Development of a coupled model to simulate and assess arsenic contamination and impact factors in the Jinsha River Basin, China.

With the increasing severity of arsenic (As) pollution, quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies. Taking the industrial-intensive Jinsha River Basin as typical area, a two-dimensional hydrodynamic water quality model coupled with Soil and Water Assessment Tool (SWAT) model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution. The effects of hydro-climate change, hydropower station construction and non-point source emissions on As were quantified based on the coupled model. The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream. Due to the enhanced rainfall, the As concentration was significantly higher during the rainy season than the dry season. Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration, but also affected the adsorption and desorption of As in sediment. Furthermore, As concentration increased with the input of non-point source pollution, with the maximum increase about 30%, resulting that non-point sources contributed important pollutant impacts to waterways. The coupled model used in pollutant behavior analysis is general with high potential application to predict and mitigate water pollution.

Deciphering environmental factors influencing phytoplankton community structure in a polluted urban river.

Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River-which is the longest river in China. As phytoplankton are sensitive indicators of trophic changes in water bodies, characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution control. Here, we used direct microscopic count and environmental DNA (eDNA) metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin (Chengdu, Sichuan Province, China). The association between phytoplankton community structure and water environmental factors was evaluated by Mantel analysis. Additional environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation modeling. At the phylum level, the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta, Chlorophyta, and Cyanophyta, in contrast with Chlorophyta, Dinophyceae, and Bacillariophyta identified by eDNA metabarcoding. In α-diversity analysis, eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic method. Phytoplankton growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios > 16:1 in all water samples. Redundancy analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton growth. The results could be useful for implementing comprehensive management of the river basin environment. It is recommended to control the discharge of point- and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients (e.g., Jianyang-Ziyang). Algae monitoring techniques and removal strategies should be improved in 201 Hospital, Hongrihe Bridge and Colmar Town areas.

Tuning and modeling cheese flavor.

Flavor is a major sensory attribute affecting consumers' preference for cheese products. Differences in cheesemaking change the cheese microenvironment, thereby affecting cheese flavor profiles. A framework for tuning cheese flavor is proposed in this study, which depicts the full picture of flavor development and modulation, from manufacturing and ripening factors through the main biochemical pathways to flavor compounds and flavor notes. Taking semi-hard and hard cheeses as examples, this review describes how cheese flavor profiles are affected by milk type and applied treatment, fat and salt content, microbiota composition and microbial interactions, ripening time, temperature, and environmental humidity, together with packaging method and material. Moreover, these factors are linked to flavor profiles through their effects on proteolysis, the further catabolism of amino acids, and lipolysis. Acids, alcohols, ketones, esters, aldehydes, lactones, and sulfur compounds are key volatiles, which elicit fruity, sweet, rancid, green, creamy, pungent, alcoholic, nutty, fatty, and sweaty flavor notes, contributing to the overall flavor profiles. Additionally, this review demonstrates how data-driven modeling techniques can link these influencing factors to resulting flavor profiles. This is done by providing a comprehensive review on the (i) identification of key factors and flavor compounds, (ii) discrimination of cheeses, and (iii) prediction of flavor notes. Overall, this review provides knowledge tools for cheese flavor modulation and sheds light on using data-driven modeling techniques to aid cheese flavor analysis and flavor prediction.

Pulsed vacuum drying of fruits, vegetables, and herbs: Principles, applications and future trends.

Pulsed vacuum drying (PVD) is a novel vacuum drying method that has demonstrated significant potential in improving energy efficiency and product quality in the drying of foods and agricultural products. The current work provides a comprehensive analysis of the latest advancements in PVD technology, including its historical development, fundamental principles, and mechanistic aspects. The impact of periodic pulsed pressure changes between vacuum and atmospheric pressure on heat and moisture transfer, as well as structural changes in foods at micro- and macro-scales, is thoroughly discussed. The article also highlights the influential drying parameters, the integration of novel auxiliary heaters, and the applications of PVD across various fruits, vegetables, and herbs. Furthermore, the review examines the current status and needs for mathematical modeling of PVD processes, identifying key challenges, research opportunities, and future trends for industrial application. The findings suggest that PVD not only enhances drying efficiency and reduces energy consumption but also preserves the nutritional value, color, and texture of dried products better than traditional methods. Future research should focus on optimizing process parameters and integrating advanced control systems to further improve the scalability and applicability of PVD technology in the food industry.

Mechanism of PARP1 Elongation Reaction Revealed by Molecular Modeling.

Poly(ADP-ribose) polymerase 1 (PARP1) plays a major role in the DNA damage repair and transcriptional regulation, and is targeted by a number of clinical inhibitors. Despite this, catalytic mechanism of PARP1 remains largely underexplored because of the complex substrate/product structure. Using molecular modeling and metadynamics simulations we have described in detail elongation of poly(ADP-ribose) chain in the PARP1 active site. It was shown that elongation reaction proceeds via the SN1-like mechanism involving formation of the intermediate furanosyl oxocarbenium ion. Intriguingly, nucleophilic 2'A-OH group of the acceptor substrate can be activated by the general base Glu988 not directly but through the proton relay system including the adjacent 3'A-OH group.

"miffy eats the rainbow!" - a colorful modeling- and reward-based intervention to increase the willingness to taste fruit and vegetables in 3-7-year-old children.

Diets rich in fruit and vegetables (F&Vs) improve cognitive functioning and reduce the risk of non-communicable diseases in children. Nevertheless, 59% of Dutch children do not meet recommended intake levels. Given the importance of color in children's food choices, the concept of "eat the rainbow" presents a promising approach. This project aimed to evaluate the effects of a modeling- and reward-based intervention to stimulate the consumption of colorful foods to increase the willingness to taste different F&Vs among children aged 3-7 years. 164 children from Dutch elementary schools participated in a nested randomized block design study. During two morning school breaks, children were invited to choose from 10 F&Vs in five different colors. Their willingness to taste and ad libitum intake were recorded. The first session served as a baseline with no intervention, while the second session involved either the Miffy intervention (modeling- and reward-based), a reward-only intervention (reward-based), or a control session. In the Miffy intervention, children listened to a story about Miffy eating the rainbow before tasting F&Vs and they received colored stickers (e.g., red sticker for tomatoes, green sticker for celery) upon tasting them. In the reward-only intervention, children received a sticker upon tasting a food. The Miffy group showed a higher probability (P(tasted) = 0.39) of tasting a food product compared to the control group (P(tasted) = 0.29; OR = 0.63, p = .035). No significant differences were observed between the Miffy and reward-only groups or between the reward-only and control groups. Both interventions did not significantly impact intake or liking of the foods. The Miffy-themed intervention demonstrates potential to enhance children's willingness to taste F&Vs, primarily due to the use of non-food incentives.

Development and evaluation of predictive models for pregnancy risk in UK dairy cows.

One suggested approach to improve the reproductive performance of dairy herds is through the targeted management of subgroups of biologically similar animals, such as those with similar probabilities of becoming pregnant, termed pregnancy risk. We aimed to use readily available farm data to develop predictive models of pregnancy risk in dairy cows. Data from a convenience sample of 108 dairy herds in the UK were collated and each herd was randomly allocated, at a ratio of 80:20, to either training or testing data sets. Following data cleaning, there were a total of 78 herds in the training data set and 20 herds in the testing data set. Data were further split by parity into nulliparous, primiparous, and multiparous subsets. An XGBoost model was trained to predict the insemination outcome in each parity subset, with predictors from farm records of breeding, calving and milk recording. Training data comprised 74,511 inseminations in 45,909 nulliparous animals, 86,420 inseminations in 39,439 primiparous animals, and 158,294 inseminations in 32,520 multiparous animals. The final models were evaluated by predicting with the testing data, comprising 31,740 inseminations in 19,647 nulliparous animals, 38,588 inseminations in 16,215 primiparous animals, and 65,049 inseminations in 12,439 multiparous animals. Model discrimination was assessed by calculating the area under receiver operating characteristic curves (AUC); model calibration was assessed by plotting calibration curves and compared across test herds by calculating the expected calibration error (ECE) in each test herd. The models were unable to discriminate between insemination outcomes with high accuracy, with an AUC of 0.63, 0.59 and 0.62 in the nulliparous, primiparous and multiparous subsets, respectively. The models were generally well-calibrated, meaning the model-predicted pregnancy risks were similar to the observed pregnancy risks. The mean (SD) ECE in the test herds was 0.038 (0.023), 0.028 (0.012) and 0.020 (0.008) in the nulliparous, primiparous and multiparous subsets respectively. The predictive models reported here could theoretically be used to identify subgroups of animals with similar pregnancy risk to facilitate targeted reproductive management; or provide information about cows' relative pregnancy risk compared with the herd average, which may support on-farm decision-making. Further research is needed to evaluate the generalizability of these predictive models and understand the source of variation in ECE between herds; however, this study demonstrates that it is possible to accurately predict pregnancy risk in dairy cows using readily available farm data.

Discerning the dynamics of urbanization-climate change-flood risk nexus in densely populated urban mega cities: An appraisal of efficient flood management through spatiotemporal and geostatistical rainfall analysis and hydrodynamic modeling.

While the contribution of climate change towards intensifying urban flood risks is well acknowledged, the role of urbanization is less known. The present study, for the first time in flood management literature, explores whether and how unplanned-cum-urbanization may overshadow the contribution of extreme rainfall to flood impacts in densely populated urban regions. To establish this hypothesis and exemplify our proposed framework, the National Capital Territory (NCT) of Delhi in India, infamous for its concurrent flood episodes is selected. The study categorically explores whether the catastrophic 2023 urban flood could have resulted in a similar degree of urban exposure and damage, had it occurred anytime in the past. A comprehensive spatiotemporal and geo-statistical analysis of rainfall over 11 stations brought about through Innovative trend analysis, Omnidirectional and directional Semi-variogram analysis, and Gini Index indicates a rise in extreme rainfalls. High-resolution land-use maps indicate about 39.53 %, 52.66 %, 56.60 %, and 69.18 % of urban footprints during 1993, 2003, 2013, and 2023, while gradient direction maps indicate a prominent urban surge towards the North-West, West, and Southwest corridors. A closer inspection of the Greenness and Urbanity indices reveals a gradual decline in the green footprints and concurrent escalation in the urban footprints over the decades. A 3-way coupled MIKE+ model was set up to replicate the July 2023 flood event; indicating about 13 % of the area experience "high" and "very-high" flood hazards. By overlaying the flood inundation and hazard maps over land-use maps for 1993, 2003, and 2013, we further establish that a similar flood event would have resulted in lesser damage and building exposure. The study offers a set of flood management options for refurbishing resilience and limiting flood risks. The study delivers critical insights into the existing urban flood management strategies while delving into the urban growth-climate change-flood risk nexus.

From sequence to function: Exploring biophysical properties of bacteriophage BFK20 lytic transglycosylase domain from the minor tail protein gp15.

Bacteriophages have evolved different mechanisms of infection and penetration of bacterial cell walls. In Siphoviridae-like viruses, the inner tail proteins have a pivotal role in these processes and often encode lytic protein domains which increase infection efficiency. A soluble lytic transglycosylase (SLT) domain was identified in the minor tail protein gp15 from the BFK20 bacteriophage. Six fragments containing this SLT domain with adjacent regions of different lengths were cloned, expressed and purified. The biophysical properties of the two best expressing fragments were characterized by nanoDSF and CD spectroscopy, which showed that both fragments had a high refolding ability of 90 %. 3D modeling indicated that the bacteriophage BFK20 SLT domain is structurally similar to lysozyme. The degradation activity of these SLT proteins was evaluated using a lysozyme activity assay. BFK20 might use its transglycosylase activity to allow efficient phage DNA entry into the host cell by degrading bacterial peptidoglycan.

Understanding antibody magnitude and durability following vaccination against SARS-CoV-2.

Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in transient antibody response against the spike protein. The individual immune status at the time of vaccination influences the response. Using mathematical models of antibody decay, we determined the dynamics of serum immunoglobulin G (IgG) and serum immunoglobulin A (IgA) over time. Data fitting to longitudinal IgG and IgA titers was used to quantify differences in antibody magnitude and antibody duration among infection-naïve and infection-positive vaccinees. We found that prior infections result in more durable serum IgG and serum IgA responses, with prior symptomatic infections resulting in the most durable serum IgG response and prior asymptomatic infections resulting in the most durable serum IgA response. These findings can guide vaccine boosting schedules.

Role of rheology in formulation and process design of hot melt extruded amorphous solid dispersions.

Hot melt extrusion (HME) has been widely used as a continuous and highly flexible pharmaceutical manufacturing process for the production of a variety of dosage forms. In particular, HME enables preparation of amorphous solid dispersions (ASDs) which can improve bioavailability of poorly water-soluble drugs. The rheological properties of drug-polymer mixtures can significantly influence the processability of drug formulations via HME and eventually the end-use product properties such as physical stability and drug release. The objective of this review is to provide an overview of various rheological techniques and properties that can be used to evaluate the flow behavior and processability of the drug-polymer mixtures as well as formulation characteristics such as drug-polymer interactions, miscibility/solubility, and plasticization to improve the HME processability. An overview of the thermodynamics and kinetics of ASD processing by HME is also provided, as well as aspects of scale-up and process modeling, highlighting rheological properties on formulation design and process development. Overall, this review provides valuable insights into critical rheological properties which can be used as a predictive tool to optimize the HME processing conditions.

Experimental and Computational Insights of Albizia amara Phytoconstituents Targeting Anthranilate Phosphoribosyltransferase from Malassezia Globosa.

The fungus Malassezia globosa is often responsible for superficial mycoses posing significant treatment challenges because of the unfavourable side effects of available antifungal drugs. To reduce potential hazards to the host and overcome these hurdles, new therapeutic medicines must be developed that selectively target enzymes unique to the pathogen. This study focuses on the enzyme anthranilate phosphoribosyltransferase (AnPRT), which is vital to M. globosa's tryptophan production pathway. To learn more about the function of the AnPRT enzyme, we modeled, validated, and simulated its structure. Moreover, many bioactive components were found in different extracts from the plant Albizia amara after phytochemical screening. Interestingly, at doses ranging from 500 to 2000 µg/ml, the chloroform extract showed significant antifungal activity, with inhibition zones measured between 11.0 ± 0.0 and 25.6 ± 0.6 mm. According to molecular docking analyses, the compounds from the active extract, particularly 2-tert-Butyl-4-isopropyl-5-methylphenol, interacted with the AnPRT enzyme's critical residues, ARG 205 and PHE 214, with an effective binding energy of -4.9 kcal/mol. The extract's revealed component satisfies the requirements for drug-likeness and shows promise as a strong antifungal agent against infections caused by M. globosa. These findings imply that using plant-derived chemicals to target the AnPRT enzyme is a viable path for the creation of innovative antifungal treatments.

Investigation of Factors Affecting Extraction of Calophyllum inophyllum Seed Oil via Response Surface Methodology.

This study used the Soxhlet apparatus to investigate honne oil (HO) extraction optimization. Twenty-four (24) experiments were formulated using the D-optimal design considering extraction time (2 - 6 h), honne weight (20 - 60 g), and particle size using acetone. The yield, functional groups, physical and chemical properties, and fatty acid composition of the HO were assessed. The optimal extraction conditions established were a time of 6 h, fine particle size, and honne weight of 20 g with a high HO yield of 70.85 wt.%. The HO had an acid value and kinematic viscosity of 35.68 mg KOH/g oil and 52.96 mm 2 /s, respectively. The observed coefficient of determination of 0.9870 suggests that the model developed for the process is efficient. The functional groups and fatty acids of the HO confirm that it is highly unsaturated with the regions of trans-unsaturation bending vibrations and double bond stretching. The properties of the HO demonstrate that it could be used to produce biodiesel, notwithstanding the necessity for pretreatment.

Three-Dimensional Finite Element Modeling of the Singer's Formant Cluster Optimization by Epilaryngeal Narrowing With and Without Velopharyngeal Opening.

This study aimed to find the optimal geometrical configuration of the vocal tract (VT) to increase the total acoustic energy output of human voice in the frequency interval 2-3.5 kHz "singer's formant cluster," (SFC) for vowels [a:] and [i:] considering epilaryngeal changes and the velopharyngeal opening (VPO). The study applied 3D volume models of the vocal and nasal tract based on computer tomography images of a female speaker. The epilaryngeal narrowing (EN) increased the total sound pressure level (SPL) and SPL of the SFC by diminishing the frequency difference between acoustic resonances F3 and F4 for [a:] and between F2 and F3 for [i:]. The effect reached its maximum at the low pharynx/epilarynx cross-sectional area ratio 11.4:1 for [a:] and 25:1 for [i:]. The acoustic results obtained with the model optimization are in good agreement with the results of an internationally recognized operatic alto singer. With the EN and the VPO, the VT input reactance was positive over the entire fo singing range (ca 75-1500 Hz). The VPO increased the strength of the SFC and diminished the SPL of F1 for both vowels, but with EN, the SPL decrease was compensated. The effect of EN is not linear and depends on the vowel. Both the EN and the VPO alone and together can support (singing) voice production.

Unraveling the ecological niche signals of Verticillium dahliae: Insights from Mediterranean landscapes.

Verticillium wilt (VW), caused by the soil-borne plant pathogenic fungus Verticillium dahliae, is a major disease impacting olive crops globally. In view of the lack of effective post-infection treatments, exclusion and avoidance strategies are essential in disease management. Assessing the risks posed by this pathogen is essential to prevent the spread and to ensure selection of suitable sites for new plantations. This study aimed to elucidate the environmental factors driving V. dahliae establishment in the Andalusia region, in southern Spain, an emblematic Mediterranean landscape for olive cultivation. To this end, we explored ecological niche signals for this fungal pathogen by analyzing 62 environmental variables across 1.6 million hectares dedicated to olive and cotton cultivation, using a 15-yr survey data on VW incidence on presence-absence from both olive and cotton fields. To ensure robust identification of ecological niche signals, we employed randomization-based, non-parametric univariate tests to compare presence records with the broader sampling universe (including absence records). Our findings identified key environmental variables that are associated significantly with V. dahliae presence, including temperature range seasonality (including mean diurnal and annual ranges), summer temperature (maximum of the warmest month, mean of the warmest quarter), and moisture and water availability (near-surface humidity, potential evapotranspiration, vapor pressure) as core niche variables for V. dahliae. Our results replicated the pathogen's known distribution, identifying the Guadalquivir Valley as a particularly high-risk area in view of its mild winters and distinct rainy seasons, providing new insights into the specific environmental conditions that facilitate the pathogen's survival and spread. Furthermore, this study introduces a novel approach to niche modeling that prioritizes variables with consistent effects and significant impact on the presence and distribution of V. dahliae and identifies potential data artifacts. This approach enhances our understanding of ecological requirements in V. dahliae and informs targeted management strategies.

Capturing Successful Aging in Daily Life: Exploring the Intensive Longitudinal Findings from a US National Sample.

BACKGROUND AND OBJECTIVES: Thus far, successful aging has been conceptualized and operationalized as a relatively static construct. Investigating daily successful aging provides a dynamic approach highlighting how successful aging can be achieved through everyday actions, giving older adults a stronger sense of control over their lives. RESEARCH DESIGN AND METHODS: We used 8-day diary data from MIDUS 2's US national sample of older adults (N=716, Mage[SD]=68.80[6.45]). Participants reported daily physical symptoms, functioning, and engagement in life (collectively, successful aging indicators), alongside daily stressors and positive events. We also correlated personal mean and standard deviation of the indicators with one-time measures of health and well-being. RESULTS: Intra-class correlation revealed substantial within-person variability in successful aging indicators. These indicators were associated with daily stressors and positive events. One-time health and well-being indicators were positively associated with personal mean levels of successful aging, although their correlations with personal standard deviations were less consistent. DISCUSSION AND IMPLICATIONS: Intra-individual variations in successful aging as everyday symptoms, functioning, and engagement with life are observable among a national sample of older adults, challenging the static view of successful aging and, instead, emphasizing the need to understand "micro-level" contributors of successful aging.

International Workers' Day: Consumption Patterns of Morphine, Codeine, and Methamphetamine in Urban and Rural Areas Based on Wastewater-Based Epidemiology.

Wastewater-based epidemiology (WBE) is a reliable means to estimate drug consumption in a specific population. By measuring the concentration of drug residues or metabolites in wastewater, the consumption behavior pattern of a specific population can be deduced. Using the WBE method, the present study, for the first time, continuously monitored the differences in the consumption of morphine (MOR), codeine (CODE), and methamphetamine (METH) in three wastewater-treatment plants in a city and two surrounding villages in Xinjiang, China during International Workers' Day and the following week. The wastewater samples were pretreated by solid-phase extraction and then analyzed by high-performance liquid chromatography-tandem mass spectrometry. Methamphetamine was not detected in rural areas and was detected only on International Workers' Day in urban areas. According to the estimation of per capita consumption, the per capita consumption of MOR, CODE, and METH in urban inhabitants was 12.04 to 23.39, 10.44 to 16.39, and 1.31 mg/day/1000 inhabitants. The per capita consumption of MOR and CODE in rural areas was 5.19 to 8.35 and 2.56 to 3.52 mg/day/1000 inhabitants. The consumption of MOR in urban and rural areas was significantly higher than that of CODE and METH. During International Workers' Day, workdays, and weekends, the consumption of MOR and CODE in urban areas is significantly higher than that in rural areas. Compared with those on weekends, the consumption of urban MOR and CODE increased more during International Workers' Day. The consumption of MOR in urban areas showed a weekend effect. The present study can provide information for subsequent research and government departments. Environ Toxicol Chem 2024;00:1-9. © 2024 SETAC.

Environmental Risk Assessment of Time-Variable Toxicant Exposure with Toxicokinetic-Toxicodynamic Modeling of Sublethal Endpoints and Moving Time Windows: A Case Study with Ceriodaphnia dubia.

Toxicokinetic-toxicodynamic (TKTD) modeling has received increasing attention in terms of the regulatory environmental risk assessment of chemicals. This type of mechanistic model can integrate all available data from individual-level bioassays into a single framework and enable refined risk assessments by extrapolating from laboratory results to time-variable exposure scenarios, based, for instance, on surface water exposure modeling (e.g., FOCUS). Dynamic energy budget (DEB) models coupled with TKTD modules (DEB-TKTD) constitute the leading approach to assess and predict sublethal effects of chemicals on individual organisms. However, thorough case studies are rare. We provide a state-of-the-art example with the standard aquatic test species Ceriodaphnia dubia and the fungicide azoxystrobin, including all steps, from bespoke laboratory toxicity tests to model calibration and validation, through to environmental risk assessment. Following the framework proposed in the European Food Safety Authority Scientific Opinion from 2018, we designed bespoke good laboratory practice-compliant laboratory toxicity studies based on test guideline 211 of the Organisation for Economic Co-operation and Development and then identified robust parameter values from those data for all relevant model parameters through model calibration. The DEB-TKTD model, DEBtox2019, then informed the design of the validation experiment. Once validated, the model was used to perform predictions for a time-variable exposure scenario generated by FOCUS. A moving time-window approach was used to perform the environmental risk assessment. This assessment method reduces uncertainty in the risk assessment while maintaining consistency with the traditional measures of risk. Environ Toxicol Chem 2024;00:1-13. © 2024 Syngenta Crop Protection AG. ibacon GmbH and The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Future climate suitability of Hemileia vastatrix in arabica coffee under CMIP6 scenarios.

BACKGROUND: Coffee (Coffea arabica L.) is one of the most important commodities today, with a high economic value worldwide. Coffee leaf rust (Hemileia vastatrix Berk. et Br.) has been showing a high impact on Brazilian coffee trees among the various diseases that attack coffee. The climate has a great influence on the development of diseases, especially when fungi are the causal agents. This study aimed to carry out the zoning of climate favorability for coffee leaf rust in the traditional and main coffee-producing regions of Brazil. The study was conducted in 13 locations in the states of Paraná, São Paulo, Rio de Janeiro, Espírito Santo, Minas Gerais, Goiás and Bahia. Air temperature and daily precipitation data for the current scenario were collected using the WorldClim version 2.1 platform for the last climatological normal and future climate change data. The ideal climate conditions for coffee leaf rust consist of a mean air temperature ranging from 21 to 25 °C and precipitation >30 mm per month. The Coupled Model Intercomparison Projects scenarios associated with the Intergovernmental Panel on Climate Change reports consisted of the Shared Socio-Economic Pathways SSP-1 2.6, SSP-2 4.5, SSP-3 7.0 and SSP-5 8.5, the latter being considered one of the most catastrophic. All steps to carry out the suitability zoning were performed in a tool using the QGIS geographic information system software. RESULTS: Zoning for coffee leaf rust had three classes: favorable, relatively favorable and unfavorable. Currently, the largest coffee-producing region in Brazil has 49.1% of its analyzed area classified as favorable, 39.2% as relatively favorable and 11.7% as unfavorable. In the current scenario, Patrocínio and Três Pontas are locations with high coffee production in which the favorable class is predominant. The state of Minas Gerais has an annual mean of 55.3% of its entire territory apt for the disease, with the highest occurrence between September and March. CONCLUSIONS: Climate change has a negative impact on the development of coffee leaf rust, mainly in the long term, as in the period of 2081-2100, in which the SSP-5 8.5 scenario led to a decrease in the favorable and unfavorable areas and an increase in the relatively favorable areas of 9.8%, 18.6% and 71.5% for the Brazilian territory, respectively. © 2024 Society of Chemical Industry.

Evolution of psychological distress with age and its determinants in later life: evidence from 17-wave social survey data in Japan.

BACKGROUND: Psychological distress (PD) is a major risk factor for mental health among middle-aged and older adults and affects their quality of life and well-being. This study aimed to examine the evolution of PD with age and the relative importance of its determinants, issues that have been insufficiently studied. METHODS: We used longitudinal data obtained from 17-wave social surveys conducted in Japan from 2005 to 2021, to track 34,128 individuals (16,555 men and 17,573 women) born between 1946 and 1955. We defined PD as a Kessler 6 score (range: 0-24) ≥ 5 and estimated fixed-effects regression models to examine the evolution of its proportion with age. We also conducted a mediation analysis to examine the relative importance of specific mediators such as self-rated health (SRH), activities of daily living (ADL), and social participation, in the association between age and PD. RESULTS: Regression model results confirmed an increase in PD with age. Poor SRH, issues with ADL, and no social participation were key mediators of aging on PD, accounting for 34.2% (95% confidence interval [CI]: 21.0-47.3%), 13.7% (95% CI: 8.2-19.3%), and 10.5% (95% CI: 8.0-13.0%), respectively; consequently increasing PD between 50 and 75 years. CONCLUSION: The results suggest the need for policy support to encourage middle-aged and older adults to promote health and increase social participation in order to prevent depression while aging.