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Overnutrition during before and pregnancy can cause maternal obesity and raise the risk of maternal metabolic diseases during pregnancy, and in offspring. Lentinus edodes may prevent or reduce obesity. This study aimed to to assess Lentinus edodes fermented products effects on insulin sensitivity, glucose and lipid metabolism in maternal and offspring, and explore its action mechanism. A model of overnutrition during pregnancy and lactation was developed using a 60 % kcal high-fat diet in C57BL6/J female mice. Fermented Lentinus edodes (FLE) was added to the diet at concentrations of 1 %, 3 %, and 5 %. The results demonstrated that FLE to the gestation diet significantly reduced serum insulin levels and homeostatic model assessment for insulin resistance (HOMA-IR) in pregnant mice. FLE can regulate maternal lipid metabolism and reduce fat deposition. Meanwhile, the hepatic phosphoinositide-3-kinase-protein kinase (PI3K/AKT) signaling pathway was significantly activated in the maternal mice. There is a significant negative correlation between maternal FLE supplementation doses and offspring body fat percentage and visceral fat content. Furthermore, FLE supplementation significantly increased offspring weaning litter weight, significantly reduced fasting glucose level, serum insulin level, HOMA-IR and serum glucose level, significantly activated liver PI3K/AKT signaling pathway in offspring, and upregulated the expression of liver lipolytic genes adipose triglyceride lipase, hormone-sensitive lipase and carnitine palmitoyltransferase 1 mRNA. Overall, FLE supplementation can regulate maternal lipid metabolism and reduce fat deposition during pregnancy and lactation, and it may improve insulin sensitivity in pregnant mothers and offspring at weaning through activation of the PI3K/AKT signaling pathway.
The extracellular matrices, such as the haemolymph, in insects are at the centre of most physiological processes and are protected from oxidative stress by the extracellular antioxidant enzymes. In this study, we identified two secreted superoxide dismutase genes (PxSOD3 and PxSOD5) and investigated the oxidative stress induced by chlorpyrifos (CPF) in the aquatic insect Protohermes xanthodes (Megaloptera: Corydalidae). PxSOD3 and PxSOD5 contain the signal peptides at the N-terminus. Structure analysis revealed that PxSOD3 and PxSOD5 contain the conserved CuZn-SOD domain, which is mainly composed of β-sheets and has conserved copper and zinc binding sites. Both PxSOD3 and PxSOD5 are predicted to be soluble proteins located in the extracellular space. After exposure to different concentrations of sublethal CPF, MDA content in P. xanthodes larvae were increased in a dose-dependent manner; SOD and CAT activities were also higher in CPF-treated groups than that in the no CPF control, indicating that sublethal CPF induces oxidative stress in P. xanthodes larvae. Furthermore, PxSOD3 and PxSOD5 expression levels and haemolymph SOD activity in the larvae were downregulated by sublethal CPF at different concentrations. Our results suggest that the PxSOD3 and PxSOD5 are putative extracellular antioxidant enzymes that may play a role in maintaining the oxidative balance in the extracellular space. Sublethal CPF may induce oxidative stress in the extracellular space of P. xanthodes by reducing the gene expression and catalytic activity of extracellular SODs.
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.
The primary focus of this article is to capture heterogeneous treatment effects measured by the conditional average treatment effect. A model averaging estimation scheme is proposed with multiple candidate linear regression models under heteroskedastic errors, and the properties of this scheme are explored analytically. First, it is shown that our proposal is asymptotically optimal in the sense of achieving the lowest possible squared error. Second, the convergence of the weights determined by our proposal is provided when at least one of the candidate models is correctly specified. Simulation results in comparison with several related existing methods favor our proposed method. The method is applied to a dataset from a labor skills training program.
This paper introduces a distributed online learning coverage control algorithm based on sparse Gaussian process regression for addressing the problem of multi-robot area coverage and source localization in unknown environments. Considering the limitations of traditional Gaussian process regression in handling large datasets, this study employs multiple robots to explore the task area to gather environmental information and approximate the posterior distribution of the model using variational free energy methods, which serves as the input for the centroid Voronoi tessellation algorithm. Additionally, taking into consideration the localization errors, and the impact of obstacles, buffer factors and centroid Voronoi tessellation algorithms with separating hyperplanes are introduced for dynamic robot task area planning, ultimately achieving autonomous online decision-making and optimal coverage. Simulation results demonstrate that the proposed algorithm ensures the safety of multi-robot formations, exhibits higher iteration speed, and improves source localization accuracy, highlighting the effectiveness of model enhancements.
Glyphodes pyloalis Walker (Lepidoptera: Pyralidae) is a destructive monophagous pest of mulberry, Morus Linnaeus (Moraceae), trees. In order to identify mulberry cultivars resistant to G. pyloalis, 12 cultivars were examined using field and in vitro testing. Field observations indicated that cultivars AlbapC, BombyL, LaeviT, and CathaB had less than 10.0% damage, with no observed damage on the CathaB cultivar. The life table parameters showed that CathaB cultivar had the longest larval and pupal duration (23.2 days in total), the shortest adult period (5.3 days), the lowest rates of both pupation (55.0%) and adult emergence (69.7%), the highest adult mortality (61.7%), the lowest average weight of pupae (30.4 mg), and the lowest daily oviposition (5.0 eggs/female/day). The larval performance of G. pyloalis in the field revealed that CathaB had the lowest larval density. Correlation analyses confirmed that significant correlations exist between all the performance parameters of G. pyloalis for both the observed damage and larval performance. Leaf characterisation of selected cultivars indicated CathaB had significantly higher values of leaf wax, trichome density, soluble glucose, and protein contents compared to MultiQ. This study would be a valuable reference for evaluating pest-resistant cultivars and establishing a theoretical foundation for managing G. pyloalis.
Multimorbidity, especially physical–mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical–mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.
Methods
A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18–65years) residing in Liaoning Province, China, to evaluate the occurrence of physical–mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical–mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.
Results
Physical–mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical–mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: ‘Affective-addiction’, ‘Anxiety’, ‘Cardiometabolic’ and ‘Gastro-musculoskeletal-respiratory’, with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.
Conclusions
The physical–mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.
The outbreak of major epidemics, such as COVID-19, has had a significant impact on supply chains. This study aimed to explore knowledge innovation in the field of emergency supply chain during pandemics with a systematic quantitative analysis.
Methods
Based on the Web of Science (WOS) Core Collection, proposing a 3-stage systematic analysis framework, and utilizing bibliometrics, Dynamic Topic Models (DTM), and regression analysis to comprehensively examine supply chain innovations triggered by pandemics.
Results
A total of 888 literature were obtained from the WOS database. There was a surge in the number of publications in recent years, indicating a new field of research on Pandemic Triggered Emergency Supply Chain (PTESC) is gradually forming. Through a 3-stage analysis, this study identifies the literature knowledge base and distribution of research hotspots in this field and predicts future research hotspots and trends mainly boil down to 3 aspects: pandemic-triggered emergency supply chain innovations in key industries, management, and technologies.
Conclusions
COVID-19 strengthened academic exchange and cooperation and promoted knowledge output in this field. This study provides an in-depth perspective on emergency supply chain research and helps researchers understand the overall landscape of the field, identifying future research directions.
Brown dwarfs are failed stars with very low mass (13–75 Jupiter mass) and an effective temperature lower than 2 500 K. Their mass range is between Jupiter and red dwarfs. Thus, they play a key role in understanding the gap in the mass function between stars and planets. However, due to their faint nature, previous searches are inevitably limited to the solar neighbourhood (20 pc). To improve our knowledge of the low mass part of the initial stellar mass function and the star formation history of the Milky Way, it is crucial to find more distant brown dwarfs. Using James Webb Space Telescope (JWST) COSMOS-Web data, this study seeks to enhance our comprehension of the physical characteristics of brown dwarfs situated at a distance of kpc scale. The exceptional sensitivity of the JWST enables the detection of brown dwarfs that are up to 100 times more distant than those discovered in the earlier all-sky infrared surveys. The large area coverage of the JWST COSMOS-Web survey allows us to find more distant brown dwarfs than earlier JWST studies with smaller area coverages. To capture prominent water absorption features around 2.7 ${\unicode{x03BC}}$m, we apply two colour criteria, $\text{F115W}-\text{F277W}+1\lt\text{F277W}-\text{F444W}$ and $\text{F277W}-\text{F444W}\gt\,0.9$. We then select point sources by CLASS_STAR, FLUX_RADIUS, and SPREAD_MODEL criteria. Faint sources are visually checked to exclude possibly extended sources. We conduct SED fitting and MCMC simulations to determine their physical properties and associated uncertainties. Our search reveals 25 T-dwarf candidates and 2 Y-dwarf candidates, more than any previous JWST brown dwarf searches. They are located from 0.3 to 4 kpc away from the Earth. The spatial number density of 900–1 050 K dwarf is $(2.0\pm0.9) \times10^{-6}\text{ pc}^{-3}$, 1 050–1 200 K dwarf is $(1.2\pm0.7) \times10^{-6}\text{ pc}^{-3}$, and 1 200–1 350 K dwarf is $(4.4\pm1.3) \times10^{-6}\text{ pc}^{-3}$. The cumulative number count of our brown dwarf candidates is consistent with the prediction from a standard double exponential model. Three of our brown dwarf candidates were detected by HST, with transverse velocities $12\pm5$, $12\pm4$, and $17\pm6$ km s$^{-1}$. Along with earlier studies, the JWST has opened a new window of brown dwarf research in the Milky Way thick disk and halo.
Dietary intervention is a key strategy for preventing and managing chronic kidney disease (CKD). However, evidence on specific foods’ effects on CKD is limited. This study aims to clarify the impact of various foods on CKD risk. We used two-sample Mendelian randomisation to analyse the causal relationships between the intake of eighteen foods (e.g., cheese, processed meat, poultry, beef and non-oily fish) and CKD risk, as well as estimated glomerular filtration rate (eGFR)cr and eGFRcys levels. The inverse variance weighting method, weighted median method, MR-Egger regression, simple mode and weighted mode were employed. The sensitivity analysis included Cochran’s Q test and the Egger intercept test. According to the main method, the IVM results indicated that frequent alcohol intake was linked to higher CKD risk (P= 0·007, 0·048). Protective factors included cheese (OR = 0·71, (95 % CI: 0·53, 0·94), P= 0·017), tea (OR = 0·66, (95 % CI: 0·43, 1·00), P= 0·048) and dried fruit (OR = 0·78, (95 % CI: 0·63, 0·98), P= 0·033). Oily fish (β = 0·051, (95 % CI: 0·001, 0·102), P= 0·046) and dried fruit (β = 0·082, (95 % CI: 0·016, 0·149), P= 0·014) were associated with elevated eGFRcys. Salad/raw vegetables (β = 0·024, (95 % CI: 0·003, 0·045), P= 0·028) and dried fruit (β = 0·013, (95 % CI: 0·001, 0·031), P= 0·014) were linked to higher eGFRcr, while cereal intake (β = –0·021, (95 % CI: −0·033, −0·010), P < 0·001) was associated with lower eGFRcr. These findings provide insights for optimising dietary strategies for CKD patients.
Patients with chronic insomnia are characterized by alterations in default mode network and alpha oscillations, for which the medial parietal cortex (MPC) is a key node and thus a potential target for interventions.
Methods
Fifty-six adults with chronic insomnia were randomly assigned to 2 mA, alpha-frequency (10 Hz), 30 min active or sham transcranial alternating current stimulation (tACS) applied over the MPC for 10 sessions completed within two weeks, followed by 4- and 6-week visits. The connectivity of the dorsal and ventral posterior cingulate cortex (vPCC) was calculated based on resting functional MRI.
Results
For the primary outcome, the active group showed a higher response rate (≥ 50% reduction in Pittsburgh Sleep Quality Index (PSQI)) at week 6 than that of the sham group (71.4% versus 3.6%) (risk ratio 20.0, 95% confidence interval 2.9 to 139.0, p = 0.0025). For the secondary outcomes, the active therapy induced greater and sustained improvements (versus sham) in the PSQI, depression (17-item Hamilton Depression Rating Scale), anxiety (Hamilton Anxiety Rating Scale), and cognitive deficits (Perceived Deficits Questionnaire-Depression) scores. The response rates in the active group decreased at weeks 8–14 (42.9%–57.1%). Improvement in sleep was associated with connectivity between the vPCC and the superior frontal gyrus and the inferior parietal lobe, whereas vPCC-to-middle frontal gyrus connectivity was associated with cognitive benefits and vPCC-to-ventromedial prefrontal cortex connectivity was associated with alleviation in rumination.
Conclusions
Targeting the MPC with alpha-tACS appears to be an effective treatment for chronic insomnia, and vPCC connectivity represents a prognostic marker of treatment outcome.
Bilinguals use languages strategically and make decisions differently depending on the language context. Here, we explored whether verbal feedback modulates language use and risk-taking in bilinguals engaged in a coin-drawing game that incentivises lying. In the game, participants announced bets in Chinese or English, and feedback on the outcome of the current bet was given in the same language. They selected Chinese over English after receiving positive feedback in Chinese, and no language difference was found when feedback was provided in English. They also tended to take more risks after receiving positive than negative feedback. Furthermore, participants were more likely to switch from one language to the other following negative feedback as compared to positive feedback, and when telling the truth, they were faster after negative than positive feedback. Thus, the language in which bilinguals receive feedback constrains language use, which may have implications for understanding interactions in multilingual communities.
To summarise the characteristics and postoperative outcomes in paediatric patients with coronary sinus septal defect.
Method:
This retrospective study recruited paediatric patients diagnosed with coronary sinus septal defect from the Guangdong Cardiovascular Institute between 2011 and 2023. Clinical characteristics, echocardiographic parameters, surgical procedures, and postoperative outcomes were collected from electronic health records.
Results:
Among the 68 patients, 50% were male, with a median age of 1.0 years. Four cases (5.9%) were diagnosed during the prenatal period. The proportions of patients with type I, II, III, and IV coronary sinus septal defect were 51.5%, 5.9%, 16.1%, and 26.5%, respectively. The most common coexisting cardiac anomalies were persistent left superior caval vein. Twenty-seven cases were either missed or misdiagnosed by echocardiogram, accounting for 39.7% of the overall cases, with type I being the most frequently missed diagnosis. Fifty-four patients underwent surgery, two patients received transcutaneous intervention, while the remaining patients did not undergo any surgery or intervention. At follow-up, two patients with type I coronary sinus septal defect died from multiorgan dysfunction, and one patient underwent reoperation due to narrowing of the extracardiac tunnel. The remaining patients did not experience any major events and recovered well.
Conclusion:
Paediatric patients with coronary sinus septal defect often do not exhibit specific clinical manifestations. Enhancing our understanding of the anatomic and haemodynamic characteristics of coronary sinus septal defect can improve the diagnostic accuracy of echocardiography. If diagnosis is suspected, confirmation can be obtained by cardiac CT and cardiac magnetic resonance. Accurate preoperative and intraoperative diagnosis of coronary sinus septal defect contributes to high surgical success rates and favourable treatment outcomes.
This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.
Systematically monitoring the baseline sensitivity of troublesome weeds to herbicides is a crucial step in the early detection of their market lifespan. Florpyrauxifen-benzyl is one of the most important herbicides used in rice production throughout the world, and has been used for 5 yr in China. Barnyardgrass is one of the main targeted weed species of florpyrauxifen-benzyl. In total, 114 barnyardgrass populations were collected from rice fields in Jiangsu Province, China, and using whole-plant bioassays they were screened for susceptibility to florpyrauxifen-benzyl. The GR50 values (representing the dose that causes a 50% reduction in fresh weight of aboveground parts) of florpyrauxifen-benzyl for all populations ranged from 1.0 to 34.5 g ai ha−1, with an average of 6.8 g ai ha−1, a baseline sensitivity dose of 3.3 g ai ha−1, and a baseline sensitivity index of 34.5. Twenty-one days after treatment with florpyrauxifen-benzyl at the labeled dose (36 g ai ha−1), 90% of the barnyardgrass populations exhibited >95% reductions in fresh weight of aboveground parts. Compared with the baseline sensitivity dose, 63, 44, and 7 populations had, respectively, no resistance (55%), low resistance (39%), and moderate resistance (6%) to florpyrauxifen-benzyl. Furthermore, the GR50 distribution of barnyardgrass populations did not show a significant correlation with collection location, planting method (direct-seeding or transplanting), or rice species (Oryza sativa L. ssp. indica or ssp. japonica) at any of rice fields where seeds had been collected (P > 0.05). In conclusion, florpyrauxifen-benzyl remains effective for barnyardgrass control in rice fields despite serious resistance challenges.
The betatron radiation source features a micrometer-scale source size, a femtosecond-scale pulse duration, milliradian-level divergence angles and a broad spectrum exceeding tens of keV. It is conducive to the high-contrast imaging of minute structures and for investigating interdisciplinary ultrafast processes. In this study, we present a betatron X-ray source derived from a high-charge, high-energy electron beam through a laser wakefield accelerator driven by the 1 PW/0.1 Hz laser system at the Shanghai Superintense Ultrafast Laser Facility (SULF). The critical energy of the betatron X-ray source is 22 ± 5 keV. The maximum X-ray flux reaches up to 4 × 109 photons for each shot in the spectral range of 5–30 keV. Correspondingly, the experiment demonstrates a peak brightness of 1.0 × 1023 photons·s−1·mm−2·mrad−2·0.1%BW−1, comparable to those demonstrated by third-generation synchrotron light sources. In addition, the imaging capability of the betatron X-ray source is validated. This study lays the foundation for future imaging applications.