Endoscopic CTR (ECTR) accounts for a growing proportion of surgeries over open CTR (OCTR). In a cost-conscious healthcare environment, it is important to characterize the drivers of high-cost care, since OCTR can be performed with similar outcomes but less costs. We investigated whether regional surgeon competition affects the type of CTR. : Using MarketScan claims data from 2018 to 2022, we calculated the Herfindahl-Hirschman Index, a measure of market competition. Multivariable regression was used to identify factors affecting the type of CTR performed, costs, and complications. There were 41,593 OCTR (71.9%) and 16,274 ECTR (28.1%) identified. Competitive markets were associated with 12% higher odds of performing ECTR, leading to an increase of $37.68 in patient out-of-pocket costs and $347.45 in total healthcare costs. Regional surgeon competition was not associated with differences in complications after CTR. Surgeons in competitive markets have greater odds of performing ECTR over OCTR, which are more costly. Surgeons should recognize the potential influence of non-medical factors in the management of carpal tunnel syndrome. The selective performance of ECTR through shared decision-making can be considered.
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Species sharing a habitat will co-evolve to make use of the available resources, as consumption is modulated by competition and negative feedback loops between consumers and resources. The dietary range of a given species determines the resources it has access to and thus the other species with which it competes. A narrow dietary range avoids competition at the cost of over-reliance on a small selection of resources; conversely a wide dietary range provides more alternatives but also more chance of competition with other species. Here, we investigate the evolution of dietary range within a mathematical model of niche formation. We find highly path dependent co-evolution dynamics characterised by long-lived quasi-stable states. Ultimately, stochastic effects drive the evolution of generalist diets, as we uncover in our analysis and simulations.
Accurately simulating heavy elements requires resolving spatial electron density competitions often obscured by traditional scalar energy metrics. Using continuous information-theoretic descriptors, we evaluate the spin-free exact two-component (sf-X2C) Hamiltonian and exact-exchange interactions across the periodic table (Z = 1-86). From the analytical hydrogenic baseline to generalized many-body frameworks, we demonstrate how the nonlinear radial decay of the effective nuclear charge dictates the macroscopic competition between direct core contraction and indirect d/f-block spatial expansion. We reveal the intrinsic spatial nonadditivity of these logarithmic descriptors. Unlike scalar energies, the coupling between relativistic kinematics and exact exchange generates state-dependent spatial cross-terms driven by localized d/f electrons, necessitating fully coupled treatments for heavy elements. Extending to molecular architectures, we introduce the continuous Kullback-Leibler (KL) divergence against a promolecular reference to quantify the spatial information cost of chemical bonding. This geometric probe decouples the concentric spatial contraction of main-group covalent bonds from the anisotropic lobe-like expansion along transition metal coordination axes. These spatial divergence signatures offer three-dimensional diagnostic constraints for parametrizing next-generation heavy-element density functional approximations.
Innovation capability is a core competency for nursing college students to adapt to the development of modern nursing and meet clinical demands. This study applied innovation ecosystem theory and aimed to identify the latent profile types of nursing college students' innovation capability and their associated factors, to provide a basis for formulating targeted training strategies. A cross-sectional survey was conducted among 1,086 nursing college students using a self-designed "Questionnaire on Innovation Capability of Nursing College Students" with good reliability and validity. Latent profile analysis (LPA) was used to classify the innovation capability types. The innovation capability of nursing college students was divided into four latent profile types: Low Innovation Capability Type (22.65%), Low-Medium Innovation Capability Type (32.97%), Medium-High Innovation Capability Type (29.93%) and High Innovation Capability Type (14.46%), showing a distribution characteristic of "larger in the middle and smaller at both ends". Multiple linear regression analysis showed that weekly self-directed learning time for innovation knowledge (β'=0.298), number of innovation competition participations (β'=0.234), clinical internship experience (β'=0.189) and age (analyzed as a continuous variable, β'=0.123) were significant positive predictors of innovation capability (all P < 0.001). The total score of innovation capability of nursing college students was 67.64 ± 8.36, with the lowest average score in the Innovation Environment dimension (2.58 ± 0.52) and the highest in the Innovation Motivation dimension (2.92 ± 0.50). Nursing college students' innovation capability presents obvious heterogeneous characteristics with four distinct profile types. Weekly self-directed learning time for innovation knowledge, participation in innovation competitions, clinical internship experience and age were identified as key factors associated with higher innovation capability. These findings suggest that targeted training strategies such as differentiated cultivation, strengthening clinical innovation training, improving self-directed learning ability and optimizing innovation incentive mechanisms may help enhance nursing college students' innovation capability. Longitudinal and interventional studies are warranted to confirm these effects.
In industrial production, the yield of desired targets derived from carbon sources is frequently diminished by the competitive influence of cellular metabolism within microbial cell factories. The bioproduction of l-valine exemplifies a classic process that is confronted with such a dilemma, substantially hindering its economic industrial-scale production. In this study, we aim to engineer a cell factory capable of efficiently synthesizing l-valine with high yield by minimizing the consumption of its precursor pyruvate through the TCA cycle under oxygen-limited conditions. Metabolic engineering-based adaptive laboratory evolution (ALE) under oxygen-limited conditions resulted in the development of an evolved strain ALE2-40 with better cell growth and enhanced l-valine yield. Through comparative omics analysis and validation experiments, it was uncovered that during the ALE process, both pyruvate dehydrogenase activity and NADH availability were significantly improved. Moreover, beneficial targets have the potential to contribute to the NADH and ATP pools, thereby further promoting l-valine synthesis. Based on these results, reverse engineering of the evolved strain ALE2-40 was further conducted. Ultimately, the final strain VAL19 demonstrated remarkable performance, achieving an impressive l-valine titer of 93.7 g/L within 28 h in a 5-L bioreactor under oxygen-limited conditions, with a remarkable yield of 60.4% from glucose-equivalent to 92.9% of the theoretical yield-and a productivity of 3.35 g/L/h. These results set a new benchmark for the fermentative production of l-valine, with the highest yield and productivity reported so far.
Thickness is a critical yet often overlooked degree of freedom governing both charge transport and surface reactivity in two-dimensional (2D) semiconductors. Here, we elucidate the thickness-dependent coupling between carrier transport and NH₃ sensing in multilayer MoS₂ field-effect transistors with controlled layer numbers. The field-effect mobility exhibits a pronounced nonmonotonic evolution, increasing from 0.13 cm² V⁻¹ s⁻¹ (6 layers) to a maximum of 20.1 cm² V⁻¹ s⁻¹ at ~21 layers before decreasing at larger thicknesses, reflecting the competition between interfacial Coulomb scattering, dielectric screening, and interlayer transport limitations. In stark contrast, the NH₃ sensing response shows a monotonic decrease with increasing thickness, with the 6-layer device delivering a response as high as 466.17% at 160 ppm. This inverse correlation arises from the progressive decoupling of surface adsorption from bulk transport due to enhanced electrostatic screening and reduced participation of inner layers. By directly linking thickness-dependent scattering physics with surface charge-transfer modulation, this work establishes a unified framework for understanding and engineering the trade-off between transport efficiency and sensing sensitivity in multilayer MoS₂. These findings highlight thickness as a key design parameter for optimizing 2D semiconductor devices across electronic and sensing.
Effective removal of per- and polyfluoroalkyl substances (PFAS) form contaminated waters remains a significant treatment challenge in remediation facilities due to their structural heterogenicity, high aqueous mobility, and frequent occurrence as complex multi-component mixtures. Although granular activated carbon (GAC) and ion exchange resins (IER) are widely used for PFAS treatment, their performance is strongly influenced by water-matrix composition and competitive adsorption among PFAS, which can accelerate breakthrough and reduce adsorption capacity. Consequently, treatment performance assessments and capacity estimates may remain uncertain under multi-component conditions. Accordingly, this study evaluates how structurally diverse PFAS compete during adsorption and displacement in single- and multi-solute systems. This unified comparison clarifies how GAC and IER chemistry influence PFAS competitive behavior. Coexisting organic and inorganic constituents, dissolved organic matter (DOM) and phosphate, were incorporated to simulate realistic water matrices and to quantify their influence on PFAS competition and displacement. Results revealed that PFAS chain length and functional group chemistry governed the competitive hierarchy, with sulfonates generally exhibiting greater surface stability and removal efficiency than carboxylates. In addition, the results demonstrated distinct surface-dependent competitive behavior across the studied sorbents. GAC exhibited pronounced inhibition and displacement of PFAS in the presence of dissolved organic matter, whereas IER maintained relatively higher selectivity toward PFAS but was more susceptible to phosphate-induced displacement, highlighting the distinct matrix sensitivities of the two sorbents. These findings provide critical insight into PFAS treatment in multi-component systems and emphasize the importance of water-matrix specific design considerations to improve treatment efficiency, particularly for short-chain PFAS.
During biparental pre- and post-hatching care, parents take on energy-consuming tasks for the offspring's benefit and further reduce their own individual costs by specializing in different care aspects. But how is biparental care evolutionarily stable when biparental care is facultative, that is, when offspring survival does not obligately rely on post-hatching care? We examine this phenomenon in the carrion-breeding beetle Nicrophorus vespilloides, whose facultative biparental care involves microbiome control of the carcass nursery through continued application of antimicrobial exudates, shielding offspring from adverse environmental conditions. While evidence suggests synergistic effects of biparental care in Nicrophorus, any adaptive benefits in terms of social immunity are unknown in this genus. We presented Nicrophorus adults with a microbial challenge while manipulating parental care patterns during the period of post-hatching care, investigating consequences in parent and offspring performance. We found that microbial environment and parental care pattern influence larval development and survival. Additionally, we show for the first time that both factors affect personal immunity response in Nicrophorus offspring, responding to challenging conditions. Simultaneously, we show that biparentally caring beetles lose more weight during post-hatching care than uniparentally caring beetles, indicating higher investment and/or higher competition with mates or offspring. We present new evidence that burying beetle offspring adjust their personal immunity based on their microbial and social environment, and that biparental care may allow parents to sustain parental care under challenging conditions, raising further questions about the interplay of care patterns and the microbial environment on immune-regulatory and developmental processes in offspring.
Balance and landing stability are critical for performance in high-intensity sports such as badminton; however, conventional balance training may not adequately replicate the intermittent visual disturbances encountered during competition. Stroboscopic visual training (SVT), which intermittently occludes visual input to challenge sensory processing, has shown potential benefits but remains underexplored in badminton-specific settings. This study aimed to investigate the effects of SVT on static balance, dynamic balance, and landing stability in trained collegiate badminton athletes. A six-week randomized controlled trial was conducted in 20 male collegiate badminton players, who were randomly assigned to either an SVT group (n = 10) or a conventional balance training group (CON, n = 10). Both groups completed identical 30-min balance training sessions three times per week. The SVT group trained with stroboscopic eyewear in active flicker mode, whereas the CON group wore identical eyewear without visual occlusion. Pre- and post-intervention assessments included static balance (eyes-closed single-leg stance), dynamic balance (Y-Balance Test), and landing stability, using the Dynamic Postural Stability Index (DPSI) and center-of-pressure (COP) variables. The SVT group demonstrated significantly greater improvements than the CON group in static balance, dynamic balance, and landing stability (P < 0.05). Specifically, the SVT group exhibited increased single-leg stance time, greater reach distances in the Y-Balance Test, and lower DPSI values, indicating improved postural stabilization after landing. These findings suggest that incorporating SVT into training may be an effective strategy for enhancing postural control and landing stability in badminton athletes. From a practical perspective, these improvements may contribute to greater movement efficiency, enhanced landing control, and faster transitions during high-intensity play. Future studies should further investigate the underlying mechanisms and the transfer of these adaptations to sport-specific performance.
Developing strategies to improve pasture yield and mitigate environmental impacts is crucial in Southeastern Brazil, where livestock farming faces competition for areas with profitable crops. Accurate evapotranspiration (ET) estimation is an essential component of managing soil water balance and evaluating pasture response to drought and water productivity. The objectives of this study were to: (1) develop a relationship between the basal crop coefficient (Kcb) derived from observed ET, and the soil-adjusted vegetation index (SAVI) from PlanetScope images; (2) integrate the Kcb-SAVI relationship into remote sensing-based soil water balance (RSWB) to generate daily Kcb and then simulate the actual evapotranspiration (ETa) of an intensively grazed tropical pasture in the state of São Paulo, Brazil; and (3) use the spatialized estimate of ETa to assess the crop water productivity ([Formula: see text]). The Kcb-SAVI relationship developed in this study showed a strong positive correlation between SAVI and Kcb, with Pearson correlation coefficient (ρ) and [Formula: see text] values of 0.89 and 0.79, respectively. Comparisons between observed and simulated ETa indicated good agreement for daily values ([Formula: see text] of 0.59 mm d-1, Willmott index of agreement ([Formula: see text]) of 0.86) and for average weekly values ([Formula: see text] of 0.38 mm d-1, [Formula: see text] of 0.93). Biases of -5% and 3% were obtained for modelled cumulative ETa in the years 2021-2022 and 2022-2023, respectively. The average [Formula: see text] values were similar for both years, 2.2 kg m-3 in 2021-2022 and 1.8 kg m-3 in 2022-2023. These findings demonstrate the potential of RSWB, ETa, and WP assessments to enhance decision-making, monitoring, and management of water resources in pasture-based livestock farming.
This article investigates how Russia employs gender-based disinformation as a strategic tool to advance its foreign policy objectives. Although existing research on gender-based foreign influence and disinformation emphasizes its domestic social effects, it has not fully explored how states instrumentalize gendered narratives to pursue broader geopolitical goals. Using qualitative content analysis of 367 pro-Kremlin disinformation articles, we identify eight narratives that Russia employs to undermine the moral legitimacy of Western states and institutions, such as NATO and the EU, while simultaneously legitimizing its own actions. We show that Russia strategically deploys disinformation to resonate with conservative audiences. Our analysis highlights two core mechanisms: legitimacy sabotage and legitimation, both of which are rooted in the contestation of moral authority. By weaponizing gendered narratives, Russia effectively reconfigures legitimacy landscapes in its favour, illustrating the broader strategic logic of gender-based disinformation within contemporary hybrid warfare tactics. This research presents a novel framework for understanding how states use identity-based narratives in the context of great power competition.
Calcium binding to native β-lactoglobulin (β-Lg) was quantified to clarify its role in dairy-relevant phenomena. Binding was measured across dairy relevant conditions, pH (5.5-7) and ionic strength (∼35-400 mmol/L) using equilibrium dialysis and inductively coupled plasma mass spectrometry (ICP-MS), with molecular dynamics simulations providing qualitative insight into binding motifs. Experimental data show that calcium binding plateaus scales linearly with intrinsic protein charge, consistent with site-specific association to Asp/Glu carboxylate groups rather than long-range electrostatics. Competitive binding by sodium ions was directly observed and explains discrepancies amongst reported binding constants. A deliberately empirical, low-parameter competitive binding model was developed for screened, dairy-relevant ionic strengths, reconciling literature values by accounting for co-ion competition and ionic strength effects. The model predicts ≤0.5 calcium ion per β-Lg monomer under milk-like conditions. The study does not model denatured state binding during heat treatment, with conclusions limited to regimes where long range electrostatics are suppressed.
Mass-independent fractionation (MIF) of mercury (Hg) provides a powerful tracer for reconstructing Hg cycling in the Earth system. Although generally attributed to photochemistry, many natural isotope signatures remain inconsistent with the established mechanisms. Here, we present experimental evidence that atmospheric plasma-induced reduction produces odd Hg-MIF with magnitudes and patterns distinct from photochemical processes. Plasma reactions yielded far larger odd-MIF signatures than photoreduction, with Δ199Hg spanning -78‰ to +28‰, the most negative Hg-MIF across all Hg-reduction experiments. The sign of Hg-MIF reverses with solution pH, yielding strongly negative Hg-MIF at pH ≥ 3.0 but positive Hg-MIF at pH ≤ 2.0. This reversal arises from competition between plasma-generated species, where solvated electrons drive negative magnetic isotope effects (MIE) at higher pH, while hydrogen radicals produce positive MIE at low pH. These findings reveal plasma chemistry as a fundamental but previously overlooked driver of Hg isotope fractionation. Given the ubiquity of natural plasmas such as lightning and aurora, plasma processes need to be integrated into models of Hg cycling in Earth's atmosphere and surface environments.
Sexual selection may increase population fitness by favouring high-condition individuals and accelerating the purging of deleterious alleles. However, it can also reduce population fitness through intra- and interlocus sexual conflict by promoting male-benefit traits that harm females and maintain polymorphism at sexually antagonistic loci. The balance between these opposing forces remains unresolved, yet it has major consequences for how sexual selection shapes population fitness and genome-wide variation. To explore the genomic and phenotypic effects of sexual selection and sexual conflict, we evolved replicated bulb mite (Rhizoglyphus robini) lines for 28 generations under male- versus female-biased sex ratios and combined phenotypic assays with whole-genome resequencing. Female fecundity and inbreeding depression did not differ between treatments, and genomic analyses revealed no treatment effect on the loss of rare, putatively deleterious SNPs. Contrary to expectations, males from male-biased lines were less harmful to stock females than males from female-biased lines. Genome-wide nucleotide diversity declined similarly across generations in both treatments, although synonymous exonic diversity declined more slowly in male-biased lines. While only a few SNPs diverged consistently between treatments, we identified large treatment-specific haplotype blocks indicating that multiple genomic regions were involved in response to sex-ratio manipulation. Overall, our results indicate that sex ratio manipulation drives evolution of male harm to females and widespread haplotype frequency changes without clear evidence for enhanced purging or maintenance of genetic diversity. The response thus appears to reflect adaptation to altered level of reproductive competition, but without measurable consequences for population fitness and genetic diversity.
Global agriculture accounts for approximately 72% of total freshwater consumption and accelerating water scarcity from population growth, and climate change is intensifying pressure on this supply, particularly in arid and semi-arid regions. Reclaimed water (RW) has emerged as a strategically important supplementary irrigation source that can alleviate freshwater competition and partially offset synthetic fertilizer demand. However, long-term RW application introduces compounding risks including soil salinity accumulation, sodicity, accumulation of potentially toxic elements, and inputs of pharmaceutical residues and microbial contaminants that threaten soil health and crop safety. This review critically examines the co-application of biochar and plant growth-promoting bacteria (PGPB) as an integrated amendment strategy for mitigating RW-induced multi-stressor challenges while enhancing crop productivity and soil biological health. Biochar improves soil aggregation, water retention, cation exchange capacity, and toxic ion immobilization, while PGPB enhance nutrient acquisition, phytohormone production, and plant stress tolerance. Critically, biochar functions as a protective carrier that extends PGPB persistence and colonization, producing synergistic outcomes that neither component reliably achieves alone. Drawing on saline irrigation, heavy metal, and water-deficit studies where RW-specific studies is limited, this review identifies mechanistic gaps, limitations, and priority research directions for advancing sustainable RW reuse in agriculture. This review integrates the existing body of knowledge on the co‐application of biochar and plant growth‐promoting bacteria (PGPB) to overcome the challenges posed by RW irrigation. While biochars are known to improve the physical, hydraulic, and microbial properties of soils, PGPBs are known to enhance nutrient utilization, phytohormone secretion, stress resistance, and biological control. There is an increasing trend to recognize the role of biochars as carriers for PGPBs, based on the perceived mutualistic benefits for enhancing soil quality, nutrient use efficiency, and crop yields. The review examines both individual and integrated biochar–PGPB functions under RW irrigation, drawing on freshwater‐based studies where RW‐specific data are limited, and outlines key research gaps for advancing sustainable crop production with RW.
This study extends the Hi-sAFe agroforestry model by incorporating the effects of elevated atmospheric CO2 on tree growth. Hi-sAFe is a process-based biophysical model that represents tree-crop interactions, but until now lacked a mechanism to simulate CO2-driven physiological responses of trees. We introduced CO2 sensitivity into the Light Use Efficiency (LUE) module and simulated the growth of Juglans nigra (black walnut) under current and future climate conditions (550 ppm CO2, + 3 °C, - 10% precipitation). Elevated CO2 increased tree height, diameter and root development in both forestry and agroforestry systems, but responses were stronger and more persistent in forestry. In agroforestry, CO2 effects were more variable over time and were strongly modulated by competition with crops, while belowground responses indicated greater root system plasticity. Climate change reduced tree growth in both systems, but CO2 partially offset these effects, particularly in forestry. These results demonstrated the importance of explicitly representing CO2 fertilisation in agroforestry models to realistically capture vegetation-climate interactions and assess the resilience of tree-crop systems under global change.
Lytic polysaccharide monooxygenases (LPMOs) are crucial for recalcitrant biomass degradation. We characterized CmLPMO10, an AA10 LPMO from Chitinibacter mangrovi FCG-7, and demonstrated its essential role in α-chitin utilization through transcriptomics and gene deletion. Biochemically, CmLPMO10 is a robust enzyme with optimal activity at 50 °C and pH 7.0, featuring unique regioselectivity: C1-specific oxidative activity on chitin and C1/C4 activity on cellulose. CmLPMO10 showed the strongest synergistic degradation of α-chitin with its homologous chitinase CmChi18B (degree of synergy: 1.96). Furthermore, CmLPMO10 also exhibited synergistic enhancement of cellulosic substrate hydrolysis when combined with the commercial cellulase preparation Celluclast® 1.5 L, achieving degree of synergy values of 1.31 for Avicel, 1.24 for PASC, and 1.55 for sugarcane bagasse-derived cellulose. Structural analysis revealed CmLPMO10 pretreats α-chitin not by forming pores but by inducing surface roughening, loosening, and selective crystallinity reduction to enhance substrate accessibility. The collaboration is finely tuned, with optimal enzyme ratios differing between chitinase partners (1:5 for CmChi18B; 1:25 for SmChiC), and exhibits nonlinear kinetics reflecting synergy-competition balance. Our work elucidates the function and mechanism of CmLPMO10 and its potential as a key biocatalyst for efficient α-chitin biomass valorization.
Since the Last Glacial Maximum (LGM) ~21.5 kya, global sea-level rise has reshaped coastal areas by contracting subaerial regions, severing mainland connections and driving the progressive fragmentation of pre-existing islands. These changes led to supersaturation of island communities, triggering community relaxation through local extinctions. However, it remains unclear which ecological processes are responsible for patterns of species extinction. Here, we integrate a paleo-coastline model with well-characterized squamate community data from 163 Mediterranean islands to assess how past geographical changes influenced community structure. We evaluate phylogenetic and functional community structure and test links to paleogeographic variables. Our findings suggest phylogenetic overdispersion (co-occurring species being more distantly related than expected by chance) dominates and is higher on older islands, implying ongoing community relaxation and that extinctions are driven more by interspecific competition than environmental filtering. Island time-since-isolation emerges as the strongest predictor of phylogenetic structuring, indicating that longer isolation drives phylogenetic overdispersion via selective extinction of close relatives. These results underline the significance of relaxation dynamics in shaping insular communities.
Accurate prediction of thermal conductivity in (nano-PEG) composites is essential for accelerating thermal management material design. This study develops a hybrid Random Forest (RF) framework optimized using eight evolutionary algorithms, including (PSO), (GA), (WOA), (GWO), (CSA), (FPA), (FA), and (BA). A dataset of 229 experimental observations was used to model thermal conductivity as a function of temperature, PEG molecular weight, nanoparticle concentration, and nanoparticle form. Among evaluated models, the Bat Algorithm-optimized RF (RF-BA) achieved highest predictive efficiency with R2 = 0.995406, MSE = 0.000196, and AARE = 1.291%, while the PSO-optimized model (RF-PSO) demonstrated the fastest optimization runtime (96.9 s) with competitive accuracy. Correlation and SHAP analyses revealed nanoparticle concentration as the dominant factor governing thermal conductivity (correlation coefficient = 0.75), followed by PEG molecular weight (0.56), temperature (0.33), and nanoparticle form (0.24). The results demonstrate that evolutionarily optimized ensemble learning provides a reliable and computationally efficient strategy for thermophysical property prediction in nano-PEG composites, offering a practical alternative to extensive experimental characterization.