Miracle-dz/UniFAR-FTUs huggingface dataset:
Late-Life High Blood Pressure and Enlarged Perivascular Spaces in the Putaminal Regions of Community-Dwelling Japanese Older Persons

Background Enlarged perivascular spaces (EPVS) of the brain may be involved in dementia, such as Alzheimer’s disease and cerebral small vessel disease (CSVD). Hypertension has been reported to be a risk factor for dementia and CSVD, but the association between blood pressure (BP) and perivascular spaces is still unclear. The aim of this study was to determine the association between BP and EPVS volumes and to examine the interactions of relevant factors. Methods A total of 9296 community-dwelling subjects aged ≥65 years participated in a brain magnetic resonance imaging and health status screening examination. Perivascular volume was measured using a software package based on deep learning that was developed in-house. The associations between BP and EPVS volumes were examined by analysis of covariance and multiple regression analysis. Results Mean EPVS volumes increased significantly with rising systolic and diastolic BP levels (P for trend = .003, P for trend<.001, respectively). In addition, mean EPVS volumes increased significantly for every 1-mmHg-increment in systolic and diastolic BPs (both P values <.001). These significant associations were still observed in the sensitivity analysis after excluding subjects with dementia. Conclusions The present data suggest that higher systolic and diastolic BP levels are associated with greater EPVS volumes in cognitively normal older people.
Les modifications du sommeil et du cycle veille/sommeil au cours du vieillissement : approche par actimétrie et imagerie cérébrale

Les alterations du sommeil et du cycle veille/sommeil au cours du vieillissement constituent des facteurs de risque de l’apparition d’un declin cognitif et de l’evolution vers une demence. Pour autant, le lien entre ces alterations et les modifications cerebrales liees a l’âge reste encore peu connu. L’objectif de cette these a ete de determiner si les modifications du sommeil et du cycle veille/sommeil constituaient un marqueur de fragilite cerebrale pouvant etre associe a l'apparition de troubles cognitifs chez des personnes âgees de la population AMImage. Nous avons d’abord montre que le desaccord existant entre les questionnaires de sommeil et les mesures objectives en actimetrie est dependant de l’etat emotionnel, renforcant ainsi l’interet d’utiliser une methode de mesure objective du sommeil (Baillet et al., 2016). Puis, grâce a l’imagerie cerebrale, nous avons observe qu’une faible amplitude du cycle veille/sommeil est associee a une alteration de la microstructure de la substance blanche, suggerant ainsi une origine vasculaire (Baillet et al., 2017). Nous avons egalement observe qu'une faible qualite de sommeil est associee a une charge amyloide plus importante au sein des regions frontales, suggerant un deficit de clairance du peptide β-amyloide lors du sommeil. Ainsi, les perturbations du sommeil et du cycle veille sommeil chez les personnes âgees seraient associees a deux processus physiopathologiques distincts aboutissant a une fragilite cerebrale. Consideres comme des facteurs de risque modifiables, des interventions visant a ameliorer leur qualite offriraient une strategie prometteuse afin de reduire le declin cognitif au cours du vieillissement.
Comprehensive analysis of m6A methylomes in idiopathic pulmonary arterial hypertension

ABSTRACT Idiopathic pulmonary arterial hypertension (IPAH) is a serious and fatal disease. Recently, m6A has been reported to play an important role in the lungs of IPAH patients and experimental pulmonary hypertension models. However, the meaning of m6A mRNAs in the peripheral blood of IPAH patients remains largely unexplored. We aimed to construct a transcriptome-wide map of m6A mRNAs in the peripheral blood of IPAH patients. M6A RNA Methylation Quantification Kit was utilized to measure the total m6A levels in the peripheral blood of IPAH patients. A combination of MeRIP-seq, RNA-seq and bioinformatics analysis was utilized to select m6A-modified hub genes of IPAH. MeRIP-qPCR and RT-qPCR were used to measure the m6A levels and mRNA levels of TP53, RPS27A, SMAD3 and FoxO3 in IPAH patients. Western blot was performed to assess the protein levels of m6A related regulators and m6A related genes in experimental PH animal models, hypoxia-treated and PDGF-BB induced PASMCs. We found that the total m6A levels were increased in peripheral blood of IPAH patients and verified that m6A levels of RPS27A and SMAD3 were significantly elevated and m6A levels of TP53 and FoxO3 were significantly reduced. The mRNA or protein levels of RPS27A, SMAD3, TP53 and FoxO3 were changed in human blood samples, experimental PH animal models and PDGF-BB induced PASMCs. Moreover, METTL3 and YTHDF1 were increased in the hypoxia induced pulmonary hypertension rat model, hypoxia-treated and PDGF-BB induced PASMCs. These finding suggested that m6A may play an important role in IPAH.
Una Revisión de los Estimadores de Matrices de Bajo Rango y Matrices Dispersas

espanolSe presenta una revision selectiva de los desarrollos mas recientes en la estimacion de la matriz de covarianza con un numero de muestras menores a la dimension ambiente. En particular se consideran estimadores para las estructuras bajo rango y dispersa, dando especial atencion a los algoritmos mas utilizados en la practica. Se presentan estimadores que recurren al uso de tecnicas clasicas como umbrales y descomposicion de valor unico (SVD), asi como estimadores mas novedosos basados en matrices aleatorias y optimizacion convexa. Una de las principales conclusiones del estudio es que a pesar de los grandes avances en el desarrollo de nuevos estimadores, temas relacionados al tiempo de computo de los programas convexos que utilizan los estimadores han sido poco explorados. Ademas, se observa la falta de trabajos sobre el desarrollo de estimadores para matrices con estructura conjuntamente dispersa y bajo rango. EnglishA selective review of the most recent developments in the estimation of the covariance matrix with a number of samples smaller than the ambient dimension is presented. In particular, estimators are considered for low rank and sparse structures, paying special attention to the algorithms most used in practice. Estimators that resort to the use of classical techniques such as thresholds and singular-value decomposition (SVD), as well as newest estimators based on random matrices and convex optimization are presented. One of the main conclusions of the study is that, in spite of the great advances in the development of new estimators, issues related to the computation time of the convex programs that use the estimators have been little explored. Additionally, lack of works on the development of estimators for matrices with jointly sparse and low rank structure is observed
Facilitating youth diabetes studies with the most comprehensive epidemiological dataset available through a public web portal

The prevalence of type 2 diabetes mellitus (DM) and prediabetes (preDM) is rapidly increasing among youth, posing significant health and economic consequences. To address this growing concern, we created the most comprehensive youth-focused diabetes dataset to date derived from National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018. The dataset, consisting of 15,149 youth aged 12 to 19 years, encompasses preDM/DM relevant variables from sociodemographic, health status, diet, and other lifestyle behavior domains. An interactive web portal, POND (Prediabetes/diabetes in youth ONline Dashboard), was developed to provide public access to the dataset, allowing users to explore variables potentially associated with youth preDM/DM. Leveraging statistical and machine learning methods, we conducted two case studies, revealing established and lesser-known variables linked to youth preDM/DM. This dataset and portal can facilitate future studies to inform prevention and management strategies for youth prediabetes and diabetes.
A fearful adult attachment style is associated with double the prevalence of chronic pain compared to secure attachment: A national survey of a South African population

Our response to threats, including pain, are believed to be learnt during our early interpersonal relationships, and can be measured through attachment style. Preliminary epidemiological evidence suggests that insecure attachment styles are more prevalent in those with chronic pain. Our aim was to determine the association between adult attachment style and chronic pain prevalence and burden in a South African population. A nationwide online survey determined adult attachment style (using The Experience in Close Relationships - Relationship Structures (ECR-RS) Questionnaire), prevalence of chronic pain and typically-associated psychological factors. In those with chronic pain, the association with attachment style and pain burden (pain sites, severity and interference, using the Brief Pain Inventory) was further determined. Results of the 2371 individuals were analyzed using multivariate generalized linear models. In our young (median age 23 years; IQR 20-28), well-educated and primarily female (74%) cohort with predominantly a middle-to-high socioeconomic status, we found a high prevalence of chronic pain (27%). All three insecure attachment styles were associated with increased chronic pain prevalence when compared to the secure attachment style (Dismissing: 31%, Odds ratio [95%CI] = 1.38 [1.02-1.85], p=0.037; Preoccupied: 42%, Odds ratio [95%CI] = 2.26 [1.62-3.13], p<0.001; Fearful: 49%, Odds ratio [95%CI] = 2.95 [2.03-4.29], p<0.001). Adult attachment style was not directly associated with the burden of chronic pain, because pain catastrophizing mediated this relationship. Adult attachment style was, however, directly associated with chronic pain prevalence, with more than double the chronic pain prevalence in the fearfully, compared to securely, attached individuals.
Long-term potentiation-based screening identifies neuronal PYGM as a synaptic plasticity regulator participating in Alzheimer’s disease

Synaptic dysfunction is an important pathological hallmark and cause of Alzheimer’s disease (AD). High-frequency stimulation (HFS)-induced long-term potentiation (LTP) has been widely used to study synaptic plasticity, with impaired LTP found to be associated with AD. However, the exact molecular mechanism underlying synaptic plasticity has yet to be completely elucidated. Whether genes regulating synaptic plasticity are altered in AD and contribute to disease onset also remains unclear. Herein, we induced LTP in the hippocampal CA1 region of wild-type (WT) and AD model mice by administering HFS to the CA3 region and then studied transcriptome changes in the CA1 region. We identified 89 genes that may participate in normal synaptic plasticity by screening HFS-induced differentially expressed genes (DEGs) in mice with normal LTP, and 43 genes that may contribute to synaptic dysfunction in AD by comparing HFS-induced DEGs in mice with normal LTP and AD mice with impaired LTP. We further refined the 43 genes down to 14 by screening for genes with altered expression in pathological-stage AD mice without HFS induction. Among them, we found that the expression of Pygm, which catabolizes glycogen, was also decreased in AD patients. We further demonstrated that down-regulation of PYGM in neurons impaired synaptic plasticity and cognition in WT mice, while its overexpression attenuated synaptic dysfunction and cognitive deficits in AD mice. Moreover, we showed that PYGM directly regulated energy generation in neurons. Our study not only indicates that PYGM-mediated energy production in neurons plays an important role in synaptic function, but also provides a novel LTP-based strategy to systematically identify genes regulating synaptic plasticity under physiological and pathological conditions.
The protease ADAM17 at the crossroads of disease: revisiting its significance in inflammation, cancer, and beyond

The protease A Disintegrin And Metalloproteinase 17 (ADAM17) plays a central role in the pathophysiology of several diseases. ADAM17 is involved in the cleavage and shedding of at least 80 known membrane‐tethered proteins, which subsequently modulate several intracellular signaling pathways, and therefore alter cell behavior. Dysregulated expression and/or activation of ADAM17 has been linked to a wide range of autoimmune and inflammatory diseases, cancer, and cardiovascular disease. In this review, we provide an overview of the current state of knowledge from preclinical models and clinical data on the diverse pathophysiological roles of ADAM17, and discuss the mechanisms underlying ADAM17‐mediated protein shedding and the potential therapeutic implications of targeting ADAM17 in these diseases.
Deconvoluting gene and environment interactions to develop an “epigenetic score meter” of disease

Human health is determined both by genetics (G) and environment (E). This is clearly illustrated in groups of individuals who are exposed to the same environmental factor showing differential responses. A quantitative measure of the gene–environment interactions (GxE) effects has not been developed and in some instances, a clear consensus on the concept has not even been reached; for example, whether cancer is predominantly emerging from “bad luck” or “bad lifestyle” is still debated. In this article, we provide a panel of examples of GxE interaction as drivers of pathogenesis. We highlight how epigenetic regulations can represent a common connecting aspect of the molecular bases. Our argument converges on the concept that the GxE is recorded in the cellular epigenome, which might represent the key to deconvolute these multidimensional intricated layers of regulation. Developing a key to decode this epigenetic information would provide quantitative measures of disease risk. Analogously to the epigenetic clock introduced to estimate biological age, we provocatively propose the theoretical concept of an “epigenetic score‐meter” to estimate disease risk.
Failure Mode and Effects Analysis Using Two-Dimensional Uncertain Linguistic Variables and Alternative Queuing Method

This study develops an improved failure mode and effects analysis (FMEA) method using two-dimensional uncertain linguistic variables (2DULVs) and alternative queuing method (AQM). The 2DULVs are employed to represent the evaluations provided by FMEA team members on the weights of risk factors and the risk of failure modes in the form of pairwise comparisons. The two-dimensional uncertain linguistic best worst method (2DUL-BWM) is used to derive the weights of risk factors. The two-dimensional uncertain linguistic AQM (2DUL-AQM) is proposed for determining the risk ranking of the identified failure modes. Finally, the maintenance of a water treatment plant is presented as an example to demonstrate the applicability and effectiveness of the proposed FMEA method. By comparing its performance with those of other existing methods, the proposed FMEA is shown to be more advantageous in ranking the risk of failure modes.
High‐flow nasal cannula oxygen therapy for the treatment of acute respiratory failure secondary to SARS‐CoV‐2 pneumonia out of ICU

High‐flow nasal cannula oxygen therapy (HFNC) has been successfully used for the treatment of acute hypoxaemic respiratory failure (AHRF) secondary to SARS‐CoV‐2 pneumonia and being effective in reducing progression to invasive mechanical ventilation. The objective of this study was to assess the usefulness of HFNC on a hospital ward for the treatment of AHRF secondary to SARS‐CoV‐2 pneumonia and its impact on the need for intensive care unit (ICU) admission and endotracheal intubation. Other objectives include identifying potential physiological parameters and/or biomarkers for predicting treatment failure and assessing the clinical course and survival.
A low-cost pose-measuring system for robot calibration

A low-cost measuring system; printed Wed, 22 May 1996 2 1. Abstract To maintain robot accuracy, calibration equipment is needed. In this paper we present a self-calibrating measuring system based on a camera in the robot hand plus a known reference object in the robot workspace. A collection of images of the reference object is obtained. Using image-processing, image-recognition and photogrammetric techniques, the positions and orientations of the camera are computed. The essential geometrical and optical camera parameters can be derived from the redundancy in the measurements. From each image the positions of markers on the reference object are extracted and the individual markers are identified. The camera positions for all images plus the parameters of the camera are solved together in a non-linear least-squares fitting procedure. Experimental results for this low-cost measuring system are presented. Current and future robot applications require accurate position control for the robot. Robot repeatability has become much better in recent years, making this possible, in principle. Yet, more is needed to realise such accurate control, namely, an accurate control model, describing all the robot properties that influence the robot's positioning. The development of such models is described by Schröer [13]. The parameters in the model may change over time and therefore need to be determined repeatedly to maintain the control accuracy. Therefore, an easy-to-operate measuring system for use on the work floor is desirable for incidental and periodic (partial) recalibration. Depending on the aims of a calibration session and the circumstances under which it is performed, different requirements must be met by the measuring and data-analysis procedures. It is easier to attain a moderate improvement in the positioning accuracy over a limited part of the reachable work space than to accurately identify all model parameters for a robot. Calibrating a robot at first installation is different from recalibrating a robot in a production line. At the University of Amsterdam, we have developed a simple measuring system based on a camera in the robot hand, plus a known reference object in the robot workspace. It can be used to measure the 6-D robot pose in a limited part of the robot operating volume. The measuring system itself has been described A low-cost measuring system; printed Wed, 22 May 1996 3 elsewhere [1]. In this paper we shall describe the various data-processing procedures required. This work described was performed for CAR, ESPRIT project nr. 5220 1. …
Metabolomic profiling of a neurodegenerative retina following optic nerve transection

The degeneration of retinal ganglion cells (RGCs) often causes irreversible vision impairment. Prevention of RGC degeneration can prevent or delay the deterioration of visual function. The present study aimed to investigate retinal metabolic profiles following optic nerve transection (ONT) injury and identify the potential metabolic targets for the prevention of RGC degeneration. Retinal samples were dissected from ONT group and non-ONT group. The untargeted metabolomics were carried out using liquid chromatography-tandem mass spectrometry. The involved pathways and biomarkers were analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and MetaboAnalyst 5.0. In the ONT group, 689 disparate metabolites were detected, including lipids and lipid-like molecules. A total of 122 metabolites were successfully annotated and enriched in 50 KEGG pathways. Among them, ‘sphingolipid metabolism’ and ‘primary bile acid biosynthesis’ were identified involved in RGC degeneration. A total of five metabolites were selected as the candidate biomarkers for detecting RGC degeneration with an AUC value of 1. The present study revealed that lipid-related metabolism was involved in the pathogenesis of retinal neurodegeneration. Taurine, taurochenodesoxycholic acid, taurocholic acid (TCA), sphingosine, and galabiosylceramide are shown as the promising biomarkers for the diagnosis of RGC degeneration.
Strategies for capillary electrophoresis: Method development and validation for pharmaceutical and biological applications—Updated and completely revised edition

This review is in support of the development of selective, precise, fast, and validated capillary electrophoresis (CE) methods. It follows up a similar article from 1998, Wätzig H, Degenhardt M, Kunkel A. “Strategies for capillary electrophoresis: method development and validation for pharmaceutical and biological applications,” pointing out which fundamentals are still valid and at the same time showing the enormous achievements in the last 25 years. The structures of both reviews are widely similar, in order to facilitate their simultaneous use. Focusing on pharmaceutical and biological applications, the successful use of CE is now demonstrated by more than 600 carefully selected references. Many of those are recent reviews; therefore, a significant overview about the field is provided. There are extra sections about sample pretreatment related to CE and microchip CE, and a completely revised section about method development for protein analytes and biomolecules in general. The general strategies for method development are summed up with regard to selectivity, efficiency, precision, analysis time, limit of detection, sample pretreatment requirements, and validation.
Gravitational wave astronomy with LIGO and similar detectors in the next decade

We describe the plans for gravitational-wave observations and astrophysics that will be carried out by the LIGO Scientific Collaboration (LSC) in the next decade using data from the LIGO Observatories in the US, and sister facilities abroad in Europe, Japan and India. We provide an overview of gravitational wave signal types that we are targeting, and the role of gravitational waves in time-domain multi-messenger astronomy. We briefly summarize what we can infer from the properties of detected signals, including astrophysical event rates and populations, tests of gravitational-wave properties, highly-dynamical and strong-field tests of General Relativity, probing matter under extreme conditions in neutron stars, and making cosmological measurements with gravitational-wave sources.
Circadian aspects in the aetiology and pathophysiology of insomnia

Because the endogenous circadian pacemaker is a very strong determinant of alertness/sleep propensity across the 24 h period, its mistiming may contribute to symptoms of insomnia (e.g., difficulties initiating sleep and maintaining sleep) and to the development of insomnia disorder. Despite the separation of insomnia and circadian rhythm disorders in diagnostic nosology implying independent pathophysiology, there is considerable evidence of co‐morbidity and interaction between them. Sleep onset insomnia is associated with later timed circadian rhythms and can be treated with morning bright light to shift rhythms to an earlier timing. It is also possible that the causal link may go in both directions and that having a delayed circadian rhythm can result in enough experiences of delayed sleep onset to lead to some conditioned insomnia or insomnia disorder further exacerbating a delayed circadian rhythm. Early morning awakening insomnia is associated with an advanced circadian phase (early timing) and can be treated with evening bright light resulting in a delay of rhythms and an improved ability to sleep later in the morning and to obtain more sleep. There is some evidence suggesting that sleep maintenance insomnia is associated with a blunted amplitude of circadian rhythm that may be treated with increased regularity of sleep and light exposure timing. However, this is an insomnia phenotype that requires considerably more circadian research as well as further insomnia clinical research with the other insomnia phenotypes incorporating circadian timing measures and treatments.