In this study, direct numerical simulations were conducted to investigate turbulent channel flow under the influence of a spanwise magnetic field, at a friction Reynolds number $ \textit{Re}_{\tau } = 180$ and Hartmann numbers $\textit{Ha}$ ranging from 0 to 15. The study elucidates how the spanwise magnetic field modulates energy spectra, near-wall streaks and energy transfer. With increasing $\textit{Ha}$, near-wall streamwise streaks elongate markedly and energetic spectral peaks move away from the wall, whereas the spanwise length of streak enlarges only marginally. At $\textit{Ha}=15$, dual spectral peaks appear near the wall, reflecting coexisting high- and low-momentum regions that alternate to form a quasi-steady organisation. Concurrently, an additional very large-scale peak arises in the outer layer ($y\gt 0.3h$), indicating a very large-scale structure that abruptly amplifies the streamwise normal stress there beyond the zero-magnetic-field level. Temporal statistics show that stronger fields reduce streak density but substantially prolong streak lifetimes, attributable to suppression of the nonlinear energy cascade and the attendant decrease in turbulent decay rates. Budget analyses further reveal that, as the field intensifies, the influence of outer-layer large scales on the viscous sublayer weakens; the dominant contributors to wall-normal energy transport shift towards larger scales; and principal energy-transfer pathways migrate away from the near-wall region. Finally, the streamwise elongation of streaks is primarily driven by the wall-normal gradient of the electric potential, while their energetic amplification is effectively damped by Joule dissipation.

This study was conducted to explore the effects of organic trace elements on milk composition, serum trace element concentrations, antioxidant and immune function, and metabolites in dairy cows. Thirty Holstein cows with similar body condition scores (3.5 ± 0.25 points) and parity were randomly divided into a control group (C), a 50% organic group (O_50), and a 100% organic group (O_100), with 10 cows in each group. The C group was fed a basal diet supplemented with 3% inorganic trace element premix, the O_50 group received 1.5% inorganic and 1.5% organic trace element premix, and the O_100 group received 3% organic trace element premix. Organic trace elements were supplemented from 21 days postpartum for 90 days. The results showed that milk protein concentration showed a linear response to organic trace element supplementation, with the highest value in the O_50 group (P < 0.05). Lactose concentration showed an increased quadratic effect (P < 0.01), whereas total solids (TS) and solid-not-fat (SNF) concentrations decreased linearly and quadratically. Serum selenium (Se) concentration increased linearly with increasing organic trace element supplementation (P < 0.05). Malondialdehyde (MDA) concentration decreased linearly (P < 0.05), whereas serum immunoglobulin A (IgA), superoxide dismutase activity, and immunoglobulin G (IgG) concentration increased significantly (P < 0.05). Liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis identified 70 and 76 differential metabolites in the O_50 and O_100 groups, respectively, compared with the C group. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that these metabolites were mainly involved in inflammatory mediator regulation, lysine degradation, sphingolipid metabolism, cytochrome P450-mediated drug metabolism, and ABC transporters. In conclusion, dietary supplementation with organic trace elements improved milk composition, antioxidant capacity, immune function, and serum metabolic profiles in dairy cows.

Previous studies highlighted the health benefits of coffee and tea, but they only focused on the comparisons between different consumptions. Consequently, the association estimate lacked a clear interpretation, as the substitution of beverages and distribution of doses were not explicitly prescribed. We focused on the ‘relative association’ to ascertain the optimal consumption strategy (including total intake and optimal allocation strategy) for coffee, tea and plain water associated with decreased mortality. Self-reported coffee, tea and plain water intake were used from the UK Biobank. Within a compositional data analysis framework, a multivariate Cox model was used to assess the relative associations after adjusting for a range of potential confounders. The lower mortality risk was observed with at least approximately 7–8 drinks/d of total consumption. When the total intake > 4 drinks/d, substituting plain water with coffee or tea was linked to reduced mortality; nevertheless, the benefit was not seen for ≤ 4 drinks/d. Besides, a balanced consumption of coffee and tea (roughly a ratio of 2:3) associated with the lowest hazard ratios of 0·55 (95 % CI 0·47, 0·64) for all-cause mortality, 0·59 (95 % CI 0·48, 0·72) for cancer mortality, 0·69 (95 % CI 0·49, 0·99) for CVD mortality, 0·28 (95 % CI 0·15, 0·52) for respiratory disease mortality and 0·35 (95 % CI 0·15, 0·82) for digestive disease mortality than other combinations. These results highlight the importance of the rational combination of coffee, tea and plain water, with particular emphasis on ensuring adequate total intake, offering more comprehensive and explicit guidance for individuals.

Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.

Large-eddy simulations have been conducted to investigate the decay law of homogeneous turbulence influenced by a magnetic field within a cubic domain, employing periodic boundary conditions. The initial integral Reynolds number is approximately 1000, while the initial interaction number $N$ ranges from 0.1–100. The results reveal that the Joule cone angle $\theta$, half of the Joule cone, decays as $\cos \theta \sim t^{-1/2}$ when $N \gg 1$. In the nonlinear stage, small-scale vortices gradually recover and restore three-dimensionality. Moreover, the corresponding critical state at small scales, marking the transition from quasi-two-dimensional structure to the onset of three-dimensionality, has been quantitatively defined. During the linear stage, based on the true magnetic damping number ($\tau _t = \rho / (\sigma {\boldsymbol{B}}^2 \cos ^2 \psi )$, where $\sigma$, $\boldsymbol{B}$ and $\psi$ denote the electrical conductivity, magnetic field and the angle between the wavevector and $\boldsymbol{B}$ in Fourier space, respectively), Moffatt’s decay law, $K \sim t^{-1/2}$, manifests at distinct times and zones in the Fourier space, with $K$ signifying turbulent kinetic energy. In the nonlinear stage, for $N \gg 1$, a $-3$ slope in the energy power spectrum is prominently observed over an extended period. The near-equivalence of the characteristic time scales of inertial and Lorentz forces in the inertial subrange suggests a quasiequilibrium state between energy transfer and Joule dissipation in Fourier space, thereby corroborating the hypothesis proposed by Alemany et al. 1979 Journal de Mecanique 18(2): 277–313. Additionally, it is observed that pressure mediates energy transfer from horizontal kinetic energy ($K_{\parallel }$) to vertical kinetic energy ($K_{\bot }$), accelerating the decay of $K_{\parallel }$. Notably, concurrent inverse and direct energy transfers emerge during the decay process. Our analysis reveals that the ratio $R$ of the maximum inverse to maximum direct energy flux correlates with the dimensionality of the turbulence, following the scaling law $R\sim (\cos \theta )^{-2.2}$.

Schistosomiasis is a parasitic disease that imposes a significant burden on society. The eggs are the primary pathogenic factor in schistosomiasis, and their accumulation in liver could lead to the formation of granulomas and liver fibrosis. However, the metabolic changes in liver resulting from schistosomiasis remain poorly understood. We established a mouse model of schistosomiasis japonica, where the eggs accumulate in the liver and form egg granulomas. We used mass spectrometry imaging to analyze the differences in metabolites among various liver regions, including the liver tissue from normal mice, the liver area outside the granulomas in schistosomiasis mice, and the granuloma region in schistosomiasis mice. There were significant differences in metabolites between different liver regions, which enriched in metabolic pathways such as the biosynthesis of unsaturated fatty acids, taurine and hypotaurine metabolism, glycerophospholipid metabolism, glycolysis/gluconeogenesis, purine metabolism, arachidonic acid metabolism, and bile secretion. In normal liver tissue, higher concentrations of oleic acid (FA (18:1)), eicosapentaenoic acid (FA (20:5)), and L-glutamine were observed. In liver regions outside the granulomas, D-glucose and pyruvic acid were elevated compared to those in normal mice. Taurine increased in the liver of schistosomiasis. Meanwhile, there were elevated uric acid and spermidine in the egg granulomas. We employed mass spectrometry imaging technology to investigate metabolic reprogramming in liver of Schistosoma japonicum-infected mice. We explored the spatial distribution of differential metabolites in liver of schistosomiasis including unsaturated fatty acids, taurine, glutamine, spermidine, and uric acid. Our research provides valuable insights for further elucidating metabolic reprogramming in schistosomiasis.

Isolated multi-MeV $\gamma$-rays with attosecond duration, high collimation and beam angular momentum (BAM) may find many interesting applications in nuclear physics, astrophysics, etc. Here, we propose a scheme to generate such $\gamma$-rays via nonlinear Thomson scattering of a rotating relativistic electron sheet driven by a few-cycle twisted laser pulse interacting with a micro-droplet target. Our model clarifies the laser intensity threshold and carrier-envelope phase effect on the generation of the isolated electron sheet. Three-dimensional numerical simulations demonstrate the $\gamma$-ray emission with 320 attoseconds duration and peak brilliance of $9.3\times 10^{24}$ photons s${}^{-1}$ mrad${}^{-2}$ mm${}^{-2}$ per 0.1$\%$ bandwidth at 4.3 MeV. The $\gamma$-ray beam carries a large BAM of $2.8 \times 10^{16}\mathrm{\hslash}$, which arises from the efficient BAM transfer from the rotating electron sheet, subsequently leading to a unique angular distribution. This work should promote the experimental investigation of nonlinear Thomson scattering of rotating electron sheets in large laser facilities.

Artificial sweeteners are generally used and recommended to alternate added sugar for health promotion. However, the health effects of artificial sweeteners remain unclear. In this study, we included 6371 participants from the National Health and Nutrition Examination Survey with artificial sweetener intake records. Logistic regression and Cox regression were applied to explore the associations between artificial sweeteners and risks of cardiometabolic disorders and mortality. Mendelian randomisation was performed to verify the causal associations. We observed that participants with higher consumption of artificial sweeteners were more likely to be female and older and have above medium socio-economic status. After multivariable adjustment, frequent consumers presented the OR (95 % CI) for hypertension (1·52 (1·29, 1·80)), hypercholesterolaemia (1·28 (1·10, 1·50)), diabetes (3·74 (3·06, 4·57)), obesity (1·52 (1·29, 1·80)), congestive heart failure (1·89 (1·35, 2·62)) and heart attack (1·51 (1·10, 2·04)). Mendelian randomisation confirmed the increased risks of hypertension and type 2 diabetes. Moreover, an increased risk of diabetic mortality was identified in participants who had artificial sweeteners ≥ 1 daily (HR = 2·62 (1·46, 4·69), P = 0·001). Higher consumption of artificial sweeteners is associated with increased risks of cardiometabolic disorders and diabetic mortality. These results suggest that using artificial sweeteners as sugar substitutes may not be beneficial.

The assessment of seed quality and physiological potential is essential in seed production and crop breeding. In the process of rapid detection of seed viability using tetrazolium (TZ) staining, it is necessary to spend a lot of labour and material resources to explore the pretreatment and staining methods of hard and solid seeds with physical barriers. This study explores the TZ staining methods of six hard seeds (Tilia miqueliana, Tilia henryana, Sassafras tzumu, Prunus subhirtella, Prunus sibirica, and Juglans mandshurica) and summarizes the TZ staining conditions required for hard seeds by combining the difference in fat content between seeds and the kinship between species, thus providing a rapid viability test method for the protection of germplasm resources of endangered plants and the optimization of seed bank construction. The TZ staining of six species of hard seeds requires a staining temperature above 35 °C and a TZ solution concentration higher than 1%. Endospermic seeds require shorter staining times than exalbuminous seeds. The higher the fat content of the seeds, the lower the required incubation temperature and TZ concentration for staining, and the longer the staining time. And the closer the relationship between the two species, the more similar their staining conditions become. The TZ staining method of similar species can be predicted according to the genetic distance between the phylogenetic trees, and the viability of new species can be detected quickly.

Energy loss of protons with 90 and 100 keV energies penetrating through a hydrogen plasma target has been measured, where the electron density of the plasma is about 1016 cm−3 and the electron temperature is about 1-2 eV. It is found that the energy loss of protons in the plasma is obviously larger than that in cold gas and the experimental results based on the Bethe model calculations can be demonstrated by the variation of effective charge of protons in the hydrogen plasma. The effective charge remains 1 for 100 keV protons, while the value for 90 keV protons decreases to be about 0.92. Moreover, two empirical formulae are employed to extract the effective charge.