Search Results (70)

Background: Obesity, gastrointestinal disorders, and mental health conditions are major drivers of employer healthcare expenditures, yet nutrition-focused interventions are infrequently reimbursed by health insurance. Precision nutrition, which integrates genetic, gut microbiome, biometric, and behavioral data to guide personalized dietary and lifestyle changes, may offer a scalable approach to reducing costs associated with diet-responsive conditions. Objectives: To evaluate the impact of a precision nutrition digital therapeutic on employer medical spending for diet-responsive conditions in self-insured U.S. health plans. Methods: We conducted a retrospective cohort study of medical claims from January 2022 to December 2024 across seven U.S. self-insured employers. Employees enrolled in a precision nutrition digital therapeutic (n = 258) were compared with never-enrolled peers (n = 8268). We estimated treatment effects using a two-stage difference-in-differences model with member and calendar-month fixed effects and clustered standard errors, focusing on per-member-per-year (PMPY) employer-paid medical spending overall and for predefined diet-responsive condition categories. PMPY estimates were defined conditional on months with positive employer-paid spending and therefore reflect changes in the intensity of spending among members generating claims rather than unconditional per-capita costs. Results: Enrollment in the precision nutrition digital therapeutic was associated with a −$3012 PMPY reduction in diet-responsive medical spending (p = 0.021) relative to non-enrolled peers on this conditional basis. The largest relative reductions were observed for digestive disorders (−$9240 PMPY; p = 0.029) and obesity (−$4884 PMPY; p = 0.007), with a smaller reduction for anxiety-related conditions (−$1356 PMPY; p = 0.043). Total medical spending decreased by −$4044 PMPY but this change did not reach statistical significance (p = 0.09). Conclusions: In this multi-employer claims analysis, participation in a precision nutrition digital therapeutic was associated with lower employer-paid medical expenditures for diet-responsive conditions, particularly digestive disorders and obesity. These findings suggest that precision nutrition digital therapeutics may represent a scalable strategy for employers to address the economic burden of chronic disease within self-insured health plans by reducing the intensity of medical spending among members. Full article

Genetic diversity is essential for species adaptation, evolution, and conservation and is a determining factor in plants of ecological and agronomic interest, such as Cereus fernambucensis (Cactaceae). This study evaluated phenotypic variability and the relative importance of morphophysiological traits in two natural populations of the species located in restinga areas in Paraíba, Brazil. Twenty subpopulations were analyzed in a completely randomized design with four replicates and 15 traits. Genetic divergence was estimated by the Mahalanobis distance and grouped via the Tocher method, whereas the relative contribution of the characters was determined via the Singh method, which is associated with a selection index to identify promising genotypes. The results indicated the formation of nine distinct groups, with the mean germination time and germination speed index being the most relevant variables for differentiation. Subpopulations 4 and 13 (area I) and 15, 16, 17, and 18 (area II) stood out as strategic genetic reservoirs for conservation and improvement. Thus, this study reinforces the importance of maintaining the genetic diversity of C. fernambucensis, especially in the face of habitat fragmentation, ensuring evolutionary resilience, enriching germplasm banks, and supporting programs for the sustainable use and valorization of the genetic resources of columnar cacti in coastal ecosystems. Full article

This study was conducted to (i) determine the association between live body weight (BW) and biometric traits, (ii) examine the effect of biometric traits on BW of Tswana sheep using MARS and CART data mining algorithms, (iii) compare the performance of the algorithms and, finally, select the best algorithm for predicting BW in Tswana sheep. BW and sixteen biometric traits were measured from 392 Tswana sheep (males = 85 and females = 307) aged three to four years. Pearson’s correlation coefficients were used to establish the relationship between BW and biometric traits. The goodness of fit criteria were computed to assess the predictive performance of the data mining algorithms and select the best-fit model for predicting BW. The results showed that BW had a positive and significant correlation with heart girth (HG) (r = 0.99); thus, HG was used as a sole predictor of BW. The goodness of fit results indicated that MARS has a higher predictive performance than the CART algorithm, suggesting that the MARS algorithm can be used to predict BW Tswana sheep. These findings are an important statistical tool for the selection and concurrent improvement of useful biometric traits in genetic improvement programs to improve BW in Tswana sheep. Full article

Background/Objectives: Paspalum nicorae Parodi is a native subtropical grass species with promising agronomic attributes, such as persistence, drought and cold tolerance, and rapid establishment. However, the species remains underutilized in breeding programs due to the absence of well-characterized germplasm and limited studies on its genetic variability and agronomic potential. This study aimed to estimate genetic parameters, predict genotypic values, and identify superior ecotypes with desirable forage traits, integrating stability and adaptability analyses. Methods: A total of 84 ecotypes were evaluated over three consecutive years for twelve morphological and forage-related traits. Genetic parameters, genotypic values, and selection gains were estimated using mixed models (REML/BLUP). Stability was assessed through harmonic means of genotypic performance, and the multi-trait genotype–ideotype distance index (MGIDI) was applied to identify ecotypes with balanced performance across traits. Results: Substantial genetic variability was detected for most traits, particularly those related to biomass accumulation, such as total dry matter, the number of tillers, fresh matter, and leaf dry matter. These traits exhibited medium to high heritability and strong potential for selection. Ecotype N3.10 consistently showed superior performance across productivity traits while other ecotypes, such as N4.14 and N1.09, stood out for quality-related attributes and cold tolerance, respectively. The application of the MGIDI index enabled the identification of 17 ecotypes with balanced multi-trait performance, supporting the simultaneous selection for productivity, quality, and adaptability. Comparisons with P. notatum suggest that P. nicorae harbors competitive genetic potential, despite its lower level of domestication. Conclusions: The integration of REML/BLUP analyses, stability parameters, and ideotype-based multi-trait selection provided a robust framework for identifying elite P. nicorae ecotypes. These findings reinforce the strategic importance of this species as a valuable genetic resource for the development of adapted and productive forage cultivars in subtropical environments. Full article

Platonia insignis Mart. is a native Amazonian fruit tree with considerable agro-industrial potential, yet it remains underutilized due to limited domestication efforts and the absence of breeding programs or improved genetic lines. This study aimed to estimate genetic parameters based on morpho-agronomic fruit traits and to identify superior genotypes from natural coastal populations in the Brazilian Amazon. Thirteen genotypes were evaluated for 16 biometric and compositional traits. Genetic parameters were estimated using REML/BLUP (Restricted Maximum Likelihood/Best Linear Unbiased Prediction) procedures, and a rank–sum selection index was applied to identify elite individuals. The results revealed substantial phenotypic and genetic variability, with broad-sense heritability values ranging from moderate to high for key traits, including longitudinal fruit diameter (0.81), fruit fresh mass (0.66), and seed fresh mass (0.75). Selection accuracy was high (≥0.96) across most traits, indicating strong experimental reliability. Genotypic correlations highlighted favorable associations among traits related to pulp yield, sugar content, and seed reduction. Six superior genotypes (G7, G1, G6, G3, G2, and G4) exhibited optimal profiles for fruit quality and productivity. These findings provide a strong foundation for breeding strategies and support the genetic conservation and domestication of P. insignis as a native species of high economic and ecological importance. Full article

Blueberry breeding requires a significant commitment of time, skilled labour, and financial resources, but it is essential to develop new cultivars that can meet challenges such as climate change, disease resistance, and changing market preferences. Intraspecific hybridisationis a widely used breeding strategy to increase genetic diversity, broaden the selection base, and develop new cultivars. By crossing different varieties and making advanced selections, breeders can introduce desirable traits such as improved fruit quality, increased yield, improved disease resistance and greater adaptability to environmental conditions. The present study aimed to evaluate the heritability of some key biometric and biochemical parameters inblueberry hybrids derived from intraspecific crosses to assess their inheritance patterns. The results can guide breeders in selecting parent combinations that maximise genetic gain, ultimately supporting the advancement of commercial blueberry production. The ‘Delicia × 4/6’ hybrid combination showed excellent performance for total polyphenol content, flavonoids, tannins, and ascorbic acid, with high genetic gain and near complete heritability, making it a promising candidate for improving antioxidant activity. The ‘Azur × Northblue’ hybrid had favourable total anthocyanin and tannin content, but an unfavourable sugar and ascorbic acid profile.The ‘Simultan × Duke’ hybrid combination showed the highest genetic gain for total soluble solids and firmness, together with high positive heterosis and heterotic progress, highlighting its potential for high-quality cultivars suitable for mechanical harvesting and storage. This research provides valuable insights into the efficiency of intraspecific hybridisationin the development of new blueberry cultivars with improved agronomic and nutritional qualities. Full article

Background/Objective: The accurate diagnosis of congenital central nervous system abnormalities is critical to pre- and postnatal prognostication and management. When an abnormality is found in the posterior fossa of the fetal brain, parental counseling is challenging because of the wide spectrum of clinical and neurodevelopmental outcomes in patients with Dandy–Walker (DW) spectrum posterior malformations. The objective of this study was to evaluate the utility of biometric measurements obtained from fetal magnetic resonance imaging (MRI) to facilitate the prenatal differentiation of Dandy–Walker (DW) spectrum malformations, including vermian hypoplasia (VH), Blake’s pouch cyst (BPC), and classic Dandy–Walker malformation (DWM). Methods: This retrospective single-center study evaluated 34 maternal–infant dyads referred for fetal MRI evaluation of suspected DW spectrum malformations identified on antenatal ultrasound. Radiologists took posterior fossa measurements, including the vermis anteroposterior (AP) diameter, vermis height (VH), and tegmento–vermian angle (TVA). The posterior fossa, fourth ventricle, and cisterna magna were classified as normal, large, or dilated. The postnatal imaging findings were evaluated for concordance. The acquired values were compared between the groups and with normative data. The genetic testing results are reported when available. Results: A total of 27 DW spectrum fetal MRI cases were identified, including 7 classic DWMs, 14 VHs, and 6 BPCs. The TVA was significantly higher in the DWM group compared with the VH and BPC groups (p < 0.001). All three groups had reduced AP vermis measurements for gestational age compared with normal fetal brains, as well as differences in the means across the groups (p = 0.002). Conclusions: Biometric measurements derived from fetal MRI can effectively facilitate the prenatal differentiation of VH, BPC, and classic DWM when assessing DW spectrum posterior fossa lesions. Standardizing biometric measurements may increase the diagnostic utility of fetal MRI and facilitate improved antenatal counseling and clinical decision-making. Full article

The authors examine the transformative impact of technological advancements on the customary traditions associated with camels in the United Arab Emirates (UAE). We conducted 21 semi-structured interviews with Emirati camel owners/breeders, focusing on the effects of innovations in breeding, racing, beauty contests, and heritage preservation. The findings reveal that genetic technologies have reshaped camel husbandry by enhancing desirable traits, while introducing commercialization. In camel racing, robotic jockeys, biometric monitoring, and GPS tracking have revolutionized training and competition, making the sport a highly regulated, technology-driven industry. Similarly, camel beauty contests have been influenced by genetic selection, aesthetic standards, and controversial cosmetic enhancements. While these advancements have increased the economic value of camels, they have also altered traditional perceptions, raising concerns about the commodification of Emirati heritage. Additionally, online platforms and digital tools have facilitated the global promotion of camels, fostering connections between owners/breeders and enthusiasts, while introducing new modes of engagement. The study demonstrates how technological progress both preserves and challenges the customary traditions associated with camels, offering insights into the intersection of modernization and cultural heritage in the UAE. Full article

Soil salinity is a major constraint on crop cultivation, affecting millions of hectares of land and increasing drastically worldwide. Identifying sources of tolerance within the crops and their wild relatives is imperative. Recently, Solanum dasyphyllum L. has been identified as source of tolerance to drought for eggplant (S. melongena L.). In this article, the potential use of S. dasyphyllum as a source of tolerance to salinity is investigated through the characterization of young plants’ performance under three salt stress treatments, well water (control), as well as 200 mM and 400 mM NaCl. Biometric parameters such as leaf and radicular biomass, plant height, root length, and biochemical parameters—such as photosynthetic pigments, main ions accumulation, proline, total soluble sugars, malondialdehyde, total phenolics, flavonoids, and antioxidant enzymes’ activity—were quantified. The results showed a certain reduction in leaf and stem plant growth up to 60% in response to extreme salinity, while root biomass was maintained under mid-salt stress. Salt stress caused toxic ions to accumulate in plant organs, up to 1600 mmol g⁻¹ dry weight Na⁺ and a 2250 mmol g⁻¹ dry weight Cl⁻ in leaves under extreme salinity exposure. However, S. dasyphyllum maintained K⁺ levels at around 450 mmol g⁻¹ in leaves and roots and 750 mmol g⁻¹ in stems, indicating a mechanism related to ion transport to cope with ion toxicity. The biochemical response indicated osmotic adjustments and antioxidant activity without the need of activating antioxidant enzymes. S. dasyphyllum has proved to be a valuable genetic tool for new eggplant breeding programs regarding salt stress, with somewhat improved performance regarding biometric parameters and ion transport. Full article

The multimodal data collection that includes physiological and psychological data, combined with data processing using artificial intelligence technology, has become a research trend in human–computer interaction. In the stage of new product design, it is necessary to consider user experience for the evaluation and prediction of new products. The paper presents a human–computer interaction study on new product design with user participation. This research adopts a combination of design neurocognition and genetic algorithms in design optimization to evaluate the usability of engineering control interfaces using eye-tracking and facial expression data. Eye-tracking and neural network technology are used to predict the appearance of humanoid robots. The paper explored the evaluation and prediction of new product design using multimodal physiological and psychological data. The research results indicate that artificial intelligence technologies represented by neural networks can fully exploit biometric data represented by eye-tracking and facial expression, improving the effectiveness of new product evaluation and prediction accuracy. The research results provide a solution based on the combination of design neurocognition and artificial intelligence technology for the evaluation and prediction of new product design in the future. Full article

The study of early dog domestication has been the focus of considerable scholarly interest in recent years, prompting extensive research aimed at pinpointing the precise temporal and geographic origins of this process. However, a consensus among studies remains elusive, with various research efforts proposing differing timelines and locations for domestication. To address the questions related to the domestication process, researchers have employed a wide range of methodologies, including genetic, biomolecular, morphometric, paleontological, biometric, and isotopic analyses, as well as dental wear analysis to reconstruct paleodiets. Each of these approaches requires access to fossil canid specimens, given that they work directly with the skeletal remains of dogs or wolves. Alternatively, some methods can yield insights into the domestication process without necessitating the physical remains of these canids. Taphonomy, for instance, enables the study of bone surfaces for tooth marks, which may serve as indirect indicators of carnivore activity, potentially attributable to dogs or wolves. This study applies a high-resolution taphonomic analysis to bones modified by carnivores at the prehistoric site of Peña Moñuz. Our aim is to identify the specific carnivores responsible for the observed bone modifications. The findings demonstrate the efficacy of this technique in identifying the agents of bite marks, suggesting that taphonomy may complement the paleogenetic, paleontological, and isotopic methodologies traditionally used to explore the origins of dog domestication Full article

In general, bark serves a protective role for trees and is genetically determined. The quantification of bark based on biometric characteristics is linked to studies on the distribution of forest species across the globe and vegetation fires. In Romania, on the other hand, the improvement of the wood traceability system requires an increase in the accuracy of the estimation of the biometric characteristics of bark and, implicitly, of the volume of wood under the bark. The aim of this study was to develop more precise models for predicting bark thickness along the stem of three key Romanian species, taking into account a comprehensive range of models and stem sections, including those with a diameter over bark smaller than 8 cm, which have been excluded in previous studies. The study is based on two datasets, one containing the national measurements of three commercially valuable forest species, i.e., Norway spruce (Picea abies (L.) Karst), European beech (Fagus sylvatica L.), and pedunculate oak (Quercus robur L.) from 12,186 trees, and a second dataset containing the measurements from 61 logs of the same species at a specific forest site. A set of seven double bark thickness (DBT) estimation models with stem diameter over bark (DOB), DOB and total tree height (H), DOB and relative height along the stem (h/H), and diameter over bark at breast height (DBH) and DOB as predictors were used. The DBT models were evaluated using the coefficient of determination (R²), mean absolute error (MAE), root mean squared error (RMSE), the Akaike information criterion (AIC), and the Bayesian information criterion (BIC). This led to the selection of two more accurate models, Model 2 (based on a third-degree polynomial) and Model 3 (based on a logarithmic function), with DOB as the predictor. Relative double bark thickness (RDBT) and proportion of bark area (PBA) were also estimated using a sixth-degree polynomial and relative height as a predictor variable after stratifying the data by DBH classes to reduce variability. The results of this study indicate that there is a need to complete the database, for all three forest species of commercial value in Romania especially for large trees with DBH greater than 60–70 cm. The models obtained for PBA are of great use to the industry and the economy, in particular in the context of the traceability of wood. This is due to the fact that PBA can be equated with the proportion of bark volume (PBV), which describes the variation in the proportion of bark in the volume of the wood assortments along the stem. For a given DBH, PBA and PBV demonstrate minimal variability in sections from the tree’s base to a relative height of 0.6; however, a pronounced increase is observed at crown level in sections above relative heights of 0.8. Full article

Findings from monitoring Greek fir forests in central Greece regarding radial growth, insect infestations, plant communities, and climate response have highlighted the urgent need for expanded field research to address critical conservation challenges within the fir forest ecosystem on Giona and Parnassus mountains. This underscores the urgency of adopting measures to mitigate the impacts of both abiotic and biotic factors. Our findings so far, encompassing biometric data, tree ring analysis, observations on plant communities, climatic response, and insect infestations—primarily Choristoneura murinana (European Bud Moth)—across various stands on the mountain, have revealed significant local infestations of varying degrees. In many instances, these infestations were detected in adult trees, particularly in sunny areas or near country roads. Furthermore, our research has revealed the varied ability of the fir trees to adapt to both minor and significant climatic variations. The proposed research aims to monitor, preserve, and protect the fir trees, utilizing new knowledge for informed decision-making in their management. The project’s scope includes studying the growth characteristics of the fir forest, mitigating threats from biological factors (primarily the moth Choristoneura murinana-Lepidoptera, Tortricidae) by involving pheromones and other biological methods, promoting natural regeneration, preserving biodiversity, and evaluating the water status of the fir trees in response to climate change. Investigating their interactions and understanding the ecosystem’s status concerning the previously mentioned aspects is a significant priority for biological and genetic diversity, landscape aesthetics, recreation, and sustainable regional development (with economic impacts on local beekeepers and guesthouse owners). The evaluation of the implementation of the National Biodiversity Strategy in Greece has shown partial or minimal progress in addressing new threats and challenges, as well as in promoting new approaches. The proposed project, with specific actions, aligns with the spirit of the National Biodiversity Strategy and contributes to the strategy goals within the framework of conservation, restoration, and the strengthening of nationwide enhancement actions. Full article

Harvesting is a serious issue in oil palm plantations after 15–20 years owing to the increased height of the trees (>9 m). The slow vertical growth of the oil palm dura genotypes is desired for increasing the D × P progenies’ productivity and economic life span upto ten years. A reduced height increment has a long-term impact on harvesting costs. The current study assessed 308 genotypes generated from African germplasm. Over a three year period, the biometric properties of eleven D × D crosses were evaluated in order to quantify genetic parameters and phenotypic correlations, and principal component analysis was performed for genetic attributes of the better-performing dwarf progenies in terms of yield. The evaluated genotypes have a highly significant influence (p < 0.01) on the majority of characteristics. The progenies yielded between 165 and 208 kg of fresh fruit bunches (FFBs) per palm every year. The height increment (HI) varied between 17% and 19%, with an overall average of 18%. Genotypes G8, G300, and G221 had the lowest yearly height increments, measuring 28.98, 29.19, and 30.87 cm, respectively. The outcome of the present study shows that they are slow-height-increment genotypes with a high FFB yield (>25 T/Ha). The creation of dura parents with a slow height increment in combination with a high bunch weight helps for prolonging the productive life of the palm to more than 35 years, adding value to obtain distinct oil palm varieties. Overall, this targeted breeding effort towards developing dwarf oil palm hybrids reflects a strategic approach to addressing specific challenges in oil palm cultivation, ultimately helping to promote the oil palm sector globally. Full article

A critical component of bus network adjustment is the accurate prediction of potential risks, such as the likelihood of complaints from passengers. Traditional simulation methods, however, face limitations in identifying passengers and understanding how their travel patterns may change. To address this issue, a pre-evaluation method has been developed, leveraging the spatial distribution of bus networks and the spatio-temporal behavior of passengers. The method includes stage of travel demand analysis, accessible path set calculation, passenger assignment, and evaluation of key indicators. First, we explore the actual passengers’ origin and destination (OD) stop from bus card (or passenger Code) payment data and biometric recognition data, with the OD as one of the main input parameters. Second, a digital bus network model is constructed to represent the logical and spatial relationships between routes and stops. Upon inputting bus line adjustment parameters, these relationships allow for the precise and automatic identification of the affected areas, as well as the calculation of accessible paths of each OD pair. Third, the factors influencing passengers’ path selection are analyzed, and a predictive model is built to estimate post-adjustment path choices. A genetic algorithm is employed to optimize the model’s weights. Finally, various metrics, such as changes in travel routes and ride times, are analyzed by integrating passenger profiles. The proposed method was tested on the case of the Guangzhou 543 route adjustment. Results show that the accuracy of the number of predicted trips after adjustment is 89.6%, and the predicted flow of each associated bus line is also consistent with the actual situation. The main reason for the error is that the path selection has a certain level of irrationality, which stems from the fact that the proportion of passengers who choose the minimum cost path for direct travel is about 65%, while the proportion of one-transfer passengers is only about 50%. Overall, the proposed algorithm can quantitatively analyze the impact of rigid travel groups, occasional travel groups, elderly groups, and other groups that are prone to making complaints in response to bus line adjustment. Full article