Bioturbation can increase time averaging by downward and upward movements of young and old shells within the entire mixed layer and by accelerating the burial of shells into a sequestration zone (SZ), allowing them to bypass the uppermost taphonomically active zone (TAZ). However, bioturbation can increase shell disintegration concurrently, neutralizing the positive effects of mixing on time averaging. Bioirrigation by oxygenated pore-water promotes carbonate dissolution in the TAZ, and biomixing itself can mill shells weakened by dissolution or microbial maceration, and/or expose them to damage at the sediment–water interface. Here, we fit transition rate matrices to bivalve age–frequency distributions from four sediment cores from the southern California middle shelf (50–75 m) to assess the competing effects of bioturbation on disintegration and time averaging, exploiting a strong gradient in rates of sediment accumulation and bioturbation created by historic wastewater pollution. We find that disintegration covaries positively with mixing at all four sites, in accord with the scenario where bioturbation ultimately fuels carbonate disintegration. Both mixing and disintegration rates decline abruptly at the base of the 20- to 40-cm-thick, age-homogenized surface mixed layer at the three well-bioturbated sites, despite different rates of sediment accumulation. In contrast, mixing and disintegration rates are very low in the upper 25 cm at an effluent site with legacy sediment toxicity, despite recolonization by bioirrigating lucinid bivalves. Assemblages that formed during maximum wastewater emissions vary strongly in time averaging, with millennial scales at the low-sediment accumulation non-effluent sites, a centennial scale at the effluent site where sediment accumulation was high but bioturbation recovered quickly, and a decadal scale at the second high-sedimentation effluent site where bioturbation remained low for decades. Thus, even though disintegration rates covary positively with mixing rates, reducing postmortem shell survival, bioturbation has the net effect of increasing the time averaging of skeletal remains on this warm-temperate siliciclastic shelf.

The trace element selenium is known to protect against oxidative damage which is known to contribute to cognitive impairment with ageing (1,2). The aim of this study was to explore the association between selenium status (serum selenium and selenoprotein P (SELENOP)) and global cognitive performance at baseline and after 5 years in 85-year-olds living in the Northeast of England.

Serum selenium and SELENOP concentrations were measured at baseline by total reflection X-ray fluorescence (TXRF) and enzyme-linked immunosorbent assay (ELISA), respectively, in 757 participants from the Newcastle 85+ study. Global cognitive performance was assessed using the Standardized Mini-Mental State Examination (SMMSE) where scores ≤25 out of 30 indicated cognitive impairment. Logistic regressions explored the associations between selenium status and global cognition at baseline. Linear mixed models explored associations between selenium status and global cognition prospectively after 5 years. Covariates included sex, body mass index, physical activity, high sensitivity C-reactive protein, alcohol intake, self-rated health, medications and smoking status.

At baseline, in fully adjusted models, there was no increase in odds of cognitive impairment with serum selenium (OR 1.004, 95% CI 0.993-1.015, p = 0.512) or between SELENOP (OR 1.006, 95% CI 0.881-1.149, p = 0.930). Likewise, over 5 years, in fully adjusted models there was no association between serum selenium and cognitive impairment (β 7.20E-4 ± 5.57E-4, p = 0.197), or between SELENOP and cognitive impairment (β 3.50E-3 ± 6.85E-3, p = 0.610).

In this UK cohort of very old adults, serum selenium or SELENOP was not associated with cognitive impairment at baseline and 5 years. This was an unexpected finding despite SELENOP’s key role in the brain and the observed associations in other studies. Further research is needed to explore the effect of selenium on global cognition in very old adults.

OBJECTIVES/GOALS: Irritability, a proneness to anger and frustration, is a transdiagnostic symptom associated with poor mental health outcomes. Levels of irritability vary across development and high-risk trajectories have been observed. This study aims to use machine learning to predict irritability trajectories across the transition to adolescence. METHODS/STUDY POPULATION: Data were from the Adolescent Brain Cognitive Development (ABCD) Study, which is a 10-year longitudinal study that tracks the brain development, cognitive skills, physical health, and psychosocial functioning of a large, national sample starting from preadolescence. The baseline sample consisted of 11,861 9-10-year-old preadolescent youth. Irritability was parent-rated at baseline, 1-year, 2-year, 3-year, and 4-year follow-ups on the Child Behavior Checklist (CBCL) irritability index. Latent class growth analysis (LCGA) was used to determine developmental trajectories of irritability. Two machine learning approaches were applied to develop predictive models of youth irritability developmental trajectories. We used baseline (preadolescent) variables that spanned a wide range of domains. RESULTS/ANTICIPATED RESULTS: Preliminary results fromthe LCGA indicated best support for a four-class model that differentiated growth trajectories in irritability across the transition to adolescence: 1) persistent low irritability (n = 8691, 73.27%), 2) moderate irritability and decreasing (n = 1257, 10.60%), 3) low to moderate irritability and increasing (n = 1295, 10.92%), and 4) chronic high irritability (n = 618, 5.21%). We expect the machine learning analyses to generate predictive models with acceptable accuracy. We hypothesize that the most important predictors in the models will originate from the youth mental health domain, including baseline youth irritability, externalizing symptoms, internalizing symptoms, and oppositional behaviors, and the parent psychopathology domain, particularly parent irritability. DISCUSSION/SIGNIFICANCE: The present study elucidates unique developmental trajectories of irritability and generates predictive models to classify high-risk irritability trajectories using machine learning approaches. Clinicians can use these predictive models to identify at-risk youth and provide early intervention to preadolescents at high risk.

There is a dearth of data on Se status in very old adults. The aims of this study were to assess Se status and its determinants in 85-year-olds living in the Northeast of England by measuring serum Se and selenoprotein P (SELENOP) concentrations and glutathione peroxidase 3 (GPx3) activity. A secondary aim was to examine the interrelationships between each of the biomarkers. In total, 757 participants (463 women, 293 men) from the Newcastle 85+ Study were included. Biomarker concentrations were compared with selected cut-offs (serum Se: suboptimal 70 µg/l and deficient 45 µg/l; SELENOP: suboptimal 4·5 mg/l and deficient 2·6 mg/l). Determinants were assessed using linear regressions, and interrelationships were assessed using restricted cubic splines. Median (inter-quartile range) concentrations of serum Se, SELENOP and of GPx3 activity were 53·6 (23·6) µg/l, 2·9 (1·9) mg/l and 142·1 (50·7) U/l, respectively. Eighty-two percentage and 83 % of participants had suboptimal serum Se (< 70 µg/l) and SELENOP (< 4·5 mg/l), and 31 % and 40 % of participants had deficient serum Se (< 45 µg/l) and SELENOP (< 2·6 mg/l), respectively. Protein intake was a significant determinant of Se status. Additional determinants of serum Se were sex, waist:hip ratio, self-rated health and disease, while sex, BMI and physical activity were determinants of GPx3 activity. There was a linear association between serum Se and SELENOP, and nonlinear associations between serum Se and GPx3 activity and between SELENOP and GPx3 activity. These findings indicate that most participants had suboptimal Se status to saturate circulating SELENOP.

I develop a novel account of how nonepistemic aims and values can appropriately influence scientific investigation. At its heart is a process of epistemic projection in which a nonepistemic aim or value is mapped to an epistemic research problem that aligns with that aim or value. Choices in research are then justified as a means of solving that research problem. This epistemic projection approach makes research responsive to nonepistemic aims and values yet remains consistent with the value-free ideal; it could be acceptable to parties on both sides of the values-in-science debate. It also promises to be useful in practice.

Laboratory animals need to be monitored to check the status of their health and welfare. Routine checks of laboratory fish are limited to visual observations of physical appearance and behaviour, but for species held in opaque-walled tanks, such checks are compromised by restricted views, poor visibility and provoked behaviour. Here, we report our experience of using in-tank underwater cameras to monitor laboratory populations of salmoniforme, perciforme and cypriniforme fish. A range of cameras and lenses were investigated and trialled. A standard VGA resolution analogue camera with a one-third-inch chip and 3.6-mm lens was selected based on size, picture quality, the proportion of tank in view and cost. A shell for the camera and mounting system were designed to minimise size and cleaning and enable flexible positioning within tanks. Cameras were connected via digital encoders to a server, making video available to the general computer network. Data collected from recordings of rainbow trout (Oncorhynchus mykiss) confirmed provoked behaviour, ie a change in distribution and increase in activity in response to direct viewing and feeding. The networked cameras therefore enable remote viewing of undisturbed behaviour in real time, providing clear, lateral views unaffected by water surface effects, and facilitate increased frequency of checking. Case studies illustrate how camera monitoring can aid detection of abnormalities in behaviour (eg lack of feeding, posture, swimming) and appearance (eg clinical signs, such as lesions), enabling earlier interventions. Furthermore, recordings provide a resource for reference and retrospective analysis, and evidence to support severity classification and identify humane end-points.

Using a mixed-methods approach, we assessed the effect of the coronavirus disease 2019 (COVID-19) pandemic on antimicrobial stewardship programs (ASPs) in Colorado hospitals. ASP leaders reported decreased time and resources, reduced rigor of stewardship interventions, inability to complete new initiatives, and interpersonal challenges. Stewardship activities may be threatened during times of acute resource pressure.

This article is a clinical guide which discusses the “state-of-the-art” usage of the classic monoamine oxidase inhibitor (MAOI) antidepressants (phenelzine, tranylcypromine, and isocarboxazid) in modern psychiatric practice. The guide is for all clinicians, including those who may not be experienced MAOI prescribers. It discusses indications, drug-drug interactions, side-effect management, and the safety of various augmentation strategies. There is a clear and broad consensus (more than 70 international expert endorsers), based on 6 decades of experience, for the recommendations herein exposited. They are based on empirical evidence and expert opinion—this guide is presented as a new specialist-consensus standard. The guide provides practical clinical advice, and is the basis for the rational use of these drugs, particularly because it improves and updates knowledge, and corrects the various misconceptions that have hitherto been prominent in the literature, partly due to insufficient knowledge of pharmacology. The guide suggests that MAOIs should always be considered in cases of treatment-resistant depression (including those melancholic in nature), and prior to electroconvulsive therapy—while taking into account of patient preference. In selected cases, they may be considered earlier in the treatment algorithm than has previously been customary, and should not be regarded as drugs of last resort; they may prove decisively effective when many other treatments have failed. The guide clarifies key points on the concomitant use of incorrectly proscribed drugs such as methylphenidate and some tricyclic antidepressants. It also illustrates the straightforward “bridging” methods that may be used to transition simply and safely from other antidepressants to MAOIs.

The process of generating FMEA following document-centric approach is tedious and susceptible to human error. This paper presents preliminary methodology for robotic manufacturing process modelling in MBSE environment with a scope of automating multiple steps of the modelling process using ontology. This is followed by the reasoning towards automatic generation of process FMEA from the MBSE model. The proposed methodology allows to establish robust and self-synchronising links between process-relevant information, reduce the likelihood of human error, and scale down time expenses.