This systematic review aims to evaluate the effectiveness of various physical environmental enrichment items such as brushes, ropes, teats, chains, balls, cowhides/blocks, at improving the welfare of indoor-housed calves, heifers, and cattle. This review of 33 peer-reviewed papers and one industry report evaluated different welfare-related outcomes following physical environmental enrichment, including feed intake, lying time, play and exploratory behaviour, aggression, stereotypic behaviour and cross-sucking behaviour. The results of the meta-analysis revealed that calves and heifers enrolled in experimental studies using enrichment items had significantly improved growth rates, and increased locomotor play, but the overall reduction in cross-sucking behaviour was small and non-significant. The effect of enrichment on feed intake, aggression/stereotypic behaviour, play behaviour, cleanliness score contrasted between studies, with some reporting improvements while others showed no effect of environmental enrichment in these parameters. The risk of bias assessment revealed limitations in researcher blinding, sequence generation, and allocation concealment across the literature assessing the effectiveness of environmental enrichment on animal welfare. Overall, this review underscores the significant positive impact of physical enrichment on the welfare and behaviour of indoor-housed cattle, while highlighting the need for further research to optimise enrichment strategies across different cattle age groups and housing conditions.

Traditional faith healers (TFHs) are often consulted for serious mental illness (SMIs) in low- and middle-income countries (LMICs). Involvement of TFHs in mental healthcare could provide an opportunity for early identification and intervention to reduce the mental health treatment gap in LMICs. The aim of this study was to identify models of collaboration between TFHs and biomedical professionals, determine the outcomes of these collaborative models and identify any mechanisms (i.e., explanatory processes) or contextual moderators (i.e., barriers and facilitators) of these outcomes. A systematic scoping review of five electronic databases was performed from inception to March 2023 guided by consultation with local experts in Nigeria and Bangladesh. Data were extracted using a predefined data charting form and synthesised narratively. Six independent studies (eight articles) satisfied the inclusion criteria. Study locations included Ghana (n = 1), Nigeria (n = 1), Nigeria and Ghana (n = 1), India (n = 1), Hong Kong (n = 1) and South Africa (n = 1). We identified two main intervention typologies: (1) Western-based educational interventions for TFHs and (2) shared collaborative models between TFHs and biomedical professionals. Converging evidence from both typologies indicated that education for TFHs can help reduce harmful practices. Shared collaborative models led to significant improvements in psychiatric symptoms (in comparison to care as usual) and increases in referrals to biomedical care from TFHs. Proposed mechanisms underpinning outcomes included trust building and empowering TFHs by increasing awareness and knowledge of mental illness and human rights. Barriers to implementation were observed at the individual (e.g., suspicions of TFHs), relationship (e.g., reluctance of biomedical practitioners to equalise their status with TFHs) and service (e.g., lack of formal referral systems) levels. Research on collaborative models for mental healthcare is in its infancy. Preliminary findings are encouraging. To ensure effective collaboration, future programmes should incorporate active participation from community stakeholders (e.g., patients, caregivers, faith healers) and target barriers to implementation on multiple levels.

Proof is given for a theorem stated but not proved by Eckart and Young in 1936, which has assumed considerable importance in the theory of lower-rank approximations to matrices, particularly in factor analysis.

A method of nonmetric multidimensional scaling is described which minimizes pairwise departures from monotonicity. The procedure is relatively simple, both conceptually and computationally. Experience to date suggests that it produces solutions comparable to those of other methods.

The solution is presented to the problem of finding that orthonormal matrix closest in the least-square sense to a given matrix of full rank. An application is shown to the problem in multiple regression analysis of determining the “importance” of each independent variable.

A simple method of monotone regression is described based on the principle of minimizing pairwise departures from monotonicity.

Declining labor force participation of older men throughout the 20th century and recent increases in participation have generated substantial interest in understanding the effect of public pensions on retirement. The National Bureau of Economic Research's International Social Security (ISS) Project, a long-term collaboration among researchers in a dozen developed countries, has explored this and related questions. The project employs a harmonized approach to conduct within-country analyses that are combined for meaningful cross-country comparisons. The key lesson is that the choices of policy makers affect the incentive to work at older ages and these incentives have important effects on retirement behavior.

Autistic children and young people (CYP) experience mental health difficulties but face many barriers to accessing and benefiting from mental health care. There is a need to explore strategies in mental health care for autistic CYP to guide clinical practice and future research and support their mental health needs. Our aim was to identify strategies used to improve mental health care for autistic CYP and examine evidence on their acceptability, feasibility, and effectiveness. A systematic review and meta-analysis were carried out. All study designs reporting acceptability/feasibility outcomes and empirical quantitative studies reporting effectiveness outcomes for strategies tested within mental health care were eligible. We conducted a narrative synthesis and separate meta-analyses by informant (self, parent, and clinician). Fifty-seven papers were included, with most investigating cognitive behavioral therapy (CBT)-based interventions for anxiety and several exploring service-level strategies, such as autism screening tools, clinician training, and adaptations regarding organization of services. Most papers described caregiver involvement in therapy and reported adaptations to communication and intervention content; a few reported environmental adjustments. In the meta-analyses, parent- and clinician-reported outcomes, but not self-reported outcomes, showed with moderate certainty that CBT for anxiety was an effective treatment compared to any comparison condition in reducing anxiety symptoms in autistic individuals. The certainty of evidence for effectiveness, synthesized narratively, ranged from low to moderate. Evidence for feasibility and acceptability tended to be positive. Many identified strategies are simple, reasonable adjustments that can be implemented in services to enhance mental health care for autistic individuals. Notable research gaps persist, however.

With its promise of nondestructive processing, rapid low-cost sampling, and portability to any field site or museum in the world, portable X-ray fluorescence (pXRF) spectrometry is rapidly becoming a standard piece of equipment for archaeologists. Even though the use of pXRF is becoming standard, the publication of pXRF analytical methods and the resulting data remains widely variable. Despite validation studies that demonstrate the importance of sample preparation, data collection settings, and data processing, there remains no standard for how to report pXRF results. In this article, we address the need for best practices in publishing pXRF analyses. We outline information that should be published alongside interpretive results in any archaeological application of pXRF. By publishing this basic information, archaeologists will increase the transparency and replicability of their analyses on an inter-analyst/inter-analyzer basis and provide clarity for journal editors and peer reviewers on publications and grant proposals for studies that use pXRF. The use of these best practices will result in better science in the burgeoning use of pXRF in archaeology.

OBJECTIVES/GOALS: Distinguishing indolent from aggressive prostate cancer and early identification of men at risk of developing aggressive, metastatic disease is of great importance. We aim to explore the relationship between N-glycan and collagen composition in prostate tumor tissue and the long-term outcome of the disease. METHODS/STUDY POPULATION: Matrix assisted laser desorption/ionization mass spectrometry can be utilized to characterize N-glycan profiles in formalin fixed paraffin embedded tissues. Collagen may also be characterized using ECM-targeted collagenase MALDI imaging. These approaches were used to analyze prostatectomy samples with different clinical outcomes. Tissue microarrays containing tissues from 75 non-progressors (no evidence of disease; NED) and 50 metastatic cases (MET) were examined. From a combined list of 90 N-glycans and 500 collagenase peptides, the average AUC intensity value for each glycan and collagen peptide was extracted and assessed as a predictor of metastatic progression. Ancestral informative markers were analyzed and polygenic hazard risk scores were generated for samples as well. RESULTS/ANTICIPATED RESULTS: Three N-glycans and three collagen peptides were found to discriminate between NED and MET cases with statistical significance. The best performing N-glycan was Hex6HexNAc6Fuc1 with an AUC of 0.77 (p<0.001). While the best performing collagen peptide was COL1A2 with an AUC of C 0.77 (p<0.001). DISCUSSION/SIGNIFICANCE: Both a collagen peptide and N-glycan were discovered as promising biomarkers to predict metastasis. Future validation studies are needed to confirm biomarker potential and to determine if the addition of these biomarkers can strengthen current genomic classifier’s ability to predict metastatic prostate cancer.

Controlling weeds is a critically important task in sugarcane production systems. Weeds compete for light, nutrients, and water, and if they are not managed properly can negatively impact sugarcane yields. Accurate detection of weeds versus desired plants was assessed using hyperspectral and pigment analyses. Leaf samples were collected from four commercial Louisiana sugarcane varieties, and nine weed species commonly found in sugarcane fields. Hyperspectral leaf reflectance data (350 to 850 nm) were collected from all samples. Plant pigment (chlorophylls and carotenoids) levels were also determined using high-performance liquid chromatography, and concentrations were determined using authentic standards and leaf area. In all cases, leaf reflectance data successfully differentiated sugarcane from weeds using canonical discrimination analysis. Linear discriminant analysis showed that the accuracy of the classification varied from 67% to 100% for individual sugarcane varieties and weed species. In all cases, sugarcane was not misclassified as a weed. Plant pigment levels exhibited marked differences between sugarcane varieties and weed species with differences in chlorophyll and carotenoid explaining much of the observed variation in reflectance. The ratio of chlorophyll a to chlorophyll b showed significant differences between sugarcane and all weed species. The successful implementation of this technology as either an airborne system to scout and map weeds or a tractor-based system to identify and spray weeds in real-time would offer sugarcane growers a valuable tool for managing their crops. By accurately targeting weeds in sugarcane fields that are emerged and growing, the total amount of herbicide applied could be decreased, resulting in cost savings for the grower and reduced environmental impacts.

Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies.

The US Senate is unique in the United States and rare internationally for its total disregard of population differences among its representational units. To analyze malapportionment’s policy impact, we devised a hypothetical reapportionment scheme that more closely approximates state population but remains favorable to small states. We developed a formula to reweight senators’ roll-call votes to reflect better state population differences. We recalculated 804 key US Senate votes between 1961 and 2019 and found that state equality in the Senate systematically biases policy outcomes toward Republican preferences.