Cruise Ship Medical Malpractice Cases: Must Admiralty Courts Steer by the Star of Stare Decisis?

Everyone from honeymooners to golden agers is lured by promises of a dream vacation aboard a luxury cruise ship

El Podcast como Herramienta Educativa para Fortalecer las Competencias Comunicativas en Niños de 6to de Primaria de Educación Básica Regular (EBR), caso: Colegio Caminito del Perú

En el Perú el déficit de lectoescritura es un problema de larga data y tiene como consecuencia la limitación de la inteligencia y con ello las posibilidades profesionales se reducen de manera drástica. La finalidad de esta investigación es fortalecer las competencias comunicativas (comprensión y expresión oral, lectura y escritura) a través del podcast de una manera novedosa. En una secuencia de actividades donde se escucha, se lee y se crea un podcast. En otras palabras el podcast se integra al proceso de la lectura: antes de la lectura los estudiantes escuchan un audio y toman nota de las partes más importantes, luego, profundizan el tema mediante una lectura, después redactan un texto que convertirán en podcast, finalmente escucharán sus audios, para que experimenten el asombro de escucharse a sí mismos con el propósito de mejorar aquello que dijeron y como lo dijeron. Esta investigación tiene dos fases: la primera es la implementación de un taller y la segunda es la observación del funcionamiento del podcast en un aula de sexto grado de primaria de educación básica regular en la ciudad de Cusco. La propuesta se realizó a través de la investigación acción. Los resultados obtenidos son prometedores, el podcast se integra con cada una de las competencias comunicativas, además permite el uso práctico de los signos de puntuación, para expresar énfasis y voz propia. Finalmente el potencial creativo del podcast en temas, voces y matices es ilimitado.In Peru, the literacy deficit is a long-standing problem, and the constraint of intelligence is a consequence, and with it, the professional possibilities are drastically reduced. The purpose of this investigation is to strengthen communicative competencies (understanding and oral expression, reading, and writing) through podcasting in a novel way; in a sequence of activities where listening, reading, and creating a podcast are possible. In other words, the podcast is integrated into the reading process: Before reading, students listen to audio and take note of the most important parts; then deepen the topic by reading, next write a text that they will convert to a podcast; and at the end they listen to their audio, to experience the amazement of listening to themselves to improve what they said and how they said it. This research has two phases: the first is the implementation of a workshop, and the second is the observation of the podcast functioning in a sixth-grade classroom of regular basic education in the city of Cusco. The proposal was made through action research. The results obtained are promising, the podcast is integrated with each of the communicative skills, and it also allows the practical use of punctuation marks, to express oneself with different emphasis and own voices. Lastly, the creative potential for themes, voices and tone is limitless

Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios

Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing's syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification

Preanalytical Pitfalls in Untargeted Plasma Nuclear Magnetic Resonance Metabolomics of Endocrine Hypertension

Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing's syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies

Machine learning-based clinical outcome prediction in surgery for acromegaly

Purpose Biochemical remission (BR), gross total resection (GTR), and intraoperative cerebrospinal fluid (CSF) leaks are important metrics in transsphenoidal surgery for acromegaly, and prediction of their likelihood using machine learning would be clinically advantageous. We aim to develop and externally validate clinical prediction models for outcomes after transsphenoidal surgery for acromegaly. Methods Using data from two registries, we develop and externally validate machine learning models for GTR, BR, and CSF leaks after endoscopic transsphenoidal surgery in acromegalic patients. For the model development a registry from Bologna, Italy was used. External validation was then performed using data from Zurich, Switzerland. Gender, age, prior surgery, as well as Hardy and Knosp classification were used as input features. Discrimination and calibration metrics were assessed. Results The derivation cohort consisted of 307 patients (43.3% male; mean [SD] age, 47.2 [12.7] years). GTR was achieved in 226 (73.6%) and BR in 245 (79.8%) patients. In the external validation cohort with 46 patients, 31 (75.6%) achieved GTR and 31 (77.5%) achieved BR. Area under the curve (AUC) at external validation was 0.75 (95% confidence interval: 0.59–0.88) for GTR, 0.63 (0.40–0.82) for BR, as well as 0.77 (0.62–0.91) for intraoperative CSF leaks. While prior surgery was the most important variable for prediction of GTR, age, and Hardy grading contributed most to the predictions of BR and CSF leaks, respectively. Conclusions Gross total resection, biochemical remission, and CSF leaks remain hard to predict, but machine learning offers potential in helping to tailor surgical therapy. We demonstrate the feasibility of developing and externally validating clinical prediction models for these outcomes after surgery for acromegaly and lay the groundwork for development of a multicenter model with more robust generalization

Transcriptional Alterations in Hereditary and Sporadic Nonfunctioning Pancreatic Neuroendocrine Tumors According to Genotype.

BACKGROUND Nonfunctioning pancreatic neuroendocrine tumors (NFPanNETs) may be sporadic or inherited because of germline mutations associated with von Hippel-Lindau disease (VHL) or multiple endocrine neoplasia type 1 (MEN1). The clinical behavior of NFPanNETs is difficult to predict, even in tumors of the same stage and grade. The authors analyzed genotype-specific patterns of transcriptional messenger RNA (mRNA) levels of NFPanNETs to understand the molecular features that determine PanNET phenotype. METHODS Thirty-two samples were included for genome-wide mRNA gene expression analysis (9 VHL-associated, 10 MEN1-associated, and 9 sporadic NFPanNETs and 4 purified normal islet cell [NIC] samples). Validation of genes was performed by real-time polymerase chain reaction analysis and immunohistochemistry. Gene expression profiles were analyzed by tumor genotype, and pathway analysis was curated. RESULTS Consensus clustering of mRNA expression revealed separate clustering of NICs, VHL-associated NFPanNETs, and MEN1-associated NFPanNETs; whereas some sporadic tumors clustered with MEN1. Four of 5 MEN1-like sporadic PanNET subtypes had loss of heterozygosity at the MEN1 gene locus. Pathway analysis demonstrated subtype-specific pathway activation, comprising angiogenesis and immune response in VHL; neuronal development in MEN1; protein ubiquitination in the new MEN1/sporadic subtype; and cytokinesis and cilium/microtubule development in sporadic NFPanNETs. Among many genes, platelet-derived growth factor receptor β (PDGFRB), lymphoid enhancer-binding factor-1 (Lef-1), cyclin-dependent kinase 4 (CDK4), and CDK6 were upregulated in VHL or MEN1 NFPanNETs, providing potential subtype-specific treatment targets. CONCLUSIONS Distinct mRNA expression patterns were identified in sporadic-associated, VHL-associated, and MEN1-associated NFPanNETs. The current results uncover new pathways involved in NFPanNETs that are subtype-specific and provide potential new diagnostic or therapeutic targets based on tumor subtype. Cancer 2017. © 2017 American Cancer Society