Reevaluating Biota Alteration: Reframing Environmental Influences on Chronic Immune Disorders and Exploring Novel Therapeutic Opportunities.

Environmental mismatches are defined as changes in the environment that induce public health crises. Well known mismatches leading to chronic disease include the availability of technologies that facilitate unhealthy diets and sedentary lifestyles, both factors that adversely affect cardiovascular health. This commentary puts these mismatches in context with biota alteration, an environmental mismatch involving hygiene-related technologies necessary for avoidance of infectious disease. Implementation of hygiene-related technologies causes a loss of symbiotic helminths and protists, profoundly affecting immune function and facilitating a variety of chronic conditions, including allergic disorders, autoimmune diseases, and several inflammation-associated neuropsychiatric conditions. Unfortunately, despite an established understanding of the biology underpinning this and other environmental mismatches, public health agencies have failed to stem the resulting tide of increased chronic disease burden. Both biomedical research and clinical practice continue to focus on an ineffective and reactive pharmaceutical-based paradigm. It is argued that the healthcare of the future could take into account the biology of today, effectively and proactively dealing with environmental mismatch and the resulting chronic disease burden.

The effect of environmental variations on the production of the principal agricultural products in Colombia.

The agricultural sector of Colombia supports the national economy and food security due to the rich lands for cultivation. Although Colombia has a vast hydrological basin, climate change can impact agricultural productivity, generating economic and social adverse effects. For this, we evaluated the impact of some environmental variables on the production of the most sold crops using production, climatic, and hydrological data of the 1121 municipalities from 2007 to 2020. We modeled the production of coffee, rice, palm oil, sugarcane, and corn, adopting a Bayesian spatio-temporal model that involved a set of environmental variables: average temperature, minimum temperature, maximum temperature, evapotranspiration, precipitation, runoff, soil moisture, vapor pressure, radiation, and wind speed. We found that increases in the average temperatures can affect coffee (-0.2% per °C), rice (-3.76% per °C), and sugarcane (-0.19% per °C) production, meanwhile, these increases can boost palm oil (+2.55% per °C) and corn (+1.28% per °C) production in Colombia. This statement implies that the agricultural sector needs to substitute land use, promoting the production of palm oil and corn. Although our results did not find a significant effect of hydrological variables in any crop, suggesting that the abundance of water in Colombia might balance the impact of these variables. The increases in vapor pressure impact all the crops negatively (between -11.2% to -0.43% per kPa), except rice, evidencing that dry air conditions affect agricultural production. Colombia must manage the production location of the traditional products and implement agro-industrial technologies to avoid the climate change impact on crops.

Life cycle assessment for the land application of food processing wash-water and solid residuals.

A life cycle assessment (LCA) study was completed to understand the environmental impacts associated with the land application of wastes produced from rural food-processing operations for final disposal. The system boundaries for the two comprised scenarios included the storage of the produced non-agriculture source material (NASM), transportation to an applicable location, land application of the NASM, and the impacts of the final emissions to the soil and groundwater for a full year. The Tool for the Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI) v2.1 was selected as the impact assessment method. Furthermore, SimaPro 8.0.4.26 was the LCA model version that was used with all the databases included. Overall, the LCA study showed that the most significant environmental impacts associated with the disposal process resulted from carcinogenic and eutrophication emissions. The component that contributed the most to carcinogenic impacts was found to be from the material required to create the concrete storage tank. Additionally, eutrophication was identified to be a potential significant impact, if proper setback requirements are not followed for the NASM material. Results of the study look to inform stakeholders about the benefits and risks encountered from NASM disposal. PRACTITIONER POINTS: Life cycle assessment was completed on a representative NASM disposal system using land application. Concrete tank used for storage of NASM had the most significant impact in carcinogenic emissions. Eutrophication impacts were the second most significant impact behind carcinogenic emissions.

Investigation on the environmental causes of tomato fruit cracking and its propagation prediction in greenhouse.

In this study, Provence tomato variety was chosen for investigating the environmental causes of tomato fruit cracking, cracks characteristics, and their propagation prediction in a greenhouse. Fruit bagging approach was used to alter the temperature and humidity and to create a microclimate around the fruit to induce fruit cracking for testing. Results showed that the fruit cracking rate increased when the environment temperature exceeded 30°C, and the difference between the highest and lowest temperature values in a day was greater than 20°C. The cracking rate was aggravated when the difference between the highest and lowest humidity values in a day was less than 20%. The proportions of top cracking, longitudinal cracking, ring cracking, radial cracking, and combined cracking were 5.4%, 16.1%, 28.3%, 26.8%, and 32.1%, respectively. The fruit shoulder was the most susceptible region to crack, followed by fruit belly and top regions, whereas longer cracks were observed in the fruit belly region indicating a higher propensity to crack propagation in that region. Finally, the measured data were used to validate an extended finite element method developed to effectively predict cracking susceptibility and propagation in tomato fruit with a relative error of 4.68%.

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering an infant's foot to a colorful mobile). Vicon motion capture data from multiple infant joints were used here to create Histograms of Joint Displacements (HJDs) to generate pose-based descriptors for 3D infant spatial trajectories. Using HJDs as inputs, machine and deep learning systems were tasked with classifying the experimental state from which snippets of movement data were sampled. The architectures tested included k-Nearest Neighbour (kNN), Linear Discriminant Analysis (LDA), Fully connected network (FCNet), 1D-Convolutional Neural Network (1D-Conv), 1D-Capsule Network (1D-CapsNet), 2D-Conv and 2D-CapsNet. Sliding window scenarios were used for temporal analysis to search for topological changes in infant movement related to functional context. kNN and LDA achieved higher classification accuracy with single joint features, while deep learning approaches, particularly 2D-CapsNet, achieved higher accuracy on full-body features. For each AI architecture tested, measures of foot activity displayed the most distinct and coherent pattern alterations across different experimental stages (reflected in the highest classification accuracy rate), indicating that interaction with the world impacts the infant behaviour most at the site of organism~world connection.

Genotype by environment interaction and stability analysis for harvest date in sugar beet cultivars.

This research assessed the quantitative and qualitative reactions of commercially grown sugar beets to four different harvest dates and their yield stability. The study followed a split-plot design within a randomized complete block design over 3 years. The main plot involved 10 sugar beet cultivars, while the subplot involved four harvest dates: August 13 (HD1), September 7 (HD2), October 3 (HD3), and November 12 (HD4). The study found that environmental conditions, genotypes, and harvest dates significantly affected various traits of sugar beet. Yearly environmental variations and their interactions with genotypes and harvest dates had substantial impacts on all measured traits at the 1% probability level. Additive main effect and multiplicative interaction analysis based on white sugar yield indicated that genotype and environment's additive effects, as well as the genotype-environment interaction, were significant at 1% probability level. Shokoufa and Arya, which exhibit high white sugar yield (WSY) and low first interaction principal component (IPC1) values, are identified as desirable due to their stability across different environments. Among the harvest dates in different years, the fourth and third dates showed a higher yield than the total average. Perfekta and Ekbatan exhibited high specific adaptability. According to the multi-trait stability index, Arta, Arya and Sina were recognized as stable and superior across all measured traits.

The economic and environmental effects of China's environmental expenditure under financing constraints.

Sound ecological and environmental governance systems are critical for promoting green and low-carbon economic transformation and high-quality development. However, financing constraints are major obstacle to the revitalization and transformation of China's real economy. In this study, we constructed an environmental dynamic stochastic general equilibrium (E-DSGE) model that incorporates two types of environmental expenditure and financing constraints, and discussed their economic and environmental effects. Based on this, we further considered the impacts of financing constraints on policy effects. Firstly, we found that increases in carbon emission reduction subsidies in government expenditure (1) increase total economic output and (2) motivate enterprises to increase emission reduction efforts and reduce pollution intensity and emissions, thereby reducing the inventory of environmental pollutants while balancing economic benefits and emission reduction. Secondly, increasing the proportion of government special expenditure on environmental protection promote output growth and directly reduces the pollution stock in the environment. However, such policies may also reduce the emission reduction efforts of enterprises, leading to increases in their pollution emissions and intensity. Lastly, the existence of financing constraints is not conducive to the growth of total output but increases the pollution control effect of emission reduction subsidies and pollution prevention expenditure. Application of the E-DSGE model offers new theoretical insight into environmental economics and macroeconomics. Moreover, the results of this study provide a reference for optimizing the structure of fiscal expenditure.

Assessing the environmental impacts of clean energy investment in Pakistan using a dynamic autoregressive distributed lag model.

In this study, the authors projected the impacts of clean energy investment on environmental degradation by applying a novel and dynamic Autoregressive Distributed Lag (DARDL) model for Pakistan from 1990 to 2022. Most researchers have used ecological footprint or CO2 emissions indicators to look at how clean energy investment affects environmental degradation, which primarily represents contamination induced by humans' consumption patterns and does not consider the impact of the supply side. Against this background, the study scrutinized the dynamic interaction between clean energy investment and environmental sustainability using the load capacity factor (LCF) as an ecological indicator in Pakistan, including economic growth, population density, trade openness, urbanization, and industrialization in the analysis. The long-run estimates from DARDL indicate that a 1 percent upsurge in clean energy investment mitigates environmental degradation by approximately 0.42 percent on average, controlling for other factors. Further, the study also revealed that a 1 percent increase in clean energy investment diminishes dirty energy consumption by approximately 0.45 percent. The validity of the findings is confirmed using alternate methods, i.e., KRLS. The study recommends that Pakistan prioritize investment in clean energy projects to promote environmental sustainability and enforce environmental regulations to reduce the adverse externalities associated with dirty energy activities.

Environmental deterioration, renewable energy, natural resource rents, and schooling in Türkiye: Does the degree of energy transition matter for environmental quality?

Within the literature on energy and environmental economics, it is generally acknowledged that renewable energy can improve environmental quality; however, certain papers suggest that an optimal level of the usage of renewable energy sources may exist. Consequently, the utilization of renewable energy sources can result in environmental degradation up to a certain threshold. Then, environmental quality can be enhanced through the continued application of renewables. This indicates that the link between renewable energy and environmental devastation is inverted U-shaped. This paper presents empirical evidence concerning this possible association between renewable energy and environmental destruction in Türkiye, a country where fossil energy predominates in the energy mix. Additionally, the paper investigates the environmental influences of natural resource rents and schooling. This study utilizes annual data from 1971 to 2020 and implements time series methodologies that rely on the Fourier approximation. The paper thus accounts for an undetermined quantity of structural breaks. The results suggest that an inverted U-shaped link occurs between renewable energy and environmental destruction, signifying renewable energy initially contributes to a diminution in environmental quality before subsequently improving it. Additionally, environmental quality is positively associated with natural resource rents and negatively associated with schooling, according to the findings. Furthermore, the findings reveal that schooling worsens the combined effect of renewable energy on environmental degradation. These conclusions are discussed in the paper.

Timing is everything: How plants optimize reproduction in a variable environment.

Organisms experience a constantly changing environment and must adjust their development to maximize fitness. These "life histories" are fantastically diverse and have fascinated biologists for decades. Recent work published in Cell reveals the complex genetic mechanisms that drive life-history variation within and among species in the Brassicaceae plant family.

The role of environmental sensitivity in the experience and processing of emotions: implications for well-being.

Several theories suggest that people differ significantly in their environmental sensitivity, defined as the capacity to perceive and process information about the environment. More sensitive people, who make up between 25% and 30% of the population, are not only more negatively affected by adverse experiences but also benefit disproportionately from positive ones, in line with differential susceptibility theory. Heightened emotional reactivity has been identified as one of the key markers of sensitivity. However, the current understanding of the relationship between sensitivity and the experience and processing of emotions remains limited. In the current paper we propose a new conceptual framework for the multiple ways in which environmental sensitivity may impact on different aspects of the experience and processing of emotions. This includes heightened perception of emotions, increased emotional reactivity, as well as the important role of emotion regulation for the well-being of highly sensitive people. In addition, we also consider rearing experiences in shaping sensitivity and emotion regulation. The reviewed empirical studies largely support the conceptual model but more research is needed to explore the dynamics between sensitivity and emotions further. Finally, we discuss several implications for well-being before making a case for the inclusion of individual differences in environmental sensitivity in affective science. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'.

A multiomic atlas of the aging hippocampus reveals molecular changes in response to environmental enrichment.

Aging involves the deterioration of organismal function, leading to the emergence of multiple pathologies. Environmental stimuli, including lifestyle, can influence the trajectory of this process and may be used as tools in the pursuit of healthy aging. To evaluate the role of epigenetic mechanisms in this context, we have generated bulk tissue and single cell multi-omic maps of the male mouse dorsal hippocampus in young and old animals exposed to environmental stimulation in the form of enriched environments. We present a molecular atlas of the aging process, highlighting two distinct axes, related to inflammation and to the dysregulation of mRNA metabolism, at the functional RNA and protein level. Additionally, we report the alteration of heterochromatin domains, including the loss of bivalent chromatin and the uncovering of a heterochromatin-switch phenomenon whereby constitutive heterochromatin loss is partially mitigated through gains in facultative heterochromatin. Notably, we observed the multi-omic reversal of a great number of aging-associated alterations in the context of environmental enrichment, which was particularly linked to glial and oligodendrocyte pathways. In conclusion, our work describes the epigenomic landscape of environmental stimulation in the context of aging and reveals how lifestyle intervention can lead to the multi-layered reversal of aging-associated decline.

Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials.

KEY MESSAGE: Incorporating feature-engineered environmental data into machine learning-based genomic prediction models is an efficient approach to indirectly model genotype-by-environment interactions. Complementing phenotypic traits and molecular markers with high-dimensional data such as climate and soil information is becoming a common practice in breeding programs. This study explored new ways to combine non-genetic information in genomic prediction models using machine learning. Using the multi-environment trial data from the Genomes To Fields initiative, different models to predict maize grain yield were adjusted using various inputs: genetic, environmental, or a combination of both, either in an additive (genetic-and-environmental; G+E) or a multiplicative (genotype-by-environment interaction; GEI) manner. When including environmental data, the mean prediction accuracy of machine learning genomic prediction models increased up to 7% over the well-established Factor Analytic Multiplicative Mixed Model among the three cross-validation scenarios evaluated. Moreover, using the G+E model was more advantageous than the GEI model given the superior, or at least comparable, prediction accuracy, the lower usage of computational memory and time, and the flexibility of accounting for interactions by construction. Our results illustrate the flexibility provided by the ML framework, particularly with feature engineering. We show that the feature engineering stage offers a viable option for envirotyping and generates valuable information for machine learning-based genomic prediction models. Furthermore, we verified that the genotype-by-environment interactions may be considered using tree-based approaches without explicitly including interactions in the model. These findings support the growing interest in merging high-dimensional genotypic and environmental data into predictive modeling.

Evaluation of the environmental factors influencing the quality of Astragalus membranaceus var. mongholicus based on HPLC and the Maxent model.

BACKGROUND: In recent years, global climate change in tandem with increased human activity has resulted in habitat degradation or the migration of rare medicinal plants, potentially impacting the quality of medicinal herbs. Astragalus membranaceus var. mongholicus is a valuable bulk medicinal material in Northwest China. As the demand for this medicinal herb continues to increase in both domestic and international markets, ensuring the sustainable development of high-quality Astragali Radix is important. In this study, the maximum entropy (Maxent) model was applied, thereby incorporating 136 distribution records, along with 39 environmental factors of A. membranaceus var. mongholicus, to assess the quality zonation and potential distribution of this species in China under climate change. RESULTS: The results showed that the elevation, annual mean temperature, precipitation of wettest month, solar radiation in June, and mean temperature of warmest quarter were the critical environmental factors influencing the accumulation of astragaloside IV and Astragalus polysaccharide in A. membranaceus var. mongholicus. Among the twelve main environmental variables, annual mean temperature, elevation, precipitation of the wettest month, and solar radiation in November were the four most important factors influencing the distribution of A. membranaceus var. mongholicus. In addition, ecological niche modelling revealed that highly suitable habitats were mainly located in central and western Gansu, eastern Qinghai, northern Shaanxi, southern Ningxia, central Inner Mongolia, central Shanxi, and northern Hebei. However, the future projections under climate change suggested a contraction of these suitable areas, shifting towards northeastern high-latitude and high-elevation mountains. CONCLUSIONS: The findings provide essential insights for developing adaptive strategies for A. membranaceus var. mongholicus cultivation in response to climate change and can inform future research on this species. By considering the identified environmental factors and the potential impacts of the predicted climate changes, we can visualize the regional distribution of high-quality Radix Astragali and develop conservation strategies to protect and restore its suitable habitats.

Rapid body colouration changes in Oryzias celebensis as a social signal influenced by environmental background.

Rapid body colouration changes in some animals, such as chameleons and octopuses, serve dual functions: camouflage and intraspecific communication. It has been hypothesized that these colouration changes originally evolved to provide camouflage and subsequently were co-opted as social signals; however, experimental model systems that are suitable for studying such evolutionary processes are limited. Here, we investigated the relationship between rapid colouration changes of the blackened markings and aggressive behaviours in male Oryzias celebensis, an Indonesian medaka fish, under triadic relationships (two males and one female) or three males conditions with two different environmental backgrounds. In an algae-covered tank, mimicking the common laboratory rearing conditions, males with blackened markings exhibited more frequent attacks towards different conspecific individuals compared with non-blackened males and females. The blackened males were seldom attacked by non-blackened males and females. By contrast, neither aggressive behaviours nor black colouration changes were observed in the transparent background condition with a brighter environment. These indicated that the blackened markings in O. celebensis serve as a social signal depending on the environmental backgrounds. Considering that such colouration changes for camouflage are widely conserved among teleost fishes, the traits are likely to be co-opted for displaying social signals in O. celebensis.

Host Species and Environment Shape the Skin Microbiota of Mexican Axolotls.

Skin microbiomes in amphibians are complex systems that can be influenced by biotic and abiotic factors. In this study, we examined the effect of host species and environmental conditions on the skin bacterial and fungal microbiota of four obligate paedomorphic salamander species, commonly known as axolotls (Ambystoma andersoni, A. dumerilii, A. mexicanum, and A. taylori), all of them endemic to the Trans-Mexican Volcanic Belt. We found that despite their permanent aquatic lifestyle, these species present a host-specific skin microbiota that is distinct from aquatic communities. We identified skin-associated taxa that were unique to each host species and that differentiated axolotl species based on alpha and beta diversity metrics. Moreover, we identified a set of microbial taxa that were shared across hosts with high relative abundances across skin samples. Specifically, bacterial communities were dominated by Burkholderiales and Pseudomonadales bacterial orders and Capnodiales and Pleosporales fungal orders. Host species and environmental variables collectively explained more microbial composition variation in bacteria (R2 = 0.46) in comparison to fungi (R2 = 0.2). Our results contribute to a better understanding of the factors shaping the diversity and composition of skin microbial communities in Ambystoma. Additional studies are needed to disentangle the effects of specific host associated and environmental factors that could influence the skin microbiome of these endangered species.

Plant development and reproduction in a changing environment.

Plants face the most diverse climatic conditions throughout their life cycle. As sessile organisms, they are remarkably resilient to adverse environments, which have been exacerbated in the current context of global change. The way in which plants sense and respond to various types of abiotic stresses varies depending on the severity of the stress and the developmental stage of the plant, affecting both vegetative and reproductive aspects. Understanding how plants respond and adapt to a changing environment is crucial for predicting and mitigating the impacts of climate change on ecosystems and ensuring the future survival and reproduction of plant species.

Global leaf sulfur stoichiometry and the relationships with nitrogen and phosphorus: phylogeny, growth form and environmental controls.

Sulfur (S) is an essential bioelement with vital roles in serving regulatory and catalytic functions and tightly coupled with N and P in plants. However, globally stoichiometric patterns of leaf S and its relationships to leaf N and P are less well studied. We compiled 31 939 records of leaf-based data for 2600 plant species across 6652 sites worldwide. All plant species were divided into different phylogenetic taxa and growth forms. Standard major axis analysis was employed to fit the bivariate element relationships. A phylogenetic linear mixed-effect model and a multiple-regression model were used to partition the variations of bioelements into phylogeny and environments, and then to estimate the importance of environmental variables. Global geometric mean leaf S, N and P concentrations were 1.44, 15.70 and 1.27 mg g-1, respectively, with significant differences among plant groups. Leaf S-N-P positively correlated with each other, ignoring plant groups. The scaling exponents of LN-LS, LP-LS and LN-LP were 0.64, 0.76 and 0.79, respectively, for all species, but differed among plant groups. Both phylogeny and environments regulated the bioelements. The variability, rather than mean temperature, controlled the bioelements. Phylogeny explained more for the concentrations of all the three bioelements than environments, of which S was the one most affected by phylogenetic taxa.

The impact of farmers' participation in green cooperative production on green performance-A study based on the moderating effect of environmental regulation.

Based on 491 farmers joining in cooperatives microscopic data in Jiangxi Province,the paper uses Ordinary Least Squares to test the influence mechanism of cooperative green production on green performance, and takes environmental regulation as a regulatory variable to explore the relationship between cooperative green production and cooperative green performance. The results have shown that: (1) The green production cooperatives have a significant positive impact on their green performance, and the impact of green production on economic performance, social performance and ecological performance gradually strengthens from weak to strong; (2) Environmental regulations have a positive regulatory effect on the relationship between cooperative green production and cooperative green performance, among which three types of environmental regulations, namely, incentive, restraint and guided, can strengthen the positive relationship between green production and green performance.

Environmental Footprints in Food Services: A Scoping Review.

The collective meals market generates significant revenue for the world economy. Food services are responsible for consuming large amounts of water and energy, as well as generating a substantial volume of waste, which is often improperly disposed of. Given the unchecked expansion of food services, the lack of proper management of environmental resources can undermine sustainability principles, posing a threat to future generations. This scoping review aimed to synthesize the existing scientific literature on carbon and water footprints in food services, describing the main methods and tools used and what strategies have been proposed to mitigate the high values of these footprints. The search for articles was performed on 6 June 2024 in seven electronic databases, using MeSH Terms and adaptations for each database from database inception. The search for local studies was complemented by a manual search in the list of references of the studies selected to compose this review. It included quantitative studies assessing footprints (water or carbon) in food services and excluded reviews, studies that reported footprints for diets, and protocols. A total of 2642 studies were identified, and among these, 29 were selected for this review. According to the findings, it was observed that meats, especially beef, contribute more to water and carbon footprint compared to other proteins. Mitigation strategies for the water footprint include promoting plant-based diets, menu changes, and awareness.