Multicenter clinical trials are essential for evaluating interventions but often face significant challenges in study design, site coordination, participant recruitment, and regulatory compliance. To address these issues, the National Institutes of Health’s National Center for Advancing Translational Sciences established the Trial Innovation Network (TIN). The TIN offers a scientific consultation process, providing access to clinical trial and disease experts who provide input and recommendations throughout the trial’s duration, at no cost to investigators. This approach aims to improve trial design, accelerate implementation, foster interdisciplinary teamwork, and spur innovations that enhance multicenter trial quality and efficiency. The TIN leverages resources of the Clinical and Translational Science Awards (CTSA) program, complementing local capabilities at the investigator’s institution. The Initial Consultation process focuses on the study’s scientific premise, design, site development, recruitment and retention strategies, funding feasibility, and other support areas. As of 6/1/2024, the TIN has provided 431 Initial Consultations to increase efficiency and accelerate trial implementation by delivering customized support and tailored recommendations. Across a range of clinical trials, the TIN has developed standardized, streamlined, and adaptable processes. We describe these processes, provide operational metrics, and include a set of lessons learned for consideration by other trial support and innovation networks.

The World Cancer Research Fund and the American Institute for Cancer Research recommend a plant-based diet to cancer survivors, which may reduce chronic inflammation and excess adiposity associated with worse survival. We investigated associations of plant-based dietary patterns with inflammation biomarkers and body composition in the Pathways Study, in which 3659 women with breast cancer provided validated food frequency questionnaires approximately 2 months after diagnosis. We derived three plant-based diet indices: overall plant-based diet index (PDI), healthful plant-based diet index (hPDI) and unhealthful plant-based diet index (uPDI). We assayed circulating inflammation biomarkers related to systemic inflammation (high-sensitivity C-reactive protein [hsCRP]), pro-inflammatory cytokines (IL-1β, IL-6, IL-8, TNF-α) and anti-inflammatory cytokines (IL-4, IL-10, IL-13). We estimated areas (cm2) of muscle and visceral and subcutaneous adipose tissue (VAT and SAT) from computed tomography scans. Using multivariable linear regression, we calculated the differences in inflammation biomarkers and body composition for each index. Per 10-point increase for each index: hsCRP was significantly lower by 6·9 % (95 % CI 1·6%, 11·8%) for PDI and 9·0 % (95 % CI 4·9%, 12·8%) for hPDI but significantly higher by 5·4 % (95 % CI 0·5%, 10·5%) for uPDI, and VAT was significantly lower by 7·8 cm2 (95 % CI 2·0 cm2, 13·6 cm2) for PDI and 8·6 cm2 (95 % CI 4·1 cm2, 13·2 cm2) for hPDI but significantly higher by 6·2 cm2 (95 % CI 1·3 cm2, 11·1 cm2) for uPDI. No significant associations were observed for other inflammation biomarkers, muscle, or SAT. A plant-based diet, especially a healthful plant-based diet, may be associated with reduced inflammation and visceral adiposity among breast cancer survivors.

Despite the increased awareness and action towards Equality, Diversity and Inclusion (EDI), the glaciological community still experiences and perpetuates examples of exclusionary and discriminatory behavior. We here discuss the challenges and visions from a group predominantly composed of early-career researchers from the 2023 edition of the Karthaus Summer School on Ice Sheets and Glaciers in the Climate System. This paper presents the results of an EDI-focused workshop that the 36 students and 12 lecturers who attended the summer school actively participated in. We identify common threads from participant responses and distill them into collective visions for the future of the glaciological research community, built on actionable steps toward change. In this paper, we address the following questions that guided the workshop: What do we see as current EDI challenges in the glaciology research community and which improvements would we like to see in the next fifty years? Contributions have been sorted into three main challenges we want and need to face: making glaciology (1) more accessible, (2) more equitable and (3) more responsible.

Studies of experimental and betting markets have shown that markets are able to efficiently aggregate information dispersed over many traders. We study information aggregation in Arrow–Debreu markets using a novel information structure. Compared to previous studies, the information structure is more complex, allows for heterogeneity in information among traders—which provides insights into the way in which information is gradually disseminated in the market—and generates situations in which all traders hold identical beliefs over the traded assets’ values, thus providing a harsh stress test for belief updating. We find little evidence for information aggregation and dissemination in early rounds. Nonetheless, after traders gain experience with the market mechanism and structure, prices converge to reveal the true state of the world. Elicited post-market beliefs reveal that markets are able to efficiently aggregate dispersed information even if individual traders remain uninformed, consistent with the marginal trader hypothesis.

Regression is a fundamental prediction task common in data-centric engineering applications that involves learning mappings between continuous variables. In many engineering applications (e.g., structural health monitoring), feature-label pairs used to learn such mappings are of limited availability, which hinders the effectiveness of traditional supervised machine learning approaches. This paper proposes a methodology for overcoming the issue of data scarcity by combining active learning (AL) for regression with hierarchical Bayesian modeling. AL is an approach for preferentially acquiring feature-label pairs in a resource-efficient manner. In particular, the current work adopts a risk-informed approach that leverages contextual information associated with regression-based engineering decision-making tasks (e.g., inspection and maintenance). Hierarchical Bayesian modeling allow multiple related regression tasks to be learned over a population, capturing local and global effects. The information sharing facilitated by this modeling approach means that information acquired for one engineering system can improve predictive performance across the population. The proposed methodology is demonstrated using an experimental case study. Specifically, multiple regressions are performed over a population of machining tools, where the quantity of interest is the surface roughness of the workpieces. An inspection and maintenance decision process is defined using these regression tasks, which is in turn used to construct the active-learning algorithm. The novel methodology proposed is benchmarked against an uninformed approach to label acquisition and independent modeling of the regression tasks. It is shown that the proposed approach has superior performance in terms of expected cost—maintaining predictive performance while reducing the number of inspections required.

In this article the authors examine the effect of including alternate test forms in a factor matrix upon the validity of the resultant factor loadings, finding that in this particular instance the effect is negligible. Comparisons of the factor loadings derived from matrices in which only one of the alternate test forms is included with those in which both forms are included reveal practically no difference in the magnitude of either the original or rotated factor loadings, or in that of the computed communalities.

In practice, nondestructive testing (NDT) procedures tend to consider experiments (and their respective models) as distinct, conducted in isolation, and associated with independent data. In contrast, this work looks to capture the interdependencies between acoustic emission (AE) experiments (as meta-models) and then use the resulting functions to predict the model hyperparameters for previously unobserved systems. We utilize a Bayesian multilevel approach (similar to deep Gaussian Processes) where a higher-level meta-model captures the inter-task relationships. Our key contribution is how knowledge of the experimental campaign can be encoded between tasks as well as within tasks. We present an example of AE time-of-arrival mapping for source localization, to illustrate how multilevel models naturally lend themselves to representing aggregate systems in engineering. We constrain the meta-model based on domain knowledge, then use the inter-task functions for transfer learning, predicting hyperparameters for models of previously unobserved experiments (for a specific design).

This article examines the evolution of bioethics over the past four decades since the publication of John Harris’ seminal work, “The Value of Life” (1985). It argues that while the core principles articulated by Harris remain relevant, bioethics has undergone significant transformation across four key domains. First, the expanding frontiers of biotechnology have necessitated engagement with complex issues beyond individual clinical ethics. Second, there has been a widening of the circle of moral concern to encompass nonhuman animals, disability rights, and global health equity. Third, bioethics has become increasingly entangled with public policy and governance. Finally, the field has seen substantial academic proliferation and institutionalization. These developments have pushed bioethics to adapt its frameworks and methodologies while maintaining fidelity to foundational principles. This article concludes by considering the future challenges and opportunities for bioethics in an increasingly complex technological and social landscape.

Tiafenacil is a new nonselective protoporphyrinogen IX oxidase (PPO)–inhibiting herbicide with both grass and broadleaf activity labeled for preplant application to corn, cotton, soybean, and wheat. Early-season corn emergence and growth often coincides in the mid-South with preplant herbicide application in cotton and soybean, thereby increasing opportunity for off-target herbicide movement from adjacent fields. Field studies were conducted in 2022 to identify the impacts of reduced rates of tiafenacil (12.5% to 0.4% of the lowest labeled application rate of 24.64 g ai ha–1) applied to two- or four-leaf corn. Corn injury 1 wk after treatment (WAT) for the two- and four-leaf growth stages ranged from 31% to 6% and 37% to 9%, respectively, whereas at 2 WAT these respective ranges were 21.7% to 4% and 22.5% to 7.2%. By 4 WAT, visible injury following the two- and four-leaf exposure timing was no greater than 8% in all instances except the highest tiafenacil rate applied at the four-leaf growth stage (13%). Tiafenacil had no negative season-long impact, as the early-season injury observed was not manifested in a reduction in corn height 2 WAT or yield. Application of tiafenacil directly adjacent to corn in early vegetative stages of growth should be avoided. In cases where off-target movement does occur, however, affected corn should be expected to fully recover with no impact on growth and yield, assuming adequate growing conditions and agronomic/pest management practices are provided.

This study examined associations between pregnancy and infant birth outcomes with child telomere length at age 17 years; and investigated if there are sex differences between pregnancy complications and telomere length. We utilised the population-based prospective Raine cohort study in Western Australia, Australia. 2900 pregnant women were recruited at 16–20 weeks’ gestation (Gen 1), and their children (Gen 2) were followed up over several years. Generalised linear models were used to examine relationships between pregnancy or birth outcomes (gestational diabetes, pre-eclampsia, preterm birth, low birth weight, macrosomia), and as a composite, with telomere length, measured via a DNA sample from blood at 17 years of age. Analyses were adjusted for a range of confounders. Among the 1202 included children, there were no differences in child telomere length for any of the individual maternal or birth weight pregnancy outcomes nor were there any significant interactions between each of the complications (individual or composite) and the sex of the child. However, females born from any of the 5 adverse outcomes had shorter telomeres (estimated mean (SE) = -0.159 (0.061), p = 0.010) than females born in the absence of these complications. Specifically, females born from a pre-eclamptic pregnancy had shorter telomeres than females not born from a pre-eclamptic pregnancy (estimated mean (SE) = -0.166 (0.072), p = 0.022). No relationships were observed in males. Further longitudinal studies are needed to understand mediating factors that are important in predicting offspring telomere length and the necessity to investigate females and males independently.

Tiafenacil is a new non-selective protoporphyrinogen IX oxidase (PPO)-inhibiting herbicide with both grass and broadleaf activity labeled for preplant application to corn (Zea mays L.), cotton (Gossypium hirsutum L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum aestivum L.). Early-season soybean emergence and growth often coincide in the U.S. Midsouth with preplant herbicide application in later-planted cotton and soybean, thereby increasing opportunity for off-target herbicide movement from adjacent fields. Field studies were conducted in 2022 to identify any deleterious impacts of reduced rates of tiafenacil (12.5% to 0.4% of the lowest labeled application rate of 24.64 g ai ha−1) applied to 1- to 2-leaf soybean. Visual injury at 1 wk after treatment (WAT) with 1/8×, 1/16×, 1/32×, and 1/64× rate of tiafenacil was 80%, 61%, 39%, and 21%, while at 4 WAT, these respective rates resulted in visual injury of 67%, 33%, 14%, and 4%. Tiafenacil at these respective rates reduced soybean height 55% to 2% and 53% to 5% at 1 and 4 WAT and soybean yield 53%, 24%, 5%, and 1%. Application of tiafenacil directly adjacent to soybean in early vegetative growth should be avoided, as severe visual injury will occur. In cases where off-target movement does occur, impacted soybean should not be expected to fully recover, and negative impact on growth and yield will be observed.

By the end of the nineteenth century, Great Britain had become a home to many immigrant communities from across Europe and the wider world. The outbreak of the Great War of 1914-18 however, saw this multi-cultural society fracture. Those from the enemy nations suffered what Panikos Panayi described as efforts ‘aimed at eradicating the German community from Britain’, including persecution, internment, and repatriation, while the State struggled to deal with the threat of espionage and sabotage. Meanwhile, other immigrants from allied countries, such as Italy and Belgium, faced forced conscription from their home governments. Both these situations would impact the many Roman Catholic clergy and members of religious communities1 resident in the United Kingdom, affecting their ability to undertake their ministry, and sometimes resulting in incarceration.

The identification and quantification of the water associated with powdered clinoptilolite and clinoptilolite-bearing tuffs were made using thermogravimetric, vacuum gravimetric, and differential scanning calorimetric techniques. Inflection points on thermogravimetric curves at approximately 80° and 170°C correspond to changes in the proportions of externally adsorbed water to loosely bound zeolitic water and loosely bound zeolitic water to tightly bound zeolitic water, respectively. These three types of water can be differentiated by temperatures and heats of dehydration obtained from differential scanning calorimetry. These temperatures and heats of hydration are 75 ± 10°C and 59.2 ± 5.9 kJ/mole H2O, 171 ± 2°C and 58.7 ± 6.1 kJ/mole H2O, and 271 ± 4°C and 78.7 ± 7.0 kJ/mole H2O for external water, loosely bound water, and tightly bound water, respectively. The ratio of loosely bound zeolitic water to tightly bound zeolitic water determined in this study is similar to that reported in the literature from structural determinations, indicating that the desorption properties of clinoptilolite are determined by the specific positions of the water molecules in the structure.

We present new stable oxygen and carbon isotope composite records (δ18O, δ13C) of speleothems from Sandkraal Cave 1 (SK1) on the South African south coast for the time interval between 104 and 18 ka (with a hiatus between 48 and 41 ka). Statistical comparisons using kernel-based correlation analyses and semblance analyses based on continuous wavelet transforms inform the relationships of the new speleothem records to other proxies and their changes through time. Between 105 and ~70 ka, changes of speleothem δ18O values at SK1 are likely related to rainfall seasonality. Variations of δ13C values are associated with changes of vegetation density, prior carbonate precipitation (PCP), CO2 degassing in the cave, and possibly variations of the abundance of C3 and C4 grasses in the vegetation. The relationships of δ18O with other proxies shift between ~70 and 48 ka (Marine Isotope Stages 4–3) so that both stable isotope records now reflect CO2 degassing, evaporation, and PCP. Similar relationships also continue after the hiatus for the deposition phase between 42 and 18 ka. Our findings support modeling results suggesting drier conditions in the study area when the Southern Hemisphere westerlies are shifted north and the paleo–Agulhas Plain is exposed.

Recent research has shown the potential of speleothem δ13C to record a range of environmental processes. Here, we report on 230Th-dated stalagmite δ13C records for southwest Sulawesi, Indonesia, over the last 40,000 yr to investigate the relationship between tropical vegetation productivity and atmospheric methane concentrations. We demonstrate that the Sulawesi stalagmite δ13C record is driven by changes in vegetation productivity and soil respiration and explore the link between soil respiration and tropical methane emissions using HadCM3 and the Sheffield Dynamic Global Vegetation Model. The model indicates that changes in soil respiration are primarily driven by changes in temperature and CO2, in line with our interpretation of stalagmite δ13C. In turn, modelled methane emissions are driven by soil respiration, providing a mechanism that links methane to stalagmite δ13C. This relationship is particularly strong during the last glaciation, indicating a key role for the tropics in controlling atmospheric methane when emissions from high-latitude boreal wetlands were suppressed. With further investigation, the link between δ13C in stalagmites and tropical methane could provide a low-latitude proxy complementary to polar ice core records to improve our understanding of the glacial–interglacial methane budget.

The reading the mind in the eyes test (RMET) – which assesses the theory of mind component of social cognition – is often used to compare social cognition between patients with schizophrenia and healthy controls. There is, however, no systematic review integrating the results of these studies. We identified 198 studies published before July 2020 that administered RMET to patients with schizophrenia or healthy controls from three English-language and two Chinese-language databases. These studies included 41 separate samples of patients with schizophrenia (total n = 1836) and 197 separate samples of healthy controls (total n = 23 675). The pooled RMET score was 19.76 (95% CI 18.91–20.60) in patients and 25.53 (95% CI 25.19–25.87) in controls (z = 12.41, p < 0.001). After excluding small-sample outlier studies, this difference in RMET performance was greater in studies using non-English v. English versions of RMET (Chi [Q] = 8.54, p < 0.001). Meta-regression analyses found a negative association of age with RMET score and a positive association of years of schooling with RMET score in both patients and controls. A secondary meta-analysis using a spline construction of 180 healthy control samples identified a non-monotonic relationship between age and RMET score – RMET scores increased with age before 31 and decreased with age after 31. These results indicate that patients with schizophrenia have substantial deficits in theory of mind compared with healthy controls, supporting the construct validity of RMET as a measure of social cognition. The different results for English versus non-English versions of RMET and the non-monotonic relationship between age and RMET score highlight the importance of the language of administration of RMET and the possibility that the relationship of aging with theory of mind is different from the relationship of aging with other types of cognitive functioning.