4-Hydroxybenzoic acid rescues multisystemic disease and perinatal lethality in a mouse model of mitochondrial disease.

Coenzyme Q (CoQ) deficiency syndrome is conventionally treated with limited efficacy using exogenous CoQ10. Poor outcomes result from low absorption and bioavailability of CoQ10 and the clinical heterogenicity of the disease. Here, we demonstrate that supplementation with 4-hydroxybenzoic acid (4HB), the precursor of the benzoquinone ring in the CoQ biosynthetic pathway, completely rescues multisystemic disease and perinatal lethality in a mouse model of CoQ deficiency. 4HB stimulates endogenous CoQ biosynthesis in tissues of Coq2 mutant mice, normalizing mitochondrial function and rescuing cardiac insufficiency, edema, and neurodevelopmental delay. In contrast, exogenous CoQ10 supplementation falls short in fully restoring the phenotype. The treatment is translatable to human use, as proven by in vitro studies in skin fibroblasts from patients with pathogenic variants in COQ2. The therapeutic approach extends to other disorders characterized by deficiencies in the production of 4HB and early steps of CoQ biosynthesis and instances of secondary CoQ deficiency.

Membrane fission via transmembrane contact.

Division of intracellular organelles often correlates with additional membrane wrapping, e.g., by the endoplasmic reticulum or the outer mitochondrial membrane. Such wrapping plays a vital role in proteome and lipidome organization. However, how an extra membrane impacts the mechanics of the division has not been investigated. Here we combine fluorescence and cryo-electron microscopy experiments with self-consistent field theory to explore the stress-induced instabilities imposed by membrane wrapping in a simple double-membrane tubular system. We find that, at physiologically relevant conditions, the outer membrane facilitates an alternative pathway for the inner-tube fission through the formation of a transient contact (hemi-fusion) between both membranes. A detailed molecular theory of the fission pathways in the double membrane system reveals the topological complexity of the process, resulting both in leaky and leakless intermediates, with energies and topologies predicting physiological events.

Allosteric control of dynamin-related protein 1 through a disordered C-terminal Short Linear Motif.

The mechanochemical GTPase dynamin-related protein 1 (Drp1) catalyzes mitochondrial and peroxisomal fission, but the regulatory mechanisms remain ambiguous. Here we find that a conserved, intrinsically disordered, six-residue Short Linear Motif at the extreme Drp1 C-terminus, named CT-SLiM, constitutes a critical allosteric site that controls Drp1 structure and function in vitro and in vivo. Extension of the CT-SLiM by non-native residues, or its interaction with the protein partner GIPC-1, constrains Drp1 subunit conformational dynamics, alters self-assembly properties, and limits cooperative GTP hydrolysis, surprisingly leading to the fission of model membranes in vitro. In vivo, the involvement of the native CT-SLiM is critical for productive mitochondrial and peroxisomal fission, as both deletion and non-native extension of the CT-SLiM severely impair their progression. Thus, contrary to prevailing models, Drp1-catalyzed membrane fission relies on allosteric communication mediated by the CT-SLiM, deceleration of GTPase activity, and coupled changes in subunit architecture and assembly-disassembly dynamics.

Allosteric control of dynamin-related protein 1-catalyzed mitochondrial fission through a conserved disordered C-terminal Short Linear Motif.

The mechanochemical GTPase dynamin-related protein 1 (Drp1) catalyzes mitochondrial fission, but the regulatory mechanisms remain ambiguous. Here we found that a conserved, intrinsically disordered, six-residue Short Linear Motif at the extreme Drp1 C-terminus, named CT-SLiM, constitutes a critical allosteric site that controls Drp1 structure and function in vitro and in vivo. Extension of the CT-SLiM by non-native residues, or its interaction with the protein partner GIPC-1, constrains Drp1 subunit conformational dynamics, alters self-assembly properties, and limits cooperative GTP hydrolysis, leading to the fission of model membranes in vitro. In vivo, the availability of the native CT-SLiM is a requirement for productive mitochondrial fission, as both non-native extension and deletion of the CT-SLiM severely impair its progression. Thus, contrary to prevailing models, Drp1-catalyzed mitochondrial fission relies on allosteric communication mediated by the CT-SLiM, deceleration of GTPase activity, and coupled changes in subunit architecture and assembly-disassembly dynamics.

KnowSeq R-Bioc package: The automatic smart gene expression tool for retrieving relevant biological knowledge.

KnowSeq R/Bioc package is designed as a powerful, scalable and modular software focused on automatizing and assembling renowned bioinformatic tools with new features and functionalities. It comprises a unified environment to perform complex gene expression analyses, covering all the needed processing steps to identify a gene signature for a specific disease to gather understandable knowledge. This process may be initiated from raw files either available at well-known platforms or provided by the users themselves, and in either case coming from different information sources and different Transcriptomic technologies. The pipeline makes use of a set of advanced algorithms, including the adaptation of a novel procedure for the selection of the most representative genes in a given multiclass problem. Similarly, an intelligent system able to classify new patients, providing the user the opportunity to choose one among a number of well-known and widespread classification and feature selection methods in Bioinformatics, is embedded. Furthermore, KnowSeq is engineered to automatically develop a complete and detailed HTML report of the whole process which is also modular and scalable. Biclass breast cancer and multiclass lung cancer study cases were addressed to rigorously assess the usability and efficiency of KnowSeq. The models built by using the Differential Expressed Genes achieved from both experiments reach high classification rates. Furthermore, biological knowledge was extracted in terms of Gene Ontologies, Pathways and related diseases with the aim of helping the expert in the decision-making process. KnowSeq is available at Bioconductor (https://bioconductor.org/packages/KnowSeq), GitHub (https://github.com/CasedUgr/KnowSeq) and Docker (https://hub.docker.com/r/casedugr/knowseq).

Microfluidic chip with pillar arrays for controlled production and observation of lipid membrane nanotubes.

Lipid membrane nanotubes (NTs) are a widespread template for in vitro studies of cellular processes happening at high membrane curvature. Traditionally NTs are manufactured one by one, using sophisticated membrane micromanipulations, while simplified methods for controlled batch production of NTs are in growing demand. Here we propose a lab-on-a-chip (LOC) approach to the simultaneous formation of multiple NTs with length and radius controlled by the chip design. The NTs form upon rolling silica microbeads covered by lipid lamellas over the pillars of a polymer micropillar array. The array's design and surface chemistry set the geometry of the resulting free-standing NTs. The integration of the array inside a microfluidic chamber further enables fast and turbulence-free addition of components, such as proteins, to multiple preformed NTs. This LOC approach to NT production is compatible with the use of high power objectives of a fluorescence microscope, making real-time quantification of the different modes of the protein activity in a single experiment possible.

Combining patch-clamping and fluorescence microscopy for quantitative reconstitution of cellular membrane processes with Giant Suspended Bilayers.

In vitro reconstitution and microscopic visualization of membrane processes is an indispensable source of information about a cellular function. Here we describe a conceptionally novel free-standing membrane template that facilitates such quantitative reconstitution of membrane remodelling at different scales. The Giant Suspended Bilayers (GSBs) spontaneously swell from lipid lamella reservoir deposited on microspheres. GSBs attached to the reservoir can be prepared from virtually any lipid composition following a fast procedure. Giant unilamellar vesicles can be further obtained by GSB detachment from the microspheres. The reservoir stabilizes GSB during deformations, mechanical micromanipulations, and fluorescence microscopy observations, while GSB-reservoir boundary enables the exchange of small solutes with GSB interior. These unique properties allow studying macro- and nano-scale membrane deformations, adding membrane-active compounds to both sides of GSB membrane and applying patch-clamp based approaches, thus making GSB a versatile tool for reconstitution and quantification of cellular membrane trafficking events.

Leukemia multiclass assessment and classification from Microarray and RNA-seq technologies integration at gene expression level.

In more recent years, a significant increase in the number of available biological experiments has taken place due to the widespread use of massive sequencing data. Furthermore, the continuous developments in the machine learning and in the high performance computing areas, are allowing a faster and more efficient analysis and processing of this type of data. However, biological information about a certain disease is normally widespread due to the use of different sequencing technologies and different manufacturers, in different experiments along the years around the world. Thus, nowadays it is of paramount importance to attain a correct integration of biologically-related data in order to achieve genuine benefits from them. For this purpose, this work presents an integration of multiple Microarray and RNA-seq platforms, which has led to the design of a multiclass study by collecting samples from the main four types of leukemia, quantified at gene expression. Subsequently, in order to find a set of differentially expressed genes with the highest discernment capability among different types of leukemia, an innovative parameter referred to as coverage is presented here. This parameter allows assessing the number of different pathologies that a certain gen is able to discern. It has been evaluated together with other widely known parameters under assessment of an ANOVA statistical test which corroborated its filtering power when the identified genes are subjected to a machine learning process at multiclass level. The optimal tuning of gene extraction evaluated parameters by means of this statistical test led to the selection of 42 highly relevant expressed genes. By the use of minimum-Redundancy Maximum-Relevance (mRMR) feature selection algorithm, these genes were reordered and assessed under the operation of four different classification techniques. Outstanding results were achieved by taking exclusively the first ten genes of the ranking into consideration. Finally, specific literature was consulted on this last subset of genes, revealing the occurrence of practically all of them with biological processes related to leukemia. At sight of these results, this study underlines the relevance of considering a new parameter which facilitates the identification of highly valid expressed genes for simultaneously discerning multiple types of leukemia.

Cardiovascular risk factors: Is the metabolic syndrome related to aging? Epidemiology in a Portuguese population.

AIMS: The primary objective of our study is to determine the prevalence of the metabolic syndrome in the population. The secondary objective is to determine the prevalence of cardiovascular risk factors, anthropometric alterations and the prevalence of target organ damage and their relationship with aging. MATERIAL AND METHODS: The sample for the study was obtained by means of a consecutive population-based demonstration in 803 adults over 18 years of age belonging to the labor force of the company Grupo Delta SA. The study was carried out according to the guidelines of the Declaration of Helsinki. The individuals included in the study voluntarily participated, once informed of the purpose of the study, giving their prior verbal consent, to the company's human resources department, in the case of Delta Group workers. RESULTS: 23.8% of the population has metabolic syndrome more prevalent in males, no smoking, no significant alcohol consumption, sedentary, with a high Body mass index (BMI). Its prevalence increases with age. CONCLUSION: We found that the prevalence of metabolic syndrome increases with age and is present in people of working age, increasing the risk of cardiovascular diseases, work-related absences, and socio-economic costs.

Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM)-based classification including feature ranking was performed. The accuracy attained exceeded the 92% in overall recognition of the 7 different cancer-related skin states. The proposed integration scheme is expected to allow the co-integration with other state-of-the-art technologies such as RNA-seq.

Integration of RNA-Seq data with heterogeneous microarray data for breast cancer profiling.

BACKGROUND: Nowadays, many public repositories containing large microarray gene expression datasets are available. However, the problem lies in the fact that microarray technology are less powerful and accurate than more recent Next Generation Sequencing technologies, such as RNA-Seq. In any case, information from microarrays is truthful and robust, thus it can be exploited through the integration of microarray data with RNA-Seq data. Additionally, information extraction and acquisition of large number of samples in RNA-Seq still entails very high costs in terms of time and computational resources.This paper proposes a new model to find the gene signature of breast cancer cell lines through the integration of heterogeneous data from different breast cancer datasets, obtained from microarray and RNA-Seq technologies. Consequently, data integration is expected to provide a more robust statistical significance to the results obtained. Finally, a classification method is proposed in order to test the robustness of the Differentially Expressed Genes when unseen data is presented for diagnosis. RESULTS: The proposed data integration allows analyzing gene expression samples coming from different technologies. The most significant genes of the whole integrated data were obtained through the intersection of the three gene sets, corresponding to the identified expressed genes within the microarray data itself, within the RNA-Seq data itself, and within the integrated data from both technologies. This intersection reveals 98 possible technology-independent biomarkers. Two different heterogeneous datasets were distinguished for the classification tasks: a training dataset for gene expression identification and classifier validation, and a test dataset with unseen data for testing the classifier. Both of them achieved great classification accuracies, therefore confirming the validity of the obtained set of genes as possible biomarkers for breast cancer. Through a feature selection process, a final small subset made up by six genes was considered for breast cancer diagnosis. CONCLUSIONS: This work proposes a novel data integration stage in the traditional gene expression analysis pipeline through the combination of heterogeneous data from microarrays and RNA-Seq technologies. Available samples have been successfully classified using a subset of six genes obtained by a feature selection method. Consequently, a new classification and diagnosis tool was built and its performance was validated using previously unseen samples.

Window size impact in human activity recognition.

Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1-2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities.

Parálisis periódica tirotóxica hipopotasémica / Hypokalemic thyrotoxic periodic paralisis

Paciente varón de 29 años, natural y procedente de Lima, mestizo, con historia de dos meses de presentar tres episodios de debilidad y dolor muscular proximal de extremidades, con inicio y predominio en muslos, que llega incluso a presentar cuadriplejia flácida, que afecta severamente las extremidades inferiores a nivel de los músculos proximales. Durante el último episodio, el nivel de potasio sérico fue 2.0 mEq/L, el electrocardiograma evidenció taquicardia leve y discreto aplanamiento de la onda T. La corrección de la hipopotasemia permitió recuperar la fuerza muscular, revertir el dolor y las alteraciones electrocardiográficas.

Male patient of 29 years old, southamerican origin, with history of two months of had presented a flaccid cuadriplejia (he had two previous episodes of less intensity), affecting severely the inferior extremities at the proximal muscle level. During the last acute attack the potassium level was in 2,0 mEq/L, the ECG showed mild tachycardia and T wave flattening. The correction of the hypokalemia allowed to recuperate the muscle strength and reverse the electrocardiographic alterations. Besides, it was shown a thyrotoxic state.

Validación de índices antropométricos alternativos como marcadores del riesgo cardiovascular / Validation of alternative anthropometric indexes cardiovascular risk markers

Introducción: La obesidad se considera un factor de riesgo cardiovascular (FRCV). Índices antropométricos clásicos, como el índice de masa corporal (IMC), la circunferencia de la cintura (CC) o el índice cintura/cadera (ICC), pueden no discriminar adecuadamente el incremento de riesgo ocasionado por la obesidad, si bien la CC es el más aceptado como marcador de riesgo cardiovascular. Dado que la estatura es importante en algunos aspectos, como la resistencia insulínica, es preciso tenerla en consideración para establecer de manera más precisa el riesgo cardiovascular. Objetivo: Comprobar la utilidad de parámetros antropométricos alternativos como marcadores de riesgo cardiovascular. Material y métodos: Se realizó un estudio descriptivo transversal en883 sujetos de la población del este de Portugal, a los que se determinaron las medidas antropométricas, presión arterial, analíticas, FRCV y otros antecedentes. El riesgo cardiovascular se calculó según el método de Framingham modificado. Resultados: Todos los índices antropométricos mostraron correlación estadística significativa con el riesgo cardiovascular, si bien el ICC(r = 0,48), el índice cintura/talla (ICT) (r = 0,41) y la CC (r = 0,45) fueron los más precisos. Cuando analizamos los datos por sexos, el ICT (r = 0,46) fue el que mejor estimaba el RCV en mujeres, y el ICC, en varones(r = 0,44).Conclusiones: El estudio realizado muestra que el ICT es un índice antropométrico de similar utilidad para estimar el riesgo cardiovascular, y es algo superior a los demás en las mujeres (AU)

Introduction: Obesity is considered as a cardiovascular risk factor (CVRF).Anthropometric indexes as body mass index (BMI) or waist-to-hip ratio (WHR)may not reflect properly an increased risk due to obesity, but abdominal circumference is the most accepted as cardiovascular risk marker. As height is important in some instances as insulin resistance, is mandatory to take it into account to evaluate more accurately cardiovascular risk. Objective: To test the utility of alternative anthropometrical indexes as cardiovascular risk markers. Material and methods: A descriptive cross-sectional study was developed with883 subjects in East Portugal, having anthropometric measurements, blood pressure, laboratory tests, CVRF, and history reported. Cardiovascular risk was calculated according to modified Framingham method. Results: All of the anthropometric indexes showed statistically significant correlation with cardiovascular risk, but WHR(r = 0.48), followed by waist-to-height ratio(r = 0.41) and abdominal circumference(r = 0.45) were the most accurate. When data were analyzed by sex, waist-to-heightratio (r = 0.46) was better in women and WHR (r = 0.44) in men. Conclusions: This study shows that waist-to-height ratio is as useful as others to estimate cardiovascular risk, being better among women (AU)

[Validation of alternative anthropometric indexes as cardiovascular risk markers]. / Validación de índices antropométricos alternativos como marcadores del riesgo cardiovascular.

INTRODUCTION: Obesity is considered as a cardiovascular risk factor (CVRF). Anthropometric indexes as body mass index (BMI) or waist-to-hip ratio (WHR) may not reflect properly an increased risk due to obesity, but abdominal circumference is the most accepted as cardiovascular risk marker. As height is important in some instances as insulin resistance, is mandatory to take it into account to evaluate more accurately cardiovascular risk. OBJECTIVE: To test the utility of alternative anthropometrical indexes as cardiovascular risk markers. MATERIAL AND METHODS: A descriptive cross-sectional study was developed with 883 subjects in East Portugal, having anthropometric measurements, blood pressure, laboratory tests, CVRF, and history reported. Cardiovascular risk was calculated according to modified Framingham method. RESULTS: All of the anthropometric indexes showed statistically significant correlation with cardiovascular risk, but WHR (r=0.48), followed by waist-to-height ratio (r=0.41) and abdominal circumference (r=0.45) were the most accurate. When data were analyzed by sex, waist-to-height ratio (r=0.46) was better in women and WHR (r=0.44) in men. CONCLUSIONS: This study shows that waist-to-height ratio is as useful as others to estimate cardiovascular risk, being better among women.