Explore the vast range of titles available.

Narcolepsy type 1 is caused by severe loss or lack of brain orexin neuropeptides. We conducted a phase 2, randomized, placebo-controlled trial of TAK-994, an oral orexin receptor 2-selective agonist, in patients with narcolepsy type 1. Patients with confirmed narcolepsy type 1 according to clinical criteria were randomly assigned to receive twice-daily oral TAK-994 (30 mg, 90 mg, or 180 mg) or placebo. The primary end point was the mean change from baseline to week 8 in average sleep latency (the time it takes to fall asleep) on the Maintenance of Wakefulness Test (range, 0 to 40 minutes; normal ability to stay awake, ≥20 minutes). Secondary end points included the change in the Epworth Sleepiness Scale (ESS) score (range, 0 to 24, with higher scores indicating greater daytime sleepiness; normal, <10) and the weekly cataplexy rate. Of the 73 patients, 17 received TAK-994 at a dose of 30 mg twice daily, 20 received 90 mg twice daily, 19 received 180 mg twice daily, and 17 received placebo. The phase 2 trial and an extension trial were terminated early owing to hepatic adverse events. Primary end-point data were available for 41 patients (56%); the main reason for missing data was early trial termination. Least-squares mean changes to week 8 in average sleep latency on the MWT were 23.9 minutes in the 30-mg group, 27.4 minutes in the 90-mg group, 32.6 minutes in the 180-mg group, and -2.5 minutes in the placebo group (difference vs. placebo, 26.4 minutes in the 30-mg group, 29.9 minutes in the 90-mg group, and 35.0 minutes the 180-mg group; P<0.001 for all comparisons). Least-squares mean changes to week 8 in the ESS score were -12.2 in the 30-mg group, -13.5 in the 90-mg group, -15.1 in the 180-mg group, and -2.1 in the placebo group (difference vs. placebo, -10.1 in the 30-mg group, -11.4 in the 90-mg group, and -13.0 in the 180-mg group). Weekly incidences of cataplexy at week 8 were 0.27 in the 30-mg group, 1.14 in the 90-mg group, 0.88 in the 180-mg group, and 5.83 in the placebo group (rate ratio vs. placebo, 0.05 in the 30-mg group, 0.20 in the 90-mg group, and 0.15 in the 180-mg group). A total of 44 of 56 patients (79%) receiving TAK-994 had adverse events, most commonly urinary urgency or frequency. Clinically important elevations in liver-enzyme levels occurred in 5 patients, and drug-induced liver injury meeting Hy's law criteria occurred in 3 patients. In a phase 2 trial involving patients with narcolepsy type 1, an orexin receptor 2 agonist resulted in greater improvements on measures of sleepiness and cataplexy than placebo over a period of 8 weeks but was associated with hepatotoxic effects. (Funded by Takeda Development Center Americas; TAK-994-1501 and TAK-994-1504 ClinicalTrials.gov numbers, NCT04096560 and NCT04820842.).

In this study, we review the application of digital technologies for health in China, examining the structure of its digital health governance. China’s digital health governance is of political commitment, cross-sectoral collaboration, and a comprehensive, all-encompassing approach that engages the entire society. However, the fragmentation of data remains a fundamental obstacle. The whole-of-society approach offers a valuable example for other low- and middle-income countries in promoting digital transformation.

In this article, we study finite mixtures of linear mixed-effects (FMLME) models that are useful for longitudinal regression modelling in the presence of heterogeneity in both fixed and random effects. These models are computationally challenging when the number of covariates is large, and traditional variable selection techniques become expensive to implement. We introduce a penalized likelihood approach, and propose a nested EM algorithm for efficient numerical computations. The resulting estimators are shown to possess consistency and sparsity properties, and to be asymptotically normally distributed. We illustrate the performance of our method through simulations and a real data example. Dans cet article, les auteurs étudient des mélanges finis de modèles linéaires à effets mixtes, qui sont utiles pour la régression de données longitudinales en présence d'hétérogénéité des composantes fixes et aléatoires. Lorsque le nombre de covariables est élevé, ces modèles sont exigeants sur le plan calculatoire et les techniques classiques de sélection de variable deviennent laborieuses. Les auteurs présentent une approche de vraisemblance pénalisée et proposent un algorithme EM emboîté afin de procéder aux calculs numériques de façon efficace. Ils démontrent les propriétés de convergence, d'éparpillement et de normalité asymptotique des estimateurs. Ils illustrent leur méthode à l'aide de données simulées et réelles.

Most introductory courses in probability include the definitions of, and relationships between, convergence in distribution, probability, and mean square. Surprisingly, there are also links between the apparently unrelated notion of statistical dependence and two of these modes of convergence. These links are virtually absent from both the research literature and probability texts. Our goal here is to fill this gap, and by so doing provide some insight into the three modes of convergence. In particular, we establish ultimate dependence between members of a sequence of convergent random variables and its nondegenerate limit when convergence is in probability and in mean square. Through simple examples and graphical displays, we convey the heuristics that underlie the main results.

Background The genetic architectures of colorectal cancer are distinct across different populations. To date, the majority of polygenic risk scores (PRSs) are derived from European (EUR) populations, which limits their accurate extrapolation to other populations. Here, we aimed to generate a PRS by incorporating East Asian (EAS) and EUR ancestry groups and validate its utility for colorectal cancer risk assessment among different populations. Methods A large-scale colorectal cancer genome-wide association study (GWAS), harboring 35,145 cases and 288,934 controls from EAS and EUR populations, was used for the EAS-EUR GWAS meta-analysis and the construction of candidate EAS-EUR PRSs via different approaches. The performance of each PRS was then validated in external GWAS datasets of EAS (727 cases and 1452 controls) and EUR (1289 cases and 1284 controls) ancestries, respectively. The optimal PRS was further tested using the UK Biobank longitudinal cohort of 355,543 individuals and ultimately applied to stratify individual risk attached by healthy lifestyle. Results In the meta-analysis across EAS and EUR populations, we identified 48 independent variants beyond genome-wide significance ( P < 5 × 10 −8 ) at previously reported loci. Among 26 candidate EAS-EUR PRSs, the PRS-CSx approach-derived PRS (defined as PRS CSx ) that harbored genome-wide variants achieved the optimal discriminatory ability in both validation datasets, as well as better performance in the EAS population compared to the PRS derived from known variants. Using the UK Biobank cohort, we further validated a significant dose-response effect of PRS CSx on incident colorectal cancer, in which the risk was 2.11- and 3.88-fold higher in individuals with intermediate and high PRS CSx than in the low score subgroup ( P trend = 8.15 × 10 −53 ). Notably, the detrimental effect of being at a high genetic risk could be largely attenuated by adherence to a favorable lifestyle, with a 0.53% reduction in 5-year absolute risk. Conclusions In summary, we systemically constructed an EAS-EUR PRS to effectively stratify colorectal cancer risk, which highlighted its clinical implication among diverse ancestries. Importantly, these findings also supported that a healthy lifestyle could reduce the genetic impact on incident colorectal cancer.

Indoor emergency response plays a critically important role in disaster management for cities, which must consider the evacuation of people in a dynamic indoor environment. The spatial model is the foundation for the specific analysis of indoor emergency responses, such as evacuations. The current spatial model for evacuation has three primary pitfalls: (1) it primarily focuses on static spatial information, such as rooms, doors, and windows, and lacks dynamic information, such as events and sensors; (2) it mainly focuses on the horizontal space and the static scene and lacks a multi-story component that considers the different properties of stairs compared to planar areas; and (3) it places emphasis on the indoor navigation calculation with a 2D/3D network, which lacks individual properties that can support more complicated analysis, such as congestion and stagnation. In this paper, we propose a dynamic indoor field model with three typical characteristics. (1) It includes not only static information but also dynamic information, such as outdoor and indoor building geometry, sensors, fire spread, and personnel behavior. (2) It supports multi-story buildings from the macro level (building level and floor level) to the micro level (room level and individual level) based on horizontal and vertical indoor space. (3) It supports spatial calculations based on a three-dimensional space grid and can analyze potential congestion and stagnation during evacuation. We design a corresponding evacuation method that supports individual evacuation route finding and evacuation assessment. We perform a series of analyses of the applicability of the proposed model and the efficiency of the designed evacuation method based on multi-story evacuation studies. The simulation includes a total evacuation population exceeding 7000 individuals, and the analysis suggests that the new model and algorithm are effective in planning indoor emergency routes that avoid potential congestion or stagnation.

Toxoplasma gondii (T. gondii) is an important apicomplexan parasite that causes zoonotic toxoplasmosis in humans and animals. Acute T. gondii infection leads to systemic immunopathology that may manifest as lung injury or pulmonary embolism. Ferroptosis is an iron-dependent regulated cell death driven by lethal lipid hydroperoxide accumulation. Emerging evidence implicates ferroptosis in infection-related tissue damage; however, the role of ferroptosis in T. gondii-induced lung injury remains to be explored. Mice were infected with T. gondii to establish a lung injury model. The body weight changes, survival rate, inflammatory cytokines, lung histopathology, and parasite burden were assessed. The key ferroptosis-related indicators involved in antioxidant, iron metabolism, and lipid metabolism pathways were analyzed in lung tissues using techniques such as transmission electron microscopy, western blotting, and immunohistochemistry. Deferiprone (DFP), an oral iron chelator that can inhibit ferroptosis, was used to investigate the potential role of ferroptosis in T. gondii lung injury. T. gondii infection induced lung injury in mice with thickening of alveolar septa and hemorrhage in alveolar spaces, accompanied by iron deposition. Crucially, T. gondii triggered ferroptosis in lung tissues of mice, evidenced by MDA elevation, GSH depletion, total iron and Fe overload, and mitochondrial cristae loss. Furthermore, iron metabolism pathways were disordered while antioxidant pathways were suppressed. DFP treatment reversed ferroptosis alterations, decreased inflammatory cytokines, attenuated pathological changes, reduced T. gondii burden, and prolonged survival of the infected mice. Our findings revealed that T. gondii infection triggered ferroptosis by compromising dysregulated iron metabolism and antioxidant defenses, playing a key role in T. gondii-induced lung injury. DFP exhibited a promising therapy effect for toxoplasmosis.

With the widespread deployment of ground, air and space sensor sources (internet of things or IoT, social networks, sensor networks), the integrated applications of real-time geospatial data from ubiquitous sensors, especially in public security and smart city domains, are becoming challenging issues. The traditional geographic information system (GIS) mostly manages time-discretized geospatial data by means of the Structured Query Language (SQL) database management system (DBMS) and emphasizes query and retrieval of massive historical geospatial data on disk. This limits its capability for on-the-fly access of real-time geospatial data for online analysis in real time. This paper proposes a hybrid database organization and management approach with SQL relational databases (RDB) and not only SQL (NoSQL) databases (including the main memory database, MMDB, and distributed files system, DFS). This hybrid approach makes full use of the advantages of NoSQL and SQL DBMS for the real-time access of input data and structured on-the-fly analysis results which can meet the requirements of increased spatio-temporal big data linking analysis. The MMDB facilitates real-time access of the latest input data such as the sensor web and IoT, and supports the real-time query for online geospatial analysis. The RDB stores change information such as multi-modal features and abnormal events extracted from real-time input data. The DFS on disk manages the massive geospatial data, and the extensible storage architecture and distributed scheduling of a NoSQL database satisfy the performance requirements of incremental storage and multi-user concurrent access. A case study of geographic video (GeoVideo) surveillance of public security is presented to prove the feasibility of this hybrid organization and management approach.

Intelligent navigation and facility management in complex indoor environments are issues at the forefront of geospatial information science. Indoor spaces with fine geometric and semantic descriptions provide a solid foundation for various indoor applications, but it is difficult to comprehensively extract free multi-floor indoor spaces from complex three-dimensional building models, such as those described using CityGML LoD4, with existing methods for the subdivision or extraction of indoor spaces based on vector topology processing. Therefore, this paper elaborates a new voxel-based approach for extracting free multi-floor indoor spaces from 3D building models. It transforms the complicated vector processing tasks into a simple raster process that consists of three steps: voxelization with semantic enhancement, voxel classification, and boundary extraction. Experiments illustrate that the proposed method can automatically and correctly extract free multi-floor indoor spaces, especially two typical kinds of open indoor spaces, namely, lobbies and staircases.

Pendant le confinement dû à la Covid-19 en Chine, l'enseignement du FLE à l'université s'est déroulé en ligne, ce qui nous invite à réfléchir sur la notion de « présence » dans le cadre de la FAD. Avec le soutien des TICE, les enseignants se sont habitués aux pratiques de la FAD pendant cette période exceptionnelle et ont même trouvé des méthodes créatives pour vaincre la discordance spatio-temporelle. Ensuite, nous constatons à travers la notion de « présence » une modification des rapports entre l'enseignant et les apprenants et aussi parmi les apprenants. Le paradigme pédagogique est ainsi en train de changer. Les présences cognitive, socio-affective et pédagogique ont émergé et nous orientent vers un enseignement post-covid hybride.