Phenylalanine (PHE) and to a lesser extent TYR are two commonly used amino acid tracers for measuring protein metabolism in a variety of species and tissues. The model examined in this paper was developed to resolve trans-organ and stable isotope dilution data collected from experiments with lactating dairy cows using these tracers. Two methods of solving the model, i.e. as two four-pool submodels, one representing PHE and the other TYR, or as an integrated eight-pool model, are investigated and the alternative solutions are contrasted. Solving the model as the two four-pool submodels rather than the integrated 8-pool model is preferred as the equations are slightly simpler and their application less susceptible to any compounding of measurement errors. The data used to illustrate the model were taken from experiments conducted to investigate the effects of high and low protein diets on the partitioning of PHE and TYR between milk protein synthesis and other metabolic fates by the mammary gland.

Low-voltage transmission electron microscopy (≤80 kV) has many applications in imaging beam-sensitive samples, such as metallic nanoparticles, which may become damaged at higher voltages. To improve resolution, spherical aberration can be corrected for in a scanning transmission electron microscope (STEM); however, chromatic aberration may then dominate, limiting the ultimate resolution of the microscope. Using image simulations, we examine how a chromatic aberration corrector, different objective lenses, and different beam energy spreads each affect the image quality of a gold nanoparticle imaged at low voltages in a spherical aberration-corrected STEM. A quantitative analysis of the simulated examples can inform the choice of instrumentation for low-voltage imaging. We here demonstrate a methodology whereby the optimum energy spread to operate a specific STEM can be deduced. This methodology can then be adapted to the specific sample and instrument of the reader, enabling them to make an informed economical choice as to what would be most beneficial for their STEM in the cost-conscious landscape of scientific infrastructure.

Contemporary theories of early development and emerging child psychopathology all posit a major, if not central role for physiological responsiveness. To understand infants’ potential risk for emergent psychopathology, consideration is needed to both autonomic reactivity and environmental contexts (e.g., parent–child interactions). The current study maps infants’ arousal during the face-to-face still-face paradigm using skin conductance (n = 255 ethnically-diverse mother–infant dyads; 52.5% girls, mean infant age = 7.4 months; SD = 0.9 months). A novel statistical approach was designed to model the potential build-up of nonlinear counter electromotive force over the course of the task. Results showed a significant increase in infants’ skin conductance between the Baseline Free-play and the Still-Face phase, and a significant decrease in skin conductance during the Reunion Play when compared to the Still-Face phase. Skin conductance during the Reunion Play phase remained significantly higher than during the Baseline Play phase; indicating that infants had not fully recovered from the mild social stressor. These results further our understanding of infant arousal during dyadic interactions, and the role of caregivers in the development of emotion regulation during infancy.

I have been thinking a lot about environmental pedagogy in American studies, especially since I started teaching a third-year interdisciplinary course, Climate Change & Culture Wars, which focusses on the post-1970s US. I wanted to know more about how others are approaching the topic as we face up to looming climate and ecological collapse. University teachers and learners across disciplines are reckoning with it, but what's going on in American studies in Britain, and what can we learn from each other and from teachers elsewhere? How is the crisis impacting on the framing of our disciplinary fields and how are we incorporating its intellectual and practical demands into pedagogic spaces and syllabi?

Maternal adversity and prenatal stress confer risk for child behavioral health problems. Few studies have examined this intergenerational process across multiple dimensions of stress; fewer have explored potential protective factors. Using a large, diverse sample of mother–child dyads, we examined associations between maternal childhood trauma, prenatal stressors, and offspring socioemotional-behavioral development, while also examining potential resilience-promoting factors. The Conditions Affecting Neurocognitive Development and Learning and Early Childhood (CANDLE) study prospectively followed 1503 mother–child dyads (65% Black, 32% White) from pregnancy. Exposures included maternal childhood trauma, socioeconomic risk, intimate partner violence, and geocode-linked neighborhood violent crime during pregnancy. Child socioemotional-behavioral functioning was measured via the Brief Infant Toddler Social Emotional Assessment (mean age = 1.1 years). Maternal social support and parenting knowledge during pregnancy were tested as potential moderators. Multiple linear regressions (N = 1127) revealed that maternal childhood trauma, socioeconomic risk, and intimate partner violence were independently, positively associated with child socioemotional-behavioral problems at age one in fully adjusted models. Maternal parenting knowledge moderated associations between both maternal childhood trauma and prenatal socioeconomic risk on child problems: greater knowledge was protective against the effects of socioeconomic risk and was promotive in the context of low maternal history of childhood trauma. Findings indicate that multiple dimensions of maternal stress and adversity are independently associated with child socioemotional-behavioral problems. Further, modifiable environmental factors, including knowledge regarding child development, can mitigate these risks. Both findings support the importance of parental screening and early intervention to promote child socioemotional-behavioral health.

Research investigating social anxiety and the impacts on romantic relationships remains scarce. An online questionnaire examining romantic relationship status, social anxiety and depression symptomology, relationship satisfaction, and several relationship processes was completed by 444 adults. Individuals with higher social anxiety were less likely to be in romantic relationships. For the 188 adults in our sample in current relationships, relationship satisfaction was not influenced by social anxiety when controlling for depression. Although it was proposed that self-disclosure, social support, trust, and conflict initiation might influence romantic relationship satisfaction, none of these mechanisms interacted with social anxiety to explain additional variance in relationship satisfaction. These findings indicate that depression symptomology may be a treatment target for socially anxious individuals wishing to improve romantic relationship satisfaction.

High-throughput grain mapping with sub-nanometer spatial resolution is demonstrated using scanning nanobeam electron diffraction (also known as 4D scanning transmission electron microscopy, or 4D-STEM) combined with high-speed direct-electron detection. An electron probe size down to 0.5 nm in diameter is used and the sample investigated is a gold–palladium nanoparticle catalyst. Computational analysis of the 4D-STEM data sets is performed using a disk registration algorithm to identify the diffraction peaks followed by feature learning to map the individual grains. Two unsupervised feature learning techniques are compared: principal component analysis (PCA) and non-negative matrix factorization (NNMF). The characteristics of the PCA versus NNMF output are compared and the potential of the 4D-STEM approach for statistical analysis of grain orientations at high spatial resolution is discussed.

Despite enormous strides in our field with respect to patient care, there has been surprisingly limited dialogue on how to train and educate the next generation of congenital cardiologists. This paper reviews the current status of training and evolving developments in medical education pertinent to congenital cardiology. The adoption of competency-based medical education has been lauded as a robust framework for contemporary medical education over the last two decades. However, inconsistencies in frameworks across different jurisdictions remain, and bridging gaps between competency frameworks and clinical practice has proved challenging. Entrustable professional activities have been proposed as a solution, but integration of such activities into busy clinical cardiology practices will present its own challenges. Consequently, this pivot towards a more structured approach to medical education necessitates the widespread availability of appropriately trained medical educationalists, a development that will better inform curriculum development, instructional design, and assessment. Differentiation between superficial and deep learning, the vital role of rich formative feedback and coaching, should guide our trainees to become self-regulated learners, capable of critical reasoning yet retaining an awareness of uncertainty and ambiguity. Furthermore, disruptive innovations such as “technology enhanced learning” may be leveraged to improve education, especially for trainees from low- and middle-income countries. Each of these initiatives will require resources, widespread advocacy and raised awareness, and publication of supporting data, and so it is especially gratifying that Cardiology in the Young has fostered a progressive approach, agreeing to publish one or two articles in each journal issue in this domain.

Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n = 3261) completing the C-19 COVID-19 symptom tracker app allowed classical twin studies of COVID-19 symptoms, including predicted COVID-19, a symptom-based algorithm to predict true infection, derived from app users tested for SARS-CoV-2. We found heritability of 49% (32−64%) for delirium; 34% (20−47%) for diarrhea; 31% (8−52%) for fatigue; 19% (0−38%) for anosmia; 46% (31−60%) for skipped meals and 31% (11−48%) for predicted COVID-19. Heritability estimates were not affected by cohabiting or by social deprivation. The results suggest the importance of host genetics in the risk of clinical manifestations of COVID-19 and provide grounds for planning genome-wide association studies to establish specific genes involved in viral infectivity and the host immune response.

Liquid phase (or liquid cell) transmission electron microscopy (LP-TEM) has been established as a powerful tool for observing dynamic processes in liquids at nanometer to atomic length scales. However, the simple act of observation using electrons irreversibly alters the nature of the sample. A clear understanding of electron-beam-driven processes during LP-TEM is required to interpret in situ observations and utilize the electron beam as a stimulus to drive nanoscale dynamic processes. In this article, we discuss recent advances toward understanding, quantifying, mitigating, and harnessing electron-beam-driven chemical processes occurring during LP-TEM. We highlight progress in several research areas, including modeling electron-beam-induced radiolysis near interfaces, electron-beam-induced nanocrystal formation, and radiation damage of soft materials and biomolecules.