Young stellar objects (YSOs) are protostars that exhibit bipolar outflows fed by accretion disks. Theories of the transition between disk and outflow often involve a complex magnetic field structure thought to be created by the disk coiling field lines at the jet base; however, due to limited resolution, these theories cannot be confirmed with observation and thus may benefit from laboratory astrophysics studies. We create a dynamically similar laboratory system by driving a $\sim$1 MA current pulse with a 200 ns rise through a $\approx$2 mm-tall Al cylindrical wire array mounted to a three-dimensional (3-D)-printed, stainless steel scaffolding. This system creates a plasma that converges on the centre axis and ejects cm-scale bipolar outflows. Depending on the chosen 3-D-printed load path, the system may be designed to push the ablated plasma flow radially inwards or off-axis to make rotation. In this paper, we present results from the simplest iteration of the load which generates radially converging streams that launch non-rotating jets. The temperature, velocity and density of the radial inflows and axial outflows are characterized using interferometry, gated optical and ultraviolet imaging, and Thomson scattering diagnostics. We show that experimental measurements of the Reynolds number and sonic Mach number in three different stages of the experiment scale favourably to the observed properties of YSO jets with $Re\sim 10^5\unicode{x2013}10^9$ and $M\sim 1\unicode{x2013}10$, while our magnetic Reynolds number of $Re_M\sim 1\unicode{x2013}15$ indicates that the magnetic field diffuses out of our plasma over multiple hydrodynamical time scales. We compare our results with 3-D numerical simulations in the PERSEUS extended magnetohydrodynamics code.

The extent to which the oro-faecal route contributes to the transmission of SARS-CoV-2 is not established.

We systematically reviewed the evidence on the presence of infectious SARS-CoV-2 in faeces and other gastrointestinal sources by examining studies that used viral culture to investigate the presence of replication-competent virus in these samples. We conducted searches in the WHO COVID-19 Database, LitCovid, medRxiv, and Google Scholar for SARS-CoV-2 using keywords and associated synonyms, with a search date up to 28 November 2023.

We included 13 studies involving 229 COVID-19 subjects – providing 308 faecal or rectal swab SARS-CoV2 reverse transcription-polymerase chain reaction (RT-PCR)-positive samples tested with viral culture. The methods used for viral culture across the studies were heterogeneous. Three studies (two cohorts and one case series) reported observing replication-competent SARS-CoV-2 confirmed by quantitative RT-PCR (qPCR) and whole-genome sequencing, and qPCR including appropriate cycle threshold changes. Overall, six (1.9%) of 308 faecal samples subjected to cell culture showed replication-competent virus. One study found replication-competent samples from one immunocompromised patient. No studies were identified demonstrating direct evidence of oro-faecal transmission to humans.

Our review found a relatively low frequency of replication-competent SARS-CoV-2 in faecal and other gastrointestinal sources. Although it is biologically plausible, more research is needed using standardized cell culture methods, control groups, adequate follow-up, and robust epidemiologic methods, including whether secondary infections occurred, to determine the role of the oro-faecal route in the transmission of SARS-CoV-2.

Direct numerical simulation (DNS) of a turbulent boundary layer over the Gaussian (Boeing) bump is performed. This boundary layer exhibits a series of adverse and favourable pressure gradients and convex and concave curvature effects before separating. These effects on turbulent boundary layers are characterised and compared with a lower-Reynolds-number flow over the same geometry. The momentum budgets are analysed in the streamline-aligned coordinate system upstream of the separation region. These momentum budgets allow the simplification of equations to facilitate an integral analysis. Integral-analysis-based approximations for Reynolds stresses in the inner and outer regions of the boundary layer are also formulated. The shear and wall-normal Reynolds stress profiles normalised by these approximations exhibit a better collapse compared with friction velocity and Zagarola–Smits normalisations in the strong favourable pressure gradient region and in the mild adverse pressure region that precedes it in this flow. Simplification of these Reynolds stress approximations along with results from the DNS are used to obtain semi-empirical approximations that are able to provide stress closure in terms of wall solution fields for the turbulent boundary layer under consideration.

Clinical outcomes of repetitive transcranial magnetic stimulation (rTMS) for treatment of treatment-resistant depression (TRD) vary widely and there is no mood rating scale that is standard for assessing rTMS outcome. It remains unclear whether TMS is as efficacious in older adults with late-life depression (LLD) compared to younger adults with major depressive disorder (MDD). This study examined the effect of age on outcomes of rTMS treatment of adults with TRD. Self-report and observer mood ratings were measured weekly in 687 subjects ages 16–100 years undergoing rTMS treatment using the Inventory of Depressive Symptomatology 30-item Self-Report (IDS-SR), Patient Health Questionnaire 9-item (PHQ), Profile of Mood States 30-item, and Hamilton Depression Rating Scale 17-item (HDRS). All rating scales detected significant improvement with treatment; response and remission rates varied by scale but not by age (response/remission ≥ 60: 38%–57%/25%–33%; <60: 32%–49%/18%–25%). Proportional hazards models showed early improvement predicted later improvement across ages, though early improvements in PHQ and HDRS were more predictive of remission in those < 60 years (relative to those ≥ 60) and greater baseline IDS burden was more predictive of non-remission in those ≥ 60 years (relative to those < 60). These results indicate there is no significant effect of age on treatment outcomes in rTMS for TRD, though rating instruments may differ in assessment of symptom burden between younger and older adults during treatment.

On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN–human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in the literature. In our view, these latter issues are contributing to many unjustified claims regarding DNN–human correspondences in vision and other domains of cognition. We explore all these issues in this response.

American Indians and Alaska Natives suffer from disproportionately high rates of chronic mental and physical health conditions. These health inequities are linked to colonization and its downstream consequences. Most of the American Indian and Alaska Native health inequities research uses a deficit framework, failing to acknowledge the resilience of American Indian and Alaska Native people despite challenging historical and current contexts. This scoping review is based on a conceptual model which acknowledges the context of colonization and its consequences (psychological and health risk factors). However, rather than focusing on health risk, we focus on protective factors across three identified domains (social, psychological, and cultural/spiritual), and summarize documented relationships between these resilience factors and health outcomes. Based on the scoping review of the literature, we note gaps in extant knowledge and recommend future directions. The findings summarized here can be used to inform and shape future interventions which aim to optimize health and well-being in American Indian and Alaska Native peoples.

OBJECTIVES/GOALS: Adult spinal deformity is commonly treated by spine surgeons. Patient treatment planning and surgical candidacy are dependent on static measurements and inconsistent heuristics which lead to high complication rates and poor outcomes. This study tests the role of supplemental longitudinal and dynamic patient data in improving surgical planning. METHODS/STUDY POPULATION: Ten adult spinal deformity surgeons at Johns Hopkins Hospital were interviewed for 30 minutes by the study team. The script was reviewed by the institutional review board to alleviate any risk of bias. Two patient sets were curated utilizing previously treated, anonymized patient data sets from a non-surveyed practitioner. Each patient set was coupled with relevant radiographic imaging (MRIs, CTs, and plain radiographs) and pertinent clinical information that is collected in a standard clinic visit. Surgeons were presented with a patient and asked to note their specific surgical plan. Subsequently, surgeons were presented with four sets of supplemental dynamic spine data and asked to note their surgical plan for each set. Shaprio-Wilks and Mann-Whitney U tests were used to assess data normality and nonnormality. RESULTS/ANTICIPATED RESULTS: Preliminary data has shown inconsistency in both surgical selection and surgical type amongst physicians when presented with initial clinical findings and radiographic reports for base patient cases. There was minimal consensus among surgeons on the number of levels fused and interbody spacer usage. Early results show that dynamic spine data may be beneficial in creating consistency between surgeons, despite inter-surgeon variability in surgical planning without this data. Posture, pain location, pain severity, and quantified activity throughout the day have been referenced as the most useful dynamic spine data to consider. Amongst all providers, the availability of dynamic spine data resulted in a change in surgical planning. DISCUSSION/SIGNIFICANCE: Recent publications have shown that spine surgery patient candidacy and surgical planning are dependent on heuristics. This has led to inconsistencies amongst surgeon preferences and increases in improper patient selection for procedures. Incorporating longitudinal dynamic data may lead to increased consistency and improved patient outcomes.

Prenatal adversity has been linked to later psychopathology. Yet, research on cumulative prenatal adversity, as well as its interaction with offspring genotype, on brain and behavioral development is scarce. With this study, we aimed to address this gap. In Finnish mother–infant dyads, we investigated the association of a cumulative prenatal adversity sum score (PRE-AS) with (a) child emotional and behavioral problems assessed with the Strengths and Difficulties Questionnaire at 4 and 5 years (N = 1568, 45.3% female), (b) infant amygdalar and hippocampal volumes (subsample N = 122), and (c) its moderation by a hippocampal-specific coexpression polygenic risk score based on the serotonin transporter (SLC6A4) gene. We found that higher PRE-AS was linked to greater child emotional and behavioral problems at both time points, with partly stronger associations in boys than in girls. Higher PRE-AS was associated with larger bilateral infant amygdalar volumes in girls compared to boys, while no associations were found for hippocampal volumes. Further, hyperactivity/inattention in 4-year-old girls was related to both genotype and PRE-AS, the latter partially mediated by right amygdalar volumes as preliminary evidence suggests. Our study is the first to demonstrate a dose-dependent sexually dimorphic relationship between cumulative prenatal adversity and infant amygdalar volumes.

Optimum nutrition plays a major role in the achievement and maintenance of good health. The Nutrition Society of the UK and Ireland and the Sabri Ülker Foundation, a charity based in Türkiye and focused on improving public health, combined forces to highlight this important subject. A hybrid conference was held in Istanbul, with over 4000 delegates from sixty-two countries joining the proceedings live online in addition to those attending in person. The primary purpose was to inspire healthcare professionals and nutrition policy makers to better consider the role of nutrition in their interactions with patients and the public at large to reduce the prevalence of non-communicable diseases such as obesity and type 2 diabetes. The event provided an opportunity to share and learn from different approaches in the UK, Türkiye and Finland, highlighting initiatives to strengthen research in the nutritional sciences and translation of that research into nutrition policy. The presenters provided evidence of the links between nutrition and disease risk and emphasised the importance of minimising risk and implementing early treatment of diet-related disease. Suggestions were made including improving health literacy and strengthening policies to improve the quality of food production and dietary behaviour. A multidisciplinary approach is needed whereby Governments, the food industry, non-governmental groups and consumer groups collaborate to develop evidence-based recommendations and appropriate joined-up policies that do not widen inequalities. This summary of the proceedings will serve as a gateway for those seeking to access additional information on nutrition and health across the globe.

Maternal protein restriction is often associated with structural and functional sequelae in offspring, particularly affecting growth and renal-cardiovascular function. However, there is little understanding as to whether hypertension and kidney disease occur because of a primary nephron deficit or whether controlling postnatal growth can result in normal renal-cardiovascular phenotypes. To investigate this, female Sprague-Dawley rats were fed either a low-protein (LP, 8.4% protein) or normal-protein (NP, 19.4% protein) diet prior to mating and until offspring were weaned at postnatal day (PN) 21. Offspring were then fed a non ‘growth’ (4.6% fat) which ensured that catch-up growth did not occur. Offspring growth was determined by weight and dual energy X-ray absorptiometry. Nephron number was determined at PN21 using the disector-fractionator method. Kidney function was measured at PN180 and PN360 using clearance methods. Blood pressure was measured at PN360 using radio-telemetry. Body weight was similar at PN1, but by PN21 LP offspring were 39% smaller than controls (Pdiet < 0.001). This difference was due to proportional changes in lean muscle, fat, and bone content. LP offspring remained smaller than NP offspring until PN360. In LP offspring, nephron number was 26% less in males and 17% less in females, than NP controls (Pdiet < 0.0004). Kidney function was similar across dietary groups and sexes at PN180 and PN360. Blood pressure was similar in LP and NP offspring at PN360. These findings suggest that remaining on a slow growth trajectory after exposure to a suboptimal intrauterine environment does not lead to the development of kidney dysfunction and hypertension.

Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data.