NARO historical phenotype dataset from rice breeding.

Data from breeding, including phenotypic information, may improve the efficiency of breeding. Historical data from breeding trials accumulated over a long time are also useful. Here, by organizing data accumulated in the National Agriculture and Food Research Organization (NARO) rice breeding program, we developed a historical phenotype dataset, which includes 6052 records obtained for 667 varieties in yield trials in 1991-2018 at six NARO research stations. The best linear unbiased predictions (BLUPs) and principal component analysis (PCA) were used to determine the relationships with various factors, including the year of cultivar release, for 15 traits, including yield. Yield-related traits such as the number of grains per panicle, plant weight, grain yield, and thousand-grain weight increased significantly with time, whereas the number of panicles decreased significantly. Ripening time significantly increased, whereas the lodging degree and protein content of brown rice significantly decreased. These results suggest that panicle-weight-type high-yielding varieties with excellent lodging resistance have been selected. These trends differed slightly among breeding locations, indicating that the main breeding objectives may differ among them. PCA revealed a higher diversity of traits in newer varieties.

Early-Life Economic Conditions and Old-Age Male Mortality: Evidence from Historical County-Level Bank Deposit Data.

This paper studies the long-run mortality effects of in-utero and early-life economic conditions. We examine how local economic conditions experienced during the Great Depression, proxied by county-level banking deposits during in-utero and first years of life, influence old-age longevity. We find that a one-standard-deviation rise in per capita bank deposits is associated with an approximately 1.7 month increase in males' longevity at old age. Additional analyses comparing state-level versus county-level economic measures provide insight on the importance of controlling for local-level confounders and exploiting more granular measures when exploring the relationship between early-life conditions and later-life mortality.

Rejoinder to the discussion on "LEAP: the latent exchangeability prior for borrowing information from historical data".

The discussions of our paper provide insights into the practical considerations of the latent exchangeability prior while also highlighting further extensions. In this rejoinder, we briefly summarize the discussions and provide comments.

LEAP: the latent exchangeability prior for borrowing information from historical data.

It is becoming increasingly popular to elicit informative priors on the basis of historical data. Popular existing priors, including the power prior, commensurate prior, and robust meta-analytic predictive prior, provide blanket discounting. Thus, if only a subset of participants in the historical data are exchangeable with the current data, these priors may not be appropriate. In order to combat this issue, propensity score approaches have been proposed. However, these approaches are only concerned with the covariate distribution, whereas exchangeability is typically assessed with parameters pertaining to the outcome. In this paper, we introduce the latent exchangeability prior (LEAP), where observations in the historical data are classified into exchangeable and non-exchangeable groups. The LEAP discounts the historical data by identifying the most relevant subjects from the historical data. We compare our proposed approach against alternative approaches in simulations and present a case study using our proposed prior to augment a control arm in a phase 3 clinical trial in plaque psoriasis with an unbalanced randomization scheme.

Power priors for replication studies.

The ongoing replication crisis in science has increased interest in the methodology of replication studies. We propose a novel Bayesian analysis approach using power priors: The likelihood of the original study's data is raised to the power of α, and then used as the prior distribution in the analysis of the replication data. Posterior distribution and Bayes factor hypothesis tests related to the power parameter α quantify the degree of compatibility between the original and replication study. Inferences for other parameters, such as effect sizes, dynamically borrow information from the original study. The degree of borrowing depends on the conflict between the two studies. The practical value of the approach is illustrated on data from three replication studies, and the connection to hierarchical modeling approaches explored. We generalize the known connection between normal power priors and normal hierarchical models for fixed parameters and show that normal power prior inferences with a beta prior on the power parameter α align with normal hierarchical model inferences using a generalized beta prior on the relative heterogeneity variance I2. The connection illustrates that power prior modeling is unnatural from the perspective of hierarchical modeling since it corresponds to specifying priors on a relative rather than an absolute heterogeneity scale.

A multitaxa approach to biodiversity inventory in Matela protected area (Terceira, Azores, Portugal).

Background: This manuscript is the first contribution of the project, "Matela - uma ilha de biodiversidade" ("Matela - an island of biodiversity"), that aims to restore the native vegetation within the Azorean Protected Area of the Terceira Island Nature Park known as the "Protected Area for the Management of Habitats or Species of Matela" (TER08), situated on Terceira Island, the Azores Archipelago, Portugal. This small fragment of native forest, positioned at a low-medium altitude (300-400 m a.s.l.), is facing some conservation impacts as a consequence of the spread of different invasive exotic plant species, mainly Pittosporumundulatum, Rubusulmifolius and Hedychiumgardnerianum. The database we present encompasses diverse taxonomic groups, including bryophytes, vascular plants, arthropods, birds and mammals. It is derived from intensive sampling campaigns conducted in 2022, but some data from a previous vascular plant survey in 2015 were also included. The objective of this study was to provide an updated inventory of bryophytes, vascular plants, arthropods, birds and mammals within this protected area. In this way we are providing the reference conditions necessary for the monitoring of the impacts of the current ongoing restoration efforts within the project "Matela - an island of biodiversity". Whenever feasible, the present inventory is juxtaposed with historical data from previous surveys conducted in Matela. New information: In the realm of bryophytes, our analysis revealed the presence of 75 taxa, comprising 44 mosses and 32 liverworts. Amongst these, 71 were indigenous, while three remained indeterminate and one, Campylopusintroflexus, was identified as invasive. A comparison with previous historical data revealed a decrease in species richness, which was partially counterbalanced by the discovery of 23 new recorded species in the area.Regarding vascular plants, we distinguished 54 species, comprising 28 indigenous and 26 introduced taxa. Almost 80% of the inventoried species (n = 43) were newly documented in Matela.The study of arthropods encompassed a total of 103 taxa. Within the realm of soil arthropods, we documented eight indigenous and 25 introduced taxa, witnessing the disappearance of endemic species alongside a substantial increase in introduced ones between 2002 and 2022. Canopy arthropods, totalling 36 indigenous and 18 introduced taxa, exhibited few changes when compared with data from 2002. SLAM traps captured 24 indigenous and 15 introduced arthropod taxa and no historical data are available for comparison.As for avian species, we noted 12 indigenous birds and one introduced species, confirming the presence of most of the historical recorded native species.The mammalian census revealed eight introduced species, setting new precedents for Matela, alongside the identification of one endemic species: the Azorean endemic bat Nyctalusazoreum.

Covariate adjusted meta-analytic predictive (CA-MAP) prior for historical borrowing using patient-level data.

Utilization of historical data is increasingly common for gaining efficiency in the drug development and decision-making processes. The underlying issue of between-trial heterogeneity in clinical trials is a barrier in making these methods standard practice in the pharmaceutical industry. Common methods for historical borrowing discount the borrowed information based on the similarity between outcomes in the historical and current data. However, individual clinical trials and their outcomes are intrinsically heterogenous due to differences in study design, patient characteristics, and changes in standard of care. Additionally, differences in covariate distributions can produce inconsistencies in clinical outcome data between historical and current data when there may be a consistent covariate effect. In such scenario, borrowing historical data is still advantageous even though the population level outcome summaries are different. In this paper, we propose a covariate adjusted meta-analytic-predictive (CA-MAP) prior for historical control borrowing. A MAP prior is assigned to each covariate effect, allowing the amount of borrowing to be determined by the consistency of the covariate effects across the current and historical data. This approach integrates between-trial heterogeneity with covariate level heterogeneity to tune the amount of information borrowed. Our method is unique as it directly models the covariate effects instead of using the covariates to select a similar population to borrow from. In summary, our proposed patient-level extension of the MAP prior allows for the amount of historical control borrowing to depend on the similarity of covariate effects rather than similarity in clinical outcomes.

A Bayesian platform trial design with hybrid control based on multisource exchangeability modelling.

Enrolling patients to the standard of care (SOC) arm in randomized clinical trials, especially for rare diseases, can be very challenging due to the lack of resources, restricted patient population availability, and ethical considerations. As the therapeutic effect for the SOC is often well documented in historical trials, we propose a Bayesian platform trial design with hybrid control based on the multisource exchangeability modelling (MEM) framework to harness historical control data. The MEM approach provides a computationally efficient method to formally evaluate the exchangeability of study outcomes between different data sources and allows us to make better informed data borrowing decisions based on the exchangeability between historical and concurrent data. We conduct extensive simulation studies to evaluate the proposed hybrid design. We demonstrate the proposed design leads to significant sample size reduction for the internal control arm and borrows more information compared to competing Bayesian approaches when historical and internal data are compatible.

Maximizing efficiency in sunflower breeding through historical data optimization.

Genomic selection (GS) has become an increasingly popular tool in plant breeding programs, propelled by declining genotyping costs, an increase in computational power, and rediscovery of the best linear unbiased prediction methodology over the past two decades. This development has led to an accumulation of extensive historical datasets with genotypic and phenotypic information, triggering the question of how to best utilize these datasets. Here, we investigate whether all available data or a subset should be used to calibrate GS models for across-year predictions in a 7-year dataset of a commercial hybrid sunflower breeding program. We employed a multi-objective optimization approach to determine the ideal years to include in the training set (TRS). Next, for a given combination of TRS years, we further optimized the TRS size and its genetic composition. We developed the Min_GRM size optimization method which consistently found the optimal TRS size, reducing dimensionality by 20% with an approximately 1% loss in predictive ability. Additionally, the Tails_GEGVs algorithm displayed potential, outperforming the use of all data by using just 60% of it for grain yield, a high-complexity, low-heritability trait. Moreover, maximizing the genetic diversity of the TRS resulted in a consistent predictive ability across the entire range of genotypic values in the test set. Interestingly, the Tails_GEGVs algorithm, due to its ability to leverage heterogeneity, enhanced predictive performance for key hybrids with extreme genotypic values. Our study provides new insights into the optimal utilization of historical data in plant breeding programs, resulting in improved GS model predictive ability.

Unequal before death: The effect of paternal education on children's old-age mortality in the United States.

A growing body of research documents the relevance of parental education as a marker of family socio-economic status for children's later-life health outcomes. A strand of this literature evaluates how the early-life environment shapes mortality outcomes during infancy and childhood. However, the evidence on mortality during the life course and old age is limited. This paper contributes to the literature by analysing the association between paternal education and children's old-age mortality. We use data from Social Security Administration death records over the years 1988-2005 linked to the United States 1940 Census. Applying a family(cousin)- fixed-effects model to account for shared environment, childhood exposures, and common endowments that may confound the long-term links, we find that having a father with a college or high-school education, compared with elementary/no education, is associated with a 4.6- or 2.6-month-higher age at death, respectively, for the child, conditional on them surviving to age 47.

Quality Tolerance Limits: A General Guidance for Parameter Selection and Threshold Setting.

The past years have sharpened the industry's understanding of a Quality by Design (QbD) approach toward clinical trials. Using QbD encourages designing quality into a trial during the planning phase. The identification of Critical to Quality (CtQs) factors and specifically Critical Data and Processes (CD&Ps) is key to such a risk-based monitoring approach. A variable that allows monitoring the evolution of risk regarding the CD&Ps is called a Quality Tolerance Limit (QTL) parameter. These parameters are linked to the scientific question(s) of a trial and may identify the issues that can jeopardize the integrity of trial endpoints. This paper focuses on defining what QTL parameters are and providing general guidance on setting thresholds for these parameters allowing for the derivation of an acceptable range of the risk.

The Siren Song of Cicadas: Early-Life Pesticide Exposure and Later-Life Male Mortality.

This paper studies the long-term effects of in-utero and early-life exposure to pesticide use on adulthood and old-age longevity. We use the cyclical emergence of cicadas in the eastern half of the United States as a shock that raises the pesticide use among tree crop growing farmlands. We implement a difference-in-difference framework and employ Social Security Administration death records over the years 1975-2005 linked to the complete count 1940 census. We find that males born in top-quartile tree-crop counties and exposed to a cicada event during fetal development and early-life live roughly 2.2 months shorted lives; those with direct farm exposure face a reduction of nearly a year. We provide empirical evidence to examine mortality selection before adulthood, endogenous fertility, and differential data linkage rates. Additional analyses suggests that reductions in education and income during adulthood are potential mechanisms of impact. Our findings add to our understanding of the relevance of early-life insults for old-age health and mortality.

Dust to Feed, Dust to Gray: The Effect of in Utero Exposure to the Dust Bowl on Old-Age Longevity.

Intensive agriculture and deep plowing caused topsoil erosion and dust storms during the 1930s, affecting agricultural income and land values for years. Given the growing literature on the relevance of in utero and early-life exposures, it is surprising that studies focusing on links between the Dust Bowl and later-life health have produced inconclusive and mixed results. We reevaluate this literature and study the long-term effects of in utero and early-life exposure to topsoil erosion caused by the 1930s Dust Bowl on old-age longevity. Specifically, using Social Security Administration death records linked with the full-count 1940 census, we conduct event studies with difference-in-differences designs to compare the longevity of individuals in high- versus low-topsoil-erosion counties before versus after 1930. We find intent-to-treat reductions in longevity of approximately 0.85 months for those born in high-erosion counties after 1930. We show that these effects are not an artifact of preexisting trends in longevity. Additional analyses suggest that the effects are more pronounced among children raised in farm households, females, and those whose mothers had lower education. We also provide suggestive evidence that reductions in adulthood income are a likely mechanism for the effects we document.

COVERT: A classless approach to generating balanced datasets for process modelling.

In this work, a classless oversampling technique, Covert, was developed to improve historical datasets from industrial processing plants to aid process modelling. Using kernel density estimation and nearest neighbour algorithms, sparse regions are identified and resampled, developing a more balanced dataset. When applied to a real dataset from a geothermal power plant, Covert outperforms current best practice (Smote) in uniformly populating the input feature space and generating credible data in the output variable. When used to develop a data-driven model Covert improved model accuracy by 20% when predicting outside the original data's feature space. Smote, however, reduced model accuracy by 6% in the same feature space. Developing reliable models of industrial processes continues to be a significant hurdle in developing a digital twin. Using Covert, existing imbalanced historical data can be used to extend the range of applicability of any process model.

Incorporation of healthy volunteers data on receptor occupancy into a phase II proof-of-concept trial using a Bayesian dynamic borrowing design.

Receptor occupancy in targeted tissues measures the proportion of receptors occupied by a drug at equilibrium and is sometimes used as a surrogate of drug efficacy to inform dose selection in clinical trials. We propose to incorporate data on receptor occupancy from a phase I study in healthy volunteers into a phase II proof-of-concept study in patients, with the objective of using all the available evidence to make informed decisions. A minimal physiologically based pharmacokinetic modeling is used to model receptor occupancy in healthy volunteers and to predict it in the patients of a phase II proof-of-concept study, taking into account the variability of the population parameters and the specific differences arising from the pathological condition compared to healthy volunteers. Then, given an estimated relationship between receptor occupancy and the clinical endpoint, an informative prior distribution is derived for the clinical endpoint in both the treatment and control arms of the phase II study. These distributions are incorporated into a Bayesian dynamic borrowing design to supplement concurrent phase II trial data. A simulation study in immuno-inflammation demonstrates that the proposed design increases the power of the study while maintaining a type I error at acceptable levels for realistic values of the clinical endpoint.

The Use of Shells of Marine Molluscs in Spanish Ethnomedicine: A Historical Approach and Present and Future Perspectives.

Since ancient times, the shells of marine molluscs have been used as a therapeutic and/or prophylactic resource. In Spain, they were part of practical guides for doctors or pharmacists until the 19th century. In general, seashells were prepared by dissolving in vinegar and were part of plasters or powders used as toothpaste, or to treat dyspepsia, heartburn and leprosy. Thus, the nacre or mother-of-pearl of various molluscs was regularly used in the Royal Colleges of Surgery and in hospitals during the times of the Cortes of Cadiz, as a medicine in galenic preparations based on powders. In contemporary Spanish ethnomedicine, seashells, with a high symbolic value, have been used as an amulet to prevent cracks in the breasts and promote their development during lactation, to avoid teething pain in young children, to eliminate stains on the face or to cure erysipelas. But, as in other countries, products derived from seashells have also been empirically applied. The two resources used traditionally have been the cuttlebone, the internal shell of cuttlefish and the nacre obtained from the external shells of some species. Cuttlebone, dried and pulverised, has been applied externally to cure corneal leukoma and in dental hygiene. In the case of nacre, a distinction must be made between chemical and physical remedies. Certain seashells, macerated in lemon juice, were used in coastal areas to remove spots on the face during postpartum. However, the most common practice in Spain mainland was to dissolve mother-of-pearl buttons in lemon juice (or vinegar). The substance thus obtained has been used to treat different dermatological conditions of the face (chloasma, acne), as well as to eliminate freckles. For the extraction of foreign bodies in the eyes, a very widespread traditional remedy has been to introduce small mother-of-pearl buttons under the lid. These popular remedies and practices are compared with those collected in classic works of medicine throughout history, and data on the pharmacological activity and pharmaceutical applications of the products used are provided. The use of cuttlebone powders is supported by different works on anti-inflammatory, immune-modulatory and/or wound healing properties. Nacre powder has been used in traditional medicines to treat palpitations, convulsions or epilepsy. As sedation and a tranquilisation agent, nacre is an interesting source for further drug development. Likewise, nacre is a biomaterial for orthopaedic and other tissue bioengineering applications. This article is a historical, cultural and anthropological view that can open new epistemological paths in marine-derived product research.

How can data visualization support interdisciplinary research? LuxTIME: studying historical exposomics in Belval.

The Luxembourg Time Machine (LuxTIME) is an interdisciplinary project that studies the historical exposome during the industrialization of the Minett region, located in the south of Luxembourg. Exposome research encompasses all external and internal non-genetic factors influencing the health of the population, such as air pollution, green spaces, noise, work conditions, physical activity, and diet. Due to the wide scope of the interdisciplinary project, the historical study of the exposome in Belval involved the collection of quantitative and qualitative data from the National Archive of Luxembourg, various local archives (e.g., the communes of Esch-sur-Alzette and Sanem), the National Library, the Library of National Statistics STATEC, the National Geoportal of Luxembourg, scientific data from other research centers, and information from newspapers and journals digitized in eluxemburgensia. The data collection and the resulting inventory were performed to create a proof of concept to critically test the potential of a multi-layered research design for the study of the historical exposome in Belval. The guiding navigation tool throughout the project was data visualization. It has facilitated the exploration of the data collected (or just the data) and the metadata. It has also been a valuable tool for mapping knowledge and defining the scope of the project. Furthermore, different data visualization techniques have helped us to reflect on the process of knowledge sharing, to understand how the relevance of certain topics changed throughout the project and why, and to learn about the publication process in different journals and the experience of the participants. Data visualization is used not only as a means to an end but also to embrace the idea of sandcastles using a speculative and process-oriented approach to advance knowledge within all research fields involved. LuxTIME has proven to be an ideal case study to explore the possibilities offered by different data visualization concepts and techniques resulting in a data visualization toolbox that could be evaluated and extended in other interdisciplinary projects.

State-level desegregation in the U.S. South and mid-life cognitive function among Black and White adults.

RATIONALE: Black adults experience worse cognitive function than their White peers. Although educational attainment is an important predictor of cognitive function, other aspects of education, including school desegregation, may also shape this relationship. For Black adults who grew up in the U.S. South in the 1950s-1970s, exposure to school desegregation may have altered life course pathways critical for later cognitive function. OBJECTIVE: We determined if state variation in exposure to school desegregation in the U.S. South was associated with cognitive function at mid-life, if the association varied by race, and if the association remained after adjustment for state-level education quality and respondents' educational attainment. METHODS: We linked historical data on state-level school desegregation to the Health and Retirement Study, a nationally representative sample of U.S. adults aged 50 and older. We restricted our sample to Black (n = 1443) and White (n = 1507) adults born between 1948 and 1963 who resided in the U.S. South during primary school. We assessed three cognition outcomes: total cognitive function, episodic memory, and mental status. We estimated race-stratified linear regression models with cluster adjustment and a final model using state fixed effects. RESULTS: Greater exposure to desegregated primary schooling was associated with higher cognitive function and episodic memory among Black but not White adults. Among Black adults, the association between school desegregation and cognitive function and episodic memory remained after adjustment for state-level education quality and educational attainment. CONCLUSIONS: Our findings suggest that state-level school desegregation efforts played a consequential role in shaping the cognitive function of Black adults who grew up in the U.S. South.

SAM: Self-adapting mixture prior to dynamically borrow information from historical data in clinical trials.

Mixture priors provide an intuitive way to incorporate historical data while accounting for potential prior-data conflict by combining an informative prior with a noninformative prior. However, prespecifying the mixing weight for each component remains a crucial challenge. Ideally, the mixing weight should reflect the degree of prior-data conflict, which is often unknown beforehand, posing a significant obstacle to the application and acceptance of mixture priors. To address this challenge, we introduce self-adapting mixture (SAM) priors that determine the mixing weight using likelihood ratio test statistics or Bayes factors. SAM priors are data-driven and self-adapting, favoring the informative (noninformative) prior component when there is little (substantial) evidence of prior-data conflict. Consequently, SAM priors achieve dynamic information borrowing. We demonstrate that SAM priors exhibit desirable properties in both finite and large samples and achieve information-borrowing consistency. Moreover, SAM priors are easy to compute, data-driven, and calibration-free, mitigating the risk of data dredging. Numerical studies show that SAM priors outperform existing methods in adopting prior-data conflicts effectively. We developed R package "SAMprior" and web application that are freely available at CRAN and www.trialdesign.org to facilitate the use of SAM priors.

Long-Term Health Benefits of Occupational Licensing: Evidence from Midwifery Laws.

During the late 19th and early 20th century, several states mandated midwifery licensing requirements to improve midwives' knowledge, education, and quality. Previous studies point to the health benefits of midwifery quality improvements for maternal and infant health outcomes. This paper exploits the staggered adoption of midwifery laws across states using event-study and difference-in-difference frameworks. We use the universe of death records in the US over the years 1979-2020 and find that exposure to a midwifery licensing law at birth is associated with a 2.5 percent reduction in cumulative mortality rates and an increase of 0.6 months in longevity during adulthood and old age. The effects are concentrated on deaths due to infectious diseases, neoplasm diseases, and suicide mortality. We also show that the impacts are confined among blacks and are slightly larger among males. Additional analyses using alternative data sources suggest small but significant increases in educational attainments, income, measures of socioeconomic status, employment, and measures of height as potential mechanism channels. We provide a discussion on the economic magnitude and policy implication of the results.