct information on health literacy in cancer patients regardless of tumour type or stage. Although more studies are needed, this version of HLS-Q12 could be used in research for collecting data on the health literacy needs of Spanish-speaking patients.

Summary: Platform trials bring the promise of making clinical research more efficient and more patient centric. While their use has become more widespread, including their prominent role during the COVID-19 pandemic response, broader adoption of platform trials has been limited by the lack of experience and tools to navigate the critical upfront planning required to launch such collaborative studies. The European Union-Patient-cEntric clinicAl tRial pLatform (EU-PEARL) initiative has produced new methodologies to expand the use of platform trials with an overarching infrastructure and services embedded into Integrated Research Platforms (IRPs), in collaboration with patient representatives and through consultation with U.S. Food and Drug Administration and European Medicines Agency stakeholders. In this narrative review, we discuss the outlook for platform trials in Europe, including challenges related to infrastructure, design, adaptations, data sharing and regulation. Documents derived from the EU-PEARL project, alongside a literature search including PubMed and relevant grey literature (e.g., guidance from regulatory agencies and health technology agencies) were used as sources for a multi-stage collaborative process through which the 10 more important points based on lessons drawn from the EU-PEARL project were developed and summarised as guidance for the setup of platform trials. We conclude that early involvement of critical stakeholder such as regulatory agencies or patients are critical steps in the implementation and later acceptance of platform trials. Addressing these gaps will be critical for attaining the full potential of platform trials for patients. Funding: Innovative Medicines Initiative 2 Joint Undertaking with support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.

Introducción: La transmisión viral a menudo se propaga en grupos, donde las infecciones se pueden rastrear hasta un caso índice o una ubicación geográfica, para así poder tomar medidas de prevención al respecto. Entender el perfil de transmisión del SARS-CoV-2 es esencial para desarrollar estrategias efectivas de prevención y control de la enfermedad. Objetivo: Determinar el perfil de transmisión del Sars-Cov-2, a partir de clúster con casos índices identificados, en la V región sanitaria (Caaguazu) del Paraguay, entre julio y octubre del 2020. Metodología: Se realizó un estudio observacional, descriptivo, de corte transversal, con fichas de notificación de casos de COVID-19 y resultados laboratoriales de la RT_PCR en pacientes diagnosticados con COVID-19 en la V Región Sanitaria entrejulio y octubre del 2020. Resultados: Fueron identificadas 703 personas con Sars-Cov-2 positivo. El 55,49% de las personas no reconoció algún nexo de contagio. Con respecto al tipo de evento donde ocurrían con mayor frecuencia los contagios, ocurrieron en Eventos Sociales en 58,14% de los casos y en el Ambiente Familiar en el 33,89%. La transmisión secundaria se observó en el 17,40% de los casos. Fueron identificados 58 Clústers, con una mediana de tamaño de los mismos de 3 (RIQ 2-4), y 267 personas (37,98%) asociadas a los mismos. Conclusión: La mayoría de las personas no reconocieron su nexo de contagio, sin embargo, en los que, si conocieron, se puede observar que la participación en eventos sociales fue el principal nexo, por lo que es fundamental realizar este tipo de ejercicios para hacer el seguimiento oportuno de los casos.

Portal hypertension may have major consequences on the pulmonary vasculature due to the complex pathophysiological interactions between the liver and lungs. Portopulmonary hypertension (PoPH), a subset of group 1 pulmonary hypertension (PH), is a serious pulmonary vascular disease secondary to portal hypertension, and is the fourth most common subtype of pulmonary arterial hypertension. It is most commonly observed in cirrhotic patients; however, patients with noncirrhotic portal hypertension can also develop it. On suspicion of PoPH, the initial evaluation is by a transthoracic echocardiogram in which, if elevated pulmonary pressures are shown, patients should undergo right heart catheterization to confirm the diagnosis. The prognosis is extremely poor in untreated patients; therefore, management includes pulmonary arterial hypertension therapies with the aim of improving pulmonary hemodynamics and moving patients to orthotopic liver transplantation (OLT). In this article, we review in detail the epidemiology, pathophysiology, process for diagnosis, and most current treatments including OLT and prognosis in patients with PoPH. In addition, we present a diagnostic algorithm that includes the current criteria to properly select patients with PoPH who are candidates for OLT.

Abstract Background A good state of oral health allows people to communicate and eat. This topic is relevant in older people given its close relationship with their general health. At present, health challenges are directed at detecting and preventing oral disorders and are seen to exclusively by dentists, because the existing instruments can only be applied by them. However, speech-language therapists undergo similar training, which would allow them to collaborate in these processes. In this context, the Oral Health Assessment Tool (OHAT) is a detection instrument with good psychometric properties that is currently available for non-dental use. The objective of this study is the translation into Chilean Spanish of the OHAT and a structural validation of that version for application by these professionals. Materials and methods A mixed qualitative-quantitative study was carried out. The OHAT instrument was adapted to Chilean Spanish and subsequently subject to structural validity and evaluation of internal consistency reliability, as well as a valuation of its reproducibility in 286 older people (166 female, 120 male) from different health contexts. Results The cultural adaptation of the instrument proved to be semantically consistent with the original instrument. Its application was considered to be speedy and simple in the pre-test. The confirmatory factor analysis evidenced the unidimensionality of the OHAT. In addition, the instrument shows good internal consistency and test–retest reliability. Conclusions The OHAT instrument was considered to possess adequate structural validity and test–retest reliability properties. Its usefulness in the context of oral health disorders of this population in Chile is discussed.

Abstract Background Emergence delirium (ED) is a mental disturbance in children during recovery from general anaesthesia. The Pediatric Anesthesia Emergence Delirium (PAED) scale is the only validated scale that assesses ED in paediatric patients undergoing general anaesthesia. The aim of this study was the translation and cross-cultural adaptation of the PAED scale into Spanish (Chile). Methods A five-stage translation and cross-cultural adaptation process was carried out. The reliability of the Spanish version of the PAED scale was evaluated in paediatric patients independently by a set of two raters (anaesthesiologists or postanaesthesia care unit nurses) in the postanaesthetic period after major outpatient surgery. ED was defined by a cut-off level of ≥ 10 points on the PAED scale. Results The PAED scale was evaluated in 353 consecutive children. Patients had a mean age of 7.4 ± 3.22 years. The preoperative ASA Physical Status class was 62%, 37%, and 1% (ASA class I, II and III, respectively). The distribution of patients by service was as follows: 45% of patients underwent paediatric surgery; 33% underwent otorhinolaryngological surgery; 11% underwent orthopaedic surgery; 10% underwent ophthalmological surgery; and 1% underwent other types of surgery. The interrater agreement ranged from 96.9% to 97.9%, with Kappa values ranging from 0.59 to 0.79. The Cronbach’s alpha value was 0.91. The ED global incidence was 9.1% and was higher in the younger age groups (3–10 years). Conclusions The translated and cross-culturally adapted Spanish version of the PAED scale is a reliable instrument to measure ED in the postanaesthetic period in Chilean children.

The interdisciplinary possibilities inherent in nuclear medicine offer an opportunity for the patient-centered development of radioactive pharmaceuticals based on specific research questions. This approach provides radiopharmaceutical manufacturers with a robust scientific foundation on which to navigate the regulatory requirements for drug approval laid down by the law. A vivid illustration of this interdisciplinary cooperation has been the development of a Zr-89-labeled PSMA ligand where reliable results have been obtained across various domains, including chemistry, radiochemistry, biochemistry, and preclinical research. This comprehensive process extended to feasibility studies conducted with carefully selected patients from a single nuclear medicine clinic. The approach demonstrates how far close collaboration between different disciplines within nuclear medicine can further the move towards patient-oriented radiopharmaceutical treatments while simultaneously meeting regulatory demands. With such a strategy, innovative radiopharmaceutical solutions can be brought to the market more swiftly and efficiently, in line with the needs of patients.

Type 2 diabetes, insulin resistance, and obesity are strongly associated and are a major health problem worldwide. Obesity largely results from a sustained imbalance between energy intake and expenditure. Therapeutic approaches targeting metabolic rate may counteract body weight gain and insulin resistance. Bone morphogenic protein 7 (BMP7) has proven to enhance energy expenditure by inducing non-shivering thermogenesis in short-term studies in mice treated with the recombinant protein or adenoviral vectors encoding BMP7. To achieve long-term BMP7 effects, the use of adeno-associated viral (AAV) vectors would provide sustained production of the protein after a single administration. Here, we demonstrated that treatment of high-fat-diet-fed mice and ob/ob mice with liver-directed AAV-BMP7 vectors enabled a long-lasting increase in circulating levels of this factor. This rise in BMP7 concentration induced browning of white adipose tissue (WAT) and activation of brown adipose tissue, which enhanced energy expenditure, and reversed WAT hypertrophy, hepatic steatosis, and WAT and liver inflammation, ultimately resulting in normalization of body weight and insulin resistance. This study highlights the potential of AAV-BMP7-mediated gene therapy for the treatment of insulin resistance, type 2 diabetes, and obesity.

Depression is a common and debilitating mental illness affecting millions of individuals, diminishing their quality of life and overall well-being. The increasing prevalence of mental health disorders has underscored the need for innovative approaches to detect and address depression. In this context, text analysis has emerged as a promising avenue. Novel solutions for text-based depression detection commonly rely on deep neural networks or transformer-based models. Although these approaches have yielded impressive results, they often come with inherent limitations, such as substantial computational requirements or a lack of interpretability. This work aims to bridge the gap between substantial performance and practicality in the detection of depression signs within digital content. To this end, we introduce a comprehensive feature framework that integrates linguistic signals, emotional expressions, and cognitive patterns. The combination of this framework with distributional representations contributes to fostering the understanding of language patterns indicative of depression and provides a deeper grasp of contextual nuances. We exploit this combination using traditional machine learning methods in an effort to yield substantial performance without compromising interpretability and computational efficiency. The performance and generalizability of our approach have been assessed through experimentation using multiple publicly available English datasets. The results demonstrate that our method yields throughput on par with more complex and resource-intensive solutions, achieving F1-scores above 70%. This accomplishment is notable, as the proposed method simultaneously preserves the virtues of simplicity, interpretability, and reduced computational overhead. In summary, the findings of this research contribute to the field by offering an accessible and scalable solution for the detection of depression in real-world scenarios.

PurposeThis study aimed to determine the test-retest reliability and concurrent validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF) in Chilean adults.MethodsA cross-sectional validation study was carried out on 161 adults aged between 35 and 65, selected from a population-based study in Temuco, Chile. IPAQ-SF was completed twice, seven days apart, to analyze the test-retest reliability with the intraclass correlation coefficient (ICC). Objective PA was assessed by accelerometry (ActiGraph GT3X+) for seven consecutive days. Intraclass correlation coefficients were used to determine the reliability. Spearman correlation coefficients (rho) and Bland-Altman plots were calculated to assess validity.Results144 subjects (52.5 ± 8.8 years, 53.9% men) answered the IPAQ-SF on both occasions and had valid accelerometry data. The IPAQ-SF showed moderate reliability for sitting time (ICC = 0.62), while it was poor for walking (ICC = 0.40), moderate PA (ICC = 0.41), vigorous PA (ICC = 0.48), and total PA (ICC = 0.33). There were weak correlations between IPAQ-SF and accelerometry for sedentary behavior (rho = 0.28, p = 0.0005), walking (rho = 0.11, p = 0.17), moderate PA (rho = 0.13, p = 0.128), vigorous PA (rho = 0.18, p = 0.03), and total PA (rho = 0.26, p = 0.002).ConclusionsThe results suggest that the IPAQ-SF test and retest would provide an acceptable measure of total SB and MVPA, and a weak correlation between IPAQ-SF and accelerometer.

Abstract Recently, it has been recommended that population-based studies report not only frequencies of vision impairment and blindness but also any ocular abnormalities that might lead an individual to seek for eyecare services. The current study aimed to determine prevalence of ocular findings regardless of visual acuity (VA) status in older adults from the Brazilian Amazon Region. Disturbances were grouped into: Eyelids; Anterior Segment; Posterior Segment; Increased intraocular pressure; and Overall Globe. The presence of an ocular finding was considered positive when any abnormality was noted, regardless of VA. Refractive errors were not considered. A total 2384 eligible persons were enumerated and 2041 (85.6%) examined. The prevalence of ocular disturbances in either eye was 87.0% and was associated with male gender, older age, lower education, and rural residence. Overall, main findings were pterygium, cataract, and pinguecula, occurring in 58.8%, 45.4% and 17.4%, respectively. Among individuals with 20/20 VA in both eyes, the most frequent findings were pterygium, pinguecula, and glaucoma cupping, occurring in 47.4%, 31.2% and 6.5%, respectively. The high prevalence of ocular findings observed in this population reinforces that different conditions might not immediately decrease VA but can indicate risk and/or discomfort symptoms and should be considered when planning public health ophthalmic services.

Mucopolysaccharidosis type IVA (MPSIVA) is a lysosomal storage disorder causing severe skeletal and non-skeletal alterations in patients. Here, the authors generate a MPSIVA rat model that mimics the disabling human pathology and develop an AAV9-Galns gene therapy to treat the disease.

IntroductionThe first-line treatment for advanced hepatocellular carcinoma (HCC) is atezolizumab plus bevacizumab, but its availability is not universal and elderly patients are underrepresented in clinical trials. There is little evidence of efficacy and tolerability in elderly patients under systemic treatment. The aims of this study were to characterize the profile of elderly patients treated with sorafenib, assess their survival and safety profile in order to extrapolate their eligibility for systemic treatment.MethodsRetrospective multicentre study of HCC patients aged ≥75 years old treated with sorafenib from January 2008 to December 2019. Demographic data, baseline characteristics, and variables related to HCC and sorafenib were recorded. Overall survival (OS) and safety were analyzed.ResultsThe study included 206 patients from 11 hospitals, median age 77.9 years; 71.4% men and 62.6% stage Barcelona Clinic Liver Cancer- C (BCLC-C). The main causes of cirrhosis were hepatitis C (60.7%) and alcohol (14.7%). Most patients (84.5%) started with sorafenib 800mg and 15.5% at lower dosage. Arterial hypertension (AHT) (74.2 vs 62.2%; standardized mean differences (STD): 26) and baseline ECOG-PS>0 (45.3 vs 34.7%; STD: 38.2) differed significantly between patients receiving low and full doses. Median OS was 15.4 months (18.2 in BCLC-B vs 13.6 in BCLC-C). OS was not modified by comorbidities, age or period with more expertise.ConclusionsSorafenib appears to be safe in elderly patients with HCC. This is the first study to characterize the profile of elderly patients to be considered for systemic treatment. These findings could be used as the reference profile for elderly candidates for atezolizumab-bevacizumab.

This is the first report of the genetic diversity of the Mycobacterium tuberculosis complex isolates found in a Mexican-Amerindian setting. In this study, we analyzed isolates collected from the Highlands region of Chiapas, Mexico, by using spoligotyping and whole-genome sequencing analyses. Seventy-three M. tuberculosis isolates were analyzed initially by spoligotyping; no new spoligotypes were identified. Nineteen percent of the isolates were identified as SIT53 (T1) (n = 14), followed by SIT42 (14%, n = 10, LAM9) and SIT119 (11%; n = 8, X1). SIT53, SIT42, and orphan isolates (16.4%, n = 12) constituted about 50% of the isolates studied and were subjected to whole-genome sequencing (WGS) analysis. Most SIT53 (10/12) isolates belonged to the Euro-American sub-lineage 4.8. Most SIT42 isolates (4/7) as .well as most orphan isolates (5/8) belonged to the lineage 4.3.3 LAM group. By comparing the single-nucleotide polymorphism (SNP) patterns of the SIT53 isolates, we found one clone (

The 2-Minute Step Test (2MST) has been presented as an alternative to the 6-Minute Walk Test (6MWT) based on the association between the two tests in older adults; however, some authors propose that it should not be a substitute but rather a complement to the latter in the fitness evaluation. Specifically, in coronary disease, despite the potential and clinical utility of 2MST, the relationship of both tests in this population is unknown. This study aimed to determine the relationship between 6MWT and 2MST and to explore the relationship of biodemographic factors for both tests in subjects with treated coronary artery disease. For this, the 6MWT and the 2MST were applied to patients with coronary artery disease treated in 6 hospitals in Chile between May 2019 and February 2020. Additionally, lower limb strength was assessed by a chair-stand test, grip strength was assessed by a dynamometer, and physical measurements were applied. In total, 163 participants underwent both tests (average age = 58.7 ± 9.8 years; 73.6% men; 64.4% revascularized by angioplasty; 28.2% revascularized by surgery, and 7.4% treated by drugs or thrombolysis). Heart rate was higher at the end of the 6MWT, while the perception of effort was greater at the end of the 2MST. There was a weak positive correlation between the 6MWT and the 2MST in subjects with treated coronary disease (r = 0.28, p = 0.0003). While age (r = –0.27), weight (r = 0.25), height (r = 0.49), and strength of both lower limbs (r = 0.41) and grip strength (r = 0.53) correlated weakly or moderately to the covered distance in 6MWT, the number of steps by the 2MST correlated only weakly to height (r = 0.23), lower limb strength (r = 0.34), and grip strength (r = 0.34). Age, weight, height, lower limb strength, and grip strength would explain better the meters walked in the 6MWT than the steps achieved in the 2MST. With these findings, we can conclude that, in patients with treated coronary artery disease, it does not seem advisable to replace 6MWT with 2MST when it is possible to do so. Additionally, the 2MST may provide additional information in the fitness evaluation. However, the usefulness of 2MST in this population needs to be further studied.

Data scientists aim to provide techniques and tools to the clinicians to manage the new coronavirus disease. Nowadays, new emerging tools based on Artificial Intelligence (AI), Image Processing (IP) and Machine Learning (ML) are contributing to the improvement of healthcare and treatments of different diseases. This paper reviews the most recent research efforts and approaches related to these new data driven techniques and tools in combination with the exploitation of the already available COVID-19 datasets. The tools can assist clinicians and nurses in efficient decision making with complex and heavily heterogeneous data, even in hectic and overburdened Intensive Care Units (ICU) scenarios. The datasets and techniques underlying these tools can help finding a more correct diagnosis. The paper also describes how these innovative AI+IP+ML-based methods (e.g., conventional X-ray imaging, clinical laboratory data, respiratory monitoring and automatic adjustments, etc.) can assist in the process of easing both the care of infected patients in ICUs and Emergency Rooms and the discovery of new treatments (drugs).

Objetivo. Comparar las propiedades diagnósticas de cinco definiciones de caso sospechoso de COVID-19 utilizadas o propuestas en Chile durante los primeros ocho meses de la pandemia. Métodos. Se analizaron las propiedades diagnósticas (sensibilidad, especificidad, y valores predictivos positivo y negativo) de tres definiciones de caso sospechoso de COVID-19 utilizadas en Chile entre marzo y octubre del 2020, y dos propuestas de definición alternativas. La muestra fue de 2 019 personas con resultados conocidos a la prueba de la reacción en cadena de la polimerasa (PCR) para SARS-CoV-2. Para elaborar el criterio 5 se aplicó una regresión logística escalonada (stepwise) optimizando los valores de sensibilidad y especificidad. Se exploró la asociación de variables demográficas, síntomas y signos con la positividad a la PCR mediante regresión logística multifactorial. Se analizaron diferentes escenarios de positividad y se compararon las curvas ROC. Resultados. La presencia de anosmia (OR = 8,00; IC95%: 5,34–11,99) y fiebre (OR = 2,15; IC95%: 1,28–3,59) y el haber tenido contacto estrecho previo con una persona enferma de COVID-19 (OR = 2,89; IC95%: 2,16–3,87) se asociaron con un resultado positivo de la PCR. Según el análisis de las curvas ROC, el criterio 5 tuvo la mayor capacidad de discriminación, aunque sin diferencias significativas con los otros cuatro criterios. Conclusiones. El criterio 5 —basado en la anosmia, el contacto estrecho con personas enfermas de COVID- 19 y la fiebre como elementos únicos suficientes— tuvo la mayor sensibilidad para identificar los casos sospechosos de COVID-19, aspecto fundamental para controlar la propagación de la pandemia.

Objetivo. Determinar la prevalencia y los factores de riesgo para sífilis en población indígena masculina de Paraguay durante el año 2017. Material y métodos. Se realizó un estudio observacional, descriptivo, con muestro probabilístico, estratificado y multietápico. Fueron incluidos indígenas de sexo masculino, mayores de 15 años de edad, de cinco familias lingüísticas residentes en Paraguay durante el periodo de estudio. Resultados. La prevalencia de sífilis en hombres de la población indígena de Paraguay fue de 4.50%. Los indígenas que tenían entre 15 y 20 años tuvieron 2.70 probabilidades de presentar sífilis. Asimismo, los participantes que reportaron múltiples parejas en el último año, sexo transaccional y consumir alcohol en la última relación sexual tuvieron 2.69, 3.06 ym 2.16 veces la probabilidad de presentar sífilis, respectivamente. Conclusiones. Se encontró una prevalencia moderada de sífilis en la población indígena masculina. La prevalencia fue de dos veces más para aquéllos que tenían más de dos parejas sexuales, sexo transaccional y que involucraban alcohol durante la práctica sexual.

Background: Stroke is the second largest single cause of death and disability in Latin America and the Caribbean (LAC). There have been large overall declines in stroke mortality rates in most LAC countries in recent decades. Objective: To analyze trends in mortality caused by stroke in LAC countries in the period 1979–2015. Methods: We extracted data for age-standardized stroke mortality rates per 100,000 in LAC for the period 1979–2015 from the World Health Organization Mortality Database. Joinpoint regression was used to analyze the trends and compute the annual percent change (APC) in LAC as a whole and by country. Analyses were conducted by gender, region and World Bank income classification. Results: Mortality from stroke has decreased in LAC over the study period by an average APC of –1.9%. Most countries showed significant downward trends, with the sharpest decreases in Chile, Colombia and Uruguay. We recorded statistically significant decreases of –1.4% and –2.4% in mortality rates in men and women, respectively, in the whole LAC. Southern and high-income countries showed the steepest decreases. Conclusions: Stroke mortality has decreased in LAC, in both sexes, especially in southern and high-income countries. Our results could serve as a reference for the development of primary prevention and acute management of stroke policies focused on countries with higher mortality.

Abstract Background The Pediatric Quality of Life Inventory™ (PedsQL™) Oral Health Scale was developed to measure oral health-related quality of life (OHRQoL). The aim of this study was to cross-culturally adapt the parent-reported version for toddlers of PedsQL™ Oral Health Scale into Spanish and to assess the acceptability, reliability and validity of this version in Chilean preschool population. Methods The PedsQL™ Oral Health Scale for toddlers was cross-culturally adapted for the Spanish language using the recommended standards. To assess metric properties, a cross-sectional study was carried out with 301 children aged 2 to 5 years in Carahue, Chile. Chilean versions of the PedsQL™ Oral Health Scale, PedsQL™ 4.0 Generic Core Scales, and Early Childhood Oral Health Impact Scale (ECOHIS) were completed by the children’s parents. Dental caries, malocclusion and dental trauma were examined by trained dentists. The PedsQL™ Oral Health Scale was administrated a second time 14–21 days after. The reliability of the scale was verified by analysis of internal consistency (Cronbach’s alpha) and reproducibility (Intraclass correlation coefficient – ICC). The validity of the construct was assessed by confirmatory factor analysis and known groups method. The convergent validity was assessed by calculating the Spearman’s correlation with the ECOHIS questionnaire. Results The PedsQL™ Oral Health Scale demonstrated good reliability, with Cronbach’s alpha coefficient of 0.79 and ICC of 0.85. A moderate-to-strong correlation was found between the PedsQL™ Oral Health Scale and the ECOHIS questionnaire (− 0.64); the PedsQL™ Oral Health Scale score was lower in children with poor than those with excellent/very good oral health (median 100 vs 85, p

Background & Aims: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems and it may have heavily impacted patients with liver cancer (LC). Herein, we evaluated whether the schedule of LC screening or procedures has been interrupted or delayed because of the COVID-19 pandemic. Methods: An international survey evaluated the impact of the COVID-19 pandemic on clinical practice and clinical trials from March 2020 to June 2020, as the first phase of a multicentre, international, and observational project. The focus was on patients with hepatocellular carcinoma or intrahepatic cholangiocarcinoma, cared for around the world during the first COVID-19 pandemic wave. Results: Ninety-one centres expressed interest to participate and 76 were included in the analysis, from Europe, South America, North America, Asia, and Africa (73.7%, 17.1%, 5.3%, 2.6%, and 1.3% per continent, respectively). Eighty-seven percent of the centres modified their clinical practice: 40.8% the diagnostic procedures, 80.9% the screening programme, 50% cancelled curative and/or palliative treatments for LC, and 41.7% modified the liver transplantation programme. Forty-five out of 69 (65.2%) centres in which clinical trials were running modified their treatments in that setting, but 58.1% were able to recruit new patients. The phone call service was modified in 51.4% of centres which had this service before the COVID-19 pandemic (n = 19/37). Conclusions: The first wave of the COVID-19 pandemic had a tremendous impact on the routine care of patients with liver cancer. Modifications in screening, diagnostic, and treatment algorithms may have significantly impaired the outcome of patients. Ongoing data collection and future analyses will report the benefits and disadvantages of the strategies implemented, aiding future decision-making. Lay summary: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems globally. Herein, we assessed the impact of the first wave pandemic on patients with liver cancer and found that routine care for these patients has been majorly disrupted, which could have a significant impact on outcomes.

Abstract Background The recent implementation of PET with prostate specific membrane antigen (PSMA)-specific radiotracers into the clinical practice has resulted in the significant improvement of accuracy in the detection of prostate carcinoma (PCa). PSMA-expression in ganglia has been regarded as an important pitfall in prostate carcinoma-PET diagnostics but has not found any practical use for diagnosis or therapy. Methods We explored this phenomenon and demonstrated the applicability of peripheral ganglia in healthy rats as surrogates for small PSMA positive lesions for the preclinical evaluation of diagnostic PCa PET probes. Healthy rats were measured with PET/CT using the tracers [18F]DCFPyL, [Al18F]PSMA-11 and [68Ga]PSMA-11. Sections of ganglia were stained with an anti-PSMA antibody. [18F]DCFPyL uptake in ganglia was compared to that in LNCaP tumor xenografts in mice. Results Whereas [18F]DCFPyL and [68Ga]PSMA-11 were stable in vivo and accumulated in peripheral ganglia, [Al18F]PSMA-11 suffered from fast in vivo deflourination resulting in high bone uptake. Ganglionic PSMA expression was confirmed by immunohistochemistry. [18F]DCFPyL uptake and signal-to-noise ratio in the superior cervical ganglion was not significantly different from LNCaP xenografts. Conclusions Our results demonstrated the non-inferiority of the novel model compared to conventionally used tumor xenografts in immune compromised rodents with regard to reproducibility and stability of the PSMA signal. Furthermore, the model involves less expense and efforts while it is permanently available and avoids tumor-growth associated animal morbidity and distress. To the best of our knowledge, this is the first tumor-free model suitable for the in vivo evaluation of tumor imaging agents.

(1) Background: The diagnosis of COVID-19 is frequently made on the basis of a suggestive clinical history and the detection of SARS-CoV-2 RNA in respiratory secretions. However, the diagnostic accuracy of clinical features is unknown. (2) Objective: To assess the diagnostic accuracy of patient-reported clinical manifestations to identify cases of COVID-19. (3) Methodology: Cross-sectional study using data from a national registry in Chile. Infection by SARS-CoV-2 was confirmed using RT-PCR in all cases. Anonymised information regarding demographic characteristics and clinical features were assessed using sensitivity, specificity, and diagnostic odds ratios. A multivariable logistic regression model was constructed to combine epidemiological risk factors and clinical features. (4) Results: A total of 2,187,962 observations were available for analyses. Male participants had a mean age of 43.1 ± 17.5 years. The most common complaints within the study were headache (39%), myalgia (32.7%), cough (31.6%), and sore throat (25.7%). The most sensitive features of disease were headache, myalgia, and cough, and the most specific were anosmia and dysgeusia/ageusia. A multivariable model showed a fair diagnostic accuracy, with a ROC AUC of 0.744 (95% CI 0.743–0.746). (5) Discussion: No single clinical feature was able to fully confirm or exclude an infection by SARS-CoV-2. The combination of several demographic and clinical factors had a fair diagnostic accuracy in identifying patients with the disease. This model can help clinicians tailor the probability of COVID-19 and select diagnostic tests appropriate to their setting.

Abstract Background The Early Childhood Oral Health Impact Scale (ECOHIS) measures the impact of dental diseases on Oral Health-Related Quality of Life both in children and their families. The aim of this study was to develop a Chilean Spanish version of the ECOHIS that is conceptually equivalent to the original and to assess its acceptability, reliability and validity in the preschool population of Chile. Methods The Chilean version of the ECOHIS was obtained through a process including forward and back-translation, expert panel, and cognitive debriefing interviews. To assess metric properties, a cross-sectional study was carried out in Carahue, Southern Chile (April–October 2016). Children younger than six years old without systemic diseases, disabilities or chronic medication from eleven public preschools were included. Parents were invited to complete the Chilean version of the ECOHIS, PedsQL™4.0 Generic Core and PedsQL Oral Health scales, and to answer global questions about their children’s general and oral health. A subsample was administrated ECOHIS a second time 14–21 days after. A clinical examination was performed to assess dental caries, malocclusion, and traumatic dental injuries. Reliability was evaluated using measures of internal consistency (Cronbach’s alpha) and reproducibility (Intraclass correlation coefficient - ICC). Construct validity was assessed by testing hypotheses based on available evidence about known groups and relationships between different instruments. Results The content comparison of the back-translation with the original ECOHIS showed that all items except one were conceptually and linguistically equivalent. The cognitive debriefing showed a suitable understanding of the Chilean version by the parents. In the total sample (n = 302), the ECOHIS total score median was 1 (IQR 6), floor effect was 41.6%, and ceiling effect 0%. Cronbach’s alpha was 0.89 and the ICC was 0.84. The correlation between ECOHIS and PedsQL™4.0 Generic Core was weak (r = 0.21), while it was strong-moderate (r = 0.64) with the PedsQL Oral Health scale. In the known groups comparison, the ECOHIS total score was statistically higher in children with poor than excellent/very good oral health (median 11.6 vs 0, p

Artificial intelligence (AI) has recently intensified in the global economy due to the great competence that it has demonstrated for analysis and modeling in many disciplines. This situation is accelerating the shift towards a more automated society, where these new techniques can be consolidated as a valid tool to face the difficult challenge of credit fraud detection (CFD). However, tight regulations do not make it easy for financial entities to comply with them while using modern techniques. From a methodological perspective, autoencoders have demonstrated their effectiveness in discovering nonlinear features across several problem domains. However, autoencoders are opaque and often seen as black boxes. In this work, we propose an interpretable and agnostic methodology for CFD. This type of approach allows a double advantage: on the one hand, it can be applied together with any machine learning (ML) technique, and on the other hand, it offers the necessary traceability between inputs and outputs, hence escaping from the black-box model. We first applied the state-of-the-art feature selection technique defined in the companion paper. Second, we proposed a novel technique, based on autoencoders, capable of evaluating the relationship among input and output of a sophisticated ML model for each and every one of the samples that are submitted to the analysis, through a single transaction-level explanation (STE) approach. This technique allows each instance to be analyzed individually by applying small fluctuations of the input space and evaluating how it is triggered in the output, thereby shedding light on the underlying dynamics of the model. Based on this, an individualized transaction ranking (ITR) can be formulated, leveraging on the contributions of each feature through STE. These rankings represent a close estimate of the most important features playing a role in the decision process. The results obtained in this work were consistent with previous published papers, and showed that certain features, such as living beyond means, lack or absence of transaction trail, and car loans, have strong influence on the model outcome. Additionally, this proposal using the latent space outperformed, in terms of accuracy, our previous results, which already improved prior published papers, by 5.5% and 1.5% for the datasets under study, from a baseline of 76% and 93%. The contribution of this paper is twofold, as far as a new outperforming CFD classification model is presented, and at the same time, we developed a novel methodology, applicable across classification techniques, that allows to breach black-box models, erasingthe dependencies and, eventually, undesirable biases. We conclude that it is possible to develop an effective, individualized, unbiased, and traceable ML technique, not only to comply with regulations, but also to be able to cope with transaction-level inquiries from clients and authorities.

Artificial intelligence (AI) is rapidly shaping the global financial market and its services due to the great competence that it has shown for analysis and modeling in many disciplines. What is especially remarkable is the potential that these techniques could offer to the challenging reality of credit fraud detection (CFD); but it is not easy, even for financial institutions, to keep in strict compliance with non-discriminatory and data protection regulations while extracting all the potential that these powerful new tools can provide to them. This reality effectively restricts nearly all possible AI applications to simple and easy to trace neural networks, preventing more advanced and modern techniques from being applied. The aim of this work was to create a reliable, unbiased, and interpretable methodology to automatically evaluate CFD risk. Therefore, we propose a novel methodology to address the mentioned complexity when applying machine learning (ML) to the CFD problem that uses state-of-the-art algorithms capable of quantifying the information of the variables and their relationships. This approach offers a new form of interpretability to cope with this multifaceted situation. Applied first is a recent published feature selection technique, the informative variable identifier (IVI), which is capable of distinguishing among informative, redundant, and noisy variables. Second, a set of innovative recurrent filters defined in this work are applied, which aim to minimize the training-data bias, namely, the recurrent feature filter (RFF) and the maximally-informative feature filter (MIFF). Finally, the output is classified by using compelling ML techniques, such as gradient boosting, support vector machine, linear discriminant analysis, and linear regression. These defined models were applied both to a synthetic database, for better descriptive modeling and fine tuning, and then to a real database. Our results confirm that our proposal yields valuable interpretability by identifying the informative features’ weights that link original variables with final objectives. Informative features were living beyond one’s means, lack or absence of a transaction trail, and unexpected overdrafts, which are consistent with other published works. Furthermore, we obtained 76% accuracy in CFD, which represents an improvement of more than 4% in the real databases compared to other published works. We conclude that with the use of the presented methodology, we do not only reduce dimensionality, but also improve the accuracy, and trace relationships among input and output features, bringing transparency to the ML reasoning process. The results obtained here were used as a starting point for the companion paper which reports on our extending the interpretability to nonlinear ML architectures.

En este artículo, nosotros proponemos un enfoque para generar una planificación fundamentada en los conceptos de k-interacción y consenso, mostrando para ello un algoritmo que acopla la planta con dichos conceptos. En este sentido, se reducirán los modelos resultantes y en consecuencia la complejidad computacional.

Abstract Background The inverse problem in electrophysiology consists of the accurate estimation of the intracardiac electrical sources from a reduced set of electrodes at short distances and from outside the heart. This estimation can provide an image with relevant knowledge on arrhythmia mechanisms for the clinical practice. Methods based on truncated singular value decomposition (TSVD) and regularized least squares require a matrix inversion, which limits their resolution due to the unavoidable low-pass filter effect of the Tikhonov regularization techniques. Methods We propose to use, for the first time, a Mercer’s kernel given by the Laplacian of the distance in the quasielectrostatic field equations, hence providing a Support Vector Regression (SVR) formulation by following the principles of the Dual Signal Model (DSM) principles for creating kernel algorithms. Results Simulations in one- and two-dimensional models show the performance of our Laplacian distance kernel technique versus several conventional methods. Firstly, the one-dimensional model is adjusted for yielding recorded electrograms, similar to the ones that are usually observed in electrophysiological studies, and suitable strategy is designed for the free-parameter search. Secondly, simulations both in one- and two-dimensional models show larger noise sensitivity in the estimated transfer matrix than in the observation measurements, and DSM−SVR is shown to be more robust to noisy transfer matrix than TSVD. Conclusion These results suggest that our proposed DSM−SVR with Laplacian distance kernel can be an efficient alternative to improve the resolution in current and emerging intracardiac imaging systems.

Diabetes is a complex metabolic disease that exposes patients to the deleterious effects of hyperglycemia on various organs. Achievement of normoglycemia with exogenous insulin treatment requires the use of high doses of hormone, which increases the risk of life-threatening hypoglycemic episodes. We developed a gene therapy approach to control diabetic hyperglycemia based on co-expression of the insulin and glucokinase genes in skeletal muscle. Previous studies proved the feasibility of gene delivery to large diabetic animals with adeno-associated viral (AAV) vectors. Here, we report the long-term (∼8 years) follow-up after a single administration of therapeutic vectors to diabetic dogs. Successful, multi-year control of glycemia was achieved without the need of supplementation with exogenous insulin. Metabolic correction was demonstrated through normalization of serum levels of fructosamine, triglycerides, and cholesterol and remarkable improvement in the response to an oral glucose challenge. The persistence of vector genomes and therapeutic transgene expression years after vector delivery was documented in multiple samples from treated muscles, which showed normal morphology. Thus, this study demonstrates the long-term efficacy and safety of insulin and glucokinase gene transfer in large animals and especially the ability of the system to respond to the changes in metabolic needs as animals grow older.

Summary: Mammalian DNA replication origins are “licensed” by the loading of DNA helicases, a reaction that is mediated by CDC6 and CDT1 proteins. After initiation of DNA synthesis, CDC6 and CDT1 are inhibited to prevent origin reactivation and DNA overreplication before cell division. CDC6 and CDT1 are highly expressed in many types of cancer cells, but the impact of their deregulated expression had not been investigated in vivo. Here, we have generated mice strains that allow the conditional overexpression of both proteins. Adult mice were unharmed by the individual overexpression of either CDC6 or CDT1, but their combined deregulation led to DNA re-replication in progenitor cells and lethal tissue dysplasias. This study offers mechanistic insights into the necessary cooperation between CDC6 and CDT1 for facilitation of origin reactivation and describes the physiological consequences of DNA overreplication. : Muñoz et al. investigate the effects of deregulated DNA replication in vivo. The combined overexpression of CDC6 and CDT1, two key proteins that activate replication origins, resulted in aberrant origin reactivation, DNA overreplication, and lethal dysplasia in the intestine and other tissues. Keywords: CDC6, CDT1, DNA replication, replication origin, tissue dysplasia

This paper describes the kinematics used for the calculation of track geometric irregularities of a new Track Geometry Measuring System (TGMS) to be installed in railway vehicles. The TGMS includes a computer for data acquisition and process, a set of sensors including an inertial measuring unit (IMU, 3D gyroscope and 3D accelerometer), two video cameras and an encoder. The kinematic description, that is borrowed from the multibody dynamics analysis of railway vehicles used in computer simulation codes, is used to calculate the relative motion between the vehicle and the track, and also for the computer vision system and its calibration. The multibody framework is thus used to find the formulas that are needed to calculate the track irregularities (gauge, cross-level, alignment and vertical profile) as a function of sensor data. The TGMS has been experimentally tested in a 1:10 scaled vehicle and track specifically designed for this investigation. The geometric irregularities of a 90 m-scale track have been measured with an alternative and accurate method and the results are compared with the results of the TGMS. Results show a good agreement between both methods of calculation of the geometric irregularities.

COVID-19 has hit the hotel sector in a hitherto unknown way. This situation is producing a fundamental change in client behavior that makes crucial an adequate knowledge of their profile to overcome an uncertain environment. Customer Relationship Management (CRM) can provide key strategies in hospitality industry by generating a great amount of valuable information about clients, whereas Big Data tools are providing with unprecedented facilities to conduct massive analysis and to focus the client-to-business relationship. However, few instruments have been proposed to handle categorical features, which are the most usual in CRMs, aiming to adapt the statistical robustness with the best interpretability for the managers. Therefore, our aim was to identify the profiles of clients from an international hotel chain using the overall data in its CRM system. An analysis method was created involving three elements: First, Multiple Correspondence Analysis provides us with a statistical description of the interactions among categories and features. Second, bootstrap resampling techniques give us information about the statistical variability of the feature maps. Third, kernel methods provide easy-to-visualize domain descriptions based on confidence areas in the maps. The proposed methodology can provide an operative and statistically principled way to scrutinize the CRM profiles in hospitality.

Cluster headache (CH) belongs to the group III of The International Classification of Headaches. It is characterized by attacks of severe pain in the ocular/periocular area accompanied by cranial autonomic signs, including parasympathetic activation and sympathetic hypofunction on the symptomatic side. Iris pigmentation occurs in the neonatal period and depends on the sympathetic tone in each eye. We hypothesized that the presence of visible or subtle color iris changes in both eyes could be used as a quantitative biomarker for screening and early detection of CH. This work scrutinizes the scope of an automatic diagnosis-support system for early detection of CH, by using as indicator the error rate provided by a statistical classifier designed to identify the eye (left vs. right) from iris pixels in color images. Systematic tests were performed on a database with images of 11 subjects (four with CH, four with other ophthalmic diseases affecting the iris pigmentation, and three control subjects). Several aspects were addressed to design the classifier, including: (a) the most convenient color space for the statistical classifier; (b) whether the use of features associated to several color spaces is convenient; (c) the robustness of the classifier to iris spatial subregions; (d) the contribution of the pixels neighborhood. Our results showed that a reduced value for the error rate (lower than 0.25) can be used as CH marker, whereas structural regions of the iris image need to be taken into account. The iris color feature analysis using statistical classification is a potentially useful technique to investigate disorders affecting the autonomous nervous system in CH.

In this paper, a multibody dynamic model of a railway vehicle that assumes that vertical and lateral dynamics are weakly coupled, has been experimentally validated using an instrumented scaled vehicle running on a 5-inch-wide experimental track. The proposed linearised model treats the vertical and lateral dynamics of the multibody system almost independently, being coupled exclusively by the suspension forces. Several experiments have been carried out at the scaled railroad facilities at the University of Seville in order to test and validate the simulation model under different working conditions. The scaled vehicle used in the experiments is a bogie instrumented with various sensors that register the accelerations and angular velocities of the vehicle, its forward velocity, its position along the track, and the wheel–rail contact forces in the front wheelset. The obtained results demonstrate how the proposed computational model correctly reproduces the dynamics of the real mechanical system in an efficient computational manner.

During the last years, Electrocardiographic Imaging (ECGI) has emerged as a powerful and promising clinical tool to support cardiologists. Starting from a plurality of potential measurements on the torso, ECGI yields a noninvasive estimation of their causing potentials on the epicardium. This unprecedented amount of measured cardiac signals needs to be conditioned and adapted to current knowledge and methods in cardiac electrophysiology in order to maximize its support to the clinical practice. In this setting, many cardiac indices are defined in terms of the so-called bipolar electrograms, which correspond with differential potentials between two spatially close potential measurements. Our aim was to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology. For this purpose, we first analyzed the basic stages of conventional cardiac signal processing and scrutinized the implications of the spatial-temporal nature of signals in ECGI scenarios. Specifically, the stages of baseline wander removal, low-pass filtering, and beat segmentation and synchronization were considered. We also aimed to establish a mathematical operator to provide suitable bipolar electrograms from the ECGI-estimated epicardium potentials. Results were obtained on data from an infarction patient and from a healthy subject. First, the low-frequency and high-frequency noises are shown to be non-independently distributed in the ECGI-estimated recordings due to their spatial dimension. Second, bipolar electrograms are better estimated when using the criterion of the maximum-amplitude difference between spatial neighbors, but also a temporal delay in discrete time of about 40 samples has to be included to obtain the usual morphology in clinical bipolar electrograms from catheters. We conclude that spatial-temporal digital signal processing and bipolar electrograms can pave the way towards the usefulness of ECGI recordings in the cardiological clinical practice. The companion paper is devoted to analyzing clinical indices obtained from ECGI epicardial electrograms measuring waveform variability and repolarization tissue properties.

During the last years, attention and controversy have been present for the first commercially available equipment being used in Electrocardiographic Imaging (ECGI), a new cardiac diagnostic tool which opens up a new field of diagnostic possibilities. Previous knowledge and criteria of cardiologists using intracardiac Electrograms (EGM) should be revisited from the newly available spatial–temporal potentials, and digital signal processing should be readapted to this new data structure. Aiming to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology, we previously presented two results: First, spatial consistency can be observed even for very basic cardiac signal processing stages (such as baseline wander and low-pass filtering); second, useful bipolar EGMs can be obtained by a digital processing operator searching for the maximum amplitude and including a time delay. In addition, this work aims to demonstrate the functionality of ECGI for cardiac electrophysiology from a twofold view, namely, through the analysis of the EGM waveforms, and by studying the ventricular repolarization properties. The former is scrutinized in terms of the clustering properties of the unipolar an bipolar EGM waveforms, in control and myocardial infarction subjects, and the latter is analyzed using the properties of T-wave alternans (TWA) in control and in Long-QT syndrome (LQTS) example subjects. Clustered regions of the EGMs were spatially consistent and congruent with the presence of infarcted tissue in unipolar EGMs, and bipolar EGMs with adequate signal processing operators hold this consistency and yielded a larger, yet moderate, number of spatial–temporal regions. TWA was not present in control compared with an LQTS subject in terms of the estimated alternans amplitude from the unipolar EGMs, however, higher spatial–temporal variation was present in LQTS torso and epicardium measurements, which was consistent through three different methods of alternans estimation. We conclude that spatial–temporal analysis of EGMs in ECGI will pave the way towards enhanced usefulness in the clinical practice, so that atomic signal processing approach should be conveniently revisited to be able to deal with the great amount of information that ECGI conveys for the clinician.

The importance of gut microbiota in health and disease is being highlighted by numerous research groups worldwide. Atherosclerosis, the leading cause of heart disease and stroke, is responsible for about 50% of all cardiovascular deaths. Recently, gut dysbiosis has been identified as a remarkable factor to be considered in the pathogenesis of cardiovascular diseases (CVDs). In this review, we briefly discuss how external factors such as dietary and physical activity habits influence host-microbiota and atherogenesis, the potential mechanisms of the influence of gut microbiota in host blood pressure and the alterations in the prevalence of those bacterial genera affecting vascular tone and the development of hypertension. We will also be examining the microbiota as a therapeutic target in the prevention of CVDs and the beneficial mechanisms of probiotic administration related to cardiovascular risks. All these new insights might lead to novel analysis and CVD therapeutics based on the microbiota.

Abstract Prevalence of type 2 diabetes (T2D) and obesity is increasing worldwide. Currently available therapies are not suited for all patients in the heterogeneous obese/T2D population, hence the need for novel treatments. Fibroblast growth factor 21 (FGF21) is considered a promising therapeutic agent for T2D/obesity. Native FGF21 has, however, poor pharmacokinetic properties, making gene therapy an attractive strategy to achieve sustained circulating levels of this protein. Here, adeno‐associated viral vectors (AAV) were used to genetically engineer liver, adipose tissue, or skeletal muscle to secrete FGF21. Treatment of animals under long‐term high‐fat diet feeding or of ob/ob mice resulted in marked reductions in body weight, adipose tissue hypertrophy and inflammation, hepatic steatosis, inflammation and fibrosis, and insulin resistance for > 1 year. This therapeutic effect was achieved in the absence of side effects despite continuously elevated serum FGF21. Furthermore, FGF21 overproduction in healthy animals fed a standard diet prevented the increase in weight and insulin resistance associated with aging. Our study underscores the potential of FGF21 gene therapy to treat obesity, insulin resistance, and T2D.

In the present work, the use of porous titanium is proposed as a solution to the difference in stiffness between the implant and bone tissue, avoiding the bone resorption. Conventional powder metallurgical technique is an industrially established route for fabrication of this type of material. The results are discussed in terms of the influence of compaction pressure and sintering temperature on the porosity (volumetric fraction, size, and morphology) and the quality of the sintering necks. A very good agreement between the predicted values obtained using a simple 2D finite element model, the experimental uniaxial compression behavior, and the analytical model proposed by Nielsen, has been found for both the Young’s modulus and the yield strength. The porous samples obtained by the loose sintering technique and using temperatures between 1000 °C −1100 °C (about 40% of total porosity) are recommended for achieving a suitable biomechanical behavior for cortical bone partial replacement.