The Puerto Rico Plain Pigeon Patagioenas inornata wetmorei suffered a severe population decline after hurricanes Irma and Maria in September 2017. We used distance sampling to estimate abundance (density and population size) in April–June 1986−2024, accounting for changes in detection probability. We used the distance-sampling abundance estimates to populate a Bayesian state–space logistic model and update posterior estimates of population carrying capacity, maximum population growth rate, population recovery time, and predicted abundance in April–June 2025−2034, accounting for observation and process variances. In addition, we used predicted abundance to assess potential extinction risk (probability Pr[N2025−2034 = 0|data]), population self-sustainability above 5,000 individuals (Pr[N2025−2034 >5,000|data]), and population surpassing the 2.5th percentile of carrying capacity (Pr[N2025−2034 >30,000|data]). The population has not recovered from the hurricanes, with estimated density averaging 0.0015 individuals/ha (bootstrapped standard error [SE] = 0.0006) and population size averaging 1,097 individuals (SE = 455) at the 749,000-ha survey region in April–June 2018−2024. Posterior mean estimates were 41,580 individuals (Markov Chain Monte Carlo standard deviation [SD] = 8,052) for population carrying capacity, 0.183 (SD = 0.056) for maximum population growth rate, six years (SD = 2) for recovery time, and 7,173 individuals (SD = 12,309) for predicted abundance in April–June 2025−2034. The population may reach self-sustainability levels (range Pr[N2025−2034 >5,000|data] = 0.326−0.631) but currently is undergoing a prolonged bottleneck and may become extinct (range Pr[N2025−2034 = 0|data] = 0.199−0.332), particularly if reproduction continues to be mostly unsuccessful, anthropogenic disturbances remain unabated, and on top of that another devastating hurricane makes landfall during the next 10 years. The Puerto Rico Plain Pigeon subspecies is in urgent need of management aiming to increase and maintain abundance above 5,000 individuals but preferably surpassing the 2.5th percentile of population carrying capacity as in the late 1990s (range Pr[N2025−2034 >30,000|data] = 0.000−0.181).

Effect modification occurs when a covariate alters the relative effectiveness of treatment compared to control. It is widely understood that, when effect modification is present, treatment recommendations may vary by population and by subgroups within the population. Population-adjustment methods are increasingly used to adjust for differences in effect modifiers between study populations and to produce population-adjusted estimates in a relevant target population for decision-making. It is also widely understood that marginal and conditional estimands for non-collapsible effect measures, such as odds ratios or hazard ratios, do not in general coincide even without effect modification. However, the consequences of both non-collapsibility and effect modification together are little-discussed in the literature.

In this article, we set out the definitions of conditional and marginal estimands, illustrate their properties when effect modification is present, and discuss the implications for decision-making. In particular, we show that effect modification can result in conflicting treatment rankings between conditional and marginal estimates. This is because conditional and marginal estimands correspond to different decision questions that are no longer aligned when effect modification is present. For time-to-event outcomes, the presence of covariates implies that marginal hazard ratios are time-varying, and effect modification can cause marginal hazard curves to cross. We conclude with practical recommendations for decision-making in the presence of effect modification, based on pragmatic comparisons of both conditional and marginal estimates in the decision target population. Currently, multilevel network meta-regression is the only population-adjustment method capable of producing both conditional and marginal estimates, in any decision target population.

Understanding the determinants of malnutrition is pivotal for public health interventions. This study aimed to identify socio-economic, demographic, dietary and maternal determinants of wasting and overweight among Brazilian children between 6 and 59 months. Data from the Brazilian National Survey on Child Nutrition were analysed (n 11 789). Children’s weight-for-height Z-scores were calculated according to the WHO growth standard and classified as wasting (Z < −2), normal weight (–2 ≤ Z ≤ 1), overweight risk (1 < Z ≤ 2) and overweight (Z > 2). Socio-economic, demographic, dietary and maternal covariables were considered. Adjusted multinomial logistic regression (OR and 95 % CI) was employed. The prevalence of overweight and wasting was 9·5 and 2·6 %, respectively. In the adjusted model, younger age (6–23 months: OR: 1·7; 95 % CI: 1·3, 2·2), consumption of ≥ 5 ultra-processed food groups (OR: 1·8; 95 % CI: 1·1, 3·1), maternal underweight (OR: 0·4; 95 % CI: 0·2, 0·9), overweight (OR: 1·5; 95 % CI: 1·2, 1·9) and mild food insecurity (OR: 0·8; 95 % CI: 0·6, 1·0) were associated with child overweight. The Brazilian Northeast (OR: 4·9; 95 % CI: 2·1, 11·3), Southeast (OR: 7·1; 95 % CI: 3·0, 16·6), South (OR: 4·7; 95 % CI: 1·8, 12·1), Midwest regions (OR: 2·7; 95 % CI: 1·2, 6·2) and maternal underweight (OR: 5·4; 95 % CI: 2·7, 10·7) were associated with wasting. Overweight in Brazil is prevalent among children between 6 and 59 months, while wasting is not a major public health problem. The main determinants of these Brazilian children’s nutritional status were age, ultra-processed food consumption and maternal nutritional status.

Preference rankings usually depend on the characteristics of both the individuals judging a set of objects and the objects being judged. This topic has been handled in the literature with log-linear representations of the generalized Bradley-Terry model and, recently, with distance-based tree models for rankings. A limitation of these approaches is that they only work with full rankings or with a pre-specified pattern governing the presence of ties, and/or they are based on quite strict distributional assumptions. To overcome these limitations, we propose a new prediction tree method for ranking data that is totally distribution-free. It combines Kemeny’s axiomatic approach to define a unique distance between rankings with the CART approach to find a stable prediction tree. Furthermore, our method is not limited by any particular design of the pattern of ties. The method is evaluated in an extensive full-factorial Monte Carlo study with a new simulation design.

Visceral leishmaniasis (VL) is a tropical disease that can be fatal if acute and untreated. Diagnosis is difficult, the treatment is toxic and prophylactic vaccines do not exist. Leishmania parasites express hundreds of proteins and several of them are relevant for the host's immune system. In this context, in the present study, 10 specific T-cell epitopes from 5 parasite proteins, which were identified by antibodies in VL patients’ sera, were selected and used to construct a gene codifying the new chimeric protein called rCHI. The rCHI vaccine was developed and thoroughly evaluated for its potential effectiveness against Leishmania infantum infection. We used monophosphoryl lipid A (MPLA) and polymeric micelles (Mic) as adjuvant and/or delivery system. The results demonstrated that both rCHI/MPLA and rCHI/Mic significantly stimulate an antileishmanial Th1-type cellular response, with higher production of IFN-γ, TNF-α, IL-12 and nitrite in vaccinated animals, and this response was sustained after challenge. In addition, these mice significantly reduced the parasitism in internal organs and increased the production of IgG2a isotype antibodies. In vivo and in vitro toxicity showed that rCHI is safe for the mammalians, and the recombinant protein also induced in vitro lymphoproliferative response and production of Th1-type cytokines by human cells, which were collected from healthy subjects and treated VL patients. These data suggest rCHI plus MPLA or micelles could be considered as a vaccine candidate against VL.

To maximize its value, the design, development and implementation of structural health monitoring (SHM) should focus on its role in facilitating decision support. In this position paper, we offer perspectives on the synergy between SHM and decision-making. We propose a classification of SHM use cases aligning with various dimensions that are closely linked to the respective decision contexts. The types of decisions that have to be supported by the SHM system within these settings are discussed along with the corresponding challenges. We provide an overview of different classes of models that are required for integrating SHM in the decision-making process to support the operation and maintenance of structures and infrastructure systems. Fundamental decision-theoretic principles and state-of-the-art methods for optimizing maintenance and operational decision-making under uncertainty are briefly discussed. Finally, we offer a viewpoint on the appropriate course of action for quantifying, validating, and maximizing the added value generated by SHM. This work aspires to synthesize the different perspectives of the SHM, Prognostic Health Management, and reliability communities, and provide directions to researchers and practitioners working towards more pervasive monitoring-based decision-support.

Most of the eggs for consumption are produced in a conventional housing system although the demand for organic eggs is increasing because consumers assume better nutritional characteristics. This study was conducted to compare the quality of organic eggs and enriched cage eggs. A total of 409 organic eggs and 385 eggs from hens housed in enriched cages were directly collected from 15 different farms, located in Spain and were analyzed within 4 days after laying. The differences in quality by removing the time bias that can be caused by marketing time were thus determined. All the hens were of three different lines, 47–50 weeks old and consumed commercial feed with the same nutritional composition. The quality traits evaluated were egg weight (EW g), egg shape index (SI), shell thickness (ST), shell percentage (SP), Haugh units (HU), dense albumen percentage (DAP), total albumen percentage (TAP), yolk color (YC), yolk percentage (YP), Roche scale (RS), moisture (M), ash content (AC), total protein (TP), total yolk carotenoids (TYC), total fat (TF), saturated fatty acids (SFA), monounsaturated fatty acids (MFA), and polyunsaturated fatty acids (PFA). Estimates of differences were obtained by generalized least squares using housing system, genetic line and their interaction as factors. Significant differences were observed for EW (65.3 vs 62.9), SI (77.60 vs 76.10), HU (83.60 vs 81.80), TAP (66.5 vs 64.17), YC (3.11 vs 1.89), RS (11.79 vs 9.48), TP (9.99 vs 8.55), TYC (4.188 vs 2.650), SFA (32.20 vs 30.00) and MFA (53.40 vs 44.20) in favor of the enriched cage system. In the organic system, the quality parameters that had higher and significant values were ST (0.34 vs 0.32), SP (10.52 vs 9.41), YP (25.20 vs 24.30), AC (1.12 vs 0.93) and PFA (26.00 vs 14.00). Significant interactions between the housing system and the hen line followed the same pattern observed for fixed effects. Organic eggs were lighter, less rounded with better shell quality and therefore showed lower Haugh unit values and a lower albumen percentage. Total protein, total fat, and lipid profile were within the usual average values for commercial eggs, although the proportion of polyunsaturated fatty acids, which are beneficial for consumers, was higher in organic eggs.

The previously unindexed laboratory X-ray powder diffraction data of mosapride dihydrogen citrate dihydrate, an API used to stimulate gastrointestinal motility, has been recorded at room temperature. Using these data, the crystal structure of this API has been refined in space group P21/c (No. 14) with a = 18.707(4) Å, b = 9.6187(1) Å, c = 18.2176(4) Å, β = 114.164(1)°, V = 2990.74(8) Å3, and Z = 4. The structure of this material corresponds to the phase associated with CSD Refcode LUWPOL determined at 93 K. The Rietveld refinement, carried out with TOPAS-Academic, proved the single nature of the sample and the quality of the data recorded.

The Mg-vermiculite from Santa Olalla has been treated with aliphatic amides—formamide (FM), acetamide (AM) and propionamide (PM)—in aqueous solution. These treatments produce the transformation towards NH4-vermiculite and interstratified NH4-vermiculite-Mg-vermiculite phases. The NH4-vermiculite, Mg-vermiculite and interstratified (mixed-layer) phases have been identified from basal X-ray diffraction (XRD) interval peaks between 10.3 Å and 14.4 Å, and confirmed by direct Fourier transform method, as well as by atomic absorption spectrometry (AAS), infrared (IR) spectroscopy and thermal analysis.

According to their NH4-vermiculite/Mg-vermiculite probability coefficients ratio (PA/PB), and PAA, these interstratified phases can be divided into 3 categories: 1) If the PA/PB ratio is ≥ 7/3 and PAA ≥ 0.7, there are interstratified phases with a strong tendency toward segregation (case of FM, AM and PM). 2) If the PA/PB ratio is between 5/5 and 6/4, with PAA in the range 0.45–0.6, there are nearly regular alternating and random interstratified phases (case of AM and PM). 3) If the PA/PB ratio is ≤ 5/5 and PAA ≤ 0.45, there are interstratified phases with a strong tendency toward alternation (case of PM).

Experimental evidence reported in the present work indicates that the mechanism of interaction of Mg-vermiculite with FM, AM and PM in an aqueous medium takes place by ion exchange of NH4 between the layers. The hydrolysis of these aliphatic amides leads to the liberation of NH4+ into the medium. It has been found that the NH4+ sorption depends on the physico-chemical characteristics of the particular aliphatic amide, and the transformation of Mg-vermiculite to interstratified and/or NH4-vermiculite phases depends on the amide concentration. These treatments allow one to control the formation of interstratified and NH4-vermiculite phases.

Many soils developed from volcanic rocks in southern Brazil exhibit spontaneous magnetization caused by the presence of fine-grained maghemite (γ-Fe2O3), but few attempts were made to quantify or characterize this important soil component. To that end, clays were separated from freely drained soils derived from acid (≥63% SiO2), intermediate (54–62% SiO2), and basic (≤53% SiO2) igneous rocks produced by the Paraná flood volcanism. The sample set included soils with a wide range of pedogenic development on different landscape positions. The Fe oxide mineralogy of these samples was examined by using a combination of selective dissolution, magnetic susceptibility, and X-ray diffraction (XRD) techniques. Hematite and maghemite were the primary Fe oxides in mature soils (Oxisols, Ultisols, and Alfisols) developed from basic rocks; whereas goethite was dominant in all other soils, especially those formed from acid-intermediate rocks. The association of maghemite with basic rock materials suggests that it was primarily formed by oxidation of lithogenic magnetite. A strong, positive correlation (R2 = 0.89) was obtained between mass specific magnetic susceptibility (χ) of the clay fractions and maghemite contents estimated by XRD. Either method could be used for quantitative analyses, but χ was more sensitive than XRD at low maghemite concentrations (<2 wt. %). The clay-sized maghem-ites were superparamagnetic with an estimated value for the mass specific magnetic susceptibility (χlf) value of 91,000 × 10−8 m3 kg−1 and frequency dependent variations of 10–15%. The maghemites also had low unit cell constants, which, if attributed entirely to replacement of Fe by Al, would correlate with Al substitutions in the range of 5–16 mole %. Selective dissolution of the soil maghemites was achieved by treatment of Fe oxide concentrates with 1.8 M H2SO4 at 75°C for 2 h.

Despite being one of the main components of anxiety and playing a pivotal role in how an individual perceives and copes with anxiogenic situations or responds to a given treatment, trait anxiety is paradoxically omitted in most animal models of anxiety. This is problematic and particularly more concerning in models that are used to screen drugs and other treatments for specific anxiety disorders and to investigate their neurobiological mechanisms. Our group has been engaged in the search for specific anxiety-related traits in animal models of anxiety. We developed two new lines of rats with strong phenotypic divergence for high (Carioca High-conditioned Freezing [CHF]) and low (Carioca Low-conditioned Freezing [CLF]) trait anxiety as expressed in the contextual fear conditioning paradigm. Here, we summarize key behavioral, pharmacological, physiological, and neurobiological differences in one these lines, the CHF rat line, relative to randomized-cross controls and discuss how far they represent a valid and reliable animal model of generalized anxiety disorder and so high trait anxiety.

Peace is a hallmark of human societies. However, certain ant species engage in long-term intergroup resource sharing, which is remarkably similar to peace among human groups. We discuss how individual and group payoff distributions are affected by kinship, dispersal, and age structure; the challenges of diagnosing peace; and the benefits of comparing convergent complex behaviours in disparate taxa.