Explore the vast range of titles available.

AimsThis study aimed to explore the mechanisms of the priming effect (PE) induced by root exudates on soil carbon pools at different stages of decomposition.MethodsThe 13 C-labeled and unlabeled glucose, glycine and oxalic acid were added to soils of 15-year old-field (OF), 15-year bare-fallow (BF) and 23-year bare-fallow plus additional 815-day laboratory incubation (BF+), which represented relatively active (OF) and more resistant (BF and BF+) soil carbon pools. The 13 C stable isotope was used to determine the PE and net carbon balance, and cumulative CO2 emission, microbial biomass carbon and dissolved organic carbon were also reported.ResultsRelative to the control, soil organic carbon (SOC) decomposition in OF, BF and BF+ was stimulated by 17.3%, 20.8% and 21.5% with glucose addition, by 12.0%, 36.9% and 52.6% with glycine addition, and by 20.8%, 58.4% and 62.8% with oxalic acid addition, respectively. Overall, oxalic acid resulted in higher cumulative PE and lower net carbon balance relative to glucose and glycine in all three soils. Moreover, the PE of BF and BF+ were larger than that of OF induced by glucose, glycine and oxalic acid.ConclusionsResistant soil carbon is more vulnerable to priming by root exudates compared to active soil carbon, and oxalic acid can induce a stronger PE than glucose and glycine, especially in more resistant soil carbon pools.

To explore the effects of UNICEF‐suggested modifiable factors, that is, water, sanitation and hygiene (WASH), early adequate feeding and health care on child malnutrition, and to examine the extent to which each factor contributes to urban–rural disparities of child malnutrition in China. Pooling two waves of regionally representative survey data from Jilin, China, in 2013 and 2018, we report on urban–rural relative risks (RRs) in the prevalence of child stunting, wasting and overweight. We employ Poisson regression to examine the effects of urban–rural setting and the three modifiable factors on the prevalence of each malnutrition outcome, that is, stunting, wasting and overweight. We perform mediation analyses to estimate the extent to which each modifiable factor could explain the urban–rural disparities in each malnutrition outcome. The prevalence of stunting, wasting and overweight were 10.9%, 6.3% and 24.7% in urban, and 27.9%, 8.2% and 35.9% in rural Jilin, respectively. The rural to urban crude RR was 2.55 (95% confidence interval [CI]: 1.92–3.39) for stunting, while the corresponding RRs for wasting and overweight were 1.31 (95% CI: 0.84–2.03) and 1.45 (95% CI: 1.20–1.76), respectively. The rural to urban RR for stunting reduced to 2.01 (95% CI: 1.44–2.79) after adjusting for WASH. The mediation analyses show that WASH could mediate 23.96% (95% CI: 4.34–43.58%) of the urban–rural disparities for stunting, while early adequate feeding and health care had no effects. To close the persistent urban–rural gap in child malnutrition, the specific context of rural China suggests that a multi‐sectoral approach is warranted that focuses on the sanitation environment and other wider social determinants of health. The enormous urban–rural disparities in child malnutrition hinder acheivement of the WHO goals. But little is known about to what extent modifiable factors, that is, water, sanitation and hygiene (WASH), early adequate feeding and access to health care explain urban–rural differences in real‐world settings. We report on the double burden of child malnutrition in rural China, where we find that WASH was the single most important factor that explained a large proportion(24.0%) of urban–rural differences in child stunting. Our finding suggests a multi‐sectoral approach that focuses on wider social determinants of health, in particular environmental sanitation for a change.

The cabbage white butterfly ( Pieris rapae ), a major agricultural pest, has become one of the most abundant and destructive butterflies in the world. It is widely distributed in a large variety of climates and terrains of China due to its strong adaptability. To gain insight into the population genetic characteristics of P . rapae in China, we resequenced the genome of 51 individuals from 19 areas throughout China. Using population genomics approaches, a dense variant map of P . rapae was observed, indicating a high level of polymorphism that could result in adaptation to a changing environment. The feature of the genetic structure suggested considerable genetic admixture in different geographical groups. Additionally, our analyses suggest that physical barriers may have played a more important role than geographic distance in driving genetic differentiation. Population history showed the effective population size of P . rapae was greatly affected by global temperature changes, with mild periods (i.e., temperatures warmer than those during glaciation but not excessively hot) leading to an increase in population size. Furthermore, by comparing populations from south and north China, we have identified selected genes related to sensing temperature, growth, neuromodulation and immune response, which may reveal the genetic basis of adaptation to different environments. Our study is the first to illustrate the genetic signatures of P . rapae in China at the population genomic level, providing fundamental knowledge of the genetic diversity and adaptation of P . rapae .

The scheduling problem in additive manufacturing is receiving increasing attention; however, few have considered the effect of scheduling decisions on machine energy consumption. This research focuses on the nesting and scheduling problem of a single selective laser melting (SLM) machine to reduce total energy consumption. Based on an energy consumption model, a nesting and scheduling problem is formulated, and a mixed integer linear programming model is proposed. This model simultaneously determines part-to-batch assignments, part placement in the batch, and the choice of build orientation to reduce the total energy consumption of the SLM machine. The energy-saving potential of the model is validated through numerical experiments. Additionally, the effect of the number of alternative build orientations on energy consumption is explored.

This study aimed to investigate the effects of exercise on excessive mitochondrial fission, insulin resistance, and inflammation in the muscles of diabetic rats. The role of the irisin/AMPK pathway in regulating exercise effects was also determined. Thirty-two 8-week-old male Wistar rats were randomly divided into four groups (n = 8 per group): one control group (Con) and three experimental groups. Type 2 diabetes mellitus (T2DM) was induced in the experimental groups via a high-fat diet followed by a single intraperitoneal injection of streptozotocin (STZ) at a dosage of 30 mg/kg body weight. After T2DM induction, groups were assigned as sedentary (DM), subjected to 8 weeks of treadmill exercise training (Ex), or exercise training combined with 8-week cycloRGDyk treatment (ExRg). Upon completion of the last training session, all rats were euthanized and samples of fasting blood and soleus muscle were collected for analysis using ELISA, immunofluorescence, RT-qPCR, and Western blotting. Statistical differences between groups were analyzed using one-way ANOVA, and differences between two groups were assessed using t-tests. Our findings demonstrate that exercise training markedly ameliorated hyperglycaemia, hyperlipidaemia, and insulin resistance in diabetic rats (p < 0.05). It also mitigated the disarranged morphology and inflammation of skeletal muscle associated with T2DM (p < 0.05). Crucially, exercise training suppressed muscular excessive mitochondrial fission in the soleus muscle of diabetic rats (p < 0.05), and enhanced irisin and p-AMPK levels significantly (p < 0.05). However, exercise-induced irisin and p-AMPK expression were inhibited by cycloRGDyk treatment (p < 0.05). Furthermore, the administration of CycloRGDyk blocked the effects of exercise training in reducing excessive mitochondrial fission and inflammation in the soleus muscle of diabetic rats, as well as the positive effects of exercise training on improving hyperlipidemia and insulin sensitivity in diabetic rats (p < 0.05). These results indicate that regular exercise training effectively ameliorates insulin resistance and glucolipid metabolic dysfunction, and reduces inflammation in skeletal muscle. These benefits are partially mediated by reductions in mitochondrial fission through the irisin/AMPK signalling pathway.

Roots can produce rhizosphere effects to acquire available nitrogen, alleviate nitrogen limitation and sustain nitrogen nutrition by regulating nitrogen cycling in the rhizosphere (Duan et al.). [...]more carbon is lost through microbial respiration, leading to accelerated decomposition of carbon in the rhizosphere (Lv et al., 2023). [...]extreme drought reduces soil heterotrophic respiration during the plant growth recession period, as well as bacterial diversity and the abundance of related functional groups. [...]greater emphasis needs to be placed on measures for carbon management that deal with the intensification of stress environments. Experiments on in-situ adult species are highly essential for optimizing ecological models and clarifying the influences of stress environments on the soil carbon cycle in the rhizosphere. [...]an interdisciplinary approach integrating agricultural science, pedology, botany, environmental and ecological science is instantly demanded to confront the challenges associated with the rhizosphere carbon cycle in relation to stressful environments.

For data-driven dynamic stability assessment (DSA) in modern power grids, DSA models generally have to be learned from scratch when faced with new grids, resulting in high offline computational costs. To tackle this undesirable yet often overlooked problem, this work develops a light-weight framework for DSA-oriented stability knowledge transfer from off-the-shelf test systems to practical power grids. A scale-free system feature learner is proposed to characterize system-wide features of various systems in a unified manner. Given a real-world power grid for DSA, selective stability knowledge transfer is intelligently carried out by comparing system similarities between it and the available test systems. Afterward, DSA model fine-tuning is performed to make the transferred knowledge adapt well to practical DSA contexts. Numerical test results on a realistic system, i.e., the provincial GD Power Grid in China, verify the effectiveness of the proposed framework.

Background With the development of pathophysiology, cardiorenal syndrome (CRS), a complex and severe disease, has received increasing attention. Monocyte to high-density lipoprotein-cholesterol ratio (MHR) and body mass index (BMI) are independent risk factors for cardiovascular diseases, but their association with CRS remains unexplored. This study aims to explore the independent and joint effects of MHR and BMI on CRS. Methods We included 42,178 NHANES participants. The determination of CRS referred to the simultaneous presence of cardiovascular disease (identified through self-report) and chronic kidney disease (eGFR < 60 mL/min per 1.73 m²). We employed multivariate weighted logistic regression to evaluate the odds ratio (OR) and 95% confidence interval (CI) for the independent and joint associations of MHR and BMI with CRS. We also conducted restricted cubic spines to explore nonlinear associations. Results The prevalence of CRS was 3.45% among all participants. An increase in both MHR and BMI is associated with a higher risk of CRS (MHR: OR = 1.799, 95% CI = 1.520–2.129, P  < 0.001, P -trend < 0.001; BMI: OR = 1.037, 95% CI = 1.023–1.051, P  < 0.001). Individuals who simultaneously fall into the highest quartile of MHR and have a BMI of 30 or more face the highest risk of CRS compared to those in the lowest MHR quartile with a BMI of less than 25 (OR = 3.45, 95% CI = 2.40–4.98, P  < 0.001). However, there is no interactive association between MHR and BMI with CRS. Conclusions Higher MHR and BMI are associated with higher odds of CRS. MHR and BMI can serve as tools for early prevention and intervention of CRS, respectively.

Particulate Matter 2.5 (PM 2.5 ) is a significant risk factor for frailty and chronic diseases. Studies on the associations between PM 2.5 and frailty, chronic diseases, and multimorbidity are scarce, especially from large cohort studies. We aimed to explore the potential association between PM 2.5 exposure and the risk of frailty, chronic diseases, and multimorbidity. We collected data from a national cohort (CHARLS) with a follow-up period of 11–18 years, totaling 13,366 participants. We obtained PM 2.5 concentration data from the Atmospheric Composition Analysis Group at Dalhousie University. PM 2.5 exposure is based on the average annual concentration in the prefecture-level city where residents live. We define frailty as the comprehensive manifestation of declining various body functions, characterized by a frailty index of 0.25 or greater, and multimorbidity as the presence of at least two or more chronic conditions. Cox proportional hazards regression was used to estimate the hazard ratio (HR) with its 95% confidence interval (95%CI). A 10-μg/m 3 increase for PM 2.5 was significantly associated with an increased risk of frailty (HR = 1.289, 95%CI = 1.257–1.322, P  < 0.001). A 10-μg/m 3 increase for PM 2.5 was significantly associated with the elevated risk for most chronic diseases. Compared to those with no morbidity or only single morbidity, a 10-μg/m 3 increase for PM 2.5 was significantly associated with the elevated risk for multimorbidity (HR = 1.220, 95%CI = 1.181–1.260, P  < 0.001). Ambient PM 2.5 exposure is a significant risk factor for frailty, chronic diseases, and multimorbidity, and some measures need to be taken to reduce PM 2.5 concentration and prevent frailty and chronic diseases.

In the era of smart agriculture, the precise labeling and recording of growth information in plants pose challenges for modern agricultural production. This study introduces strontium aluminate particles coated with H3PO4 as luminescent labels capable of spatial embedding within plants for information encoding and storage during growth. The encapsulation with H3PO4 imparts stability and enhanced luminescence to SrAl2O4:Eu2+,Dy3+ (SAO). Using SAO@H3PO4 as a low-damage luminescent label, we implement its delivery into plants through microneedles (MNs) patches. The embedded SAO@H3PO4 within plants exhibits sustained and unaltered high signal-to-noise afterglow emission, with luminous intensity remaining at approximately 78% of the original for 27 days. To cater to diverse information recording needs, MNs of various geometric shapes are designed for loading SAO@H3PO4, and the luminescent signals in different shapes can be accurately identified through a designed program, the corresponding information can be conveniently viewed on a computer. Additionally, inspired by binary information concepts, MNs patches with specific arrangements of luminescent and non-luminescent points are created, resulting in varied luminescent MNs arrays on leaves. An advanced camera system with a tailored program accurately identifies and maps the labels to the corresponding recorded information. These findings showcase the potential of low-damage luminescent labels within plants, paving the way for convenient and widespread storage of plant growth information.