An Ionization Cone in the Dwarf Starburst Galaxy NGC 5253

There are few observational constraints on how the escape of ionizing photons from starburst galaxies depends on galactic parameters. Here, we report on the first major detection of an ionization cone in NGC 5253, a nearby starburst galaxy. This high-excitation feature is identified by mapping the emission-line ratios in the galaxy using [S III] lambda 9069, [S II] lambda 6716, and H_alpha narrow-band images from the Maryland-Magellan Tunable Filter at Las Campanas Observatory. The ionization cone appears optically thin, which is suggestive of the escape of ionizing photons. The cone morphology is narrow with an estimated solid angle covering just 3% of 4pi steradians, and the young, massive clusters of the nuclear starburst can easily generate the radiation required to ionize the cone. Although less likely, we cannot rule out the possibility of an obscured AGN source. An echelle spectrum along the minor axis shows complex kinematics that are consistent with outflow activity. The narrow morphology of the ionization cone supports the scenario that an orientation bias contributes to the difficulty in detecting Lyman continuum emission from starbursts and Lyman break galaxies.Comment: 5 pages, 4 figures, Accepted to ApJ Letter

Knockdown of TNFR1 by the sense strand of an ICAM-1 siRNA: dissection of an off-target effect

Tumor necrosis factor (TNF) initiates local inflammation by triggering endothelial cells (EC) to express adhesion molecules for leukocytes such as intercellular adhesion molecule-1 (ICAM-1 or CD54). A prior study identified siRNA molecules that reduce ICAM-1 expression in cultured human umbilical vein EC (HUVEC). One of these, ISIS 121736, unexpectedly inhibits TNF-mediated up-regulation of additional molecules on EC, including E-selectin (CD62E), VCAM-1 (CD106) and HLA-A,B,C. 736 siRNA transfection was not toxic for EC nor was there any evidence of an interferon response. 736 Transfection of EC blocked multiple early TNF-related signaling events, including activation of NF-κB. IL-1 activation of these same pathways was not inhibited. A unifying explanation is that 736 siRNA specifically reduced expression of mRNA encoding tumor necrosis factor receptor 1 (TNFR1) as well as TNFR1 surface expression. A sequence with high identity to the 736 antisense strand (17 of 19 bases) is present within the 3′UTR of human TNFR1 mRNA. An EGFP construct incorporating the 3′UTR of TNFR1 was silenced by 736 siRNA and this effect was lost by mutagenesis of this complementary sequence. Chemical modification and mismatches within the sense strand of 736 also inhibited silencing activity. In summary, an siRNA molecule selected to target ICAM-1 through its antisense strand exhibited broad anti-TNF activities. We show that this off-target effect is mediated by siRNA knockdown of TNFR1 via its sense strand. This may be the first example in which the off-target effect of an siRNA is actually responsible for the anticipated effect by acting to reduce expression of a protein (TNFR1) that normally regulates expression of the intended target (ICAM-1)

Increased ICAM-1 Expression Causes Endothelial Cell Leakiness, Cytoskeletal Reorganization and Junctional Alterations

Tumor necrosis factor (TNF)-induced ICAM-1 in endothelial cells (EC) promotes leukocyte adhesion. Here we report that ICAM-1 also effects EC barrier function. Control- or E-selectin-transduced human dermal microvascular EC (HDMEC) form a barrier to flux of proteins and to passage of current (measured as transendothelial electrical resistance or TEER). HDMEC transduced with ICAM-1 at levels comparable to that induced by TNF show reduced TEER, but do so without overtly changing their cell junctions, cell shape, or cytoskeleton organization. Higher levels of ICAM-1 further reduce TEER, increase F/G-actin ratios, rearrange the actin cytoskeleton to cause cell elongation, and alter junctional zona occludens 1 and vascular endothelial-cadherin staining. Transducing with ICAM-1 lacking an intracellular region also reduces TEER. TNF-induced changes in TEER and shape follow a similar time course as ICAM-1 induction; however, the fall in TEER occurs at lower TNF concentrations. Inhibiting NF-κB activation blocks ICAM-1 induction; TEER reduction, and shape change. Specific small-interfering RNA knockdown of ICAM-1 partially inhibits TNF-induced shape change. We conclude that moderately elevated ICAM-1 expression reduces EC barrier function and that expressing higher levels of ICAM-1 affects cell junctions and the cytoskeleton. Induction of ICAM-1 may contribute to but does not fully account for TNF-induced vascular leak and EC shape change

Performance of Deaf Participants in an Abstract Visual Grammar Learning Task at Multiple Formal Levels: Evaluating the Auditory Scaffolding Hypothesis

Previous research has hypothesized that human sequential processing may be dependent upon hearing experience (the “auditory scaffolding hypothesis”), predicting that sequential rule learning abilities should be hindered by congenital deafness. To test this hypothesis, we compared deaf signer and hearing individuals’ ability to acquire rules of different computational complexity in a visual artificial grammar learning task using sequential stimuli. As a group, deaf participants succeeded at all levels of the task; Bayesian analysis indicates that they successfully acquired each of several target grammars at ascending levels of the formal language hierarchy. Overall, these results do not support the auditory scaffolding hypothesis. However, age- and education-matched hearing participants did outperform deaf participants in two out of three tested grammars. We suggest that this difference may be related to verbal recoding strategies in the two groups. Any verbal recoding strategies used by the deaf signers would be less effective because they would have to use the same visual channel required for the experimental task

Artificial Grammar Learning Capabilities in an Abstract Visual Task Match Requirements for Linguistic Syntax

Whether pattern-parsing mechanisms are specific to language or apply across multiple cognitive domains remains unresolved. Formal language theory provides a mathematical framework for classifying pattern-generating rule sets (or “grammars”) according to complexity. This framework applies to patterns at any level of complexity, stretching from simple sequences, to highly complex tree-like or net-like structures, to any Turing-computable set of strings. Here, we explored human pattern-processing capabilities in the visual domain by generating abstract visual sequences made up of abstract tiles differing in form and color. We constructed different sets of sequences, using artificial “grammars” (rule sets) at three key complexity levels. Because human linguistic syntax is classed as “mildly context-sensitive,” we specifically included a visual grammar at this complexity level. Acquisition of these three grammars was tested in an artificial grammar-learning paradigm: after exposure to a set of well-formed strings, participants were asked to discriminate novel grammatical patterns from non-grammatical patterns. Participants successfully acquired all three grammars after only minutes of exposure, correctly generalizing to novel stimuli and to novel stimulus lengths. A Bayesian analysis excluded multiple alternative hypotheses and shows that the success in rule acquisition applies both at the group level and for most participants analyzed individually. These experimental results demonstrate rapid pattern learning for abstract visual patterns, extending to the mildly context-sensitive level characterizing language. We suggest that a formal equivalence of processing at the mildly context sensitive level in the visual and linguistic domains implies that cognitive mechanisms with the computational power to process linguistic syntax are not specific to the domain of language, but extend to abstract visual patterns with no meaning

Detecting context dependence in the expression of life history trade-offs

1. Life history trade-offs are one of the central tenets of evolutionary demography. Trade-offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero-sum game between somatic and reproductive functions. While theory predicts that trade-offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. 2. One way to improve the detection of trade-offs is by accounting for the environmental context, as trade-off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. 3. Here, we present a hierarchical multivariate 'covariance reaction norm' model, adapted from Martin (2023), to help detect context dependence in the expression of life-history trade-offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade-offs. 4. We then apply it to empirical datasets of yellow-bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof-of-concept showing that new insights can be gained by applying our methodology, such as detecting trade-offs only in specific environments. 5. We discuss its potential for application to many of the existing long-term demographic datasets and how it could improve our understanding of trade-off expression in particular, and life history theory in general

Digital health for optimal supportive care in oncology: benefits, limits, and future perspectives

Background Digital health provides solutions that capture patient-reported outcomes (PROs) and allows symptom monitoring and patient management. Digital therapeutics is the provision to patients of evidence-based therapeutic interventions through software applications aimed at prevention, monitoring, management, and treatment of symptoms and diseases or for treatment optimization. The digital health solutions collecting PROs address many unmet needs, including access to care and reassurance, increase in adherence and treatment efficacy, and decrease in hospitalizations. With current developments in oncology including increased availability of oral drugs and reduced availability of healthcare professionals, these solutions offer an innovative approach to optimize healthcare resource utilization. Design This scoping review clarifies the role and impact of the digital health solutions in oncology supportive care, with a view of the current segmentation according to their technical features (connection to sensors, PRO collection, remote monitoring, self-management in real time…), and identifies evidence from clinical studies published about their benefits and limitations and drivers and barriers to adoption. A qualitative summary is presented. Results Sixty-six studies were identified and included in the qualitative synthesis. Studies supported the use of 38 digital health solutions collecting ePROs and allowing remote monitoring, with benefits to patients regarding symptom reporting and management, reduction in symptom distress, decrease in unplanned hospitalizations and related costs and improved quality of life and survival. Among those 38 solutions 21 provided patient self-management with impactful symptom support, improvement of QoL, usefulness and reassurance. Principal challenges are in developing and implementing digital solutions to suit most patients, while ensuring patient compliance and adaptability for use in different healthcare systems and living environments. Conclusions There is growing evidence that digital health collecting ePROs provide benefits to patients related to clinical and health economic endpoints. These digital solutions can be integrated into routine supportive care in oncology practice to provide improved patient-centered care