Regulation of Myc transcription by an enhancer cluster dedicated to pluripotency and early embryonic expression.

MYC plays various roles in pluripotent stem cells, including the promotion of somatic cell reprogramming to pluripotency, the regulation of cell competition and the control of embryonic diapause. However, how Myc expression is regulated in this context remains unknown. The Myc gene lies within a ~ 3-megabase gene desert with multiple cis-regulatory elements. Here we use genomic rearrangements, transgenesis and targeted mutation to analyse Myc regulation in early mouse embryos and pluripotent stem cells. We identify a topologically-associated region that homes enhancers dedicated to Myc transcriptional regulation in stem cells of the pre-implantation and early post-implantation embryo. Within this region, we identify elements exclusively dedicated to Myc regulation in pluripotent cells, with distinct enhancers that sequentially activate during naive and formative pluripotency. Deletion of pluripotency-specific enhancers dampens embryonic stem cell competitive ability. These results identify a topologically defined enhancer cluster dedicated to early embryonic expression and uncover a modular mechanism for the regulation of Myc expression in different states of pluripotency.

Restored glyoxylate metabolism after AGXT gene correction and direct reprogramming of primary hyperoxaluria type 1 fibroblasts.

Primary hyperoxaluria type 1 (PH1) is a rare inherited metabolic disorder characterized by oxalate overproduction in the liver, resulting in renal damage. It is caused by mutations in the AGXT gene. Combined liver and kidney transplantation is currently the only permanent curative treatment. We combined locus-specific gene correction and hepatic direct cell reprogramming to generate autologous healthy induced hepatocytes (iHeps) from PH1 patient-derived fibroblasts. First, site-specific AGXT corrected cells were obtained by homology directed repair (HDR) assisted by CRISPR-Cas9, following two different strategies: accurate point mutation (c.731T>C) correction or knockin of an enhanced version of AGXT cDNA. Then, iHeps were generated, by overexpression of hepatic transcription factors. Generated AGXT-corrected iHeps showed hepatic gene expression profile and exhibited in vitro reversion of oxalate accumulation compared to non-edited PH1-derived iHeps. This strategy set up a potential alternative cellular source for liver cell replacement therapy and a personalized PH1 in vitro disease model.

A Biophysics Toolbox for Reliable Data Acquisition and Processing in Integrated Force-Confocal Fluorescence Microscopy.

Integrated single-molecule force-fluorescence spectroscopy setups allow for simultaneous fluorescence imaging and mechanical force manipulation and measurements on individual molecules, providing comprehensive dynamic and spatiotemporal information. Dual-beam optical tweezers (OT) combined with a confocal scanning microscope form a force-fluorescence spectroscopy apparatus broadly used to investigate various biological processes, in particular, protein:DNA interactions. Such experiments typically involve imaging of fluorescently labeled proteins bound to DNA and force spectroscopy measurements of trapped individual DNA molecules. Here, we present a versatile state-of-the-art toolbox including the preparation of protein:DNA complex samples, design of a microfluidic flow cell incorporated with OT, automation of OT-confocal scanning measurements, and the development and implementation of a streamlined data analysis package for force and fluorescence spectroscopy data processing. Its components can be adapted to any commercialized or home-built dual-beam OT setup equipped with a confocal scanning microscope, which will facilitate single-molecule force-fluorescence spectroscopy studies on a large variety of biological systems.

[Relationship between thyroid function changes with work-/night-shifts and history of thyroid pathology among health personnel].

BACKGROUND: The study aim was to analyze the relationship between functional thyroid pathology and the exposure to work shifts / night shifts, and describe the most prevalent thyroid disorders based on the type of shift. METHODOLOGY: Cross-sectional study performed in the emergency department of a hospital in Almeria (Spain). Relationships between thyroxine and thyrotropin levels (TSH) and work shifts, professional category and history of thyroid pathology were analyzed. RESULTS: The study included 133 workers; 80.5% female, average age was 46.11 years (38 - 65), and 52% were part of the nursing staff; thyroid disorders were more frequent in female participants. Most participants (81.2%) had rotating shifts schedules and 11.3% night shifts (12.1% female and 7.7% male). Thyroid alterations were found in 27% of the participants (usually elevated TSH levels and normal thyroxine levels), particularly in those doing night shifts (61.1%). TSH alterations were more frequent in individuals doing night shifts than in rotating shifts (53.3 vs 13.0%; p<0.001). Individuals working night shifts had mean TSH values in the normal range, although significantly higher than the individuals in the rest of the shifts; thyroxine levels were found to be similar. No thyroid disorders were found in day shift participants. Night shift and a history of thyroid pathology were independent predictors of thyroid disorders. CONCLUSIONS: Night shift schedules and history of thyroid disorders are more frequent in female, both related to the presence of thyroid disorders, indicating the need to include the evaluation of these disorders in health surveillance programs and analyze gender differences.

Asociación de alteraciones de la función tiroidea con turnicidad/nocturnidad laboral y antecedentes de patología tiroidea en profesionales sanitarios / Relationship between thyroid function changes with work-/night-shifts and history of thyroid pathology among health personnel

Fundamento. El objetivo de este estudio es analizar la asociación entre la patologia funcional tiroidea y la exposición a turnicidad/nocturnidad laboral, y describir los trastornos tiroideos más prevalentes por turno de trabajo. Metodología. Estudio transversal realizado en un servicio de urgencias hospitalario de Almería (España). Se relacionaron los niveles de tiroxina y tirotropina (TSH) con el turno, la categoría profesional y los antecedentes de patologia tiroidea. Resultados. Se incluyeron 133 trabajadores, 80,5% mujeres, edad media 46,11 años (38 a 65) y 52% personal enfermero; las mujeres mostraron más frecuentemente antecedentes tiroideos. El 81,2% trabajaba en turno rotatorio y el 11,3% en turno nocturno (12,1% de mujeres y 7,7% de hombres). El 27% mostró alteraciones tiroideas, más frecuentemente niveles elevados de TSH con niveles normales de tiroxina, especialmente en turno nocturno (61,1%). Las alteraciones de TSH fueron más frecuentes en turno nocturno que en rotatorios (53,3 vs 13,0%; p<0,001). El turno nocturno presentó valores medios de TSH en rango normal pero significativamente superiores al resto de turnos, mientras los niveles de tiroxina fueron similares. El turno diurno no presentó alteraciones. El turno nocturno y la presencia de antecedentes fueron predictores independientes de presentar alteraciones tiroideas. Conclusiones. El turno nocturno y los antecedentes de patología tiroidea fueron más frecuentes en mujeres, y ambos se asociaron con la presencia de alteraciones tiroideas, indicando la necesidad de incluir la evaluación de dichas alteraciones en los programas de vigilancia de salud y de analizar las diferencias por sexo. (AU)

Background. The study aim was to analyze the relationship between functional thyroid pathology and the exposure to work shifts / night shifts, and describe the most prevalent thyroid disorders based on the type of shift. Methodology. Cross-sectional study performed in the emergency department of a hospital in Almeria (Spain). Relationships between thyroxine and thyrotropin levels (TSH) and work shifts, professional category and history of thyroid pathology were analyzed. Results. The study included 133 workers; 80.5% female, average age was 46.11 years (38 – 65), and 52% were part of the nursing staff; thyroid disorders were more frequent in female participants. Most participants (81.2%) had rotating shifts schedules and 11.3% night shifts (12.1% female and 7.7% male). Thyroid alterations were found in 27% of the participants (usually elevated TSH levels and normal thyroxine levels), particularly in those doing night shifts (61.1%). TSH alterations were more frequent in individuals doing night shifts than in rotating shifts (53.3 vs 13.0%; p<0.001). Individuals working night shifts had mean TSH values in the normal range, although significantly higher than the individuals in the rest of the shifts; thyroxine levels were found to be similar. No thyroid disorders were found in day shift participants. Night shift and a history of thyroid pathology were independent predictors of thyroid disorders. Conclusions. Night shift schedules and history of thyroid disorders are more frequent in female, both related to the presence of thyroid disorders, indicating the need to include the evaluation of these disorders in health surveillance programs and analyze gender differences. (AU)

Influence of Dietary Lipid Source Supplementation on Milk and Fresh Cheese from Murciano-Granadina Goats.

This study analyzes the influence of the incorporation of flaked linseed and fish oil in the diet on the resulting milk and cheese. Three dietary treatments were assayed in 350 milking Murciano-Granadina multiparous goats in full-lactation: a control diet and two experimental diets, one including flaked linseed (FL) at 3.88% of dry matter, and the other containing salmon oil (SO) at 2.64% of dry matter for three periods of 21 d. None of the dietary treatments affected the daily milk yield, cheese yield, or the physicochemical parameters of the milk and cheese. Regarding the fatty acid profile (FA), the milk and cheese from animals whose diets were supplemented with SO had a higher percentage of fatty acids than those obtained with the FL-supplemented diet, except for C18:0, C18:1, C18:2 n-6, trans-9, trans-12 C18:2, cis-9, trans-11 C18:2, C18:3, and C19:0, which reached their highest levels in milk obtained with the diet supplemented with FL. The decrease in the percentage of C16:0 was greater in the milk derived from the FL diet than from the SO diet. The FL-supplemented diet improved the nutritional value of milk due to a reduction in saturated fatty acids (SFAs) and increases in polyunsaturated fatty acids (PUFAs) and conjugated linoleic acid (CLA). The decrease in n-6/n-3 in the observed milk was more pronounced with the FL diet. No differences in the sensory profile were found for the milk and cheese derived from the different dietary treatments. Dietary n-3 treatments modified the fatty acid profile without making any sensory difference to milk and fresh cheese, accompanied by marginal modifications to the physicochemical profile. We conclude that dietary supplementation with flaked linseed or fish oil produces milk and cheese from Murciano-Granadina goats with a higher nutritional quality without modifying the sensory profile of the corresponding products obtained from animals that were fed a routine diet.

¿Podrían ayudarnos los algoritmos de machine learning en la predicción de hemorragia masiva a nivel prehospitalario? / Could machine learning algorithms help us in predicting massive hemorrhage at the prehospital level?

Objetivo: Comparación de la capacidad predictiva de diferentes algoritmos de machine learning (AML) respecto a escalas tradicionales de predicción de hemorragia masiva en pacientes con enfermedad traumática grave (ETG). Diseño: Sobre una base de datos de una cohorte retrospectiva con variables clínicas prehospitalarias y de resultado de hemorragia masiva se realizó un tratamiento de la base de datos para poder aplicar los AML, obteniéndose un conjunto total de 473 pacientes (80% entrenamiento, 20% validación). Para la modelización se realizó imputación proporcional y validación cruzada. El poder predictivo se evaluó con la métrica ROC y la importancia de las variables mediante los valores Shapley. Ámbito: Atención extrahospitalaria del paciente con ETG. Pacientes: Pacientes con ETG atendidos en el medio extrahospitalario por un servicio médico extrahospitalario desde enero de 2010 hasta diciembre de 2015 y trasladados a un centro de trauma en Madrid. Intervenciones: Ninguna. Variables de interés principales: Obtención y comparación de la métrica ROC de 4 AML: random forest, support vector machine, gradient boosting machine y neural network con los resultados obtenidos con escalas tradicionales de predicción. Resultados: Los diferentes AML alcanzaron valores ROC superiores al 0,85, teniendo medianas cercanas a 0,98. No encontramos diferencias significativas entre los AML. Cada AML ofrece un conjunto de variables diferentes, pero con predominancia de las variables hemodinámicas, de reanimación y de deterioro neurológico. Conclusiones: Los AML podrían superar a las escalas tradicionales de predicción en la predicción de hemorragia masiva. (AU)

Objective: Comparison of the predictive ability of various machine learning algorithms (MLA) versus traditional prediction scales for massive hemorrhage in patients with severe traumatic injury (ETG). Design: On a database of a retrospective cohort with prehospital clinical variables and massive hemorrhage outcome, a treatment of the database was performed to be able to apply the different MLA, obtaining a total set of 473 patients (80% training and 20% validation). For modeling, proportional imputation and cross validation were performed. The predictive power was evaluated with the ROC metric and the importance of the variables using the Shapley values. Setting: Out-of-hospital care of patients with ETG. Participants: Patients with ETG treated out-of-hospital by a prehospital medical service from January 2010 to December 2015 and transferred to a trauma center in Madrid. Interventions: None. Main variables of interest: Obtaining and comparing the ROC curve metric of 4 MLAs: random forest, support vector machine, gradient boosting machine and neural network with the results obtained with traditional prediction scales. Results: The different MLA reached ROC values higher than 0.85, having medians close to 0.98. We found no significant differences between MLAs. Each MLA offers a different set of more important variables with a predominance of hemodynamic, resuscitation variables and neurological impairment. Conclusions: MLA may be helpful in patients with massive hemorrhage by outperforming traditional prediction scales. (AU)

Shock Index and Physiological Stress Index for reestratifying patients with intermediate-high risk pulmonary embolism.

OBJECTIVE: Study and Evaluation of Two Scores: Shock Index (SI) and Physiological Stress Index (PSI) as discriminators for proactive treatment (reperfusion before decompensated shock) in a population of intermediate-high risk pulmonary embolism (PE). DESIGN: Using a database from a retrospective cohort with clinical variables and the outcome variable of "proactive treatment", a comparison of the populations was conducted. Optimal cut-off for "proactive treatment" points were obtained according to the SI and PSI. Comparisons were carried out based on the cut-off points of both indices. SETTING: Patients admitted to a mixed ICU for PE. PARTICIPANTS: Patients >18 years old admitted to the ICU with intermediate-high risk PE recruited from January 2015 to October 2022. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Population comparison and metrics regarding predictive capacity when determining proactive treatment. RESULTS: SI and PSI independently have a substandard predictive capacity for discriminating patients who may benefit from an early reperfusion therapy. However, their combined use improves detection of sicker intermediate-high risk PE patients (Sensitivity = 0.66) in whom an early reperfusion therapy may improve outcomes (Specificity = 0.9). CONCLUSIONS: The use of the SI and PSI in patients with intermediate-high risk PE could be useful for selecting patients who would benefit from proactive treatment.

Could machine learning algorithms help us predict massive bleeding at prehospital level?

OBJECTIVE: Comparison of the predictive ability of various machine learning algorithms (MLA) versus traditional prediction scales (TPS) for massive hemorrhage (MH) in patients with severe traumatic injury (STI). DESIGN: On a database of a retrospective cohort with prehospital clinical variables and MH outcome, a treatment of the database was performed to be able to apply the different AML, obtaining a total set of 473 patients (80% training, 20% validation). For modeling, proportional imputation and cross validation were performed. The predictive power was evaluated with the ROC metric and the importance of the variables using the Shapley values. SETTING: Out-of-hospital care of patients with STI. PARTICIPANTS: Patients with STI treated out-of-hospital by a out-of-hospital medical service from January 2010 to December 2015 and transferred to a trauma center in Madrid. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Obtaining and comparing the "Receiver Operating Characteristic curve" (ROC curve) metric of four MLAs: "random forest" (RF), "vector support machine" (SVM), "gradient boosting machine" (GBM) and "neural network" (NN) with the results obtained with TPS. RESULTS: The different AML reached ROC values higher than 0.85, having medians close to 0.98. We found no significant differences between AMLs. Each AML offers a different set of more important variables with a predominance of hemodynamic, resuscitation variables and neurological impairment. CONCLUSIONS: MLA may be helpful in patients with HM by outperforming TPS.