Trichostrongylus spp. are globally distributed gastrointestinal nematodes that affect ruminants and humans, posing significant veterinary and public health challenges. Despite their zoonotic potential, the temporal dynamics of Trichostrongylus infection remain poorly understood globally. This study aimed to estimate long-term trends in Trichostrongylus prevalence in humans, ovines, and bovines using time series modelling. A systematic review identified 240 eligible studies with annual prevalence data across 60 countries. Following Kalman smoothing, annual prevalence time series were constructed for each host species covering 1947–2024 for humans, 1966–2024 for ovines, and 1962–2024 for bovines. ARIMA models were fitted separately: ARIMA(0,1,1) for humans, ARIMA(3,0,0) for ovines, and ARIMA(0,1,1) for bovines. Model selection was based on Stationary R2, RMSE, MAPE, and the Ljung-Box Q test for residual independence. Forecast 95% confidence intervals were reported to convey uncertainty in the projected trends. All three models demonstrated good in-sample fit and adequate residual diagnostics. Infection rates in humans and bovines are projected to decline, from 4.64% to 3.73% in humans and from 20.11% to 11.76% in bovines by 2034. In contrast, the ovine model forecasts an increase in infection rates, from 6.50% to 15.56%. This increase in ovines may reflect greater pasture exposure and environmental persistence of infective larvae, while improvements in hygiene and livestock management likely contribute to the declining trends observed in humans and bovines. The rising infection rate in ovines, coupled with sustained zoonotic risk, underscores the need for integrated One Health surveillance and control efforts.

The threshold values of visceral fat area (VFA) proposed by existing studies for predicting metabolic syndrome (MetS) are contentious, necessitating further empirical evidence. We conducted a cross-sectional study to assess VFA using bioelectrical impedance analysis technology among middle-aged and elderly individuals in the Sichuan area of China. First, we compared the predictive ability of VFA, waist circumference (WC) and body mass index (BMI) among participants with MetS (excluding WC). In males, the area under the receiver operating characteristic curve (AUC) was 0·680 for VFA, 0·670 for WC and 0·665 for BMI, with corresponding optimal cut-off values of 77·45 cm2, 83·50 cm and 24·19 kg/m2. In females, the AUC values and optimal cut-offs were 0·628 (103·55 cm2) for VFA, 0·671 (77·50 cm) for WC and 0·643 (24·32 kg/m2) for BMI. Additionally, for MetS defined with WC included, the AUC of VFA for prediction was higher in males (0·785) than in females (0·717), with optimal cut-offs of 85·15 cm2 (males) and 109·55 cm2 (females). Further age-stratified analysis revealed sex-specific VFA cut-offs: in males, 80·95 cm2 (45–59 years), 85·15 cm2 (60–74 years) and 77·50 cm2 (≥ 75 years); in females, 109·65 cm2 (45–59 years), 112·15 cm2 (60–74 years) and 103·05 cm2 (≥ 75 years). In conclusion, VFA is an effective predictor of MetS, with its optimal cut-off value varying by age and being higher in females than in males.

Based on the characteristics of the variable pivot gait during the human load-carrying, this paper proposes a double-leg coordination assistance principle for load-carrying: assisting support of the guiding leg at the heel-pivot stage by the spring to reduce the collision, which can reduce the ankle moment of the following leg that is performing the push-off at the toe-pivot stage. A novel unpowered load-carrying exoskeleton (ULE) with a double-support closed-chain configuration is designed, and the theoretical verification is carried out. Five subjects participate in the load-carrying and metabolic cost experiments for assisting and energy-saving effect evaluation, and the angle and moment of human joints, plantar pressure, spring compression and human net metabolic rate are analyzed. Compared with carrying load by the human alone, wearing the novel ULE with spring reduces the human peak ankle moment performing the push-off by up to 11.9 ± 1.6% (Mean±SE, 10 kg), average ankle moment over the support phase by up to 36.8 ± 9.1% (Mean±SE, 5 kg) and the average vertical plantar pressure by up to 8.1 ± 1%% (Mean±SE, 15 kg). Meanwhile, wearing the novel ULE reduces the human net metabolic rate by 5.6 ± 0.5% (Mean±SE, 10 kg), 4.1 ± 0.7% (Mean±SE, 15 kg) and 5.9 ± 1.6% (Mean±SE, 20 kg). The results show that the novel ULE can provide support and joint moment assistance over the whole support phase while reducing human net metabolic rate. This study can also be applied to the powered load-carrying exoskeleton, providing a new avenue.

An experimental study of the equation of state for metallic powders under impact loading was carried out at a high-energy laser facility. A laser-ablatable micro-target was obtained to satisfy the laser equation of state for experimental study, and the precise characterization of the initial density was realized. The technique boosts the pressure of copper powder to 1400 GPa. The data consistency can effectively distinguish the data trends under different initial densities (~4.05 and 4.50 g/cm3). Experimental data can effectively distinguish the differences between the high-pressure Thomas–Fermi model and the Thomas–Fermi–Kirzhnits model, providing strong support for the WEOS-Pα model of the Institute of Applied Physics and Computational Mathematics, which is more in line with the actual state description of the material. This experimental technique can be extended to study the high-pressure physical properties of other powder particles.

Based on the stubbed coupled line for matching a load, we design an impedance transformer matched the load of ${{\text{Z}}_{\text{L}}} = 100{\Omega }$, working at four frequencies in this paper. This proposed transformer comprises two sections of coupled line constructed from parallel-coupled transmission lines. Two different types of the proposed transformer are given and analyzed, and we derive carefully about the open-circuit form equations for impedance transformer. We fabricate an impedance transformer to certify the validity of design equations theoretically, and the frequency is measured at 0.7/2.4/3.6/5.3 GHz. The measured results are in good agreement with the simulated results at each frequency.

The Chinese pangolin Manis pentadactyla is categorized as Critically Endangered on the IUCN Red List, but the development of effective conservation strategies is hindered by a lack of data on its distribution range and population dynamics. In addition, standardized survey and analysis methods are required to facilitate the sharing of results and maximize conservation effectiveness. To fill these knowledge and methodological gaps, we investigated the occurrence of pangolin burrows in the subtropical forest ecosystem of Fujian, China. We surveyed a total of 70 transects across five land-cover types within the Fujian Junzifeng National Nature Reserve and detected 87 burrows. The majority of burrows (87%) were located in mixed conifer and broadleaf forests. We used six environmental variables in a generalized linear model to examine the relationship between the occurrence of burrows and environmental factors. The average model results from the best model set showed that the distribution of burrows was significantly influenced by forest type. For effective pangolin conservation, we recommend that local conservation authorities prioritize the protection of mixed conifer and broadleaf forests. Our findings support the local conservation of the Chinese pangolin and the standardization of surveys and conservation efforts across the species’ range.

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.

Emission line galaxies (ELGs) are crucial for cosmological studies, particularly in understanding the large-scale structure of the Universe and the role of dark energy. ELGs form an essential component of the target catalogue for the Dark Energy Spectroscopic Instrument (DESI), a major astronomical survey. However, the accurate selection of ELGs for such surveys is challenging due to the inherent uncertainties in determining their redshifts with photometric data. In order to improve the accuracy of photometric redshift estimation for ELGs, we propose a novel approach CNN–MLP that combines convolutional neural networks (CNNs) with multilayer perceptrons (MLPs). This approach integrates both images and photometric data derived from the DESI Legacy Imaging Surveys Data Release 10. By leveraging the complementary strengths of CNNs (for image data processing) and MLPs (for photometric feature integration), the CNN–MLP model achieves a $\sigma_{\mathrm{NMAD}}$ (normalised median absolute deviation) of 0.0140 and an outlier fraction of 2.57%. Compared to other models, CNN–MLP demonstrates a significant improvement in the accuracy of ELG photometric redshift estimation, which directly benefits the target selection process for DESI. In addition, we explore the photometric redshifts of different galaxy types (Starforming, Starburst, AGN, and Broadline). Furthermore, this approach will contribute to more reliable photometric redshift estimation in ongoing and future large-scale sky surveys (e.g. LSST, CSST, and Euclid), enhancing the overall efficiency of cosmological research and galaxy surveys.

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.

Major depressive disorder (MDD) and coronary heart disease (CHD) can both cause significant morbidity and mortality. The association of MDD and CHD has long been identified, but the mechanisms still require further investigation. Seven mRNA microarray datasets containing samples from patients with MDD and CHD were downloaded from Gene Expression Omnibus. Combined matrixes of MDD and CAD were constructed for subsequent analysis. Differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on shared DEGs were conducted to identify pivotal pathways. A protein-protein network was also applied to further investigate the functional interaction. Results showed that 24 overlapping genes were identified. Enrichment analysis indicated that the shared genes are mainly associated with immune function and ribosome biogenesis. The functional interactions of shared genes were also demonstrated by PPI network analysis. In addition, three hub genes including MMP9, S100A8, and RETN were identified. Our results indicate that MDD and CHD have a genetic association. Genes relevant to immune function, especially IL-17 signalling pathway may be involved in the pathogenesis of MDD and CHD.

Loneliness and social isolation are prevalent concerns among older adults and can lead to negative health consequences and a reduced lifespan. New technologies are increasingly being developed to help address loneliness and social isolation in older adults, including monitoring systems, social networks, robots, companions, smart televisions, augmented reality (AR) and virtual reality (VR) applications. This systematic review maps human-centered design (HCD) and user-centered design (UCD) approaches, human needs, and contextual factors considered in current technological interventions designed to address the problems of loneliness and social isolation in older adults. We conducted a scoping review and in-depth examination of 98 papers through a qualitative content analysis. We found 12 studies applying either an HCD or UCD approach and observed strengths in continuous user involvement and implementation in field studies but limitations in participant inclusion criteria and methodological reporting. We also observed the consideration of important human needs and contextual factors. However, more research is needed on stakeholder perspectives, the functioning of applications in different housing environments, as well as studies that include diverse socio-economic groups.

Purple nutsedge (Cyperus rotundus L.) is one of the world’s resilient upland weeds, primarily spreading through its tubers. Its emergence in rice (Oryza sativa L.) fields has been increasing, likely due to changing paddy-farming practices. This study aimed to investigate how C. rotundus, an upland weed, can withstand soil flooding and become a problematic weed in rice fields. The first comparative analysis focused on the survival and recovery characteristics of growing and mature tubers of C. rotundus exposed to soil-flooding conditions. Notably, mature tubers exhibited significant survival and recovery abilities in these environments. Based on this observation, further investigation was carried out to explore the morphological structure, nonstructural carbohydrates, and respiratory mechanisms of mature tubers in response to prolonged soil flooding. Over time, the mature tubers did not form aerenchyma but instead gradually accumulated lignified sclerenchymal fibers, with lignin content also increasing. After 90 d, the lignified sclerenchymal fibers and lignin contents were 4.0 and 1.1 times higher than those in the no soil-flooding treatment. Concurrently, soluble sugar content decreased while starch content increased, providing energy storage, and alcohol dehydrogenase activity rose to support anaerobic respiration via alcohol fermentation. These results indicated that mature tubers survived in soil-flooding conditions by adopting a low-oxygen quiescence strategy, which involves morphological adaptations through the development of lignified sclerenchymal fibers, increased starch reserves for energy storage, and enhanced anaerobic respiration. This mechanism likely underpins the flooding tolerance of mature C. rotundus tubers, allowing them to endure unfavorable conditions and subsequently germinate and grow once flooding subsides. This study provides a preliminary explanation of the mechanism by which mature tubers of C. rotundus from the upland areas confer flooding tolerance, shedding light on the reasons behind this weed’s increasing presence in rice fields.

Dietary n-3 PUFA may have potential benefits in preventing peptic ulcer disease (PUD). However, data from observational epidemiological studies are limited. Thus, we conducted a Mendelian randomisation analysis to reveal the causal impact of n-3 PUFA on PUD. Genetic variants strongly associated with plasma levels of total or individual n-3 PUFA including plant-derived α-linolenic acid and marine-derived EPA, DPA and DHA were enrolled as instrumental variables. Effect size estimates of the n-3 PUFA-associated genetic variants with PUD were evaluated using data from the UK biobank. Per one sd increase in the level of total n-3 PUFA in plasma was significantly associated with a lower risk of PUD (OR = 0·91; 95 % CI 0·85, 0·99; P = 0·020). The OR were 0·81 (95 % CI 0·67, 0·97) for EPA, 0·72 (95 % CI 0·58, 0·91) for DPA and 0·87 (95 % CI 0·80, 0·94) for DHA. Genetically predicted α-linolenic acid levels in plasma had no significant association with the risk of PUD (OR = 5·41; 95 % CI 0·70, 41·7). Genetically predicted plasma levels of n-3 PUFA were inversely associated with the risk of PUD, especially marine-based n-3 PUFA. Such findings may have offered an effective and feasible strategy for the primary prevention of PUD.