Explore the vast range of titles available.

Decomposing the uncertainty of global climate models is highly instructive in understanding climate change. However, it remains unclear whether sources of uncertainty have changed as the models have evolved and the extents to which uncertainty in temperature and precipitation are narrowed after bias correction (BC). We quantified uncertainty in temperature and precipitation projections over global land from three sources—model uncertainty, scenario uncertainty, and internal variability—and compared results from the models participating in the 5th and 6th phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). In addition, we investigated the potential of four BC methods for narrowing uncertainty in temperature and precipitation over the globe and individual continents. Raw projections of temperature and precipitation have greater uncertainty and lower fractional uncertainty relative to their anomalies. The largest temperature uncertainties appear in high‐latitude and high‐altitude regions, and the largest precipitation uncertainties are in low‐latitude regions and mountainous and coastal areas. For uncertainties in CMIP6 temperatures, the contribution from model uncertainty decreases with time (from 99% to 39%), while the contribution from scenario uncertainty increases with time (from 0.01% to 61%). For precipitation projections, the contribution from model uncertainty predominates (98%), while the contributions from scenario uncertainty (1.8%) and internal variability (0.2%) are extremely low. Four BC methods have exhibited excellent ability to reduce uncertainty, and among them, BC and spatial disaggregation has the best performance. These findings can help us better understand the characteristics of the models, while also providing decision makers with more accurate information to address climate mitigation and adaptation measures. Plain Language Summary Global climate models (GCMs) have a powerful ability to reproduce past climate characteristics and project future climate evolution, and they are currently one of the most effective tools for climate change research. However, quantitative climate projections from GCMs are subject to high uncertainty due to our incomplete knowledge of climate, insufficient representation of climate system, and limited computer resources. Clarifying uncertainty sources can provide important scientific support for enhancing the credibility of future projection results and resolve relevant scientific questions for subsequent modeling applications. In this study, we tried to quantify the uncertainty in temperature and precipitation projections from three sources‐model uncertainty, scenario uncertainty, and internal variability‐arising from model outputs of 21 phase 5 of the Coupled Model Intercomparison Project and 26 phase 6 of the Coupled Model Intercomparison Project GCMs. We also investigated the potential of four bias correction methods for narrowing uncertainty in temperature and precipitation projections over the globe and continents. Key Points For uncertainties in phase 6 of the Coupled Model Intercomparison Project temperatures, the contribution of model uncertainty decreases with time, while the contribution of scenario uncertainty increases with time For precipitation projections, the model uncertainty predominates (98%) the total uncertainty Four bias correction (BC) methods have exhibited excellent ability to reduce uncertainty, and BC and spatial disaggregation has the best performance

The mammalian SUMO-targeted E3 ubiquitin ligase Rnf4 has been reported to act as a regulator of DNA repair, but the importance of RNF4 as a tumor suppressor has not been tested. Using a conditional-knockout mouse model, we deleted Rnf4 in the B cell lineage to test the importance of RNF4 for growth of somatic cells. Although Rnf4-conditional-knockout B cells exhibited substantial genomic instability, Rnf4 deletion caused no increase in tumor susceptibility. In contrast, Rnf4 deletion extended the healthy lifespan of mice expressing an oncogenic c-myc transgene. Rnf4 activity is essential for normal DNA replication, and in its absence, there was a failure in ATR-CHK1 signaling of replication stress. Factors that normally mediate replication fork stability, including members of the Fanconi anemia gene family and the helicases PIF1 and RECQL5, showed reduced accumulation at replication forks in the absence of RNF4. RNF4 deficiency also resulted in an accumulation of hyper-SUMOylated proteins in chromatin, including members of the SMC5/6 complex, which contributes to replication failure by a mechanism dependent on RAD51. These findings indicate that RNF4, which shows increased expression in multiple human tumor types, is a potential target for anticancer therapy, especially in tumors expressing c-myc.

Age-related macular degeneration (AMD) progresses to vision-threatening dry and wet forms, with no effective dry AMD treatments available. The sulfated polysaccharide (GNP, 25.8 kDa) derived from Gelidium crinale exhibits diverse biological activities and represents a potential source of novel therapeutic agents. This study employed a hydrogen peroxide (H2O2)-induced oxidative stress and epithelial–mesenchymal transition (EMT) model in retinal pigment epithelial (RPE) cells to investigate GNP’s protective mechanisms against both oxidative damage and EMT. The results demonstrated that GNP effectively suppressed oxidative stress, with the 600 μg/mL dose significantly inhibiting excessive reactive oxygen species (ROS) generation to levels comparable to untreated controls. Concurrently, at concentrations of 200–600 μg/mL, GNP inhibited NF-κB signaling and increased the Bax/Bcl-2 ratio, effectively counteracting H2O2-induced oxidative damage and cell apoptosis. Furthermore, in H2O2-treated ARPE-19 cells, 600 μg/mL GNP significantly reduced the secretion of N-cadherin (N-cad), Vimentin (Vim), and α-smooth muscle actin (α-SMA), while increasing E-cadherin (E-cad) expression, consequently inhibiting cell migration. Mechanistically, GNP activated the Nrf2/HO-1 pathway, thereby mitigating oxidative stress. These findings suggest that GNP may serve as a potential therapeutic agent for dry AMD.

The Unit Commitment Problem (UCP) is a critical component of power market decision-making and is typically formulated as Mixed Integer Programming (MIP). Given the complexity of solving MIPs, efficiently solving large-scale UCPs remains a significant challenge. This paper presents a hybrid Graph Neural Network (GNN)–Linear Programming (LP) framework to accelerate the solution of large-scale Unit Commitment Problems (UCPs) while maintaining the quality of solutions. By analyzing variable stability through historical branch-and-bound (B&B) trajectories, we classify MIP variables into dynamically adjustable stable and unstable groups. We adopt an MIP formulation that includes multiple types of binary variables—such as commitment, startup, and shutdown variables—and extract additional information from these auxiliary binary variables. This enriched representation provides more candidates for stable variable fixation, helping to improve variable refinement, mitigate suboptimality, and enhance computational efficiency. A bipartite GNN is trained offline to predict stable variables based on system topology and historical operational patterns. During online optimization, instance-specific root LP solutions refine these predictions, enabling adaptive variable fixation via a dual-threshold mechanism that integrates GNN confidence and LP relaxations. To mitigate suboptimality risks, we introduce temporally flexible fixation strategies—hard fixation for variables with persistent stability and soft fixation allowing limited temporal adjustments—alongside a GNN-guided branching rule to prioritize unstable variables. Numerical experiments demonstrate that jointly fixing commitment, startup, and shutdown variables yields better performance compared to fixing only commitment variables. Ablation studies further validate the importance of hard fixation and customized branching strategies, especially for large-scale systems.

Luminescent materials that simultaneously embody bright singlet and triplet excitons hold great potential in optoelectronics, signage, and information encryption. However, achieving high-performance white-light emission is severely hampered by their inherent unbalanced contribution of fluorescence and phosphorescence. Herein, we address this challenge by pressure treatment engineering via the hydrogen bonding cooperativity effect to realize the mixture of n –π*/π–π* transitions, where the triplet state emission was boosted from 7% to 40% in isophthalic acid (IPA). A superior white-light emission based on hybrid fluorescence and phosphorescence was harvested in pressure-treated IPA, and the photoluminescence quantum yield was increased to 75% from the initial 19% (blue-light emission). In-situ high-pressure IR spectra, X-ray diffraction, and neutron diffraction reveal continuous strengthening of the hydrogen bonds with the increase of pressure. Furthermore, this enhanced hydrogen bond is retained down to the ambient conditions after pressure treatment, awarding the targeted IPA efficient intersystem crossing for balanced singlet/triplet excitons population and resulting in efficient white-light emission. This work not only proposes a route for brightening triplet states in organic small molecules, but also regulates the ratio of singlet and triplet excitons to construct high-performance white-light emission. The authors demonstrate that high-pressure treatment of IPA endows the material with enhanced hydrogen bonding, which brightens the white-light emission by regulating the ratio of singlet and triplet exciton populations.

Background Vaccine hesitancy among young Chinese remains a challenge, contributing to low vaccination rates for the nonavalent Human Papillomavirus (HPV) vaccine. This study evaluated the knowledge and acceptance of this vaccine among students at a southern Chinese university and identified factors influencing these outcomes. Methods This cross-sectional, anonymous questionnaire survey was conducted from April to November 2023 at a multi-campus university in southern China. The questionnaire was comprised of three sections: the first collected demographic data; the second evaluated students’ knowledge of the nonavalent HPV vaccine on a scale from 0 to 15, with cut-off points at 5 and 10 delineating low, medium, and high knowledge levels, respectively; the third section assessed vaccine acceptance on a scale from 8 to 40, using scores above the 50th percentile as the benchmark for positive acceptance. Results Among the participants, 18% demonstrated low-level, 40.20% medium-level, and 41.70% high-level knowledge of the nonavalent HPV vaccine. Notably, 71.95% of respondents showed positive acceptance, whereas 28.05% expressed negative acceptance. Male students and those with lower economic conditions (monthly living expenses below 1000 RMB, P = 0.004; 1000-1499 RMB, P = 0.012) exhibited lower knowledge levels. As for acceptance, female students and those with higher monthly living expenses (1000-1499 RMB, P = 0.007; 1500-1999 RMB, P = 0.002; over 2000 RMB, P = 0.002) demonstrated greater vaccine acceptance. A positive correlation was noted between the level of knowledge and vaccine acceptance (rs = 0.256, P < 0.001). Conclusions Gender and economic status are significantly associated with nonavalent HPV vaccine knowledge and acceptance among university students. These findings highlight the potential impact of targeted educational initiatives, especially for economically disadvantaged male students, in enhancing vaccine uptake rates. Plain Language Summary Many young people in China are hesitant to get the nine - valent HPV vaccine, which protects against certain types of viruses that can cause cancer. This study looked at how much students at a university in southern China know about the nine - valent HPV vaccine and whether they are willing to get vaccinated. We asked students to fill out a survey between April and November 2023 to gather this information. The survey showed that knowledge about this vaccine varied: about 18% of the students knew very little, 40% had a moderate understanding, and roughly 42% knew a lot about this vaccine. Interestingly, more than 70% of the students were open to getting the vaccine, but about 28% were not. We found that male students and those with less money generally knew less about the vaccine and were more likely to not accept it. There was also a clear link between how much students knew about the vaccine and their willingness to get vaccinated. This suggests that teaching students more about this vaccine, especially boys and those from poorer backgrounds, could encourage more of them to get vaccinated. This is important because increasing vaccine rates can help prevent diseases spread by the virus.

Documenting the spatiotemporal changes in vegetation cover and hydrological cycle of the Earth system and understanding how they interact are important especially under climate warming. In this research, we quantified the changes in vegetation and evapotranspiration (E) across China during 1982–2015 and then revealed the complex relationships in climate–vegetation–evapotranspiration system. Results show that the upward trend in vegetation leaf area index (LAI) during 2000–2015 (an increase of 0.95% per year) was almost 8 times the trend during 1982–1999. The zones of the Loess Plateau and the Three‐North Shelter Forest Program are the most notable areas for LAI increases between these two periods, with increases of 11.65% and 2.87%, respectively. Increased LAI, along with the warming climate, has accelerated E across China in the past several decades, and the annual increase in the E rate was 0.34% (1.34 mm year−1) during 1982–1999 and 0.40% (1.62 mm year−1) during 2000–2015. The zones of the Loess Plateau and the karst landform are the most notable areas for transpiration increases, with individual increases of 10% and 5%, respectively. In general, the dominant causes for evaporation changes across all of China are temperature and precipitation, while the main reasons for transpiration changes include temperature, LAI, and sunshine duration. This study improves our understanding of the relationships within the climate–vegetation–evapotranspiration system and provides important support for future ecological policies across China. Plain Language Summary It is well known that the Chinese government has been making great efforts in setting up a high‐quality ecological environment in the past several decades, and it proposed and implemented a series of ecological restoration projects from the 1980s, especially since 1999. As a result, vegetation cover and hydrological processes, which are the key components of the Earth ecosystem, have experienced large variability. Identifying the spatiotemporal change patterns and the dominant driving factors of vegetation leaf area index (LAI) and evapotranspiration (E) variability is of great significance to provide supports for future sustainable environmental policies across China. This study revealed the spatiotemporal changes in LAI and E and then identify the main driving factors of E changes. Results show that ecological restoration projects are the most important causes for LAI increase across China in the past decades, compared with the favorable climate conditions and CO2 fertilization. Temperature and precipitation are the key driving factors for evaporation changes, while temperature, LAI, and sunshine duration are the major factors for transpiration changes on the monthly scale over all of China. Key Points Ecological projects are the most important reasons for increased leaf area index across China during the past several decades The dominant causes for monthly evaporation changes across China are temperature and precipitation Ecological projects greatly affect the distribution of water resources in water‐limited areas because of accelerated transpiration

Glioblastoma (GBM) is a highly invasive malignancy with a poor prognosis, primarily attributable to its diffuse infiltration into adjacent brain tissue, thereby complicating effective surgical resection. Current imaging modalities often struggle to accurately identify tumor boundaries. Here, we identify general control non-repressed protein 5 (GCN5) as a promising molecular target for GBM imaging, as it is expressed in GBM lesions within brain tissue, and its expression levels are significantly correlated with GBM grading. We develop a dual-modal probe with a particle size of 20 nm, capable of efficiently traversing the blood-brain barrier (BBB) to target GCN5 through adsorptive-mediated transcytosis (AMT). The probe employs dendrimers (Den) as carriers, which are loaded with a small molecule inhibitor specifically designed to target GCN5. This probe enhances the preoperative delineation of GBM boundaries using magnetic resonance imaging (MRI) and facilitates intraoperative fluorescence image-guided surgical procedures. Our work introduces a promising tool for boundary delineation, offering new opportunities for the precise resection of GBM. The development of imaging agents capable of clearly defining tumor margins is essential for GBM intraoperative navigation. Here this group identifies GCN5 as a promising molecular target for GBM imaging therefore designs a dual mode nanoprobe for BBB crossing and in vivo visualization of typical GBM tumor boundaries.

The incidence of type 2 diabetes mellitus (T2DM) complicated with osteoporosis (OP) (T2DM‐OP) is growing. Dapagliflozin and metformin are commonly prescribed to manage glycemic levels in T2DM patients. We investigated the clinical efficacy of combining dapagliflozin with metformin in elderly patients with T2DM‐OP. Totally 144 T2DM‐OP patients were prospectively enrolled and allocated into two groups: the Metformin and Dapagliflozin + Metformin groups. Each group received treatment for 12 months. Fasting peripheral blood samples were collected before and after 12 months of treatment. Glycemic parameters and bone metabolic parameters were measured using oral glucose tolerance test, automatic biochemical analyzers, or liquid chromatography. Bone mineral density (BMD) changes at lumbar vertebrae (L1‐4), femoral neck (FN) and total hip (TH) were assessed using dual‐energy X‐ray bone mineral densitometry. Pain severity was evaluated using the visual analog scale (VAS). The total effective rate, fracture incidence, and adverse reaction rate were also evaluated. After 12 months, both groups showed improvements in glycemic parameters, bone metabolic parameters, and BMD at L1‐4, FN, and TH, and reductions in VAS scores. The Dapagliflozin + Metformin group exhibited more significant improvements. The overall effective rate was higher and fracture incidence, was lower in Dapagliflozin + Metformin group, with comparable rates of adverse reactions and safety profiles between the two groups. Taken together, treatment with a combination of dapagliflozin and metformin led to improvements in blood glucose levels, bone metabolism, and BMD in elderly patients with T2DM‐OP, demonstrating superior efficacy and safety compared to metformin monotherapy.

Hyperphosphorylated α-synuclein in Lewy bodies and Lewy neurites is a characteristic neuropathological feature of Parkinson’s disease (PD) and Dementia with Lewy bodies (DLB). The catalytic subunit of the specific phosphatase, protein phosphatase 2A (PP2A) that dephosphorylates α-synuclein, is hypomethylated in these brains, thereby impeding the assembly of the active trimeric holoenzyme and reducing phosphatase activity. This phosphatase deficiency contributes to the accumulation of hyperphosphorylated α-synuclein, which tends to fibrillize more than unmodified α-synuclein. Eicosanoyl-5-hydroxytryptamide (EHT), a fatty acid derivative of serotonin found in coffee, inhibits the PP2A methylesterase so as to maintain PP2A in a highly active methylated state and mitigates the phenotype of α-synuclein transgenic (SynTg) mice. Considering epidemiologic and experimental evidence suggesting protective effects of caffeine in PD, we sought, in the present study, to test whether there is synergy between EHT and caffeine in models of α-synucleinopathy. Coadministration of these two compounds orally for 6 mo at doses that were individually ineffective in SynTg mice and in a striatal α-synuclein preformed fibril inoculation model resulted in reduced accumulation of phosphorylated α-synuclein, preserved neuronal integrity and function, diminished neuroinflammation, and improved behavioral performance. These indices were associated with increased levels of methylated PP2A in brain tissue. A similar profile of greater PP2A methylation and cytoprotection was found in SH-SY5Y cells cotreated with EHT and caffeine, but not with each compound alone. These findings suggest that these two components of coffee have synergistic effects in protecting the brain against α-synuclein–mediated toxicity through maintenance of PP2A in an active state.