Blackgrass is a highly competitive weed in wheat fields and has increasingly evolved resistance to acetolactate synthase (ALS)-inhibiting herbicides. Ten field populations were screened, resulting in the selection of one highly resistant population (R-06) and one susceptible population (S-19) for detailed study. Whole-plant bioassays, ALS gene sequencing, molecular docking, metabolic inhibitor assays, glutathione S-transferase (GST) and ALS activity assays, and cross-resistance profiling were conducted to dissect the mechanisms of resistance. ALS sequencing identified three amino acid substitutions in R-06: Pro232Thr (P232T), His363Lys (H363K), and Trp574Leu (W574L). While W574L is a well-characterized ALS resistance-conferring mutation, P232T and H363K are outside major resistance hotspots and may serve secondary or compensatory roles. Molecular docking analyses predicted altered binding of mesosulfuron-methyl in the mutant ALS model, consistent with structural changes in the binding pocket. Metabolic inhibitor assays using malathion, piperonyl butoxide (PBO), and NBD-Cl resulted in modest increases in herbicide sensitivity, with a maximum reduction factor of 2.95 for PBO. GST activity was higher in R-06 at a single sampling time point (3 DAT). In addition, R-06 showed reduced sensitivity to several ALS inhibitors and reduced efficacy against selected herbicides with alternative modes of action. High-level resistance to mesosulfuron-methyl in the R-06 population is primarily associated with the ALS target-site mutation Trp574Leu, while the roles of Pro232Thr, His363Lys, and metabolism appear secondary and remain unresolved. These findings highlight complex resistance patterns in blackgrass and emphasize the need for diversified and integrated weed management strategies.

Neonates are highly susceptible to infection, a major cause of neonatal death, given their immature immune system. Comprehensive studies examining multiple immune-response-related proteins in relation to neonatal infection are scarce. We conducted a nested case-control study within the Shenzhen Baoan Birth and Twin (SZBBTwin) cohort, measuring 92 immune-response-related proteins in cord plasma of 149 twins (including 34 discordant twin pairs) with proximity extension assay. All twins were followed for clinical diagnoses of infection from birth until 27 days of age. Wilcoxon rank-sum test was used to determine differentially abundant proteins (DAPs) between infected and noninfected neonates, the predictive performance of which was evaluated by receiver operating characteristic curves, and their functions and pathways were annotated through enrichment analysis. Logistic regression was used to assess the associations between levels of proteins and risk of neonatal infection. Finally, five DAPs (ITGA11, FCRL6, DDX58, SH2D1A, and EDAR) were identified for neonatal infection, and the area under the curve of the five DAPs achieved 0.835 for infection prediction. Enrichment analysis indicated that five DAPs were mainly involved in immune function and cell binding, and they were mainly enriched in the nuclear factor kappa-B pathway. A higher level of ITGA11 was associated with an increased risk of neonatal infection in all twins (OR 3.00; 95% CI [1.33, 6.78]) and discordant twin pairs (OR 5.50; 95% CI [1.20, 25.23]). In conclusion, multiple immune-response-related proteins in cord plasma, particularly ITGA11, are associated with the risk of neonatal infection in twins.

Recruitment and retention challenges continue to hinder the success of clinical trials. Artificial intelligence (AI) has emerged as a promising means to optimize various clinical trial processes; however, its impact specifically on recruitment and retention has not been comprehensively evaluated. This scoping review utilized the Joanna Briggs Institute framework and adhered to PRISMA-ScR guidelines, systematically searching literature published between January 2018 and June 2024 across multiple databases. Of the 21,573 records screened, 121 studies were included. A meta-analysis was conducted to quantitatively assess the performance of AI-driven tools. AI applications for patient screening demonstrated strong performance, achieving a pooled sensitivity of 0.91 (95% CI: 0.84–0.95) and an area under the curve (AUC) of 0.79 (95% CI: 0.72–0.85). AI tools employed for eligibility identification and classification also exhibited strong outcomes, with pooled sensitivities of 0.80 (95% CI: 0.76–0.84) and 0.92 (95% CI: 0.84–0.96), respectively, and precisions of 0.84 (95% CI: 0.80–0.88) and 0.91 (95% CI: 0.85–0.95). AI tools aimed at identifying patient cohorts showed moderate effectiveness (pooled sensitivity: 0.70 [95% CI: 0.52–0.84]; AUC: 0.74 [95% CI: 0.61–0.84]). Overall, AI presents significant potential for enhancing clinical trial recruitment and retention, with effectiveness varying across specific applications. These findings underscore AI’s valuable role in improving trial efficiency and data quality.

Clay minerals in the Yishu fault zone, as typical products of hydrothermal activity, carry critical information regarding subsurface geothermal processes. To clarify their hyperspectral remote sensing characteristics and their guiding value for geothermal resource exploration, this study takes the Yishu fault zone and three key subareas (Tangtou, Tongjing and Fangzi) as the research objects. Based on ZY1-02D hyperspectral remote sensing data, combined with principal component analysis and the Crósta method, we analysed the spectral features of typical clay minerals (illite, montmorillonite and chlorite) and extracted their spatial distribution patterns. In addition, ZY1-02E thermal infrared data were used to invert the land surface temperature so as to explore the spatial correlation between clay mineral distribution and geothermal anomalies. The results show that the spatial distribution of clay minerals is closely associated with fault structures, being mainly concentrated along the four major fault belts of the Yishu fault zone and their surrounding areas. High-intensity hydrothermal alteration zones dominated by clay minerals exhibit significant spatial overlap with surface temperature anomalies. The consistent distribution of clay minerals and known geothermal fields further confirms that the hyperspectral characteristics of clay minerals can effectively indicate the upwelling channels and accumulation zones of geothermal fluids. This study provides a rapid and accurate technical method for geothermal resource prospecting in the Yishu fault zone and other tectonically similar regions.

Surfactants at the air–sea interface are known to alter surface wave dynamics by modifying surface tension and Marangoni stresses. In this study, we perform two-dimensional direct numerical simulations of gravity-capillary waves with insoluble surfactants using a coupled phase field and volume-of-fluid method. We consider a nonlinear equation of state for surface tension and resolve Marangoni stresses induced by surfactant concentration gradients. We explore a broad parameter space characterised by initial wave steepness $ak$, Bond number $\textit{Bo}$ (comparing gravity and surface tension), Reynolds number $\textit{Re}$ (comparing inertia and viscosity), and the importance of surfactant concentration and strength of the gradient, characterised by a surfactant parameter $\beta$. We analyse the impact of surfactants on wave patterns, surface roughness, wave breaking, energy dissipation and surface vorticity. Our results reveal a non-monotonic dependence of wave shape, roughness, vorticity and energy dissipation on $\beta$, which is found to be governed by Marangoni effects that peak at intermediate surfactant concentrations. Wave regime transition at high $\textit{Bo}$ is governed by an effective $\textit{Bo}$, which accounts for the reduction in surface tension induced by surfactants. We further introduce a rescaled parameter $\textit{Bo}\,\textit{Re}^{-1/2}\,(ak)^{-1}$ based on force balance, which collapses the transition boundaries across different $\textit{Re}$. These findings provide a systematic understanding of surfactant-modulated wave dynamics for both laboratory and geophysical applications.

Sexual dimorphism, a widespread phenomenon, has been extensively researched in extant and fossil crustaceans. However, identifying sexual dimorphism in phyllocarid fossils preserved as isolated parts is often challenging, except in cases where the specimens are exceptionally well preserved, including those with soft tissues. This study proposes a novel approach by introducing the use of geometric morphometric techniques to identify sexual dimorphism in phyllocarid fossils based on carapace morphology. It presents a comprehensive re-analysis of Soomicaris ordosensis Liu et al., 2023a, carapaces from the Upper Ordovician in North China and Tarim Plates. Elliptic Fourier analysis was applied to quantify the size and shape variation in nearly 100 specimens. The results demonstrate the presence of significant sexual dimorphism in the length and shape of the S. ordosensis carapace. The carapace shape exhibited variation between the sexes: the posterodorsal margin of one group of carapaces gradually extends backward to form a posterodorsal spine; the carapaces of the other group have a convex posterior margin and lack a posterodorsal spine. Additionally, both types manifest an overall allometric growth pattern, albeit with distinct growth coefficients. Furthermore, the observed approximately 1:1 ratio between the two forms suggests that the population of S. ordosensis may have exhibited a dioecious mating system. Geometric morphometrics are a highly effective method for elucidating the subtle variations in the carapace morphology of S. ordosensis, thereby underscoring the cryptic dimorphism characteristics of fossil animals. This finding offers the first indirect evidence for egg-brooding behavior within the extinct order Archaeostraca.

To determine values for the digestible indispensable amino acid score (DIAAS), it is recommended that ileal amino acid (AA) digestibility values obtained in growing pigs are used to characterise protein quality in different foods. Therefore, an experiment was conducted to determine the standardised ileal digestibility (SID) of AA in eight energy ingredients (barley, sorghum, wheat, brown rice, rice bran, wheat bran, cassava and paddy rice) fed to pigs, where SID values in pigs can be used to calculate approximate DIAAS values in humans. Among the data obtained for all energy ingredients, significant variations (P < 0·01) in CP and AA composition were observed. Rice bran and wheat bran had the highest CP (16·43 % and 18·16 %, respectively) and DIAAS scores of 81–88 for adult, qualifying as ‘good’ protein sources (> 75). Cassava, with the lowest CP (2·74 %), was limited by sulphur amino acid (54). Lysine (Lys) was the first-limiting AA in barley (74), sorghum (51) and wheat (49), with SID values lowest in wheat (71·04 %). Brown rice and paddy rice showed higher SIDLys (87·51 % and 78·13 %, respectively). These findings highlight the potential of bran-based ingredients and Lys fortification to improve protein quality in grain-dependent diets, providing the scientific basis to combat protein malnutrition.

Species in the genus Echinochloa present a major management challenge in rice production worldwide. Understanding the herbicide resistance status of Echinochloa is crucially necessary for raising awareness and developing effective management programs. This study investigated the status of herbicide resistance by junglerice, the predominant Echinochloa species in Texas rice fields. A total of 58 junglerice populations collected during a field survey (2015–2016) of Texas rice fields were screened with two preemergence herbicides; quinclorac (Group 4) and clomazone (Group 13); and four postemergence herbicides: fenoxaprop (Group 1), imazethapyr (Group 2), quinclorac (Group 4), and propanil (Group 5). At 21 d after application (DAA) of herbicide treatments, percent survival, and percent visible injury data were recorded. Based on the injury levels observed, the populations were categorized into being either putative resistant (≤50% injury), less sensitive (51% to 90% injury), or susceptible (≥91% injury). Results showed that herbicide resistance is widespread among the junglerice populations surveyed in Texas. About 5% of the populations showed multiple resistance to all four postemergence herbicides that were evaluated. Dose-response assays were conducted on the populations with the lowest injury ratings to determine the extent of resistance and revealed a >70-fold resistance to imazethapyr, a >15-fold resistance to propanil, and a 3-fold resistance to fenoxaprop, compared with a susceptible check. The results suggested that integrated management practices are needed to manage junglerice in Texas rice production.

We examine how ambient temperature $T$ (23–90 $^\circ \mathrm{C}$) alters the dynamics of spark-induced cavitation bubbles across a range of discharge energies. As $T$ rises, the collapse of an isolated spherical bubble weakens monotonically, as quantified by the Rayleigh collapse factor, minimum volume and maximum collapse velocity. When the bubble is generated near a rigid wall, the same thermal attenuation is reflected in reduced jet speed and diminished migration. Most notably, at $T \gtrsim 70\,^\circ \text{C}$, we observe a previously unreported phenomenon: secondary cavitation nuclei appear adjacent to the primary bubble interface where the local pressure falls below the Blake threshold. The pressure reduction is produced by the over-expansion of the primary bubble itself, not by rarefaction waves as suggested in earlier work. Coalescence between these secondary nuclei and the parent bubble seeds pronounced surface wrinkles that intensify Rayleigh–Taylor instability and promote fission, providing an additional route for collapse strength attenuation. These findings clarify the inception mechanism of high-temperature cavitation and offer physical insight into erosion mitigation in heated liquids.

This paper introduces a high single-pulse energy, narrow-linewidth mid-infrared self-optical parametric oscillator (mid-IR SOPO) with a cavity length of 120 mm and a Nd:MgO:PPLN crystal. To achieve high single-pulse energy and high peak power in mid-IR light sources, a LiNbO3 electro-optic Q-switch (EOQ) is introduced for the first time in a mid-IR SOPO. A narrow-linewidth EOQ-SOPO rate equation is formulated, and experiments are conducted using a single Fabry–Pérot etalon. At a 500 μs pump pulse width, a 4.71 mJ single-pulse idler light at 3838.2 nm is achieved, with a linewidth of 0.412 nm, single-pulse width of 4.78 ns and peak power of 985 kW. At 200 μs, the idler light at 3845.2 nm exhibits a minimum linewidth of 0.212 nm.

This paper introduces a novel ray-tracing methodology for various gradient-index materials, particularly plasmas. The proposed approach utilizes adaptive-step Runge–Kutta integration to compute ray trajectories while incorporating an innovative rasterization step for ray energy deposition. By removing the requirement for rays to terminate at cell interfaces – a limitation inherent in earlier cell-confined approaches – the numerical formulation of ray motion becomes independent of specific domain geometries. This facilitates a unified and concise tracing method compatible with all commonly used curvilinear coordinate systems in laser–plasma simulations, which were previously unsupported or prohibitively complex under cell-confined frameworks. Numerical experiments demonstrate the algorithm’s stability and versatility in capturing diverse ray physics across reduced-dimensional planar, cylindrical and spherical coordinate systems. We anticipate that the rasterization-based approach will pave the way for the development of a generalized ray-tracing toolkit applicable to a broad range of fluid simulations and synthetic optical diagnostics.

Hand, foot, and mouth disease (HFMD) shows spatiotemporal heterogeneity in China. A spatiotemporal filtering model was constructed and applied to HFMD data to explore the underlying spatiotemporal structure of the disease and determine the impact of different spatiotemporal weight matrices on the results. HFMD cases and covariate data in East China were collected between 2009 and 2015. The different spatiotemporal weight matrices formed by Rook, K-nearest neighbour (KNN; K = 1), distance, and second-order spatial weight matrices (SO-SWM) with first-order temporal weight matrices in contemporaneous and lagged forms were decomposed, and spatiotemporal filtering model was constructed by selecting eigenvectors according to MC and the AIC. We used MI, standard deviation of the regression coefficients, and five indices (AIC, BIC, DIC, R2, and MSE) to compare the spatiotemporal filtering model with a Bayesian spatiotemporal model. The eigenvectors effectively removed spatial correlation in the model residuals (Moran’s I < 0.2, p > 0.05). The Bayesian spatiotemporal model’s Rook weight matrix outperformed others. The spatiotemporal filtering model with SO-SWM was superior, as shown by lower AIC (92,029.60), BIC (92,681.20), and MSE (418,022.7) values, and higher R2 (0.56) value. All spatiotemporal contemporaneous structures outperformed the lagged structures. Additionally, eigenvector maps from the Rook and SO-SWM closely resembled incidence patterns of HFMD.

Research on the association between the Chinese visceral adiposity index (CVAI) and hyperuricaemia (HUA) is scarce, and whether the association differs by sex is unclear. This research aimed to explore sex-specific associations between CVAI and HUA and to compare CVAI’s predictive performance with other adiposity indices using data from 22 171 adults (30–79 years) in the China Multi-Ethnic Cohort study (Chongqing region). The prevalence of HUA was 20·9 % in men and 9·7 % in women. Multivariable logistic regression analyses were utilised to assess the adjusted OR and 95 % CI. After multivariable adjustment, CVAI was associated with HUA in men (OR Q4 v. Q1 = 3·31, 95 % CI 2·73, 4·03) and women (OR Q4 v. Q1 = 7·20, 95 % CI 5·12, 10·12). Moreover, significant interactions were observed between BMI and CVAI on HUA in both sexes (all Pinteraction < 0·001), with the strongest associations in those with BMI < 24·0 kg/m2. The OR (95 % CI) across different BMI groups (< 24·0, 24·0–27·9, ≥ 28·0 kg/m²) were 1·87 (1·63, 2·13), 1·65 (1·48, 1·85) and 1·30 (1·14, 1·49) for men and 2·76 (2·18, 3·51), 2·46 (1·98, 3·07) and 1·87 (1·47, 2·39) for women, respectively. Additionally, CVAI showed satisfactory predictive performance for HUA in women, with the largest area under the receiver operating characteristic curve of 0·735, but not in men (0·660). These findings suggest a close association between CVAI and HUA, particularly pronounced in those with BMI < 24·0 kg/m², and a stronger association in women than in men.