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Abstract Oral corticosteroid use is limited by side effects, some caused by off‐target actions on the mineralocorticoid receptor that disrupt electrolyte balance. AZD9567 is a selective, nonsteroidal glucocorticoid receptor modulator. The efficacy, safety, and tolerability of AZD9567 and prednisolone were assessed in a phase IIa study. Anti‐inflammatory mechanism of action was also evaluated in vitro in monocytes from healthy donors. In this randomized, double‐blind, parallel‐group, multicenter study, patients with active rheumatoid arthritis were randomized 1:1 to AZD9567 40 mg or prednisolone 20 mg once daily orally for 14 days. The primary end point was change from baseline in DAS28‐CRP at day 15. Secondary end points included components of DAS28‐CRP, American College of Rheumatology (ACR) response criteria (ACR20, ACR50, and ACR70), and safety end points, including serum electrolytes. Overall, 21 patients were randomized to AZD9567 (n = 11) or prednisolone (n = 10), and all completed the study. As anticipated, AZD9567 had a similar efficacy profile to prednisolone, with no clinically meaningful (i.e., >1.0) difference in change from baseline to day 15 in DAS28‐CRP between AZD9567 and prednisolone (least‐squares mean difference: 0.47, 95% confidence interval: −0.49 to 1.43). Similar results were observed for the secondary efficacy end points. In vitro transcriptomic analysis showed that anti‐inflammatory responses were similar for AZD9567, prednisolone, and dexamethasone. Unlike prednisolone, AZD9567 had no effect on the serum sodium:potassium ratio. The safety profile was not different from that of prednisolone. Larger studies of longer duration are required to determine whether AZD9567 40 mg may in the future be an alternative to prednisolone in patients with inflammatory disease.

Abstract Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

This study aimed to investigate the effect of selfie behavior to individual performance with extrovert personality as a moderating variable. Inconsistence result of the past research on narcissism topic is a uniqueness gap for this research. Previous research finding a positive and negative effect of selfie behavior to outcome. In this research we including personality as a moderating variable to clearly the result of selfismeffect to individual outcome. The other research gap is from the research sample. We using Gen.Z for the sample because that’s is under research and Gen. Z very closely with “selfie phenomena”. The study was conducted with 100 respondents. The sample technique of this research is non-probability sampling with purposive sampling technique. Sample of this research is Generation Z that’s based on previous research is under research. We have to test validity (face validity and factor loading) &reliability (cronbach’s alpha, AVE, and composite reliability) before hypothesis testing. We using a Partial Least Square 3 (PLS) for solve measurement of this research. The findings of the research is supported to hypothesis 1 that selfie behavior give a positive impact to individual performance. Hypothesis 2 is too supported that extrovert strength the relationship selfie behavior and individual performance. The conclusion that clarify the inconsistence previous research, that selfie behavior give a positive impact to individual performance, and extrovert strengthen relationship selfie behavior and individual performance.

The cells of the immune system respond to a great variety of different signals that frequently reach them simultaneously. Computational models of signaling pathways and cellular behavior can help us explore the biochemical mechanisms at play during such responses, in particular when those models aim at incorporating molecular details of intracellular reaction networks. Such detailed models can encompass hypotheses about the interactions among molecular binding domains and how these interactions are modulated by, for instance, post-translational modifications, or steric constraints in multi-molecular complexes. In this way, the models become formal representations of mechanistic immunological hypotheses that can be tested through quantitative simulations. Due to the large number of parameters (molecular abundances, association-, dissociation-, and enzymatic transformation rates) the goal of simulating the models can, however, in many cases no longer be the fitting of particular parameter values. Rather, the simulations perform sweeps through parameter space to test whether a model can account for certain experimentally observed features when allowing the parameter values to vary within experimentally determined or physiologically reasonable ranges. We illustrate how this approach can be used to explore possible mechanisms of immunological pathway crosstalk. Probing the input-output behavior of mechanistic pathway models through systematic simulated variations of receptor stimuli will soon allow us to derive cell population behavior from single-cell models, thereby bridging a scale gap that currently still is frequently addressed through heuristic phenomenological multi-scale models.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits.sup.1,2. Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal (http://azphewas.com/). The authors analyse rare protein-coding genetic variants for association with 18,780 traits in the UK Biobank cohort., Author(s): Quanli Wang [sup.1] , Ryan S. Dhindsa [sup.1] , Keren Carss [sup.2] , Andrew R. Harper [sup.2] , Abhishek Nag [sup.2] , Ioanna Tachmazidou [sup.2] , Dimitrios Vitsios [sup.2] [...]

Oral corticosteroid use is limited by side effects, some caused by off‐target actions on the mineralocorticoid receptor that disrupt electrolyte balance. AZD9567 is a selective, nonsteroidal glucocorticoid receptor modulator. The efficacy, safety, and tolerability of AZD9567 and prednisolone were assessed in a phase IIa study. Anti‐inflammatory mechanism of action was also evaluated in vitro in monocytes from healthy donors. In this randomized, double‐blind, parallel‐group, multicenter study, patients with active rheumatoid arthritis were randomized 1:1 to AZD9567 40 mg or prednisolone 20 mg once daily orally for 14 days. The primary end point was change from baseline in DAS28‐CRP at day 15. Secondary end points included components of DAS28‐CRP, American College of Rheumatology (ACR) response criteria (ACR20, ACR50, and ACR70), and safety end points, including serum electrolytes. Overall, 21 patients were randomized to AZD9567 (n = 11) or prednisolone (n = 10), and all completed the study. As anticipated, AZD9567 had a similar efficacy profile to prednisolone, with no clinically meaningful (i.e., >1.0) difference in change from baseline to day 15 in DAS28‐CRP between AZD9567 and prednisolone (least‐squares mean difference: 0.47, 95% confidence interval: −0.49 to 1.43). Similar results were observed for the secondary efficacy end points. In vitro transcriptomic analysis showed that anti‐inflammatory responses were similar for AZD9567, prednisolone, and dexamethasone. Unlike prednisolone, AZD9567 had no effect on the serum sodium:potassium ratio. The safety profile was not different from that of prednisolone. Larger studies of longer duration are required to determine whether AZD9567 40 mg may in the future be an alternative to prednisolone in patients with inflammatory disease. [ABSTRACT FROM AUTHOR]

Abstract The gold standard for precise diagnostic classification of brain tumors requires tissue sampling, which carries relevant procedural risks. Brain biopsies often have limited sensitivity and fail to address tumor heterogeneity, because small tissue parts are being examined. This study aims to explore the detection and quantification of diagnostically relevant somatic copy number aberrations (SCNAs) in cell-free DNA (cfDNA) extracted from cerebrospinal fluid (CSF) in a real-world cohort of patients with defined brain tumor subtypes. A total of 33 CSF samples were collected from 30 patients for cfDNA extraction. Shallow whole-genome sequencing was conducted on CSF samples containing > 3ng of cfDNA and corresponding tissue DNA from nine patients. The sequencing cohort encompassed 26 samples of 23 patients, comprising 12 with confirmed CNS cancer as compared to 11 patients with either ambiguous CNS lesions (n = 5) or non-cancer CNS lesions (n = 6). After mapping and quality filtering SCNAs were called by depth-of-coverage analyses with a binning of 5.5 Mbp. SCNAs were exclusively identified in CSF cfDNA from brain tumor patients (10/12, 83%). In tumor patients, SCNAs were detectable in cfDNA from all patients with, but also in five of seven patients without tumor cells detected by CSF cytopathology. A substantial number of shared SCNAs were traceable between tissue and CSF in matched pair analyses. Additionally, some SCNAs unique to either CSF or tissue indicating spatial heterogeneity or tumor evolution. Also, diagnostically relevant genomic alterations as well as essential and desirable SCNAs as implemented in the current WHO classification of CNS tumors for certain primary brain tumor subtypes were traceable. In summary, this minimally invasive cfDNA-based LB approach employing shallow whole genome sequencing demonstrates potential for providing a molecularly informed diagnosis of CNS cancers, mapping tumor heterogeneity, tracking tumor evolution, and surveilling tumor patients. Further prospective trials are warranted.

Abstract Microresonator frequency combs (microcombs) hold great potential for precision metrology within a compact form factor, impacting a wide range of applications such as point-of-care diagnostics, environmental monitoring, time-keeping, navigation and astronomy. Through the principle of self-injection locking, electrically-driven chip-based microcombs with minimal complexity are now feasible. However, phase-stabilisation of such self-injection-locked microcombs—a prerequisite for metrological frequency combs—has not yet been attained. Here, we address this critical need by demonstrating full phase-stabilisation of a self-injection-locked microcomb. The microresonator is implemented in a silicon nitride photonic chip, and by controlling a pump laser diode and a microheater with low voltage signals (less than 1.57 V), we achieve independent control of the comb’s offset and repetition rate frequencies. Both actuators reach a bandwidth of over 100 kHz, enabling phase-locking of the microcomb to external frequency references. These results establish photonic chip-based, self-injection-locked microcombs as low-complexity yet versatile sources for coherent precision metrology in emerging applications.

Abstract Functionally relevant coronary artery disease (fCAD) can result in premature death or nonfatal acute myocardial infarction. Its early detection is a fundamentally important task in medicine. Classical detection approaches suffer from limited diagnostic accuracy or expose patients to possibly harmful radiation. Here we show how machine learning (ML) can outperform cardiologists in predicting the presence of stress-induced fCAD in terms of area under the receiver operating characteristic (AUROC: 0.71 vs. 0.64, p = 4.0E-13). We present two ML approaches, the first using eight static clinical variables, whereas the second leverages electrocardiogram signals from exercise stress testing. At a target post-test probability for fCAD of

Neutrophil recruitment from blood to extravascular sites of sterile or infectious tissue damage is a hallmark of early innate immune responses, and the molecular events leading to cell exit from the bloodstream have been well defined (1,2). Once outside the vessel, individual neutrophils often show extremely coordinated chemotaxis and cluster formation reminiscent of the swarming behaviour of insects (3-11). The molecular players that direct this response at the single-cell and population levels within the complexity of an inflamed tissue are unknown. Using two-photon intravital microscopy in mouse models of sterile injury and infection, we show a critical role for intercellular signal relay among neutrophils mediated by the lipid leukotriene B4, which acutely amplifies local cell death signals to enhance the radius of highly directed interstitial neutrophil recruitment. Integrin receptors are dispensable for long-distance migration (12), but have a previously unappreciated role in maintaining dense cellular clusters when congregating neutrophils rearrange the collagenous fibre network of the dermis to form a collagen-free zone at the wound centre. In this newly formed environment, integrins, in concert with neutrophil-derived leukotriene B4 and other chemoattractants, promote local neutrophil interaction while forming a tight wound seal. This wound seal has borders that cease to grow in kinetic concert with late recruitment of monocytes and macrophages at the edge of the displaced collagen fibres. Together, these data provide an initial molecular map of the factors that contribute to neutrophil swarming in the extravascular space of a damaged tissue. They reveal how local events are propagated over large-range distances, and how auto-signalling produces coordinated, self-organized neutrophil-swarming behaviour that isolates the wound or infectious site from surrounding viable tissue., Neutrophil swarming has been observed using intravital microscopy in inflamed, infected or sterilely wounded tissues (3-11,13), and a series of sequential phases have been described (3,4): (1) initial chemotaxis of [...]

Ion channels are integral membrane proteins mediating ion flow in response to changes in their environment. Among the different types of ion channels reported to date, the super-family of TRP channels stands out since its members have been linked to many pathophysiological processes. The family comprises 6 subfamilies and 28 members in mammals, which are widely distributed throughout most tissues and organs and have an important role in several aspects of cellular physiology. It has been evidenced that abnormal expression, post-translational modifications, and channel trafficking are associated with several pathologies, such as cancer, cardiovascular disease, diabetes, and brain disorders, among others. In this review, we present an updated summary of the mechanisms involved in the subcellular trafficking of TRP channels, with a special emphasis on whether different post-translational modifications and naturally occurring mutagenesis affect both expression and trafficking. Additionally, we describe how such changes have been associated with the development and progress of diverse pathologies associated with the gain or loss of functional phenotypes. The study of these processes will not only contribute to a better understanding the role of TRP channels in the different tissues but will also present novel possible therapeutic targets in diseases where their activity is dysregulated.

Abstract Background Given the widespread use of Point-of-Care UltraSound (PoCUS) in clinical practice, with ultrasound machines becoming more portable and affordable, recommendations and position statements from ultrasound societies now promote teaching PoCUS in the undergraduate curriculum. Nevertheless, surveys about PoCUS teaching in European medical schools are lacking. This survey aims to overview the current and future undergraduate PoCUS courses in the European Union (EU). Results A questionnaire was sent to medical schools in 26 of the 27 countries of the EU; Luxembourg is the only country without a medical school. The survey was completed by the dean or a member of the medical school with knowledge of the medical curriculum. Of the 58 medical schools from 19 countries that responded to the survey, 18 (31.0%) from 13 (68.4%) EU countries reported the existence of an undergraduate PoCUS curriculum and a further 16 (27.6%) from 12 (41.4%) EU countries intended to offer it in the future. No significant difference was observed between the current and future PoCUS curricula regarding its content and purpose. Less than 40 h of theoretical teaching is provided in all the medical schools and less than 40 h of practical training is provided in 12 (75%) of the 16 medical schools which answered this specific question. Of the 40 (69%) surveyed medical schools that do not currently teach PoCUS, 20 (50%) intend to offer PoCUS courses in the future. Conclusion Although the lack of teaching hours in curricula suggests that most PoCUS courses are introductory in nature and that medical students are possibly not trained to become autonomous in clinical practice, evaluating the feasibility and impact of PoCUS teaching on clinical practice should be promoted. The medical schools that intend to develop this curriculum should be encouraged to implement validated tools to objectively assess their programs and students’ performances.

Abstract Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer–Emmet–Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed.

Understanding document layouts is vital for enhancing document exploration and information retrieval for sighted individuals. However, for blind and visually impaired people, it becomes challenging to have access to layout information using typical assistive technologies such as screen readers. In this paper, we examine the potential benefits of presenting documents on two-dimensional (2D) refreshable tactile displays. These displays enable the tactile perception of 2D data, offering the advantage of dynamic and interactive functionality. Despite their potential, the development of user interfaces (UIs) for such displays has not advanced significantly. Thus, we propose a design of an intelligent tactile user interface (TUI), incorporating touch and audio feedback to represent documents in a tactile format. Our exploratory study for evaluating this approach revealed satisfaction from participants with the experience of directly viewing documents in their true form, rather than relying on screen-reading interpretations. Additionally, participants offered recommendations for incorporating additional features and refining the approach in future iterations. To facilitate further research and development, we have made our dataset and models publicly available.