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Each year, hundreds of millions of people are infected with arboviruses such as dengue, yellow fever, chikungunya, and Zika, which are all primarily spread by the notorious mosquito Aedes aegypti. Traditional control measures have proven insufficient, necessitating innovations. In response, here we generate a next-generation CRISPR-based precision-guided sterile insect technique (pgSIT) for Ae. aegypti that disrupts genes essential for sex determination and fertility, producing predominantly sterile males that can be deployed at any life stage. Using mathematical models and empirical testing, we demonstrate that released pgSIT males can effectively compete with, suppress, and eliminate caged mosquito populations. This versatile species-specific platform has the potential for field deployment to effectively control wild populations of disease vectors.

One of the alternatives for effective storage of irregularly produced renewable energy is hydrogen energy. In order to realize a hydrogen-based society, not only environmentally friendly production of hydrogen but also effective storage is very important. Underground hydrogen storage technology is a technology that has evolved from the technology for storing natural gas underground, and includes waste gas fields, salt domes, aquifers, and rock cavities. When stored underground, hydrogen is converted into high-pressure gaseous hydrogen, liquefied hydrogen, and ammonia. Liquefied hydrogen requires extremely low storage temperatures, and ammonia is a toxic substance that requires separate handling, and energy loss occurs during the conversion process. To compensate for this, research on liquefied hydrogen, such as multilayer insulation technology, is being conducted. Ammonia has successfully extracted high-purity hydrogen by developing a membrane reactor. Ammonia toxicity can be prevented by strengthening leak detection and blocking facilities. Among these, ammonia was found to be the most suitable for underground storage in terms of economic feasibility, environment, and commercialization.

In the context of the San Gavain hydroelectric power station diversion tunnel project in Peru, this paper studies the surrounding rock instability mechanism using a combination of numerical simulation methods and model test and presents the enclosing rock instability criterion based on the catastrophe model. The study demonstrates that the distribution of stress and displacement during tunnel excavation is more affected by the presence of laminated joints; the thinner the layer thickness, the more prominent the influence of laminations, and the higher the deformation of the surrounding rock. With the increase in layer thickness, the resultant displacement shows the law of gradual decrease; when the layer thickness is greater than 16 cm, the rate of decrease gradually slows down, and the maximum displacement is 0.201 mm. The failure mode of the layered perimeter rock tunnel with a 45° inclination angle primarily shows up as tensile deformation at the left arch shoulder and shear slip deformation at the right arch foot under the combined action of blasting disturbance load and excavation. Based on the instability analysis of the fold catastrophe model and cups catastrophe model, the influence of bending deformation between layers of surrounding rock is generally greater than shear slip deformation. The instability criterion Δ＜0 exists in all working conditions, bending instability damage may occur in all cases. When the layer thickness is greater than 24 cm, the shear slip instability criterion is greater than zero for 0–2 ms, and the system is always in a stable state, and when the layer thickness is less than 24 cm, the system may be destabilized at 1.5 ms.

ObjectivesTraditional electric energy storage has limitations in scale, duration, and environmental impact.Moreover, the renewable energy absorption capacity in the microgrid is low, and low-carbon and economy cannot be taken into account in planning. In order to solve the above problems, based on the basic working principle of hydrogen energy storage, hydrogen energy storage was incorporated into the microgrid instead of traditional electric energy storage, and a low-carbon and economic synergy bi-level optimization configuration model of microgrid with hydrogen energy storage was established.MethodsThe upper-level planning model aimed at minimizing the comprehensive equivalent annual value of the microgrid, based on the joint operation of electricity and hydrogen. The carbon trading mechanism was introduced to plan the capacity of various power generation equipments in the microgrid, which can enhance the low-carbon of the system. The lower-level operation model aimed to minimize the sum of the absolute values of the difference between the new energy output and the load demand. The model also encouraged users to adopt diversified demand-side response behaviors with the goal of accurately tracking the new energy output curve, and feeded back the user’s energy consumption behavior to the upper-level model to optimize the load curve. On the basis of improving the absorption capacity of new energy, the system economy is further improved, deeply exploring the synergy between the low-carbon and economic characteristics of microgrids.ResultsThe simulation results of microgrid in a certain industrial park show that the proposed method yields a planning scheme with excellent low-carbon and economy. Compared with the traditional planning method, the low-carbon and economy are improved by 53.6% and 37.1%, respectively.ConclusionsThe model presented in this paper not only enhances the capacity for new energy absorption but also further improves the system economic performance. It achieves a synergistic enhancement of the microgrid low-carbon and economy.

Combining CO2 and green hydrogen to produce methanol can simultaneously realize CO2 conversion and green hydrogen storage. Methanol can be used as a green low-carbon fuel or industrial platform product for large-scale application, which is of great significance to promote the further development of Carbon Capture, Utilization and Storage (CCUS) technology. Non-thermal plasma (NTP) can activate CO2 under mild conditions for hydrogenation reaction and obtain specific products such as methanol by combining with catalysts to tailor the reaction routes, but the underlying reaction mechanism is still unclear. Based on this, the reaction mechanism and process coupling laws of the NTP-enhanced CO2 hydrogenation with assistance of Cu/γ-Al2O3 for methanol production were investigated by combining hydrogenation experiments in a dielectric barrier discharge (DBD) reactor with continuously-pulsed discharge plasma simulations. The experiments investigation showed that 18.74% CO2 conversion and 36.28% CH3OH selectivity could be achieved by combining NTP and 10% Cu/γ-Al2O3 at 80 ℃ and 0.1 MPa. The on-line discharge parameters monitoring and in-situ emission spectroscopy (OES) showed that the localized discharge was enhanced by Cu/γ-Al2O3, which increased the average electron energy and density, thus promote the CO and H generation and their surface consumption reaction, resulting in the weakening of spectral intensity. Furthermore, the sensitivity and ROP analyses indicated that the active substances such as H and CO in NTP promoted methanol generation efficiently by alternating the corresponding L-H routes, which usually had higher energy barriers, via E-R reactions such as CO2(S)+H→COOH(S), CO+H(S)→HCO(S), CO(S)+H→HCO(S), and CH3O(S)+H→CH3OH(S). The reaction pathways analysis revealed that the formate (HCOO*) pathway was the main pathway for methanol generation on the Cu/γ-Al2O3 surface, where the reaction CH3O(S)+H(S)→CH3OH(S)+Cu(S) was the rate-limiting step. The generation of CO(S) via the CO2(S)→COOH(S)→CO(S) in the RWGS+CO hydrogenation pathway and its rapid desorption played a vital role in reducing CH3OH selectivity. Uncertainty analysis demonstrated that although increasing the CO2 adsorption rate could effectively improve its conversion, but would not increase CO selectivity when H(S) was insufficient. The optimal CO2 and H2 adsorption rate ratio was predicated to be γ(H2)/γ(CO2)=7～8. Improving CO(S) adsorption stability and enhancing H2 electron collisional dissociation to promote H generation could promote reactions of CO(S)→HCO(S) and CH3O(S)→CH3OH(S), thus facilitated a CO2 conversion of 27.4% and CH3OH selectivity of 51% synergistically.

Men are traditionally portrayed as being successful in sports, and male teachers in physical activities are portrayed as successful teachers. How do female teachers perceive the gender role of kindergarten teachers in early childhood physical activities? Using hegemonic masculinity theory as an analytical tool, semi-structured interviews with female public kindergarten teachers from four cities in Zhejiang Province, China were conducted. The study found that although most Chinese female teachers had traditional gender stereotypes about the role of physical activity teachers in kindergartens, these gender stereotypes were not firmly established. As the questions were contextualized and deepened, thinking about the deeper elements of early childhood physical activity was activated. They did not seem to believe that women were incapable of leading young children in physical activities, nor did they believe that women were not important in ideal early childhood physical activities. By deconstructing the male-only nature of 'hegemonic masculinity', they reconstructed the masculinity that children need in early childhood physical activities and constructed a more equal concept of teachers' gender in early childhood physical activities.

Gastric cancer, as one of the malignant tumors with a significant disease burden globally, emphasizes the importance of early diagnosis and personalized treatment for improving patient prognosis. In recent years, clinical prediction models (CPMs) have played a crucial role in predicting disease risks, assisting medical decision-making, and evaluating clinical prognosis and benefits as tools for risk–benefit assessment. Nomograms, as an important visualization form of clinical prediction models, have been increasingly applied in tumor-related research. Numerous studies have constructed multiple nomogram models by integrating clinical, pathological, laboratory, imaging data, and genetic characteristics, providing an accurate and effective tool for predicting the risk of gastric cancer, early diagnosis, treatment response assessment, and prognosis analysis. This article aims to review the current clinical applications and research progress of nomograms in gastric cancer, with the goal of providing robust references and theoretical support for clinical practice.

BackgroundWomen are more likely to fall or even die when the ladder falls, which seriously affects the quality of daily life. It is necessary to better understand the plantar mechanism of the ladder falls and put forward reasonable suggestions.MethodTwenty healthy young women volunteered to participate in the experiment. The study used the F-scan plantar pressure to explore the difference in the plantar pressure in the dominance of the leading foot across four step descent height conditions. The landing strategy employed was recorded during the experiment. The Center of Pressure (COP), along with its medial-lateral (ML) and anterior-posterior (AP) adjustment velocities, and the VCOP, RCOP-ML, and RCOP-AP were analyzed.ResultWith an increase in the step height, significant enhancements were observed in the VCOP-ML (p < 0.001), VCOP-AP (p < 0.001), RCOP-ML (p < 0.001), and RCOP-AP (p < 0.001) during landing. There was no significant difference in the kinematic parameters of plantar pressure during stair descent, regardless of whether the dominant foot or non-dominant foot was the leading foot.ConclusionThis study found that among young women, an increase in step height during descent significantly affected the plantar pressure and led to greater COP adjustment in the directions of ML and AP, increasing the risk of injury. At a step height of 5 cm, the first choice of the landing strategy for female subjects began to change from the hindfoot to the forefoot. Although there were no significant differences in plantar pressure data and landing strategies between subjects using the dominant side and nondominant side as the forefoot, the dominant side forefoot exhibited better postural balance control than the nondominant side forefoot.

ObjectiveResearch on predictive models for hospital mortality in patients who have survived 24 h following cardiopulmonary resuscitation (CPR) is limited. We aim to explore the factors associated with hospital mortality in these patients and develop a predictive model to aid clinical decision-making and enhance the survival rates of patients post-resuscitation.MethodsWe sourced the data from a retrospective study within the Dryad dataset, dividing patients who suffered cardiac arrest following CPR into a training set and a validation set at a 7:3 ratio. We identified variables linked to hospital mortality in the training set using Least Absolute Shrinkage and Selection Operator (LASSO) regression, as well as univariate and multivariate logistic analyses. Utilizing these variables, we developed a prognostic nomogram for predicting mortality post-CPR. Calibration curves, the area under receiver operating curves (ROC), decision curve analysis (DCA), and clinical impact curve were used to assess the discriminability, accuracy, and clinical utility of the nomogram.ResultsThe study population comprised 374 patients, with 262 allocated to the training group and 112 to the validation group. Of these, 213 patients were dead in the hospital. Multivariate logistic analysis revealed age (OR 1.05, 95% CI: 1.03–1.08), witnessed arrest (OR 0.28, 95% CI: 0.11–0.73), time to return of spontaneous circulation (ROSC) (OR 1.05, 95% CI: 1.02–1.08), non-shockable rhythm (OR 3.41, 95% CI: 1.61–7.18), alkaline phosphatase (OR 1.01, 95% CI: 1–1.01), and sequential organ failure assessment (SOFA) (OR 1.27, 95% CI: 1.15–1.4) were independent risk factors for hospital mortality for patients who survived 24 h after CPR. ROC of the nomogram showed the AUC in the training and validation group was 0.827 and 0.817, respectively. Calibration curves, DCA, and clinical impact curve demonstrated the nomogram with good accuracy and clinical utility.ConclusionOur prediction model had accurate predictive value for hospital mortality in patients who survived 24 h after CPR, which will be beneficial for assisting in identifying high-risk patients and intervention. Further confirmation of the model's accuracy required external validation data.

ABSTRACT The surface water extent of global lakes/reservoirs is a fundamental input data for many studies. Although some datasets are currently available, issues such as incomplete data or spatial inconsistencies persist. In this study, a new Global Lakes/Reservoirs Surface Extent Dataset (GLRSED), which provides a more comprehensive spatial extent and basic attributes (e.g., name, area, source, depth and type) of 2.17 million individual features, was developed based on HydroLAKES and OpenStreetMap (OSM). In addition, by spatially overlaying with mountainous polygon, lakes/reservoirs in mountainous areas were identified. The Global Reservoir and Dam database (GRanD), GlObal geOreferenced Database of Dams (GOODD), Georeferenced global Dams and Reserves (GeoDAR) dataset, and OSM were used to distinguish reservoirs from natural lakes. The lakes/reservoirs in the rivers were identified by overlaying them with the Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD). Similarly, endorheic, glacier‐fed and permafrost‐fed lakes/reservoirs were identified using the same method. Furthermore, the coverage of the SWOT ground track for each lake/reservoir in the GLRSED was calculated to explore the potential of SWOT in monitoring water resources. Although preliminary and with some limitations, this dataset is promising. It can provide essential data for monitoring global lakes/reservoirs, support refined water resource management, and facilitate comprehensive studies on the impacts of human activities and climate change on these water bodies.

IntroductionThere are few studies on the effect of rumen fluid transplantation on the fecal flora of yaks. Yak fecal flora is closely related to their health. This study aimed to evaluate the effects of rumen fluid transplantation on growth performance and fecal flora indicators.MethodsTwenty 6-month healthy male yaks (weight: 57.20 ± 7.80 kg) were selected from grazing yaks in an alpine meadow pasture at an altitude of approximately 3,400 m. They were then transferred to a farm and randomly divided into a control group (CON; n = 10) and a rumen fluid transplantation group (RT; n = 10). Separate single-pen rearing was performed in two pens using the same rearing environment and feeding method, and all yaks were earmarked for identification. In addition, 10 yaks that had been adapted to stall fattening feed in 1 month were selected as the rumen fluid donor group to provide fresh rumen fluid. Ruminal fluid transplantation trials were conducted on the 1st, 3rd, and 5th weeks. Overall, 1 L of ruminal fluid was transplanted to each yak in the RT and CON groups. The formal trial then began with both groups fed the same diet. After this, yak feed intake was recorded daily; yaks were weighed on days 1, 30, and 60 of the formal trial; and yak feces were collected directly from the ground on days 1, 4, 7, 14, 30, and 60 to compare the microbial composition of the feces using 16S rRNA sequencing data.ResultsThe results showed that rumen fluid transplantation significantly increased the alpha diversity of fecal microflora (P < 0.05), and on day 30 of the experiment, both the operational taxonomic unit (OTU) and Shannon index were significantly higher in the RT group than the CON group (P < 0.05). In the principal coordinate analysis (PCoA) plot, the intestinal flora of the RT group was significantly different (P < 0.05) on days 1–7 but not significantly different after day 14. In contrast, the intestinal flora of the CON group was significantly different (P < 0.05) on days 1–14 but not significantly different after day 30. Compared with the CON group, the relative abundance of Firmicutes in the RT group was significantly lower on days 1, 4, 7, and 14 (P < 0.05); the relative abundance of Bacteroidetes in the RT group was significantly higher on days 1, 4, 14, and 30 and significantly lower on day 7 (P < 0.05); the relative abundance of Tenericutes in the RT group was significantly higher on day 30 (P < 0.05); the relative abundance of Actinobacteria in the RT group was significantly higher on day 60 (P < 0.05); the relative abundance of Ruminococcaceae_UCG-005 in the RT group was significantly lower on days 4, 7, 14, and 60 (P < 0.05); the relative abundance of Unidentified in the RT group was significantly higher on days 1, 4, and 7 days (P < 0.05); and the relative abundance of Rikenellaceae_RC9_gut_group, Bacteroides, and Christensenellaceae_R-7_group in the RT group was significantly higher on day 1 (P < 0.05). Moreover, Actinobacteria was positively correlated with ADG and negatively correlated with DMI; Tenericutes was positively correlated with weight and negatively correlated with F/G. Metabolism of terpenes and polyketones, metabolism of other amino acids, and energy metabolism were higher in the RT group than in the CON group. LEfSe analysis showed that 32 species were more abundant in the RT group and 11 in the CON group. In conclusion, our findings suggest that rumen fluid transplantation improved the stability of the intestinal tract of yaks, improved the immunity of yaks, and reduced the occurrence of intestinal diseases; rumen fluid transplantation remodeled the structure of the intestinal flora, shortened the time of remodeling the intestinal flora of yaks during the transition period, and accelerated yak adaptation to digest housed rations, reducing the DMI. The findings of this study provide new insights into yak microbial community transplantation and a reference for improving feed efficiency in the yak industry.

Introduction Previous population-based studies, mainly from high-income countries, have shown that a higher forced vital capacity (FVC) is associated with a lower risk of developing cardiometabolic diseases. The aim of this study was to assess the longitudinal association between spirometry measures and the onset of cardiometabolic diseases across sites in low-income, middle-income and high-income countries.Methods The study population comprised 5916 individuals from 15 countries participating in the Burden of Obstructive Lung Disease baseline and follow-up assessments. Postbronchodilator forced expiratory volume in 1 s (FEV1), FVC and FEV1/FVC were measured at baseline. Participants who reported having doctor-diagnosed hypertension, diabetes, heart disease and stroke at follow-up but not at baseline were considered new cases of these diseases. The association between lung function and the onset of participant-reported cardiometabolic diseases was assessed in each site using regression models, and estimates were combined using random effects meta-analysis. Models were adjusted for sex, age, smoking, body mass index and educational level.Results Participants with greater per cent predicted FVC were less likely to have new-onset diabetes (OR per 10%=0.91, 95% CI 0.84 to 0.99), heart disease (OR per 10%=0.86, 95% CI 0.80 to 0.92) and stroke (OR per 10%=0.81, 95% CI 0.73 to 0.89) during the follow-up period (mean±SD 9.5±3.6 years). A greater percentage of FEV1 was associated with a lower risk of onset of heart disease and stroke. No significant association was found between FEV1/FVC and onset of reported cardiometabolic diseases, except for a higher risk of diabetes (OR per 10%=1.21, 95% CI 1.08 to 1.35) in participants with higher FEV1/FVC.Conclusions The findings of this study suggest that a low FVC is more important than a low FEV1/FVC as a risk factor for developing cardiometabolic diseases. The value of including FVC in risk score models to improve their precision in predicting the onset of cardiometabolic diseases should be explored.

BackgroundStroke is the leading cause of disability globally, with antiplatelet therapy being crucial for secondary prevention but also increasing bleeding risks. This requires careful dosage adjustments to balance thrombosis and bleeding risks.ObjectiveThis study compared the efficacy and safety of low-dose versus standard-dose antiplatelet therapy in stroke patients.MethodsWe conducted a comprehensive search across multiple databases, including PubMed, Embase, the Cochrane Library, ClinicalTrials.gov, CNKI, and the Wanfang Medical Database, up to March 2024. Only randomized controlled trials assessing low-dose antiplatelet therapy in stroke patients were considered. The Cochrane Risk of Bias Tool (RoB 2) was used for quality. Performed meta-analysis using Stata 15.0, with relative risk (RR) and 95% confidence interval (CI) as effect estimates.ResultsTen studies involving 7,703 Asia participants, mainly from China and Japan, were analyzed. The meta-analysis revealed that low-dose reduces the risk of bleeding (RR 0.51; 95% CI 0.27, 0.98) compared to standard dose, with similar risks for stroke (RR 1.04; 95% CI 0.69, 1.55), myocardial infarction (MI) (RR 1.91; 95% CI 0.88, 4.12), all-cause death (ACD) (RR 1.17; 95% CI 0.38, 3.62), and major bleeding (RR 0.74; 95% CI 0.16, 3.30). Subgroup analysis revealed that compared to standard-dose clopidogrel, low-dose clopidogrel increased the risk of MI. Notably, this increased risk was observed specifically within the Chinese population but not in the Japanese population. Low-dose clopidogrel and low-dose prasugrel reduce the risk of bleeding compared to standard-dose clopidogrel, but there is no statistically significant difference. Low-dose aspirin significantly reduces the risk of bleeding compared to standard-dose aspirin.ConclusionIn patients with stroke in Asia, low-dose antiplatelet therapy significantly reduces the risk of bleeding compared to standard doses, with consistent risks of stroke, MI, ACD, major bleeding, and discontinuation due to bleeding.

The Chinese government has proposed shifting the regulation of energy consumption and intensity towards a dual control system of total carbon emissions and carbon emission intensity gradually, aiming to promote the continued role of green finance in optimizing resource allocation. To reveal the impact and mechanism of green finance on urban carbon emissions and intensity in China, this paper constructs a general equilibrium model based on endogenous growth theory and employs a two-way fixed effects model for empirical testing. The study finds that: (1) The development of green finance significantly inhibits both the total carbon emissions and carbon emission intensity of Chinese cities. (2) The impact of green finance on urban carbon emissions and intensity exhibits significant regional heterogeneity. In the northeastern regions of China, southeastern regions of the Hu Line, non-resource-based cities, and areas with higher financial efficiency, green finance can significantly reduce both urban carbon emissions and carbon emission intensity. However, in central and western regions and resource-based cities, green finance only suppresses urban carbon emission intensity. (3) Green finance can reduce urban carbon emissions and intensity through two channels: economic scale expansion and technological advancement, while the channel of industrial structure optimization has not yet shown a significant effect. Through research, it can be found that balancing the differences in green finance and carbon emission functions across regions, while fully optimizing the use and allocation mechanisms of resource elements from aspects such as technological innovation, environmental protection, and energy conservation, can enhance the quality and efficiency of economic development. This is of significant importance for green finance in promoting the realization of dual carbon control.

Longitudinal segmental smoke exhaust is often used for fire tunnels longer than 5 km. With the combined effect of longitudinal ventilation in the main tunnel and fan suction in the exhaust shaft, the smoke exhaust path is different from that of a traditional single-tube tunnel. Findings reported in the literature is insufficient to support the rapid development of extra-long road tunnels. In this paper, a numerical model was established by FDS (Fire Dynamics Simulator), and a 1:15 model test platform was built for verification. The effects of different longitudinal velocities, exhaust velocities, bifurcation angles, and exhaust shaft slopes on tunnel fires were analyzed for the longitudinal ventilation combined with shaft exhaust smoke evacuation mode (LVSE). The results show that when the exhaust velocity is greater than 4.5 m/s, increasing the exhaust velocity has a limited effect on reducing the smoke length downstream of the exhaust shaft. The bifurcation angle has a significant effect on the velocity distribution in the ventilation shaft and the main tunnel. When the bifurcation angle is less than 45°, the airflow in the main tunnel is more likely to enter the exhaust shaft, and the velocity in the exhaust shaft is more than 5 m/s. It is more favorable to reduce the smoke length when the slope of the exhaust shaft is not less than 7 %. The high-temperature flue gas collects and forms a vortex near the vent under the LVSE mode, which makes the temperature decay rate slower than that when only longitudinal ventilation is used. The temperature decay model for the LVSE mode is obtained. This study is intended to provide a reference basis for the fire safety design of extra-long road tunnels under the LVSE mode.

BackgroundThe Arp2/3 complex is a key regulator of tumor metastasis, and targeting its subunits offers potential for anti-metastatic therapy. However, the expression profiles, prognostic relevance, and diagnostic value of its subunits across cancers remain poorly understood. This study aims to investigate the clinical relevance of Arp2/3 complex subunits, particularly ARPC1A, in pan-cancer, and to further analyze the potential biological mechanisms of ARPC1A, as well as its association with immune infiltration and chemotherapy drug sensitivity.MethodsTo explore the differential expression of Arp2/3 complex subunits and their clinical relevance across cancers, we analyzed data from TCGA and GTEx databases. The relationship between ARPC1A and immune infiltration, as well as its interactions with functional proteins, was examined using the TCPA and TIMER2.0 databases. Gene Set Enrichment Analysis (GSEA) was performed to identify ARPC1A-associated signaling pathways. Chemotherapy drug sensitivity correlated with ARPC1A expression was assessed using CellMiner, GDSC, and CTRP databases. The effect of ARPC1A on c-Myc expression was validated by quantitative PCR (qPCR) and Western blot. Finally, the biological role of ARPC1A in non-small cell lung cancer (NSCLC) cells was further validated using CCK-8, EdU incorporation, colony formation, and Transwell assays.ResultsThe Arp2/3 complex subunits, particularly ARPC1A, are frequently overexpressed in a majority of cancers, correlating with poor prognostic outcomes and demonstrating significant diagnostic utility. Copy number variations may play a role in the dysregulation of Arp2/3 complex subunit expression. The small molecule X4.5.dianilinophthalimide has shown promise as a targeted therapeutic agent in a pan-cancer context. Functional predictions indicate that ARPC1A is implicated in oxidative phosphorylation pathways and cell proliferation-related signaling pathways, including those mediated by MYC, with ASNS potentially acting as an upstream regulator. Furthermore, ARPC1A has been implicated in the resistance to chemotherapy drugs, including gefitinib. In vitro experiments corroborate that ARPC1A may enhance malignant phenotypes in non-small cell lung cancer (NSCLC) cells through the regulation of c-Myc expression.ConclusionOur study offers novel insights into targeting Arp2/3 complex subunits as an anti-cancer strategy and underscores the potential of ARPC1A as a novel biomarker for tumor diagnosis, prognosis, and the prediction of immune therapy responses.

Polo-like kinase 1 (PLK1), a key regulator of the G2/M phase in mitosis, is frequently overexpressed in numerous tumors. Although PLK1 inhibitors have emerged as promising therapeutic agents for cancer, their use has been linked to significant anemia in a subset of patients, yet the underlying mechanisms remain poorly understood. In this study, we utilized an in vitro human umbilical cord blood-derived CD34+ cell-based erythroid differentiation system, alongside a murine model, to investigate the impact of PLK1 inhibitors on erythropoiesis. Our results indicate that PLK1 inhibitors, specifically GSK461364 and BI6727, significantly suppress the proliferation of erythroid cells, resulting in G2/M phase cell cycle arrest, increased apoptosis in erythroid cells, and the formation of abnormally nucleated late-stage erythroblasts. In vivo, administration of PLK1 inhibitors in mice induced severe anemia, as evidenced by a marked reduction in red blood cells and hemoglobin levels. More specifically, PLK1 inhibition impaired the differentiation and erythroid commitment of hematopoietic stem cells in the bone marrow, resulting in abnormal accumulation of BFU-E cells and reduced proliferation and differentiation of CFU-E, and a decrease in the number of terminal erythrocytes. Mechanistically, PLK1 inhibitors primarily induce apoptosis in erythroid cells by reducing Mitochondrial membrane potential and arresting the cell cycle at the G2/M phase. Overall, our findings underscore the critical role of PLK1 in erythropoiesis and shed light on the mechanisms underlying PLK1 inhibitor-induced anemia, providing essential guidance for developing strategies to prevent and manage anemia in clinical applications of PLK1-targeted therapies.

ABSTRACT Background and Purpose Liver cancer has a high recurrence rate of 50%~70% for early‐stage patients. Minimal residual disease (MRD) is strongly linked to liver cancer early recurrence. Identifying MRD through reliable prognostic biomarkers, such as circulating tumor DNA (ctDNA), could significantly benefit these patients by enabling timely intervention and improved outcomes. Materials and Methods A prospective study enrolled 32 liver cancer patients undergoing radical surgery. Peripheral blood samples (8 mL) were collected before and after surgery. In this study, we expanded upon our previously developed multi‐omics assay, initially designed for liver cancer early detection by calculating a cancer signal score (PHCC), to determine the MRD status (named SeekInCure). This process integrated protein tumor marker alpha‐fetoprotein (AFP) and cancer genomic hallmarks, copy number aberration (CNA) and fragment size (FS). Results Of the enrolled patients, 78.1% were in early stages, and before surgery, 87.5% of patients had successfully detected the cancer signal in blood. After radical surgery, 23 patients were MRD‐negative, exhibiting better overall survival compared to the MRD‐positive patients (n = 9, p

ObjectiveAnxiety and depression-like symptoms occur in the early stages of Alzheimer’s disease. Hippocampal Sirtuin 1 (SIRT1) signaling mediates anxiety- and depression-like behavior. Exercise training improves anxiety and depression-like behavior in various disease models, such as the rat chronic restraint stress model, rat model of posttraumatic stress disorder, and rat model of fetal alcohol spectrum disorders. Here, we aimed to investigate whether exercise ameliorates anxiety- and depression like behaviors in APP/PS1 mice and explore the potential mechanisms.MethodsAfter eight weeks of exercise intervention, we assessed anxiety- and depression-like behaviors in Alzheimer’s disease (AD) model mice. We then measured the levels of SIRT1, peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC1α), nuclear respiratory factor 1 (NRF1), mitochondrial transcription factor A (TFAM), and mitochondrial biogenesis (CO2, ATP6, and mitochondrial content) using immunofluorescence, reverse transcription-quantitative real-time PCR, and transmission electron microscopy. Finally, we investigated the effects of pharmacological activation of SIRT1 on anxiety- and depression-like behaviors, the SIRT1/PGC-1α/NRF1/TFAM signaling axis, and mitochondrial biogenesis.ResultsWe first observed that treadmill exercise improved anxiety- and depression-like behaviors in six-month-old APP/PS1 mice and increased SIRT1 levels in the hippocampus. Pharmacological activation of hippocampal SIRT1 function also reduced anxiety and depression-like behaviors in APP/PS1 mice. Meanwhile, both treadmill exercise and pharmacological activation of hippocampal SIRT1 increased the levels of PGC1α, NRF1, TFAM, and enhanced mitochondrial biogenesis (CO2, ATP6, or mitochondrial content) in the hippocampus of APP/PS1 mice.ConclusionThese findings reveal that treadmill exercise reduces anxiety- and depression-like behaviors in six-month-old APP/PS1 mice by enhancing the SIRT1-dependent PGC-1α/NRF1/TFAM axis, promoting mitochondrial biogenesis in the hippocampus.

Bisphenol S (BPS) derivatives have potential reproductive developmental toxicity and have been found in the environment and in breast milk. The level of infant exposure and the source are currently unknown. In this study, we investigated BPS and six derivatives (together referred to as BPs) in urine samples from mothers and infants, indoor dust, breast milk and infant formula in Beijing, China. BPS, diphenyl sulfone (DPS) and 4-allyloxy-4′-hydroxydiphenyl sulfone (BPS-MAE) were the main BPs. Notably, the concentration of DPS in infants’ urine was higher than that of BPS, which warrants attention. Infants have higher daily intake levels than mothers. Exclusively breastfed infants have a higher risk of BPs exposure than exclusively formula-fed infants. For exclusive breastfed infants, the contribution of individual BPs through breast milk was 23.2% to 93.6%. While for exclusively formula-fed infants, the contribution of individual BPs through infant formula was 30.5% to 70.3%. The contribution of individual BPs through indoor dust was no more than 10%. The results suggesting that infants can be exposed to BPs through other pathways. This is the first comprehensive assessment of maternal and infants exposure to BPS derivatives, providing insights into the sources of infant exposure.

Summary: Small for gestational age (SGA) infants affected by placental insufficiency are exposed to the risk of stillbirth and long-term complications. Based on RNA-seq and mass spectrometry, we identified dysregulated RNAs and proteins from the comparisons of SGA placental tissues and controls. We revealed two SGA-relevant co-expression modules (SRMs) that also significantly distinguished SGA from controls. Then we performed an integrated analysis of transcriptomic and proteomic profiles to trace their links to SGA as well as their significant correlations. For the core functional molecules we screened, we revealed their potential upstream regulators and validated them experimentally in an independent cohort. Overall, we pointed out insights into different molecular pathways for the pathological mechanisms of SGA and indicated potential target molecules that may be drivers of placental aberrations in the SGA infants.

The aging of pancreatic beta cells is closely associated with various diseases, such as impaired glucose tolerance, yet the underlying regulatory mechanisms remain unclear. In this study, we screened young and aged mouse pancreatic beta cells' high-throughput sequencing data from the GEO public database. Utilizing bioinformatics techniques, we identified the key regulatory factor YY1 in the aging process of pancreatic islets. We observed a significant decrease in the expression of YY1 in a D-gal-induced mouse model of pancreatic aging and an H2O2-induced MIN6 cell model of aging. Moreover, both vivo and vitro models, we found that the YY1 agonist eudesmin (EDN) improved glucose intolerance in mice, alleviated aging of pancreatic beta cells, and downregulated the expression of cell cycle protein P21. Mechanistically, we discovered that EDN inhibited the P38/JNK MAPK pathway in aging cells. In summary, our study confirms the regulatory role of the transcription factor YY1 in the aging process of pancreatic beta cells. This finding may provide a new approach for the clinical treatment of pancreatic aging-related diseases such as impaired glucose tolerance or diabetes.

ABSTRACTThe arginine deiminase system (ADS) has been identified in various bacteria and functions to supplement energy production and enhance biological adaptability. The current understanding of the regulatory mechanism of ADS and its effect on bacterial pathogenesis is still limited. Here, we found that the XRE family transcriptional regulator XtrSs negatively affected Streptococcus suis virulence and significantly repressed ADS transcription when the bacteria were incubated in blood. Electrophoretic mobility shift (EMSA) and lacZ fusion assays further showed that XtrSs directly bind to the promoter of ArgR, an acknowledged positive regulator of bacterial ADS, to repress ArgR transcription. Moreover, we provided compelling evidence that S. suis could utilize arginine via ADS to adapt to acid stress, while ΔxtrSs enhanced this acid resistance by upregulating the ADS operon. Moreover, whole ADS-knockout S. suis increased arginine and antimicrobial NO in the infected macrophage cells, decreased intracellular survival, and even caused significant attenuation of bacterial virulence in a mouse infection model, while ΔxtrSs consistently presented the opposite results. Our experiments identified a novel ADS regulatory mechanism in S. suis, whereby XtrSs regulated ADS to modulate NO content in macrophages, promoting S. suis intracellular survival. Meanwhile, our findings provide a new perspective on how Streptococci evade the host’s innate immune system.

ABSTRACTThis study aimed to provide data for the clinical features of invasive pneumococcal disease (IPD) and the molecular characteristics of Streptococcus pneumoniae isolates from paediatric patients in China. We conducted a multi-centre prospective study for IPD in 19 hospitals across China from January 2019 to December 2021. Data of demographic characteristics, risk factors for IPD, death, and disability was collected and analysed. Serotypes, antibiotic susceptibility, and multi-locus sequence typing (MLST) of pneumococcal isolates were also detected. A total of 478 IPD cases and 355 pneumococcal isolates were enrolled. Among the patients, 260 were male, and the median age was 35 months (interquartile range, 12–46 months). Septicaemia (37.7%), meningitis (32.4%), and pneumonia (27.8%) were common disease types, and 46 (9.6%) patients died from IPD. Thirty-four serotypes were detected, 19F (24.2%), 14 (17.7%), 23F (14.9%), 6B (10.4%) and 19A (9.6%) were common serotypes. Pneumococcal isolates were highly resistant to macrolides (98.3%), tetracycline (94.1%), and trimethoprim/sulfamethoxazole (70.7%). Non-sensitive rates of penicillin were 6.2% and 83.3% in non-meningitis and meningitis isolates. 19F-ST271, 19A-ST320 and 14-ST876 showed high resistance to antibiotics. This multi-centre study reports the clinical features of IPD and demonstrates serotype distribution and antibiotic resistance of pneumococcal isolates in Chinese children. There exists the potential to reduce IPD by improved uptake of pneumococcal vaccination, and continued surveillance is warranted.

Objective The relationship between serum total cholesterol (TC) and triglyceride (TG) levels and mortality in maintenance hemodialysis (MHD) patients remains inconsistent. We aimed to explore the individual and combined association of TC and TG levels with the risk of mortality in Chinese MHD patients.Methods 1036 MHD patients were enrolled in this multicenter, prospective cohort study. The serum levels of total cholesterol and triglycerides were measured at baseline. The primary outcome was all-cause mortality and secondary outcome was cardiovascular disease (CVD) mortality.Results During a median follow-up duration of 4.4 years (IQR= 2.0–7.9 years), 549 (53.0%) patients died, and 297 (28.7%) deaths were attributed to CVD. Compared with patients with TC levels in the first three quartiles (

Non-landslide samples influence the outcomes of landslide susceptibility assessment. Existing studies did not fully consider the equilibrium between landslide and non-landslide samples in similar environments, resulting in poor reliability of landslide susceptibility assessment. This study proposed a non-landslide samples optimization method with a constraint of disaster-pregnant environment similarity to construct the balanced landslide and non-landslide samples. We employed the heterogeneous stacking and blending ensemble learning models to generate the landslide susceptibility assessment. This study focused on the Bailong River Basin with complex environment and frequent landslides as the study area. First, we extracted 12 landslide influencing factors based on multiple sources and analyzed the spatial distribution patterns of landslides. Second, we constructed similar environments based on the assessment units obtained from the curvature watershed method and selected an equal amount of both landslide and non-landslide samples in every different environment. Finally, three classic neural network models, namely multilayer perceptron, convolutional neural network, and gated recurrent unit were used as base models for stacking and blending ensemble learning models to assess landslide susceptibility. The findings suggested that the landslide susceptibility assessment results with optimized non-landslide samples were more reliable, especially the proposed method improved the prediction results in sample-sparse regions. The stacking ensemble constructed in this study demonstrated the highest area under the curve of 0.88 for the testing dataset, outperforming the blending ensemble and three base models. The issue of unreliable landslide susceptibility assessment results in sample-sparse regions within complex environments can be effectively addressed by considering the balanced sampling of non-landslide samples under the constraint of similar environments.

Growing environmental challenges and expanding megaprojects have necessitated green transformation of the construction industry. This paper takes the Shenzhong Link Project as an example to explore the capacities required for achieving the goal of green innovation, as well as its micro-expression and behavioral path. We begin with the idea that megaprojects are complex, and then we dissect the capacities from both soft and hard system levels, categorizing them into basic and composite capacities. Then, we form the integration of capacities to realize green innovation of megaprojects. Green development is an essential prerequisite for high-quality megaproject development. Our approach provides a guided study on how to enhance the role of micro-internal drivers in the management of attaining green innovation in megaprojects to help project managers achieve green performance and promote quality development.

The COVID-19 pandemic increased the burden due to school closures and stay-at-home orders, disrupting the community energy balance. This study examines rising obesity trends among Korean adolescents during school closures, focusing on gender differences and immigrant-origin youths – those of foreign descent or with at least one foreign-born parent. We analysed data from the Korea Youth Risk Behavior Web-based Survey (KYRBS) (N = 539,187). The study aims to assess BMI trends between 2013 and 2022, examine the impact of school closures, and explore differential obesity risks among immigrant-origin youths by gender. Regression models with interaction terms were used to analyse BMI trends and pandemic effects on immigrant-origin youths compared to non-immigrant-origin youths, with gender subgroup analyses. Results show increased BMI for all adolescents, with a notable rise and higher overweight risks in immigrant-origin male adolescents during COVID-19. These findings highlight the need for gender-specific interventions in schools for immigrant-origin youths.

Improving the sustainability and processability of shape memory composites is key to expanding their applications. This work introduces a novel bio-based shape memory composite resin with renewable cellulose nanocrystals, suitable for stereolithography (SLA) printing. We prepared epoxy soybean oil-based composites by incorporating Itaconic acid monomethyl ester (IAME) modified cellulose nanocrystals (CNCs-IAME) into IAME modified epoxy soybean oil (IESO). The CNCs-IAME/IESO composite resin, with a viscosity of 1.01–1.22 Pa•s, is ideal for SLA printing. Adding 0.75 wt% CNCs-IAME particles enhances mechanical properties, yielding a tensile strength of 19.54 MPa and elongation at a break of 34.03%. Demonstrated applications include flexible supports and temperature-responsive sensors. This innovative composite offers excellent sustainability and SLA-printability, showing great potential for new bio-based heat-activated shape memory materials.

NDVI (Normalized Difference Vegetation Index) is an essential tool for climate and environmental monitoring, but it is often contaminated by clouds and unfavorable atmospheric conditions. In this study, we designed a new, simple yet effective method for reconstructing data, which we call the Hybrid Filter. This study is the first to reconstruct missing NDVI time series data in cloud-prone areas by combining several data reconstruction techniques with a forecasting technique based on Exponential Moving Average (EMA). The study was conducted in Cilegon City and Batu City using NDVI time series data from the Landsat 8 satellite for the period 2014-2022. Experimental results show that the hybrid filter significantly outperforms the Spatio-Temporal Savitzky-Golay (STSG) filter, Gap Filling Savitzky-Golay (GFSG) filter, Savitzky-Golay (SG) filter, and Whittaker filter. The hybrid filter is capable of recovering missing data with high accuracy, stability, noise reduction, and maintaining the temporal integrity of NDVI data even under conditions of large data gaps and high missing data rates, making it a reliable solution for NDVI analysis in cloud-prone areas. These findings affirm the superiority of the hybrid filter in producing accurate and reliable NDVI data for vegetation and environmental monitoring.

In the evolving landscape of the digital era, edge computing emerges as an essential paradigm, especially critical for low-latency, real-time applications and Internet of Things (IoT) environments. Despite its advantages, edge computing faces severe limitations in storage capabilities and is fraught with reliability issues due to its resource-constrained nature and exposure to challenging conditions. To address these challenges, this work presents a tailored storage mechanism for edge computing, focusing on space efficiency and data reliability. Our method comprises three key steps: relation factorization, column clustering, and erasure encoding with compression. We successfully reduce the required storage space by deconstructing complex database tables and optimizing data organization within these sub-tables. We further add a layer of reliability through erasure encoding. Comprehensive experiments on TPC-H datasets substantiate our approach, demonstrating storage savings of up to 38.35% and time efficiency improvements by 3.96x in certain cases. Furthermore, our clustering technique shows a potential for additional storage reduction up to 40.41%.