Despite the widespread occurrence of mostly low concentrations of molecular hydrogen (H₂) in nature, the quantity of commercially recoverable natural hydrogen underground remains uncertain. Two production variants are conceptually considered: a self-replenishing system, in which underground generation balances off-take; and accumulation systems, in which H₂ is trapped underground over long periods and is extracted similarly to conventional natural gas deposits. To assess the potential of natural hydrogen, we compiled and harmonised global data on H₂ flow rates, flux rates, and concentrations from various sources like seeps, springs, mines, and wells. Across different geological settings, observed large natural H₂ flow rates typically fall between 10⁵ and 10⁷ cubic meters per year (m³/yr). When comparing these values to the output of producing natural gas wells and economic viability thresholds for modelled H₂ projects, we find that commercially viable rates must be at least an order of magnitude higher (≥ 10⁷-10⁸ m³/yr). Furthermore, sustained production at high hydrogen purity over two to three decades is generally required for commercial success. Based on this analysis, we argue that economically recoverable natural hydrogen from self-replenishing systems is unlikely.

Integrated pest management (IPM) aims to control crop pests while balancing environmental sustainability and farm profitability. Under IPM, pesticides are applied only when pest or disease pressure surpasses economic thresholds, even after the implementation of non-chemical control strategies, thus implying that reducing pesticide use below IPM standards entails economic losses. In response, some European Union member states have introduced compensation schemes for farms adopting pesticide reduction strategies, such as zero-fungicide approaches. However, it remains critical to determine under which conditions these financial incentives sufficiently offset economic losses and support fungicide reduction. Using commodity prices and fungicide application costs observed between 2018 and 2023, IPM-based fungicide use across 25 winter wheat trials generated an average net return of €67 ha-1 if disease monitoring was provided free of charge and €41 ha-1 if the farms had to bear the costs of disease monitoring themselves. The economic viability of compensation schemes depended on several key market factors: higher commodity prices, increased fungicide efficacy and low fungicide application costs enhanced the profitability of fungicide use, while low commodity prices and fungicide efficacy and high fungicide application costs made compensation schemes more attractive. The success of financial incentives for fungicide reduction is challenged by high commodity prices, highly effective fungicides and low-cost application services. Given the strong influence of commodity prices on fungicide profitability, reductions are most likely to occur in lower-value market segments (e.g. grain for animal feed production), where compensation schemes gain economic leverage more easily. © 2026 Society of Chemical Industry.

ABSTRACT Traditional air conditioners suffer from low energy efficiency and exacerbate grid peak loads. While ice storage offers energy‐saving potential, the systematic regulation of ice packing fraction (IPF) on cooling consumption and its synergy with dynamic carbon emissions remains unexplored. This study investigates the energy use, carbon footprint, and economics of ice slurry cooling across six Chinese climate zones, revealing for the first time the regulatory effect of IPF gradients. We demonstrate that pump power consumption decreases exponentially with increasing IPF, yielding 40%–60% reductions per 5% IPF increment. Critically, carbon reduction rates plateau (8.67%–8.92%) above 20% IPF, with peak reductions reaching 22% at 30% IPF. We propose a novel “IPF‐electricity price‐dynamic carbon emission factor” collaborative framework—incorporating a viscosity‐driven pump model and a dynamic COP optimization algorithm—providing a universal approach for low‐carbon cooling transitions. Economic analysis identifies 25% IPF as the key inflection point, beyond which further concentration increases yield minimal cost savings (only 0.08%). This integrated framework quantifies economic and emission thresholds, enabling optimal, sustainable cooling management.

Rice (Oryza sativa L.) production in the Philippines remains highly vulnerable to recurrent outbreaks of the Rice Black Bug (RBB; Scotinophara coarctata F.) and White Stemborer (WSB; Scirpophaga innotata W.), two of the most destructive pests in Southeast Asian rice ecosystems. Classical economic threshold levels (ETLs) are difficult to estimate in smallholder settings due to the lack of cost–loss data, often leading to either delayed or excessive pesticide application. To address this, the present study developed an adaptive outbreak-forecasting framework that integrates the Number–Size (N–S) fractal model with machine learning (ML) classifiers to define and predict pest regime transitions. Seven years (2018–2024) of light-trap surveillance data from the Philippine Rice Research Institute–Midsayap Experimental Station were combined with daily climate variables from the NASA POWER database, including air temperature, humidity, precipitation, wind, soil moisture, and lunar phase. The N–S fractal model identified natural breakpoints in the log–log cumulative frequency of pest counts, yielding early-warning and severe-outbreak thresholds of 134 and 250 individuals for WSB and 575 and 11,383 individuals for RBB, respectively. Eight ML algorithms such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, Balanced Bagging, LightGBM, XGBoost, and CatBoost were trained on variance-inflation-filtered climatic and temporal predictors. Among these, CatBoost achieved the highest predictive performance for WSB at the 94.3rd percentile (accuracy = 0.932, F1 = 0.545, ROC–AUC = 0.957), while Logistic Regression performed best for RBB at the 75.1st percentile (F1 = 0.520, ROC–AUC = 0.716). SHAP (SHapley Additive exPlanations) analysis revealed that outbreak probability increases under warm nighttime temperatures, high surface soil moisture, moderate humidity, and calm wind conditions, with lunar phase exerting additional modulation of nocturnal pest activity. The integrated fractal–ML approach thus provides a statistically defensible and ecologically interpretable basis for adaptive pest surveillance. It offers an early-warning system that supports data-driven integrated pest management (IPM), reduces unnecessary pesticide use, and strengthens climate resilience in Philippine rice ecosystems.

Survey on whitefly infestation in cotton were conducted across six districts of Haryana - Sirsa, Fatehabad, Hisar, Jind, Rohtak and Bhiwani from 2012 to 2015. A total of 618 farmer’s fields were examined in July, August and September each year, with fields selected randomly at an interval of 8-10 km. In 2012, whitefly population remained below economic threshold (ET) in July and August, exceeding ET in only 5% of fields during September. In contrast, 2013 recorded higher infestations, with populations above ET in 8%, 28%, and 44% of fields in July, August, and September, respectively. Similar trends were observed in 2014 and 2015, with particularly high infestations in August, affecting 43% and 56% of fields, respectively. Increased humidity and reduced temperatures as a result of rains in late June appeared to favor whitefly proliferation. Notably, rainfall events—97.3 mm in mid-June 2013, 76.6 mm in June 2014, and 161 mm in June 2015 could have been the reason for rapid build-up of whitefly populations from July onwards in these years.

Goal. The article presents the results of studies conducted in 2023—2025 on the effectiveness of neonicotinoid–pyrethroid insecticides in protecting winter oilseed rape (Brassica napus oleifera bienis D.C.) for controlling the population density of Ceutorhynchus assimilis Payk. Methods. The research was carried out on the winter oilseed rape variety Veritas at SТОV «Rozdilnianske», Rozdilnianskyi District, Odesa Region. The identification of species composition and the assessment of phytophagous insect population dynamics were performed using route surveys accor­ding to gene­rally accepted entomological me­thods. Results. It was established that the most harmful pest was the seed weevil (Ceutorhynchus assimilis Payk.), which significantly reduced both yield and seed quality. Among the tested insecticides, the highest technical efficiency was demonstrated by Inzak Zeon, CS (acetamiprid, 200 g/L + lambda-cyhalothrin, 80 g/L), showing 68.6—88.8% effectiveness, whereas Proteus 110 OD, SC (deltamethrin, 10 g/L + thiacloprid, 100 g/L) exhibited a lower efficiency of 62.0—75.8%. Conclusions. Weather conditions had a notable effect on the stability of insecticide performance: in 2024, the efficiency decreased due to high air temperatures (up to +29°C), while in 2023 and 2025 the insecticides performed more consistently. The study proved that the use of modern insecticides reduces pest populations below the economic threshold of harmfulness, which is essential for obtaining high and stable yields of quality rapeseed. The obtained results are of practical importance for improving the system of integrated pest management of winter oilseed rape under the conditions of Southern Ukraine.

Tuta absoluta (Meyrick), the tomato leaf miner, is a major pest of tomato in Nepal, and can cause an 80–100% reduction in yield if left untreated. Monitoring of the adult moth population and a field experiment were conducted in Surkhet District, Nepal, with eight treatments replicated three times in a RCB design. The tested treatments included (i)Bacillus thuringiensis var. kurstaki (Bt.k) @2 g/L of water, (ii) Nimbicidine (Azadirachtin 300 ppm) @4 ml/L of water (iii) Neem 1500 (Azadirachtin 0.15 EC) @4 ml/L of water, (iv) B. bassiana (2.0% A.S.) @4 ml/L of water, (v) Bacculo virus, SC, >2x1013 (TutaVir) @2ml/10L of water, (vi) Alternate spray of Bt.k and Neem 1500 and (vii) Chlorantraniliprole 18.5% SC (standard check), and (viii) Water spray (control). Observations were made in six-day intervals, in which data on leaf damage, bud damage percentage, percent fruit damage, as well as average number of larvae, bore hole, and yield attributes were recorded. The monitoring results revealed the average population of moths above Economic Threshold Level (ETL). The percentage fruit damage was lowest in the Chlorantraniliprole 18.5% SC (1.48%) followed by alternate spray of Bt.k and Neem 1500 (1.81%) while the marketable yield was at par in both treatments. The B:C ratio showed that alternate spray of Bt.k and Neem 1500 and Chlorantraniliprole 18.5% SC were the superior as compared to others. This study concludes that the alternate spray of Bt.k and Neem 1500 is the most effective biorational pesticide for the management of T. absoluta in field conditions.

Climate change is expected to reduce coffee yields and intensify infestations by Hypothenemus hampei, the most destructive coffee pest worldwide. Strengthening host plant resistance offers a sustainable approach to mitigate these impacts. This study aimed to characterize F3 progenies derived from crosses between Castillo®—a variety with high agronomic performance and resistance to Hemileia vastatrix—and Ethiopian Coffea arabica introductions exhibiting antibiosis to H. hampei for agronomic traits and, for the first time, modeled reductions in H. hampei infestation under projected climate change scenarios. Thirteen F3 progenies with medium plant stature, rust resistance, and high productivity were selected using a 6 × 7 lattice design. Antibiosis was quantified under controlled conditions by infesting individual coffee beans with a single female borer and validated under field conditions by artificially infesting productive branches with 100 females. Relative to the susceptible control, oviposition decreased by 18.0–25.8% under controlled conditions and by 24.1–69.8% in the field. To anticipate progeny performance under warmer conditions, simulation modeling integrating laboratory and field data under Neutral and El Niño scenarios for the Naranjal and Paraguaicito experimental stations, indicated that progenies exhibiting 34–55% reductions in oviposition would maintain infestation below the economic damage threshold (5%) throughout the eight-month fruit development period. Progenies with the highest antibiosis (55%) would reach the action threshold (2%) only in the seventh month. These findings demonstrate the potential of antibiosis-based resistance to reduce insecticide use and strengthen integrated pest management under projected climate change scenarios.

Stink bugs (Hemiptera: Pentatomidae) have emerged as an important pest species complex in soybean production systems across the southeastern United States. Changing cropping practices and climatic conditions are reshaping the stink bug communities in the region. Understanding community differences will be important to tailor integrated pest management programs sensitive to variation in species composition. In this 3-year study (2022-2024), we characterized stink bug diversity and abundance in 154 commercial soybean fields distributed across 3 soybean-producing ecoregions (Coastal Plain, Piedmont, and Mountains) in 2 southeastern states, North Carolina and Virginia. Standardized 25-sweep samples were collected at 10 locations per field during the soybean reproductive stages. Field-level samples were used to evaluate the probability of exceeding the recommended economic threshold for damage. We observed differences in stink bug community composition and spatial variation in the distribution of common stink bug species across the ecoregions. Additionally, the risk of soybean fields exceeding the recommended economic threshold differed across the ecoregions, with the Mountain region at the greatest risk. This result highlights the importance of regionally specific scouting and management recommendations that are sensitive to species composition differences. This work also provides a benchmark to assess range shifts of stink bug species in North Carolina and Virginia.

Spodoptera frugiperda is a key pest in Latin America, capable of causing significant economic losses if management is not timely. Estimation of economic thresholds adapted to local conditions and specific varieties is essential to optimizing control and reducing unnecessary use of insecticides. The objective of this study was to estimate the economic threshold of S. frugiperda in short stature maize, Delfín variety, under field conditions in northern Sinaloa, Mexico. We set up seven treatments with different levels of artificial infestation (0-25%), plus a regional control, in a completely random design. We evaluated the percentage of damaged plants, with an estimated loss of 32.515 kg/ha for each 1% of damage. Considering a US $325 t-1 price of maize and US $127 ha-1 cost of control, we determined an economic threshold of 12.05% damaged plants. This value is a practical tool for better decision-making in S. frugiperda management in Delfín variety maize. We recommend validation in different agroecological contexts and growing seasons.

Abstract To what extent does refugee protection in Western Europe depend on the ethno-religious and gender identity of asylum seekers? This article examines how selective humanitarianism, shaped by the identity of asylum seekers and migrants, shapes their protection status. It offers an analysis of Germany’s response to Yezidi refugees, in comparison with that of France, in the wake of the genocidal campaign carried out by the Islamic State in 2014. Drawing on fieldwork that includes interviews with Yezidi refugees and stakeholders in Germany, we argue that contemporary asylum regimes operate through three interrelated mechanisms: the securitization of certain groups, selective humanitarian exceptions, and neoliberal selection criteria. The Yezidi experience illustrates how these mechanisms generate hierarchies of protection, wherein even recognized victims of genocide must meet increasingly economic thresholds to secure lasting refuge. While specialized programs for women survivors represent important humanitarian innovations, they often exclude male family members, thereby producing new forms of vulnerability. Struggling to align with dominant narratives of economically valuable migrants, Yezidis encounter a renewed form of liminality in Europe.

The whitefly is a prevalent pest in bean crops. Although it feeds on sap and can transmit phytopathogenic viruses, many farmers and existing literature do not fully acknowledge its potential harm to bean crops. To address this, it is crucial to quantify the Damage Index (DI), Economic Injury Level (EIL), and Economic Threshold (ET) to aid in decision-making and prevent economic losses. This study aimed to quantify the DI of whiteflies in a bean crop under field conditions. A bean plot was established with three treatments: Buffer Zone, Chemical Control, and No Control. Whitefly adults per leaflet were monitored every 14 days throughout the crop cycle. Yield per plant for each treatment was estimated and related to whitefly populations using linear regressions. The EIL and ET were calculated based on the region’s socioeconomic context. The estimated DI was 3.52 grams of dry beans per plant (47 kg per hectare) for each whitefly adult found per leaflet. Consequently, the EIL and ET were 14 and 8 adult whiteflies per leaflet, respectively. Whitefly populations can significantly reduce yields and result in economic losses for local farmers if not properly managed.

Stink bug feeding on soybean pods requires vigilant crop protection due to low economic thresholds. This study used extracellular plant electrophysiology (EPE) to continuously monitor plant electrical signals (ES) during infestation. Greenhouse experiments evaluated crop infestation scenarios with the insecticide Verdavis (isocycloseram and lambda-cyhalothrin). Plant ES were recorded for different infestation periods, and related crop damage was compared with EPE output. Based on these experiments, an EPE model was developed to quantify spike occurrences. Distinct spike counts emerged within the first day of infestation: infested plants with visual damage after 7 days generated significantly more ES spikes compared to non-infested controls (p < 0.001). Conversely, plants that showed only marginal damage after 7 days did not exhibit significant differences in ES spike generation (p = 0.058). Treated plants generated similar spike patterns as non-infested plants, indicating effective plant protection. Manual insect removal led to rapid reduction of spike count. Additionally, more spikes were recorded during the day (p < 0.001), but spike output was similar between pod- and stem-inserted electrodes during day (p = 0.837) and night (p = 0.328). This study demonstrates that EPE can be used as a minimally invasive method for real-time monitoring of plant protection, providing insights into plant–insect interactions and insect control measures.

Introduction Artificial Intelligence has shown measurable gains in diagnostic accuracy, workflow efficiency, and clinical outcomes in stroke care. However, economic sustainability remains a critical consideration for widespread adoption. Health economic evaluations,particularly cost‐effectiveness analyses (CEAs),offer vital insights into the value of AI integration from payer and policymaker perspectives. This systematic review aims to synthesize current evidence on the cost‐effectiveness of AI technologies across the stroke care continuum. Methods Following PRISMA and CHEERS 2022 guidelines, we systematically searched MEDLINE, Embase, NHS Economic Evaluation Database, and IEEE Xplore from inception to June 2025. We included studies that performed CEAs, cost‐utility analyses, or cost‐benefit analyses on AI applications in any phase of stroke care (prehospital, acute,subacute,or rehabilitation). Key data extracted included setting, AI type,comparator strategy, perspective,time horizon,cost components, effectiveness metrics (QALYs gained), and incremental cost‐effectiveness ratios (ICERs). Data were synthesized and visualized using R and Python. Results A total of 17 eligible studies involving 11 countries were included, with sample sizes ranging from 500 to 150,000 patients. The majority were model‐based CEAs (n=14), with 3 using real‐world implementation data. Most analyses adopted a healthcare payer or societal perspective and applied time horizons of 1 year to lifetime. Across studies, AI‐driven imaging triage and LVO detection consistently demonstrated cost‐effectiveness, with ICERs ranging from $7,000 to $14,000 per QALY gained. Workflow optimization tools integrating AI with telestroke networks reduced door‐to‐needle time by up to 15 minutes and achieved an ICER of $7,000/QALY.Prognostic models and post‐stroke rehabilitation AI systems showed more variable results ($16,000‐$21,000/QALY),primarily due to limited evidence on long‐term outcome gains and higher upfront technology costs.All reviewed ICERs were well below conventional willingness‐to‐pay thresholds($50,000/QALY), indicating high economic value. Sensitivity analyses showed robustness to cost assumptions and healthcare setting variability. However, only 4 studies accounted for implementation barriers such as clinician training, regulatory overhead, and interoperability costs. Reporting quality was high (CHEERS compliance score &gt;85%)in 12 studies but varied in modeling transparency. Conclusion AI applications in stroke care, particularly for acute imaging triage and LVO detection, are consistently cost‐effective under established health economic thresholds. Workflow optimization AI yields the highest value, whereas rehabilitation‐focused tools need further outcome validation. Despite promising economics, few studies incorporate real‐world integration challenges. Health systems aiming to scale AI must align investment strategies with long‐term outcome modeling and equity considerations. Future research should focus on prospective CEAs embedded in clinical trials and health system implementation frameworks to better capture real‐world value. image

Red clover, Trifolium pratense L., is a perennial forage legume grown for seed production in Western Canada, contributing significantly to regional agricultural economies. The lesser clover leaf weevil, Hypera nigrirostris Fab. (Coleoptera: Curculionidae), is a key pest of red clover seed crops, with larval feeding capable of reducing seed yields by up to 50%. Despite its impact, no economic thresholds (ET) currently exist to guide insecticide application for this pest. As a result, prophylactic treatments are used that increase production costs, increase the potential for insecticide resistance, and pose risks to pollinators, which are essential for red clover seed production. This study established a quantitative relationship between larval density and red clover seed yield under field conditions and used these data to develop economic injury levels (EIL) and practical ETs across a range of seed price scenarios. Yield losses were strongly associated with increasing larval densities, and thresholds varied with changing economic conditions. These resulting thresholds provide the first data-driven guidance for managing H. nigrirostris in North American red clover seed systems, offering a foundation for cost-effective, pollinator-conscious pest management strategies.

Leaf-feeding insect pests are often encountered in soybean, Glycine max (L.) Merr., but rarely cause defoliation to exceed established action thresholds in the North Central United States. Pest managers often question these thresholds and apply insecticides when pest densities are well below recommended levels. Furthermore, assessing soybean defoliation in the field is often perceived as too time-consuming. Our objectives were to (i) determine the extent of insect defoliation injury in the North Central United States relative to economic thresholds, (ii) characterize spatial patterns of insect defoliation within soybean fields, and (iii) compare visual estimates of soybean defoliation obtained from the entire soybean canopy with those obtained from individual leaflets. We assessed insect defoliation in 65 soybean fields in 7 states in 2019 and 2020. Only 1 field exceeded an economic threshold computed using updated economic data applied to established relationships between leaf tissue removal and yield loss. The most common pests observed included the Japanese beetle, Popillia japonica Newman; the bean leaf beetle, Cerotoma trifurcata (Förster); the green cloverworm, Hypena scabra (F.); and grasshoppers (Orthoptera: Acrididae). We did not observe consistent "edge effects" in defoliation, likely due to the variety of leaf-feeding insect pest species we encountered. We computed sequential sampling plans that suggested relatively few samples would lead to a decision not to apply an insecticide for defoliating insects in most soybean fields. Defoliating insects rarely cause economic damage in the North Central United States based on current conditions.

In recent years, the problem of pests seriously affects the yield and quality of crop, posing a major challenge to the safe production of crop, which have seriously hindered the development of China’s agriculture. How to quickly and accurately monitor pests, timely grasp the occurrence dynamics of pests, and prevent and control pests is of great significance for reducing crop yield losses. Considering the discontinuity of spraying pesticides and releasing natural enemies in the process of pest control, and the Filippov system’s ability to accurately depict switching states and human intervention measures, a non-smooth Filippov predator-prey system with threshold strategies is investigated incorporating several different functional responses, such as Holling II functional response and ratio functional response etc, which should be selectively applied dependent on the population of the prey. The aim of this study is to investigate the complex dynamics including bistabilities of the ecosystem when the relative populations of the prey and predator is substantially different, by modelling the non-smooth Filippov system with multiple switchable functional responses for the very first time, which is believed to be more realistic for modeling the dynamics of real ecosystem, thus the solution of the present work may be more suitable for real world applications such as for the integrated pest management. The validity of the proposed system is assessed by simulation, and bifurcation set of equilibria and the global stability of equilibria has been numerically obtained through an arbitrary set of parameters. Moreover, the dynamic behaviors of proposed system, such as the existence of various equilibria and their global stabilities; the existence of various domains such as the sliding domain, escaping domain and crossing domain, have been analyzed in great details in the present work. It is shown that the sliding region and escaping region cannot coexist when the density of the prey and predators is substantially different. It is further demonstrated that the real equilibrium and pseudo-equilibrium points can coexist when the population of the prey is less than that of the predator; and only the virtual equilibrium and pseudo-equilibrium can coexist in the case of when the population of the prey is more than that of the predator.In particular, it is noted that all trajectories of the prey and predators population are eventually converging into certain equilibrium points as it is demonstrated in the numerical simulation. This implies that there exists global asymptotic stability of equilibrium points under the proposed system, in which the population of preys eventually reaches a steady state of density at the real equilibrium and pseudo-equilibrium points. This work also highlights the significant role of the threshold in the process of pest controls: it is seen from this work that different types of equilibrium points can occur dependent on the choice of the economic threshold (ET). The conclusions obtained will be applied to Unmanned Aerial Vehicle (UAV) to spray pesticides and release natural enemies in a timely and quantitative manner, thereby achieving efficient and rapid monitoring and control of large-scale crop. This can more effectively ensure stable and high crop yields, provide theoretical guidance for scientific prevention and control, and is of great significance for reducing the burden on farmers, promoting agricultural development, and realizing agricultural modernization.

The fungus Beauveria bassiana (Unioeste 76) was tested against the soybean pest Euschistus heros in laboratory, greenhouse, and field. In the laboratory, insects were sprayed with pure conidia (TC) suspended in distilled water or in an oil dispersion formulation (OD; vegetable oil) at a concentration of 109 conidia/mL. The UV-B radiation and heat tolerance of the conidia were also assessed. After 12 days, the mortality rates in the laboratory were 70% for the TC treatment and 80% for the OD treatment. In the greenhouse pre-infestation bioassay, which used soybean plants in cages, the fungal treatments resulted in 52% and 47% mortality for the TC and OD formulations, respectively. In the post-infestation bioassay, both fungal treatments caused 83% mortality. In the field trial conducted on soybean plots (14 × 18 m), the treatments included: (i) biological: OD (109 conidia/mL); (ii) chemical insecticide; (iii) biological + chemical, all applied at 150 L/ha. Insect numbers were evaluated using beating-sheet sampling. In the final population sample, the biological treatment showed a population density similar to the chemical treatment (0.94 and 0.83 insects/m, respectively), both below the economic threshold. Conidia tolerance to UV-B radiation was similar across both treatments, but conidia in oil were less tolerant to heat. These results suggest that strategically combining both approaches (B. bassiana with chemical insecticides), with careful consideration of application intervals, could provide a sustainable and effective method for managing natural populations of E. heros.

ObjectivesTo investigate the association between red cell distribution width (RDW) and early kidney injury.MethodsData were obtained from the 2003–2004 National Health and Nutrition Examination Survey, including 3,633 adult participants. Early kidney injury was defined according to the 2024 Kidney Disease: Improving Global Outcomes guidelines as eGFR ≥60 mL/min/1.73 m2 with urinary albumin-to-creatinine ratio (UACR) 30–300 mg/g, or eGFR 45–60 mL/min/1.73 m2 with UACR <30 mg/g. Multivariate logistic regression was used to assess the association between RDW and early kidney injury, adjusting for demographic, socioeconomic, and clinical confounders (age, sex, race, education, poverty index, hypertension, diabetes). Receiver operating characteristic curves were applied to determine the optimal RDW cutoff, and restricted cubic spline (RCS) models were used to explore dose–response relationships.ResultsAfter adjusting for confounders, there is a positive correlation between RDW and early kidney injury (OR = 1.26, 95% CI: 1.08–1.45, p = 0.013). RDW quartile analysis showed that the highest quartile group (>13.1%) had a 1.74-fold risk compared to the lowest group (<12.1%) (95% CI: 1.27–2.40, p < 0.001). RCS confirmed a nonlinear dose–response relationship (nonlinear p < 0.05). The area under the curve for RDW predicting early kidney injury was 0.86. At the optimal cutoff value of 12.7%, sensitivity was 87.5% and specificity was 71.42%. In the hypertensive population (n = 1,190), RDW still significantly predicted early kidney injury (OR = 1.26, 95% CI: 1.10–1.47, p = 0.007).ConclusionElevated RDW is significantly associated with the risk of early kidney injury and is robust in the hypertensive population. RDW > 12.7% can serve as an economical and convenient screening threshold, especially suitable for early risk stratification of high-risk groups in resource-limited areas. Future prospective studies are needed to validate its causal mechanism and clinical utility.

Abstract Horn flies (Haematobia irritans) are among the most economically detrimental ectoparasites in beef cattle, negatively impacting animal welfare and productivity by reducing feed intake and growth performance. The industry-standard economic injury threshold (EIT) of 200 flies per animal has been widely used to determine the point at which intervention is necessary. However, individual tolerance to horn fly infestation varies, and a one-size-fits-all threshold may not be suitable for optimal herd management. The objective of this study was to determine individualized EITs for beef heifers using Bayesian changepoint models, incorporating both subjective and image-based horn fly counts, as well as growth performance metrics. Data were collected from 337 heifers at two University of Georgia research farms (Eatonton and Calhoun) over three years (2022–2024). At each time point (March, June, and August), animals were weighed, and horn fly infestation was assessed using two methods: trained evaluator assessments (subjective counts) and image-based fly counts. Bayesian changepoint models were implemented to determine the exact threshold at which growth performance started declining (EIT), the rate of decline after reaching this threshold (DPO), and an upper limit beyond which additional fly burden no longer affected performance (UST). The results indicated substantial variation in EIT across animals, with estimates ranging from 261 to 322 flies, depending on the growth interval considered. This suggests that the widely accepted industry threshold (200 flies) may underestimate tolerance in some animals while being too high for others. The rate of decline in growth performance (DPO) also varied, emphasizing the need for individualized fly management strategies. Furthermore, the two-changepoint model identified an upper threshold (UST), at which further increases in fly burden did not significantly impact growth, reinforcing the idea that fly tolerance is not uniform across all animals. These findings demonstrate that Implementing data-driven EITs tailored to individual, or herd-level susceptibility could improve economic outcomes by optimizing intervention timing and reducing unnecessary pesticide applications. Future research can focus on validating these thresholds in different genetic lines and management environments, further enhancing precision livestock farming approaches.