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As cities like Beijing expand rapidly, green and blue spaces (GBS)—essential for ecosystem services (ESs) such as clean air, flood control, and recreation—are increasingly threatened. This 20-year study examines how urban expansion and policy interventions have shaped Beijing’s GBS. While green initiatives have increased natural areas, unchecked urban sprawl has fragmented these spaces, reducing their environmental benefits. Satellite data and urban planning analyses underscore a key lesson: maintaining well-connected natural zones is critical for urban resilience. These findings are broadly applicable for rapidly growing cities globally, urging urban planners to integrate ecological conservation with development, and to safeguard healthy environments and vibrant communities.
Technical Summary
This study quantifies the spatiotemporal dynamics of urban GBS in Beijing, evaluating their essential role in delivering ESs and strengthening urban resilience. Although China has achieved substantial progress in urban greening, the ecological impacts of rapid urbanization on GBS configuration and connectivity have not been comprehensively quantified. Using an integrated analytical framework combining principal component analysis and multiple linear regression, we reveal how urban development strategies have shaped GBS dynamics over two decades. A spatially explicit analysis, utilizing geographically weighted regression, further elucidates the heterogeneous relationships among the normalized difference vegetation index, human footprint index, and ESs delivery capacity. Notably, socioeconomic incentives and green infrastructure governance—especially objective indicators such as forest, garden, and greenspace area—have effectively driven GBS expansion. However, urban expansion has led to pronounced fragmentation of peri-urban GBS, suggesting potential degradation of their ecosystem service support functions. These findings emphasize the need for adaptive GBS management strategies that balance ecological conservation with sustainable urban growth in rapidly developing cities.
Social Media Summary
Urban growth fragments green and blue spaces, reducing vital ecosystem services. Balancing conservation with development is essential for sustainable cities.
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.
Milk fat is a crucial component for evaluating the production performance and nutritional value of goat milk. Previous research indicated that the composition of ruminal microbiota plays a significant role in regulating milk fat percentage in ruminants. Thus, this study aimed to identify key ruminal microorganisms and blood metabolites relevant to milk fat synthesis in dairy goats as a mean to explore their role in regulating milk fat synthesis. Sixty clinically healthy Xinong Saanen dairy goats at mid-lactation and of similar body weight, and similar milk yield were used in a feeding study for 15 days. Based on daily milk yield of dairy goats and the results of milk component determination on the 1st and 8th days, five goats with the highest milk fat content (H group) and five goats with the lowest milk fat content (L group) were selected for further analysis. Before the morning feeding on the 15th day of the experiment, samples of milk, blood and ruminal fluid were collected for analyses of components, volatile fatty acids, microbiota and metabolites. Results revealed that acetate content in the rumen of H group was greater compared with L group. H group had abundant beneficial bacteria including Ruminococcaceae_UCG-005, Saccharofermentans, Ruminococcaceae-UCG-002 and Prevotellaceae_UCG-3, which were important for plant cellulose and hemicellulose degradation and immune regulation. Metabolomics analysis revealed H group had greater relative concentrations of 4-acetamidobutanoic acid and azelaic acid in serum, and had lower relative concentrations of Arginyl-Alanine, SM(d18:1/12:0) and DL-Tryptophan. These altered metabolites are involved in the sphingolipid signaling pathway, arginine and proline metabolism. Overall, this study identified key ruminal microorganisms and serum metabolites associated with milk fat synthesis in dairy goats. These findings offer insights for enhancing the quality of goat milk and contribute to a better understanding of the regulatory mechanisms involved in milk fat synthesis in dairy goats.
Parental psychopathology is a known risk factor for child autistic-like traits. However, symptom-level associations and underlying mechanisms are poorly understood.
Methods
We utilized network analyses and cross-lagged panel models to investigate the specific parental psychopathology related to child autistic-like traits among 8,571 adolescents (mean age, 9.5 years at baseline), using baseline and 2-year follow-up data from the Adolescent Brain Cognitive Development study. Parental psychopathology was measured by the Adult Self Report, and child autistic-like traits were measured by three methods: the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 autism spectrum disorder (ASD) subscale, the Child Behavior Checklist ASD subscale, and the Social Responsiveness Scale. We also examined the mediating roles of family conflict and children’s functional brain connectivity at baseline.
Results
Parental attention-deficit/hyperactivity problems were central symptoms and had a direct and the strongest link with child autistic-like traits in network models using baseline data. In longitudinal analyses, parental attention-deficit/hyperactivity problems at baseline were the only significant symptoms associated with child autistic-like traits at 2-year follow-up (β = 0.014, 95% confidence interval [0.010, 0.018], FDR q = 0.005), even accounting for children’s comorbid behavioral problems. The observed association was significantly mediated by family conflict (proportion mediated = 11.5%, p for indirect effect <0.001) and functional connectivity between the default mode and dorsal attention networks (proportion mediated = 0.7%, p for indirect effect = 0.047).
Conclusions
Parental attention-deficit/hyperactivity problems were associated with elevated autistic-like traits in offspring during adolescence.
Seed chemical composition and oxidation after long-term storage may affect seed longevity, seed germination and seedling normality after planting. By screening the entire USDA cultivated peanut germplasm collection for fatty acid composition, we identified the -01 inventory of accession PI 268941 with the following characteristics: (a) two distinct seed fatty acid profiles (high oleate 78.9% and normal oleate 48.19%); (b) two FAD2B genotypes (with and without a functional point mutation of 435DelT within the FAD2B gene); and (c) uniform plant morphology and seed-coat color. This inventory had been stored at −18°C within the same sealed aluminum bag for 30 years and was acquired to investigate the relationship between seed chemical composition and seed performance after planting using individual seed analysis. Our results indicated that (1) the spontaneous point-functional mutation 435T deletion of FAD2B within the accession led to the high and normal oleate seeds; (2) additional unidentified compounds observed during analysis may be due to a higher oxidation rate in normal oleate seeds than in high oleate seeds; (3) the high oleate seeds had significantly higher rates of seed germination and seedling normality than the normal oleate seeds; and (4) the seedling performance highly and significantly correlated with fatty acid composition and extra peaks. Our results suggest that high oleic acid significantly extends the viability of long-term stored peanut seeds. The information revealed in this study will be useful for germplasm preservation as well as the selection of seeds for planting and agricultural production based on seed fatty acid composition and storage length.
Precise stratification of patients into homogeneous disease subgroups could address the heterogeneity of phenotypes and enhance understanding of the pathophysiology underlying specific subtypes. Existing literature on subtyping patients with major depressive disorder (MDD) mainly utilized clinical features only. Genomic and imaging data may improve subtyping, but advanced methods are required due to the high dimensionality of features.
Methods
We propose a novel disease subtyping framework for MDD by integrating brain structural features, genotype-predicted expression levels in brain tissues, and clinical features. Using a multi-view biclustering approach, we classify patients into clinically and biologically homogeneous subgroups. Additionally, we propose approaches to identify causally relevant genes for clustering.
Results
We verified the reliability of the subtyping model by internal and external validation. High prediction strengths (PS) (average PS: 0.896, minimum: 0.854), a measure of generalizability of the derived clusters in independent datasets, support the validity of our approach. External validation using patient outcome variables (treatment response and hospitalization risks) confirmed the clinical relevance of the identified subgroups. Furthermore, subtype-defining genes overlapped with known susceptibility genes for MDD and were involved in relevant biological pathways. In addition, drug repositioning analysis based on these genes prioritized promising candidates for subtype-specific treatments.
Conclusions
Our approach successfully stratified MDD patients into subgroups with distinct clinical prognoses. The identification of biologically and clinically meaningful subtypes may enable more personalized treatment strategies. This study also provides a framework for disease subtyping that can be extended to other complex disorders.
We presented an attosecond-precision timing detector based on linear optics. The minimum measurement floor is 1×10–10 fs2/Hz with only 1 mW input optical power. With this novel technique, the residual dispersion of a 5.2 km fiber link is characterized and precisely compensated. Finally, a comprehensive feedback model has been developed to analyze the noise coupling in a long-distance link stabilization system. The simulation results demonstrate an out-of-loop jitter of merely 359 as, integrated at [1 Hz, 1 MHz], at 1 mW input power per photodetector of our timing detector. Remarkably, the system is capable of maintaining sub-femtosecond precision even at optical power levels as low as 240 nW (for a 5.2 km link length), or link lengths as long as 20 km (with 1 μW optical power), respectively.
This article is concerned with the spreading speed and traveling waves of a lattice prey–predator system with non-local diffusion in a periodic habitat. With the help of an associated scalar lattice equation, we derive the invasion speed for the predator. More specifically, when the dispersal kernel of the predator is exponentially bounded, the invasion speed is finite and can be characterized in terms of principal eigenvalues; while the dispersal kernel is algebraically decaying, the invasion speed is infinite and the accelerated spreading rate is obtained. Furthermore, the existence and non-existence of traveling waves connecting the semi-equilibrium point to a uniformly persistent state are established.
Postpartum maternal diet quality has been linked with optimal infant feeding practices. However, whether maternal diet quality during pregnancy influences infant feeding practices remains unclear. The present study explored the relationship between maternal diet quality in pregnancy and infant feeding practices in Australian women. A brief 15-item FFQ was used to collect maternal dietary data (n 469). Diet quality was calculated using a modified 2013 Dietary Guideline Index (DGI). Multivariable linear and logistic regressions with adjustment for covariates were used to examine associations between maternal diet quality in pregnancy and infant feeding practices: infant feeding mode, breast-feeding duration and timing of solids introduction. Higher DGI score during pregnancy was associated with higher odds of breast-feeding than formula/mixed feeding (adjusted OR (AOR) 1·03, 95 % CI 1·00, 1·07), longer breast-feeding duration (adjusted β 0·09, 95 % CI 0·03, 0·15) and higher odds of breast-feeding for ≥ 6 months (AOR 1·04, 95 % CI 1·02, 1·07) than for < 6 months. Associations between maternal DGI score and breast-feeding variables were moderated by maternal country of birth, with significant associations observed in Australian-born mothers only. No association was found between maternal DGI score and timing of solids introduction. Higher maternal diet quality was associated with better infant feeding practices, and the association was moderated by country of birth. Our findings provide evidence to support the initiation of dietary interventions to promote diet quality during pregnancy, particularly among Australian-born women. Further research could explore underlying mechanisms linking maternal diet quality and infant feeding practices.
We establish hyperweak boundedness of area functions, square functions, maximal operators, and Calderón–Zygmund operators on products of two stratified Lie groups.
Observations of the intracluster medium (ICM) in the outskirts of galaxy clusters reveal shocks associated with gas accretion from the cosmic web. Previous work based on non-radiative cosmological hydrodynamical simulations have defined the shock radius, $r_{\text{shock}}$, using the ICM entropy, $K \propto T/{n_\mathrm{e}}^{2/3}$, where T and $n_{\text{e}}$ are the ICM temperature and electron density, respectively; the $r_{\text{shock}}$ is identified with either the radius at which K is a maximum or at which its logarithmic slope is a minimum. We investigate the relationship between $r_{\text{shock}}$, which is driven by gravitational hydrodynamics and shocks, and the splashback radius, $r_{\text{splash}}$, which is driven by the gravitational dynamics of cluster stars and dark matter and is measured from their mass profile. Using 324 clusters from The Three Hundred project of cosmological galaxy formation simulations, we quantify statistically how $r_{\text{shock}}$ relates to $r_{\text{splash}}$. Depending on our definition, we find that the median $r_{\text{shock}} \simeq 1.38 r_{\text{splash}} (2.58 R_{200})$ when K reaches its maximum and $r_{\text{shock}} \simeq 1.91 r_{\text{splash}} (3.54 R_{200})$ when its logarithmic slope is a minimum; the best-fit linear relation increases as $r_{\text{shock}} \propto 0.65 r_{\text{splash}}$. We find that $r_{\text{shock}}/R_{200}$ and $r_{\text{splash}}/R_{200}$ anti-correlate with virial mass, $M_{200}$, and recent mass accretion history, and $r_{\text{shock}}/r_{\text{splash}}$ tends to be larger for clusters with higher recent accretion rates. We discuss prospects for measuring $r_{\text{shock}}$ observationally and how the relationship between $r_{\text{shock}}$ and $r_{\text{splash}}$ can be used to improve constraints from radio, X-ray, and thermal Sunyaev-Zeldovich surveys that target the interface between the cosmic web and clusters.
Although dietary factors have been examined as potential risk factors for liver cancer, the evidence is still inconclusive. Using a diet-wide association analysis, our research evaluated the associations of 126 foods and nutrients on the risk of liver cancer in a Chinese population. We obtained the diet consumption of 72,680 women in the Shanghai Women’s Health Study using baseline dietary questionnaires. The association between each food and nutrient and liver cancer risk was quantified by Cox regression model. A false discovery rate of 0.05 was used to determine the foods and nutrients which need to be verified. Totally 256 incident liver cancer cases were identified in 1,267,391 person-years during the follow-up duration. At the statistical significance level (P ≤ 0.05), higher intakes of cooked wheaten foods, pear, grape and copper were inversely associated with liver cancer risk, while spinach, leafy vegetables, eggplant and carrots showed the positive associations. After considering multiple comparisons, no dietary variable was associated with liver cancer risk. Similar findings were seen in the stratification, secondary and sensitivity analyses. Our findings observed no significant association between dietary factors and liver cancer risk after considering multiple comparisons in Chinese women. More evidence is needed to explore the associations between diet and female liver cancer occurrence.
Firefighters are frequently exposed to traumatic events and stressful environments and are at particularly high risk of depressive symptoms.
Aims:
The present study aimed to examine the impact of a combined internet-delivered cognitive behavioral therapy (iCBT) and attention bias modification (ABM) intervention to reduce depressive symptoms in firefighters.
Method:
The study was a randomized controlled trial carried out in Kunming, China, and involved the recruitment of 138 active firefighters as participants. The intervention lasted for an 8-week duration, during which participants participated in ABM exercises on alternating days and concurrently underwent eight modules of iCBT courses delivered through a smartphone application. Baseline and post-intervention assessments were conducted to evaluate the effects of the intervention.
Results and Discussion:
Results indicated that the combined iCBT and ABM intervention was significantly effective in reducing symptoms of depression compared with the no intervention control group (U=1644, p<0.001, Wilcoxon r=0.280). No significant change was observed in attention bias post-intervention (U=2460, p=0.737, Wilcoxon r=0.039), while a significant increase was observed in attention-bias variability (U=3172, p<0.001, Wilcoxon r=–0.287). This study provides evidence for the effectiveness of the combined iCBT and ABM intervention in reducing depressive symptoms among firefighters. This study provides conceptual support and preliminary evidence for the effectiveness of the combined iCBT and ABM intervention in reducing depressive symptoms among firefighters.
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.
We consider linear-fractional branching processes (one-type and two-type) with immigration in varying environments. For $n\ge0$, let $Z_n$ count the number of individuals of the nth generation, which excludes the immigrant who enters the system at time n. We call n a regeneration time if $Z_n=0$. For both the one-type and two-type cases, we give criteria for the finiteness or infiniteness of the number of regeneration times. We then construct some concrete examples to exhibit the strange phenomena caused by the so-called varying environments. For example, it may happen that the process is extinct, but there are only finitely many regeneration times. We also study the asymptotics of the number of regeneration times of the model in the example.
Sediments within accretionary complexes, preserving key information on crust growth history of Central Asian Orogenic Belt, did not get enough attention previously. Here, we conduct comprehensive geochemical study on the turbidites from the North Tianshan Accretionary Complex (NTAC) in the Chinese West Tianshan orogen, which is a good example of sediments derived from juvenile materials. The turbidites, composed of sandstone, siltstone, and argillaceous siliceous rocks, are mainly Carboniferous. All the investigated samples have relatively low Chemical Index of Alteration values (35–63) and Plagioclase Index of Alteration values (34–68), indicating relatively weak weathering before erosion and deposition. The sandstone and siltstone, and slate samples display high Index of Compositional Variability values of 0.89–1.50 and 0.89–0.93, suggesting a relatively immature source. The sandstones and siltstones were mainly derived from intermediate igneous rocks, and the slates from felsic igneous rocks, formed in oceanic/continental arc settings. The investigated samples roughly display high positive εNd(t) values (mainly at +5.5 to +7.9, except one spot at +0.8), with corresponding Nd model ages at 672 Ma–522 Ma (except one at ∼1.1 Ga). Combined with the previous studies, we suggest that the turbidites in the NTAC were mainly derived from intermediate to felsic igneous rocks with juvenile arc signature, and thus the northern Chinese West Tianshan is a typical site with significant Phanerozoic crust growth.
As a required sample preparation method for 14C graphite, the Zn-Fe reduction method has been widely used in various laboratories. However, there is still insufficient research to improve the efficiency of graphite synthesis, reduce modern carbon contamination, and test other condition methodologies at Guangxi Normal University (GXNU). In this work, the experimental parameters, such as the reduction temperature, reaction time, reagent dose, Fe powder pretreatment, and other factors, in the Zn-Fe flame sealing reduction method for 14C graphite samples were explored and determined. The background induced by the sample preparation process was (2.06 ± 0.55) × 10–15, while the 12C– beam current were better than 40μA. The results provide essential instructions for preparing 14C graphite of ∼1 mg at the GXNU lab and technical support for the development of 14C dating and tracing, contributing to biology and environmental science.
A new vacuum line to extract CO2 from carbonate and dissolved inorganic carbon (DIC) in water was established at Guangxi Normal University. The vacuum line consisted of two main components: a CO2 bubble circulation region and a CO2 purification collection region, both of which were made of quartz glass and metal pipelines. To validate its reliability, a series of carbonate samples were prepared using this system. The total recovery rate of CO2 extraction and graphitization exceeded 80%. Furthermore, the carbon content in calcium carbonate exhibited a linear relationship with the CO2 pressure within the system, demonstrating its stability and reliability. The system was also employed to prepare and analyze various samples, including calcium carbonate blanks, foraminiferal, shell, groundwater, and subsurface oil-water samples. The accelerator mass spectrometry (AMS) results indicated that the average beam current for 12C- in the samples exceeded 40 μA. Additionally, the contamination introduced during the liquid sample preparation process was approximately (1.77 ± 0.57) × 10−14. Overall, the graphitized preparation system for carbonate and DIC in water exhibited high efficiency and recovery, meeting the requirements for samples dating back to approximately 30,000 years.