Inferring causal molecular networks: empirical assessment through a community-based effort.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Blue Hill Ship Building

https://digitalmaine.com/blue_hill_documents/1180/thumbnail.jp

Bilateral regional extracranial blood flow regulation to hypoxia and unilateral duplex ultrasound measurement error

Whether blood flow regulation to hypoxia is similar between left and right internal carotid arteries (ICA) and vertebral arteries (VA) is unclear. Extracranial blood flow is regularly calculated by doubling a unilateral assessment; however, lateral artery differences may lead to measurement error. This study aimed to determine extracranial blood flow regulation to hypoxia when factoring for vessel type (ICA or VA) and vessel side (left or right) effects, and investigate unilateral assessment measurement error compared to bilateral assessment. In a repeated-measures crossover design, extracranial arteries of 44 participants were assessed bilaterally by Duplex ultrasound during 90 minutes of normoxic and poikilocapnic hypoxic (12.0% fraction of inspired oxygen) conditions. Linear mixed model analyses revealed no ‘Condition’ × ‘Vessel Type’ × ‘Vessel Side’ interaction for blood flow, vessel diameter, and flow velocity (all P > 0.05) indicating left and right ICA and VA blood flow regulation to hypoxia was similar. Bilateral hypoxic reactivity was comparable [ICA, 1.4 (1.0) vs VA, 1.7 (1.1) Δ%·ΔSpO2-1; P = 0.12]. Compared to bilateral assessment, unilateral mean measurement error of the relative blood flow response to hypoxia was up to 5%, but individual errors reached 37% and were greatest in ICA and VA with the smaller resting blood flow due to a ratio-scaling problem. In conclusion, left and right ICA and VA regulation to hypoxia is comparable when factoring for vessel type and vessel side. Assessing the ICA and VA vessels with the larger resting blood flow, not the left or right vessel, reduces unilateral measurement error

Fibrillar vs crystalline nanocellulose pulmonary epithelial cell responses: Cytotoxicity or inflammation?

Nanocellulose (NC) is emerging as a highly promising nanomaterial for a wide range of applications. Moreover, many types of NC are produced, each exhibiting a slightly different shape, size, and chemistry. The main objective of this study was to compare cytotoxic effects of cellulose nanocrystals (CNC) and nanofibrillated cellulose (NCF). The human lung epithelial cells (A549) were exposed for 24 h and 72 h to five different NC particles to determine how variations in properties contribute to cellular outcomes, including cytotoxicity, oxidative stress, and cytokine secretion. Our results showed that NCF were more toxic compared to CNC particles with respect to cytotoxicity and oxidative stress responses. However, exposure to CNC caused an inflammatory response with significantly elevated inflammatory cytokines/chemokines compared to NCF. Interestingly, cellulose staining indicated that CNC particles, but not NCF, were taken up by the cells. Furthermore, clustering analysis of the inflammatory cytokines revealed a similarity of NCF to the carbon nanofibers response and CNC to the chitin, a known immune modulator and innate cell activator. Taken together, the present study has revealed distinct differences between fibrillar and crystalline nanocellulose and demonstrated that physicochemical properties of NC are critical in determining their toxicity