In many areas of psychology, correlation-based network approaches (i.e., psychometric networks) have become a popular tool. In this paper, we propose an approach that recursively splits the sample based on covariates in order to detect significant differences in the structure of the covariance or correlation matrix. Psychometric networks or other correlation-based models (e.g., factor models) can be subsequently estimated from the resultant splits. We adapt model-based recursive partitioning and conditional inference tree approaches for finding covariate splits in a recursive manner. The empirical power of these approaches is studied in several simulation conditions. Examples are given using real-life data from personality and clinical research.

We present the Cosmological Double Radio Active Galactic Nuclei (CosmoDRAGoN) project: a large suite of simulated AGN jets in cosmological environments. These environments sample the intra-cluster media of galaxy clusters that form in cosmological smooth particle hydrodynamics (SPH) simulations, which we then use as inputs for grid-based hydrodynamic simulations of radio jets. Initially conical jets are injected with a range of jet powers, speeds (both relativistic and non-relativistic), and opening angles; we follow their collimation and propagation on scales of tens to hundreds of kiloparsecs, and calculate spatially resolved synthetic radio spectra in post-processing. In this paper, we present a technical overview of the project, and key early science results from six representative simulations which produce radio sources with both core- (Fanaroff-Riley Type I) and edge-brightened (Fanaroff-Riley Type II) radio morphologies. Our simulations highlight the importance of accurate representation of both jets and environments for radio morphology, radio spectra, and feedback the jets provide to their surroundings.

The potential utilization of a cold-contact approach to research recruitment, where members of the research team are unknown to the patient, has grown with the expanded use of electronic health records (EHRs) and affiliated patient portals. Institutions that permit this strategy vary in their implementation and management of it but tend to lean towards more conservative approaches. This process paper describes the Medical University of South Carolina’s transition to an opt-out model of “cold-contact” recruitment (known as patient outreach recruitment or POR), wherein patients can be contacted so long as they do not express an unwillingness to receive such communication. The work highlights the benefits of this model by explaining how it, in many ways, supports and protects autonomy, beneficence, and justice for patients. The paper then describes the process of standing up the recruitment strategy, communicating the change to patients and the community, and documenting study team contact and patient research preference. Data supporting increased access to potentially eligible patients of greater diversity as well as initial researcher feedback on perceived success of POR is also shared. The paper ends with a discussion of next steps to enhance the POR process via more detailed data collection and reengagement with community stakeholders.

Building on Ellis et al.’s theorization for potent dimensions of environmental adversity, the present work sought to evaluate how environmental harshness and unpredictability might function directly and in interaction with child sensory processing sensitivity (SPS) to shape the development of child socioemotional functioning. Participants were 235 young children (Mage = 2.97 at the first measurement occasion) and their parents, who were followed for two consecutive annual measurement occasions. Child SPS was measured through behavioral observation across multiple tasks within the laboratory setting. Greater environmental unpredictability was significantly associated with the development of children’s externalizing problems over a year only for children with high SPS. Follow-up analyses indicated that the unpredictability-x-SPS interaction was consistent with differential susceptibility, such that high SPS children showed greater increases in externalizing problems under high unpredictability, but also lower increases/greater decreases in externalizing problems under low unpredictability. Such association did not apply to children with low SPS.

Diets varying in SFA and MUFA content can impact glycaemic control; however, whether underlying differences in genetic make-up can influence blood glucose responses to these dietary fatty acids is unknown. We examined the impact of dietary oils varying in SFA/MUFA content on changes in blood glucose levels (primary outcome) and whether these changes were modified by variants in the stearoyl-CoA desaturase (SCD) gene (secondary outcome). Obese men and women participating in the randomised, crossover, isoenergetic, controlled-feeding Canola Oil Multicenter Intervention Trial II consumed three dietary oils for 6 weeks, with washout periods of ˜6 weeks between each treatment. Diets studied included a high SFA/low MUFA Control oil (36·6 % SFA/28·2 % MUFA), a conventional canola oil (6·2 % SFA/63·1 % MUFA) and a high-oleic acid canola oil (5·8 % SFA/74·7 % MUFA). No differences in fasting blood glucose were observed following the consumption of the dietary oils. However, when stratified by SCD genotypes, significant SNP-by-treatment interactions on blood glucose response were found with additive models for rs1502593 (P = 0·01), rs3071 (P = 0·02) and rs522951 (P = 0·03). The interaction for rs3071 remained significant (P = 0·005) when analysed with a recessive model, where individuals carrying the CC genotype showed an increase (0·14 (sem 0·09) mmol/l) in blood glucose levels with the Control oil diet, but reductions in blood glucose with both MUFA oil diets. Individuals carrying the AA and AC genotypes experienced reductions in blood glucose in response to all three oils. These findings identify a potential new target for personalised nutrition approaches aimed at improving glycaemic control.

Although recognized as one of the most significant cultural transformations in North America, the reintroduction of the horse to the continent after AD 1492 has been rarely addressed by archaeological science. A key contributing factor behind this limited study is the apparent absence of equine skeletal remains from early historic archaeological contexts. Here, we present a multidisciplinary analysis of a horse skeleton recovered in Lehi, Utah, originally attributed to the Pleistocene. Reanalysis of stratigraphic context and radiocarbon dating indicates a historic age for this horse (cal AD 1681–1939), linking it with Ute or other Indigenous groups, whereas osteological features demonstrate its use for mounted horseback riding—perhaps with a nonframe saddle. DNA analysis indicates that the animal was a female domestic horse, which was likely cared for as part of a breeding herd despite outliving its usefulness in transport. Finally, sequentially sampled stable carbon, oxygen, and strontium isotope values from tooth enamel (δ13C, δ18O, and 87Sr/86Sr) suggest that the horse was raised locally. These results show the utility of archaeological science as applied to horse remains in understanding Indigenous horse pastoralism, whereas consideration of the broader archaeological record suggests a pattern of misidentification of horse bones from early historic contexts.

The EAT–Lancet Commission promulgated a universal reference diet. Subsequently, researchers constructed an EAT–Lancet diet score (0–14 points), with minimum intake values for various dietary components set at 0 g/d, and reported inverse associations with risks of major health outcomes in a high-income population. We assessed associations between EAT–Lancet diet scores, without or with lower bound values, and the mean probability of micronutrient adequacy (MPA) among nutrition-insecure women of reproductive age (WRA) from low- and middle-income countries (LMIC). We analysed single 24-h diet recall data (n 1950) from studies in rural DRC, Ecuador, Kenya, Sri Lanka and Vietnam. Associations between EAT–Lancet diet scores and MPA were assessed by fitting linear mixed-effects models. Mean EAT–Lancet diet scores were 8·8 (SD 1·3) and 1·9 (SD 1·1) without or with minimum intake values, respectively. Pooled MPA was 0·58 (SD 0·22) and energy intake was 10·5 (SD 4·6) MJ/d. A one-point increase in the EAT–Lancet diet score, without minimum intake values, was associated with a 2·6 (SD 0·7) percentage points decrease in MPA (P < 0·001). In contrast, the EAT–Lancet diet score, with minimum intake values, was associated with a 2·4 (SD 1·3) percentage points increase in MPA (P = 0·07). Further analysis indicated positive associations between EAT–Lancet diet scores and MPA adjusted for energy intake (P < 0·05). Our findings indicate that the EAT–Lancet diet score requires minimum intake values for nutrient-dense dietary components to avoid positively scoring non-consumption of food groups and subsequently predicting lower MPA of diets, when applied to rural WRA in LMIC.