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Abstract Introduction Glioma, particularly glioblastoma (GBM), is a highly malignant brain tumor with poor prognosis despite current therapeutic approaches. The tumor microenvironment (TME), plays a crucial role in glioma progression by promoting invasion and drug resistance. Angiogenesis, the formation of new blood vessels, is a tightly regulated process involving endothelial cell activation, proliferation, and migration. In cancer, angiogenesis becomes dysregulated, leading to excessive blood vessel formation. Methods We enrolled bulk data of TCGA-LGG/GBM, CGGA-693, and CGGA-325 cohorts, scRNA data of GSE162631, GSE84465, and GSE138794 cohorts. Identification of malignant cells was conducted by “copycat” R package. The “AUCell” R package scored the activity of target gene set of each single cell. Consensus clustering was applied using the “ConsensusClusterPlus” R package, while tumor-infiltrating immune cells were determined using “IOBR” R package. To construct a prognostic model, we used LASSO and multiCOX algorithms based on the expression levels of the 15 hub genes, the efficacy of which was verified by KM and ROC analysis. Results We identified 4 different malignant cell subclusters in glioma and disclosed their distinct gene expression patterns and interactions within TME. We identified differentially expressed immune-related genes (DE-ARGs) in glioma and found 15 genes that were specifically expressed in the malignant glioma cell populations. Glioma cells with higher expression of these DE-ARGs were associated with gliogenesis, glial cell development, and vasculature development. We found that tumor-infiltrating monocytes were the main interacting cell type within glioma TME. Using the expression patterns of the 15 screened DE-ARGs, we categorized glioma samples into 2 molecular clusters with distinct immune features, suggesting a possible relationship between angiogenesis and immune activation and recruitment. We constructed a prognostic model based on the expression levels of the 15 DE-ARGs and evaluated its predictive ability for glioma patient outcomes, which displayed exceedingly high efficacy. Conclusion We characterized different malignant cell subclusters in glioma and investigate their gene expression patterns and interactions within TME. We constructed a prognostic model based on the expression levels of the 15 DE-ARGs and evaluated its predictive ability for glioma patient outcomes, which displayed exceedingly high efficacy.

Abstract The chemical recycling of polyester wastes is of great significance for sustainable development, which also provides an opportunity to access various oxygen-containing chemicals, but generally suffers from low efficiency or separation difficulty. Herein, we report anatase TiO2 supported Ru and Mo dual-atom catalysts, which achieve transformation of various polyesters into corresponding diols in 100% selectivity via hydrolysis and subsequent hydrogenation in water under mild conditions (e.g., 160 °C, 4 MPa). Compelling evidence is provided for the coexistence of Ru single-atom and O-bridged Ru and Mo dual-atom sites within this kind of catalysts. It is verified that the Ru single-atom sites activate H2 for hydrogenation of carboxylic acid derived from polyester hydrolysis, and the O-bridged Ru and Mo dual-atom sites suppress hydrodeoxygenation of the resultant alcohols due to a high reaction energy barrier. Notably, this kind of dual-atom catalysts can be regenerated with high activity and stability. This work presents an effective way to reconstruct polyester wastes into valuable diols, which may have promising application potential.

BackgroundWe aim to develop a new prognostic model that incorporates inflammation, nutritional parameters and clinical-pathological features to predict overall survival (OS) and disease free survival (DFS) of breast cancer (BC) patients.MethodsThe study included clinicopathological and follow-up data from a total of 2857 BC patients between 2013 and 2021. Data were randomly divided into two cohorts: training (n=2001) and validation (n=856) cohorts. A nomogram was established based on the results of a multivariate Cox regression analysis from the training cohorts. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. Furthermore, decision curve analysis (DCA) was performed to assess the clinical value of the nomogram.ResultsA nomogram was developed for BC, incorporating lymphocyte, platelet count, hemoglobin levels, albumin-to-globulin ratio, prealbumin level and other key variables: subtype and TNM staging. In the prediction of OS and DFS, the concordance index (C-index) of the nomogram is statistically greater than the C-index values obtained using TNM staging alone. Moreover, the time-dependent AUC, exceeding the threshold of 0.7, demonstrated the nomogram’s satisfactory discriminative performance over different periods. DCA revealed that the nomogram offered a greater overall net benefit than the TNM staging system.ConclusionThe nomogram incorporating inflammation, nutritional and clinicopathological variables exhibited excellent discrimination. This nomogram is a promising instrument for predicting outcomes and defining personalized treatment strategies for patients with BC.

Abstract Chemical recycling of plastic wastes is of great significance for sustainable development, which also represents a largely untapped opportunity for the synthesis of value-added chemicals. Herein, we report a novel and general strategy to degrade polyesters via directly breaking the Calkoxy-O bond by nucleophilic substitution of halide anion of ionic liquids under mild conditions. Combined with hydrogenation over Pd/C, 1-butyl-2,3-dimethylimidazolium bromide can realize the deconstruction of various polyesters including aromatic and aliphatic ones, copolyesters and polyester mixtures into corresponding carboxylic acids and alkanes; meanwhile, tetrabutylphosphonium bromide can also achieve direct decomposition of the polyesters with β-H into carboxylic acids and alkenes under hydrogen- and metal-free conditions. It is found that the hydrogen-bonding interaction between ionic liquid and ester group in polyester enhances the nucleophilicity of halide anion and activates the Calkoxy-O bond. The findings demonstrate how polyester wastes can be a viable feedstock for the production of carboxylic acids and hydrocarbons.

In the modern era, the significance of incentive mechanisms spans a variety of fields, including the development of smart cities, the dynamics within social information networks, and the realm of online education. This study introduces an innovative incentive strategy, grounded in the use of blockchain contracts, aimed at cultivating reliable interactions among participants while simultaneously bolstering the security and effectiveness of digital learning resources. By capitalizing on the inherently decentralized architecture of blockchain technology, this research unveils a novel approach to digital learning resources, encompassing both the concept and its associated storage framework. Moreover, the study proposes a dynamic optimization model specifically designed for the blockchain of educational resources. This model is crafted to fit seamlessly within the context of real-world educational settings, taking into careful consideration the diverse viewpoints of all stakeholders engaged with particular educational materials. In the realm of practical education, particularly within the domain of computer science, this approach emphasizes the integration of pertinent learning materials into blockchain nodes, thereby addressing key educational content. By implementing a blockchain smart contract, an incentive mechanism is created that rewards both learners and resource contributors, effectively encouraging active participation in resource development and quality improvement. This mechanism effectively tackles challenges in the learning process, such as inaccurate resource access, reduced learning efficiency, and the scarcity of current, high-quality online resources. Experimental findings show that the smart contract-driven online learning resource incentive mechanism significantly improves teaching effectiveness.

Abstract The chemical transformation of waste polymers into value-added chemicals is of significance for circular economy and sustainable development. Herein, we report upcycling poly(succinates) (PSS) with amines into N-substituted succinimides over succinimide anion-based ionic liquids (ILs, e.g, 1,8-diazabicyclo[5.4.0]undec-7-ene succinimide, [HDBU][Suc]). Assisted with H2O, [HDBU][Suc]) showed the best performance, which could achieve complete transformation of a series of PSS into succinimide derivatives and corresponding diols under mild and metal-free conditions. Mechanism investigation indicates that the cation-anion confined hydrogen-bonding interactions among IL, H2O, ester group, and amino/amide groups, strengthens nucleophilicity of the N atoms in amino/amide groups, and improves electrophilicity of carbonyl C atom in ester group. The attack of the amino/amide N atom on carbonyl C of ester group results in cleavage of carbonyl C-O bond in polyester and formation of amide group. This strategy is also effective for aminolysis of poly(trimethylene glutarate) to glutarimides, and poly(1,4-butylene adipate) to caprolactone diimides.

Surveillance is an essential work on infectious diseases prevention and control. When the pandemic occurred, the inadequacy of traditional surveillance was exposed, but it also provided a valuable opportunity to explore new surveillance methods. This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness (ILI) surveillance. A novel hybrid model (multiattention bidirectional gated recurrent unit (MABG)–susceptible–exposed–infected–removed (SEIR)) was developed, which leveraged a deep learning algorithm (MABG) to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever, pyrexia, cough, sore throat, anti-fever medicine, and runny nose. By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019 (COVID-19) cases, a transmission dynamics model (SEIR) was formulated to estimate the transmission dynamics and epidemic curve of SARS-CoV-2. During the COVID-19 pandemic, when conventional surveillance measures have been suspended temporarily, cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19. In the specific case of Beijing, it has been ascertained that cumulative infection attack rate surpass 80.25% (95% confidence interval (95% CI): 77.51%–82.99%) since December 17, 2022, with the apex of the outbreak projected to transpire on December 12. The culmination of existing patients is expected to occur three days subsequent to this peak. Effective reproduction number (Rt) represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic, remained below 1 since December 17, 2022. The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support. Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks. Syndrome surveillance on COVID-19 should be established to following on the epidemic, clinical severity, and medical resource demand.

BackgroundBreast cancer (BC) is the most common and prominent deadly disease among women. Predicting BC survival mainly relies on TNM staging, molecular profiling and imaging, hampered by subjectivity and expenses. This study aimed to establish an economical and reliable model using the most common preoperative routine blood tests (RT) data for survival and surveillance strategy management.MethodsWe examined 2863 BC patients, dividing them into training and validation cohorts (7:3). We collected demographic features, pathomics characteristics and preoperative 24-item RT data. BC risk factors were identified through Cox regression, and a predictive nomogram was established. Its performance was assessed using C-index, area under curves (AUC), calibration curve and decision curve analysis. Kaplan-Meier curves stratified patients into different risk groups. We further compared the STAR model (utilizing HE and RT methodologies) with alternative nomograms grounded in molecular profiling (employing second-generation short-read sequencing methodologies) and imaging (utilizing PET-CT methodologies).ResultsThe STAR nomogram, incorporating subtype, TNM stage, age and preoperative RT data (LYM, LYM%, EOSO%, RDW-SD, P-LCR), achieved a C-index of 0.828 in the training cohort and impressive AUCs (0.847, 0.823 and 0.780) for 3-, 5- and 7-year OS rates, outperforming other nomograms. The validation cohort showed similar impressive results. The nomogram calculates a patient’s total score by assigning values to each risk factor, higher scores indicating a poor prognosis. STAR promises potential cost savings by enabling less intensive surveillance in around 90% of BC patients. Compared to nomograms based on molecular profiling and imaging, STAR presents a more cost-effective, with potential savings of approximately $700-800 per breast cancer patient.ConclusionCombining appropriate RT parameters, STAR nomogram could help in the detection of patient anemia, coagulation function, inflammation and immune status. Practical implementation of the STAR nomogram in a clinical setting is feasible, and its potential clinical impact lies in its ability to provide an early, economical and reliable tool for survival prediction and surveillance strategy management. However, our model still has limitations and requires external data validation. In subsequent studies, we plan to mitigate the potential impact on model robustness by further updating and adjusting the data and model.

Abstract Background IL-33 is a multifunctional cytokine with dual functions. However, the clinicopathological and prognostic significance of IL-33 in cancer patients, especially in patients with hepatocellular carcinoma (HCC), remains controversial. Therefore, we conducted a study of 565 patients with HCC and 561 healthy controls and performed a meta-analysis to quantitatively evaluate the above problems. Methods We collected blood from 565 patients with HCC and 561 healthy controls. ELISA was used to detect the concentrations of IL-33 and ST2 in the serum, and RT‒PCR was used to detect the levels of IL-33 and ST2 mRNA. Meanwhile, we collected comprehensive literature on IL-33 and the clinical characteristics of cancer patients retrieved from the PubMed, Web of Science and CNKI databases as of December 2022. An odds ratio (OR) with a 95% confidence interval (CI) was used to estimate the impact through overall and stratified analyses. Results Compared with the healthy control group, the levels of ST2 mRNA and serum in the peripheral blood of HCC patients increased (p 0.05). In the meta-analysis section, at the tissue level, the overall analysis showed that the expression of IL-33 was positively correlated with tumor stage, histological grade, distant metastasis, and tumor size. Compared with patients with low IL-33 expression, the 3-year overall survival (OS) rate (OR = 3.467, p

The BeiDou Navigation Satellite System (BDS) has developed rapidly, and the combination of BDS Phase II (BDS-2) and BDS Phase III (BDS-3) has attracted wide attention. It is found that there are code ISBs between BDS-2 and BDS-3, which may have a certain impact on the BDS-2 and BDS-3 combined positioning. This paper focuses on the performance of BDS-2/BDS-3 combined B1I single-frequency pseudorange positioning and investigates the positioning performance with and without code ISBs correction for different types of receivers, include geodetic GNSS receivers and low-cost receivers. The results show the following: (1) For geodetic GNSS receivers, the code ISBs of each receiver is about −0.3 m to −0.8 m, and the position deviation is reduced by 7% after correcting code ISBs. The code ISBs in the baseline with homogeneous receivers has a little influence on the positioning result, which can be ignored. The code ISBs in the baseline with heterogeneous receivers is about −0.5 m, and the position deviation is reduced by 4% after correcting code ISBs. (2) The code ISBs in the low-cost receivers are significantly larger than those in the geodetic GNSS receivers, and the impact on the positioning performance of the low-cost receivers is significantly greater than that on the geodetic GNSS receivers. After correcting the code ISBs, the position deviation of low-cost receivers can be reduced by around 12% for both undifferenced and differenced modes. (3) For low-cost receivers, correcting the code ISBs can increase the number of epochs successfully solved, which effectively improves the low-cost navigation and positioning performance. (4) The carrier-phase-smoothing method can effectively reduce the distribution dispersion of code ISBs and make the estimation of ISBs more accurate. The STD values of estimated code ISBs in geodetic GNSS receivers are reduced by about 40% after carrier-phase smoothing, while the corresponding values are reduced by about 7% in low-cost receivers due to their poor carrier-phase observation quality.

Global navigation satellite system (GNSS) provides users with all-weather, continuous, high-precision positioning, navigation, and timing (PNT) services. In the operation and use of GNSS, the influence of the space environment is a factor that must be considered. For example, during geomagnetic storms, a series of changes in the Earth’s magnetosphere, ionosphere, and upper atmosphere affect GNSS’s positioning performance. To investigate the positioning performance of global satellite navigation systems during geomagnetic storms, this study selected three geomagnetic storm events that occurred from September to December 2023. Utilizing the global positioning system (GPS)/Beidou navigation satellite system (BDS) dual-system, kinematic precise point positioning (PPP) experiments were conducted, and the raw observational data from 100 stations worldwide was analyzed. The experimental results show that the positioning accuracy of some stations in high-latitude areas decreases significantly when using the conventional Geometry Free (GF) cycle-slip detection threshold during geomagnetic storms, which means that the GF is no longer applicable to high-precision positioning services. Meanwhile, there is no significant change in the satellite signal strengths received at the stations during the period of the decrease in positioning accuracy. Analyzing the cycle-slip rates for stations where abnormal accuracy occurred, it was observed that stations experiencing a significant decline in positioning accuracy exhibited serious cycle-slip misjudgments. To improve the kinematic PPP accuracy during magnetic storms, this paper proposes an adaptive threshold for cycle-slip detection and designs five experimental strategies. After using the GF adaptive threshold, the station positioning accuracy improved significantly. It achieved the accuracy level of the quiet period, while the cycle-slip incidence reached the average level. During magnetic storms, the ionosphere changes rapidly, and the use of the traditional GF constant threshold will cause serious cycle-slip misjudgments, which makes the dynamic accuracy in high latitude areas and some mid-latitude areas uncommon, while the use of the GF adaptive threshold can alleviate this phenomenon and improve the positioning accuracy in the high-latitude regions and some of the affected mid-latitude areas during the magnetic storms.

Diaspore dispersal is crucial in shaping plant population dynamics, biodiversity, and ecosystem functions. The effect of the vegetation structure on the secondary wind dispersal of diaspores with different appendage types is not well understood. Using a wind tunnel and a high-definition video camera, we accurately measured the lift-off and dispersal velocities of diaspores from sixteen plant species across six wind velocities (2, 4, 6, 8, 10, and 12 m s−1) under six simulated vegetation structures. Vegetation structure and appendage type were pivotal factors, explaining 41.1% and 42.3% of the variance in lift-off velocity and accounting for 12.0% and 25.3% of the variability in diaspore dispersal velocity, respectively. Vegetation coverage was the main factor influencing near-surface wind velocity, and the lift-off and dispersal velocities of diaspores changed significantly when vegetation coverage exceeded 40%. Diaspores with one wing, having high lift-off velocities and low dispersal velocities, adopt the anti-long-distance wind dispersal strategy, whereas diaspores with pappus, having low lift-off velocities and high dispersal velocities, adopt the long-distance wind dispersal strategy. In contrast, diaspores with thorn, discoid, balloon, and four wings adopt the non-long-distance wind dispersal strategy, suitable for environments such as low-coverage deserts and desert steppes but not high-coverage typical steppes. This study could help comprehend the effect of the vegetation structure on the dispersal process of diaspores, which facilitate habitat restoration and biodiversity conservation of grassland and forest ecosystems.

Abstract Pendrin (SLC26A4) is an anion exchanger expressed in the apical membranes of selected epithelia. Pendrin ablation causes Pendred syndrome, a genetic disorder associated with sensorineural hearing loss, hypothyroid goiter, and reduced blood pressure. However its molecular structure has remained unknown, limiting our understanding of the structural basis of transport. Here, we determine the cryo-electron microscopy structures of mouse pendrin with symmetric and asymmetric homodimer conformations. The asymmetric homodimer consists of one inward-facing protomer and the other outward-facing protomer, representing coincident uptake and secretion- a unique state of pendrin as an electroneutral exchanger. The multiple conformations presented here provide an inverted alternate-access mechanism for anion exchange. The structural and functional data presented here disclose the properties of an anion exchange cleft and help understand the importance of disease-associated variants, which will shed light on the pendrin exchange mechanism.

Abstract High-rate electrolysis of CO2 to C2+ alcohols is of particular interest, but the performance remains far from the desired values to be economically feasible. Coupling gas diffusion electrode (GDE) and 3D nanostructured catalysts may improve the efficiency in a flow cell of CO2 electrolysis. Herein, we propose a route to prepare 3D Cu-chitosan (CS)-GDL electrode. The CS acts as a “transition layer” between Cu catalyst and the GDL. The highly interconnected network induces growth of 3D Cu film, and the as-prepared integrated structure facilitates rapid electrons transport and mitigates mass diffusion limitations in the electrolysis. At optimum conditions, the C2+ Faradaic efficiency (FE) can reach 88.2% with a current density (geometrically normalized) as high as 900 mA cm−2 at the potential of −0.87 V vs. reversible hydrogen electrode (RHE), of which the C2+ alcohols selectivity is 51.4% with a partial current density of 462.6 mA cm−2, which is very efficient for C2+ alcohols production. Experimental and theoretical study indicates that CS induces growth of 3D hexagonal prismatic Cu microrods with abundant Cu (111)/Cu (200) crystal faces, which are favorable for the alcohol pathway. Our work represents a novel example to design efficient GDEs for electrocatalytic CO2 reduction (CO2RR).

Synthesizing nitrogen (N)-containing molecules from biomass derivatives is a new strategy for production of this kind of chemicals. Herein, for the first time we present the synthesis of N-substituted aryl pyrroles via reductive amination/cyclization of levulinic acid (LA) with primary aromatic amines and hydrosilanes (e.g., PMHS) over CsF, and a series of N-substituted aryl pyrroles could be obtained in good to excellent yields at 120 °C. The mechanism investigation indicates that the reaction proceeds in two steps: the cyclization between amine and LA occurs first to form intermediate 5-methyl-N-alkyl-1,3-dihydro-2H-pyrrolones and their isomeride (B), and then the chemo- and region-selective reduction of intermediates take place to produce the final products. This approach for synthesis of N-substituted aryl pyrroles can be performed under mild and green conditions, which may have promising applications.

BackgroundPatients with intraventricular hemorrhage (IVH) are at a higher risk of developing hydrocephalus and often require external ventricular drainage or long-term ventriculoperitoneal shunt surgery.ObjectiveTo investigate whether cerebrospinal fluid drainage in patients with IVH due to aneurysmal subarachnoid hemorrhage (aSAH) reduces the incidence of chronic hydrocephalus.MethodA retrospective analysis was conducted on patients with aSAH treated at our hospital between January 2020 and December 2022. The first analysis compared patients with and without IVH, while the second analysis compared IVH patients with and without chronic hydrocephalus. The third analysis compared IVH patients who underwent in different drainage methods which is lumbar drainage (LD) or external ventricular drainage (EVD). The primary outcome measure was the incidence of chronic hydrocephalus.ResultOf the 296 patients hospitalized with aSAH, 108 (36.5%) had IVH, which was associated with a significantly higher incidence of chronic hydrocephalus compared to patients without IVH (49.1% vs. 16.5%, p

Purpose: Slow transit constipation (STC) is a common gastrointestinal disorder characterized by altered gut microbiota and reduced number of enterochromaffin cells (ECs). Astragaloside IV (AS-IV), a low drug permeability saponin, has showed beneficial effects on patients with STC. However, the specific mechanism by which AS-IV regulates STC remains unclear. In this study, we aimed to investigate the effect of AS-IV on STC and its associated mechanisms involving gut microbiota.Methods: The effect of AS-IV on STC was evaluated on STC mice induced with loperamide. We measured defecation frequency, intestinal mobility, ECs loss, and colonic lesions in STC mice treated with AS-IV. We also analyzed the changes in gut microbiota and metabolites after AS-IV treatment. Moreover, we investigated the relationship between specific gut microbes and altered fecal metabolites, such as 3-bromotyrosine (3-BrY). We also conducted in vitro experiments to investigate the effect of 3-BrY on caspase-dependent apoptosis of ECs and the activation of the p38 MAPK and ERK signaling pathways induced by loperamide.Results: AS-IV treatment promoted defecation, improved intestinal mobility, suppressed ECs loss, and alleviated colonic lesions in STC mice. AS-IV treatment also affected gut microbiota and metabolites, with a significant correlation between specific gut microbes and altered fecal metabolites such as 3-BrY. Furthermore, 3-BrY may potentially reduce caspase-dependent apoptosis of ECs and protect cell survival by inhibiting the activation of the p38 MAPK and ERK signaling pathways induced by loperamide.Conclusion: Our findings suggest that changes in gut microbiota and ECs mediated the therapeutic effect of STC by AS-IV. These results provide a basis for the use of AS-IV as a prebiotic agent for treating STC. The specific mechanism by which AS-IV regulates gut microbiota and ECs warrants further investigation.

Objective: Arrhythmias are prevalent symptoms of cardiovascular disease, necessitating accurate and timely detection to mitigate associated risks. Detecting arrhythmias from ECGs quickly and accurately holds great significance in preventing heart disease and reducing mortality. This research endeavors to outperform previous studies by developing a scientific neural network model capable of training and predicting ECG signals for 11 categories of arrhythmias, accounting for up to 5 co-existing labels. Methods: In this study, we initially address the issue of imbalanced datasets by employing Borderline SMOTE and Cluster Centroids techniques during preprocessing. Subsequently, we propose a novel SAR model that combines attention and resnet mechanisms. The dataset is subjected to a 10-fold validation process to train and evaluate the model. Finally, several metrics such as HammingLoss, RankingLoss, F1-score, AUC and Coverage are used to evaluate the model. Results: By evaluating the results of the tests, the average Hamming Loss is 1.12 %, the average Ranking Loss is 1.17 %, the average Micro F1-score is 98.46 %, the average Micro AUC is 98.76 %, and the average Coverage is 3.2762. The results show that the SAR model outperforms previous related studies on the task of classifying arrhythmia signals with multiple categories and labels. Conclusion: The SAR model demonstrated excellent performance in accurately classifying multi-category and multi-label arrhythmia signals, affirming its scientific validity. Compared with previous studies, the model achieves a certain improvement in performance, which can help cardiologists to achieve scientific and accurate diagnosis of arrhythmia diseases.

Purpose: Salvage treatment of recurrent cervical cancer of patients with a history of radiotherapy is currently a major clinical challenge. The purpose of our study was to retrospectively analyze clinical outcomes of radiation in patients with recurrent cancer who have previously received radiotherapy at our hospital and further explore the efficacy and safety of this treatment modality. Methods: All consecutive patients who underwent re-irradiation were included in our department between January 2015 and December 2017. All the patients received Volumetric Modulated Arc Therapy (VMAT) alone or VMAT followed by three dimensional–image-guided brachytherapy (3D-IGBT). The volume and dose for re-irradiation depended on previous radiation fields, dosimetry and recurrence sites. All patients received systemic chemotherapy before or after re-irradiation. Results: Fifty patients were included in our study. The median time from primary radiotherapy to re-irradiation was 12 months. Local recurrence, which was the most common failure following primary treatment, was present in 25 patients (50.0 %) while regional recurrence, loco-regional recurrence and distant recurrence combined in-filed recurrence was present in 8 (16.0 %), 9 (18.0 %) and 8 patients (16.0 %). Re-irradiation dose to lymph nodes was 45 Gy with or without a boost up to 55–60 Gy, and to the gross mass was 36–45 Gy with or without a boost up to 45–61 Gy. The median follow-up period was 22 (range,4–59) months. The 3-year local control (LC), progression-free survival (PFS), and overall survival (OS) rates were 58.0, 38.7, and 44.4 %, respectively. The median time of PFS and OS was 14 and 26 months, respectively. The interval between two successive radiotherapies beyond 12 months was significantly associated with better LC and PFS (p ≤ 0.05), but without the benefit of OS (p > 0.05). Serum SCC antigen level less than 1.5 ng/ml had a significantly better impact on PFS (p ≤ 0.05). Overall, 14 patients (28 %) experienced ≥ grade 3 acute toxicities, while 9 (18 %) experienced ≥ grade 3 late toxicities. Conclusions: Re-irradiation with VMAT is an effective and safe salvage treatment option with a reasonably good clinical outcome and toxicity profile in selected patients. In our experience, recurrent cancer patients with an interval between two successive radiotherapy courses beyond 12 months and with a serum SCC-Ag level less than 1.5 ng/ml, had improved outcomes.

Lift-off velocity, the wind speed at which a diaspore starts moving during secondary wind dispersal, representing diaspore mobile capacity, may greatly depend on vegetation where dispersal takes place. However, how vegetation structure influences lift-off velocity and which is the most important vegetation attribute remain unknown. The vegetation with various attributes (four coverages-0, 10 %, 20 % and 30 %, three life-form compositions-herb, shrub and herb + shrub, two vertical patterns-one and two layers, and two horizontal patterns-uniform and aggregated) were set up for the wind tunnel experiment. Diaspores of 30 species varied in wing loading, terminal velocity, mass, projected area, length, width, height, and shape index were selected to measure their lift-off velocity within various vegetation structures. Lift-off velocity significantly increased with the increasing vegetation coverage, in the case of any life-form composition, vertical pattern and horizontal pattern of vegetation. For the vertical pattern of vegetation, the lift-off velocity in one-layer vegetation was significantly higher than that in two-layer vegetation, but only for 10 % vegetation coverage. Both the life-form composition and the horizontal pattern of vegetation had no influences on lift-off velocity. The correlation between lift-off velocity and diaspore attributes (length, width, height, projected area, mass and wing loading) increased with vegetation coverage and the correlation in two-layer vegetation was larger than that in one-layer vegetation. Our results indicate that vegetation coverage is the key vegetation attribute determining lift-off velocity during secondary wind dispersal. Lift-off velocity is also influenced by diaspore traits, but their relationships tend to be regulated by vegetation attributes, especially the coverage and vertical pattern of vegetation. Our study demonstrates the important role of vegetation coverage in determining the second dispersal capacity, which is helpful to understand the dispersal strategies of plants in response to vegetation structure and succession.

Chikungunya fever (CHIF), a vector-borne disease transmitted mainly by Aedes albopictus and Aedes aegypti, is caused by Chikungunya virus (CHIKV) infection. To date, it is estimated that 39% of the world’s population is at risk of infection for living in countries and regions where CHIKV is endemic. However, at present, the cellular receptors of CHIKV remains not clear, and there are no specific drugs and vaccines for CHIF. Here, the cytotoxicity of calpain-2 protein activity inhibitor III and specific siRNA was detected by MTT assays. The replication of CHIKV was detected by qPCR amplification and plaque assay. Western blot was used to determine the level of the calpain-2 protein and vimentin protein. Immunofluorescence was also operated for detecting the rearrangement of vimentin protein. Our results indicated that calpain-2 protein activity inhibitor III and specific siRNA might suppress CHIKV replication. Furthermore, CHIKV infection led to vimentin remodeling and formation of cage-like structures, which could be inhibited by the inhibitor III. In summary, we confirmed that calpain-2 protein influenced chikungunya virus replication and regulated vimentin rearrangement caused by chikungunya virus infection, which could be important for understanding the biological significance of CHIKV replication and the future development of antiviral strategies.

A class of inexpensive aminoanthraquinone organic dyes are shown to facilitate visible-light-driven CO2 reduction. Overall reaction efficiencies were found to be optimal when both electron donating and accepting groups were on a single dye molecule.

Coverage is a prominent indicator for measuring the quality of service in directional sensor networks. From the perspective of energy and deployment costs, full coverage may be expensive or unrealistic, partial coverage can operate more energy-efficient by scheduling working status of sensors. In certain practical application scenarios, irregular obstacles like trees, mountains, buildings, and vehicles, which have adverse influence on QoC, often exist in the field of interest (FoI). Meanwhile, due to sensors may fall near the border of the FoI, it also has effect on the coverage contribution. In this paper, we assume that sensors are randomly deployed in a square FoI with irregular shape obstacles existence, and introduce the concept of occlusion coverage of partial targets. Afterwards, we take the border effects into account and derive the critical sensor density for achieving an expected coverage ratio with a high probability. Finally, we conduct a series of simulation experiments to verify the accuracy between simulation results and numerical results, and take analysis of mean absolute error between them. The results show that our method has good performance on estimating critical sensor density.

Deep learning technology has become one of the most important technologies in remote sensing land classification applications. Its powerful sample-learning and information-mining abilities promote the continuous improvement of classification accuracy. A large volume of high-quality and representative sample data is the premise for the successful application of deep learning technology. Conventional methods of obtaining samples through manual delineation or surface surveys require a great deal of manpower and material resources. Therefore, the inability to obtain sufficient and widely representative high-quality samples is one of the key factors limiting the application of deep learning technology. In this study, the method of generating sample data obtains high-confidence classification results from a variety of existing high-quality classification products as deep learning samples, which are then used to support the application of deep learning technology for land-cover classification. When the three global land-cover classification products, FROM-GLC-2015, GLC_FCS30-2015, and GlobeLand30, have the same type of discrimination, the sample is considered a high-confidence sample. Based on this, a large volume of sample data widely distributed around the world was obtained. Using the extracted samples, a random forest classifier was trained using multiple types of information from the Landsat data, and land-cover classification was achieved. Application experiments were conducted in several typical regions, and the classification results were verified. The results showed that the classification accuracy of random forests under the support of samples generated using the sample extraction method proposed in this article was considerably higher than that of the three land-cover classification products.

Background & Aims: Liver macrophage-mediated inflammation contributes to the pathogenesis of the nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH). Odd skipped-related 1 (Osr1) is a putative transcription factor previously reported to be involved in NASH progression; however, the underlying mechanisms remain unknown. The current study focused on the role of Osr1 in macrophage polarization and metabolism and its associated functions in the inflammation-induced pathogenesis of NASH. Methods: OSR1/Osr1 expression patterns were compared in normal and NASH patients and mouse livers. NASH was established and compared between hepatocyte-specific Osr1 knockout (Osr1ΔHep), macrophage-specific Osr1 knockout (Osr1ΔMφ), and wild-type (Osr1F) mice fed with 3 different chronic obesogenic diets and methionine choline-deficient diet. Using genetic and therapeutic strategies in vitro and in vivo, the downstream targets of Osr1 and the associated mechanisms in inflammation-induced NASH were established. Results: Osr1 was expressed in both hepatocytes and macrophages and exhibited different expression patterns in NASH. In NAFLD and NASH murine models, deleting Osr1 in myeloid cells (Osr1ΔMφ), but not hepatocytes, aggravated steatohepatitis with pronounced liver inflammation. Myeloid Osr1 deletion resulted in a polarization switch toward a pro-inflammatory phenotype associated with reduced oxidative phosphorylation activity. These inflamed Osr1ΔMφ macrophages promoted steatosis and inflammation in hepatocytes via cytokine secretion. We identified 2 downstream transcriptional targets of Osr1, c-Myc, and PPARγ and established the Osr1-PPARγ cascade in macrophage polarization and liver inflammation by genetic study and rosiglitazone treatment in vivo. We tested a promising intervention strategy targeting Osr1-PPARγ by AAV8L-delivered Osr1 expression or rosiglitazone that significantly repressed NAFLD/NASH progression in Osr1F and Osr1ΔMφ mice. Conclusions: Myeloid Osr1 mediates liver immune homeostasis and disrupting Osr1 aggravates the progression of NAFLD/NASH.

Robust optimization is a new modeling method to study uncertain optimization problems, which is to find a solution with good performance for all implementations of uncertain input. This paper studies the optimal location allocation of processing plants and distribution centers in uncertain supply chain networks under the worst case. Considering the uncertainty of the supply chain and the risk brought by the uncertainty, a data-driven two-stage sparse distributionally robust risk mixed integer optimization model is established. Based on the complexity of the model, a distribution-separation hybrid particle swarm optimization algorithm (DS-HPSO) is proposed to solve the model, so as to obtain the optimal location allocation scheme and the maximum expected return under the worst case. Then, taking the fresh-food supply chain under the COVID-19 as an example, the impact of uncertainty on location allocation is studied. This paper compares the data-driven two-stage sparse distributionally robust risk mixed integer optimization model with the two-stage sparse risk optimization model, and the data results show the robustness of this model. Moreover, this paper also discusses the impact of different risk weight on decision-making. Different decision makers can choose different risk weight and obtain corresponding benefits and optimal decisions. In addition, the DS-HPSO is compared with distribution-separation hybrid genetic algorithm and distributionally robust L-shaped method to verify the effectiveness of the algorithm.

Immune checkpoint inhibitors and antiangiogenic agents have shown some activity in patients with late-stage gastric cancer. Here the authors report the results of a phase II trial of neoadjuvant anti-PD1 (camrelizumab), antiangiogenic agent (apatinib), and chemotherapy (S-1 ± Oxaliplatin) in stage T4a/bN + M0 gastric cancer patients.

Since the last IAEA-FEC in 2021, significant progress on the development of long pulse steady state scenario and its related key physics and technologies have been achieved, including the reproducible 403 s long-pulse steady-state H-mode plasma with pure radio frequency (RF) power heating. A thousand-second time scale (∼1056 s) fully non-inductive plasma with high injected energy up to 1.73 GJ has also been achieved. The EAST operational regime of high β _P has been significantly extended ( H _98y2 > 1.3, β _P ∼ 4.0, β _N ∼ 2.4 and n _e / n _GW ∼ 1.0) using RF and neutral beam injection (NBI). The full edge localized mode suppression using the n = 4 resonant magnetic perturbations has been achieved in ITER-like standard type-I ELMy H-mode plasmas with q _95 ≈ 3.1 on EAST, extrapolating favorably to the ITER baseline scenario. The sustained large ELM control and stable partial detachment have been achieved with Ne seeding. The underlying physics of plasma-beta effect for error field penetration, where toroidal effect dominates, is disclosed by comparing the results in cylindrical theory and MARS-Q simulation in EAST. Breakdown and plasma initiation at low toroidal electric fields (

To accurately replicate actual production and save production costs, this study examines the influence of the tempering process on the structure, mechanical properties, and corrosion resistance of E690 marine steel. Various techniques were employed to evaluate its properties, behavior, and performance, including metallurgical microscopy, scanning electron microscopy, transmission electron microscopy, electron backscatter diffraction, impact experiments, tensile tests, and electrochemical corrosion tests. The results indicate that as the tempering temperature increases, the tempering degree of the tempered martensite structure improves, the martensite strip coarsens, the size of the precipitated carbide increases, and the proportion of large-angle grain boundaries decreases. Consequently, the tensile strength and yield strength initially increase and then decrease, while the impact toughness and elongation gradually improve. At a tempering temperature of 600 °C, the steel exhibits the best overall mechanical properties, with a tensile strength of 729 MPa, yield strength of 649 MPa, and elongation of 18%. Furthermore, at a tempering temperature of 550 °C, the test steel shows an optimal corrosion resistance, with a corrosion rate of 0.03233 mm y ^−1 and an open-circuit potential of −0.36 V.

Desertification in degraded grasslands is manifested through the development of bare sandy patches, which eventually lead to habitat fragmentation. The ability of these bare sandy patches to regenerate naturally through in-situ soil seed banks is not well understood. To fill this knowledge gap, we randomly selected 24 bare sandy patches with areas ranging from 19 to 898 m2 in a desertified grassland of the Horqin sandy land, Northern China to determine whether soil seed bank can be used for natural regeneration of bare sandy patches. Species composition and density of soil seed bank as well as aboveground vegetation composition, abundance and coverage were investigated. We then determined their relationships with in-situ habitat characteristics. Our observations showed that the studied area had low soil seed bank density and species richness, as well as depauperate soil seed bank communities. Consequently, local soil seed bank was not able to provide sufficient seed source for natural regeneration. This was indicated by the relationships between aboveground vegetation, soil seed bank and the in-situ habitat characteristics. For bare patches with an area between 300 m2 and 900 m2, increase the soil seed bank density and species richness should be the main restoration measures. For bare patches with a small area of less than 50 m2, restoration of vegetation density should be the main measure. Our data highlighted that different extents of desertification, indicated by different bare patches, are requiring distinct restoration measures.

Abstract Double narrowband induced perfect absorption in the terahertz region is achieved in a graphene–dielectric–gold hybrid metamaterial, whose physical mechanism is analyzed using the coupled-mode theory (CMT), which agreed well with the finite-difference time-domain (FDTD) simulation. This study found that the Fermi level of graphene can be adjusted to improve the absorptivity when the refractive index (RI) n d of the chosen dielectric cannot achieve a good absorption effect. In addition, the blue shift of absorption spectrum can be used in the design of dual-frequency electro-optical switches, of which the modulation degree of amplitude (MDA) can reach as high as 94.05% and 93.41%, indicating that this is a very promising electro-optical switch. Most significantly, the RI sensing performance is investigated, which shows an ultra-high absorption sensitivity S A = 4.4°/RIU, wavelength sensitivity S λ = 9.8°/RIU, and phase shift sensitivity S φ = 2691°/RIU. At last, an interesting finding is that the two peaks (R1 and R2) of plasmon-induced absorption (PIA) show different polarization characteristics (insensitive or sensitive) to the incident light angle; this polarization-sensitive is particularly important for the PIT/PIA-based optical polarizers. Undoubtedly, this paper is of great significance to the research and design of terahertz photonic devices and sensors.

The transformation of carbon dioxide (CO2) into fuels and chemicals is an interesting topic, which has been paid much attention in recent years. The materials with specific functionalities are highly required for CO2 capture and conversion, which have been widely investigated. As an emerging material platform, porous organic polymers (POPs) have attracted considerable scientific interest due to their distinctive properties such as tailorable functionalization, large surface areas, adjustable porosity, versatile polymerizations, good physicochemical and thermal stability. Our group focuses on designing and synthesizing POPs via introducing CO2-philic groups and organic ligands into the skeletons of the polymers and immobilizing metal active species onto their surface, and a series of POPs with functional groups, such as azo, Tröger's base, fluorine, phenolic –OH, have been prepared for CO2 transformation. In this review article, we mainly introduce our recent work on design of POPs-based catalysts for CO2 transformation, which include POPs-based catalysts for cycloaddition reactions of epoxides and propargylic alcohols with CO2, for reductive transformation of CO2 with H2, for photocatalytic/electrocatalytic reduction of CO2. In addition, the perspectives of the POP-based catalysts for CO2 transformation will be discussed as well.

This paper studies the problem of facility location in a hybrid uncertain environment with both randomness and fuzziness. We establish a data-driven two-stage fuzzy random mixed integer optimization model, by considering the uncertainty of transportation cost and customer demand. Given the complexity of the model, this paper based on particle swarm optimization (PSO), beetle antenna search algorithm (BAS) and interior point algorithm, a hybrid intelligent algorithm (HIA) is proposed to solve two-stage fuzzy random mixed integer optimization model, yielding the optimal facility location and maximal expected return of supply chain simultaneously. Finally, taking the supply chain of medical mask in Shanghai as an example, the influence of uncertainty on the location of processing factory was studied. We compare the HIA with hybrid PSO and hybrid genetic algorithm (GA), to validate the proposed algorithm based on the computational time and the convergence rate.

ObjectiveMucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) modulates the inflammatory immune response and organ dysfunction, which are closely implicated in sepsis pathogenesis and progression. This study aimed to explore the role of MALT1 in sepsis-induced organ injury, immune cell dysregulation, and inflammatory storms.MethodsSeptic mice were constructed by intraperitoneal injection of lipopolysaccharide, followed by overexpression or knockdown of MALT1 by tail vein injection of the corresponding lentivirus. Mouse naïve CD4+ T cells and bone marrow-derived macrophages were treated with MALT1 overexpression/knockdown lentivirus plus lipopolysaccharide.ResultsIn the lungs, livers, and kidneys of septic mice, MALT1 overexpression exaggerated their injuries, as shown by hematoxylin and eosin staining (all p

Changes in grassland soil organic carbon stock (SOCS) may significantly affect the regional climate and carbon cycle of terrestrial ecosystems. However, how the impact of climate factors on SOCS and the dominant climate factors are regulated by the area scale of grasslands remains unclear. To understand the scale effects of climate on SOCS and how to accurately estimate SOCS at different scales, three area scales were defined by extending grassland types on the basis of meadow, typical and desert grasslands (Scale I (average area 37.22 × 104 km2) included each of these three types of grasslands, Scale II (average area 74.45 × 104 km2) was achieved by a pairwise combination of these three types of grasslands. Scale III (area 111.67 × 104 km2) was an aggregate of these three types of grasslands), the relationship between climate factors (i.e., mean annual precipitation, mean annual temperature, annual maximum temperature, annual minimum temperature, mean annual ground temperature, mean annual humidity, annual sunshine duration, annual maximum depth of accumulated snow, and the number of snow-covered days) and SOCS at the three scales were explored in the grasslands of northern China. Our results indicated that the total SOCS in grasslands at the three scales was ordered as desert grassland

Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and COVID-19 in terms of their data sources, mathematical models, and key findings. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we selected 47 articles from the Web of Science Core Collection up to September 2020. Restricting human mobility reduced the transmission of COVID-19, although the effectiveness and stringency of policy implementation vary temporally and spatially across different stages of the pandemic. We call for prompt and sustainable measures to control the pandemic. We also recommend researchers 1) to enhance multi-disciplinary collaboration; 2) to adjust the implementation and stringency of mobility-control policies in corresponding to the rapid change of the pandemic; 3) to improve mathematical models used in analysing, simulating, and predicting the transmission of the disease; and 4) to enrich the source of mobility data to ensure data accuracy and suability.

The drought resistance of eight commonly used apple rootstocks under natural drought conditions was examined to provide clues for the selection, promotion, and utilization of drought-resistant apple rootstocks. The ultrastructural differences and physiological and biochemical characteristics of the leaves of eight apple rootstocks under drought stress were observed. The index changes were used to rank drought resistance by the membership function method comprehensively. The results showed that the leaf thickness, palisade tissue thickness, sponge tissue thickness, net photosynthetic rate, and chlorophyll content were significantly higher in 'Fupingqiuzi' than those of other rootstocks at various stress conditions. The leaf water content and water use efficiency of 'Qingzhen 1' were significantly higher than those of other rootstocks under different stress conditions. The root vigor of 'B.9' was significantly higher than that of other rootstocks. The results of membership function analysis showed that the drought resistance of different rootstocks was in the order: 'Fupingqiuzi' > 'Qingzhen 1' > 'B.9' > 'MM.111' > 'GM256' > 'MM.106' > 'M.26' > 'M.9-Nic29'. 'Fupingqiuzi' had the strongest drought resistance, and 'Qingzhen 1' and 'B.9' were also relatively drought-resistant. These rootstocks can be used as raw materials for drought-resistant apple rootstock breeding and are propagated and utilized in arid areas.

Abstract Seed dispersal has received much research attention. The plant canopy can intercept diaspores, but the effect of the plant canopy (the aboveground portion of a plant consisting of branches and leaves) on dispersal distance has not been explored empirically. To determine the effect of plant canopy on seed dispersal distance, a comparison of diaspores falling through open air and through plant canopy was made in a wind tunnel using three wind speeds and diaspores with various traits. Compared with diaspores falling through open air, the dispersal distance of diaspores falling through plant canopy was decreased or increased, depending on wind speed and diaspore traits. When falling through a plant canopy, dispersal distance of diaspores with thorns or those without appendages was promoted at low wind speed (2 m s−1), while that of diaspores with low wing loading (0.5 mg mm−2) and terminal velocity (2.5 m s−1) was promoted by relatively high (6 m s−1) wind speed. A plant canopy could increase seed dispersal distance, which may be due to the complicated updraft generated by canopy. The effect of maternal plants on seed dispersal regulates the distribution pattern and the species composition of the community.

Qianjinba is primarily cultivated in the southern regions of China and finds extensive use in traditional Chinese medicine (TCM) for conditions such as rheumatism, arthralgia, and gynecological ailments. It has been officially recognized as a protected variety of TCM by the state. The aim of this study was to investigate the therapeutic potential of Qianjinba polysaccharide (QJBDT) in treating rheumatoid arthritis (RA) in mice, along with a preliminary exploration of its mechanisms for inhibiting RA in these animals. Kunming mice (KM) were randomly divided into several groups, including a normal group, a model group (LPS group), low-dose, medium-dose, and high-dose QJBDT groups, as well as a positive control group (TGP group), each consisting of 10 mice. To induce inflammation and create an RA model, type II collagen was injected into the right hind foot joint. Following a 7-day modeling period, various concentrations of QJBDT and the positive control drug total glycoside of peony were administered via gavage once a day for 21 consecutive days. Throughout the study, we monitored and recorded the mice's weight, measured foot swelling, and assessed the arthritis index on a weekly basis. We also conducted pathological examinations of joint tissues and analyzed the signal pathway of p38 mitogen-activated protein kinase (MAPK) as well as the protein expression of nuclear factor NF-κB in the mice's right foot joint tissues. Additionally, we employed ELISA to detect the levels of interleukin-β (IL-β), IL-17, and tumor necrosis factor-α (TNF-α) in the mice's serum. The results of this study revealed that QJBDT effectively reduced the degree of foot swelling and the arthritis index in collagen-induced arthritis mice while improving their weight loss (P < 0.05). Furthermore, it alleviated the pathological damage observed in the mice's joints. Notably, the expression of transcription factors p38 and NF-κB proteins was down-regulated (P < 0.05), and the levels of inflammatory cytokines IL-β, IL-17, and TNF-α in the mice's serum were decreased (P < 0.05). In conclusion, this study demonstrated that polysaccharides could inhibit the expression of transcription factors p38 and NF-κB, reduce the production of inflammatory factors, and alleviate the progression of RA to a certain extent. [ABSTRACT FROM AUTHOR]

Tropospheric delay (TD) parameter estimation is a critical issue underlying high-precision data processing for global navigation satellite systems (GNSSs). The most widely used TD parameter estimation methods are the random walk (RW) and piece-wise constant (PWC). The RW method can effectively track rapid variations of tropospheric delay, but it may introduce excessive noise. In contrast, the PWC method introduces less noise, but it is less adaptable to cases of large variations of tropospheric delay. To address the problem of how to choose the optimal TD parameter estimation method, this paper investigates the variation patterns of international GNSS service zenith tropospheric delay (IGS ZTD) products and proposes a combined strategy model for TD parameter estimation. Firstly, this paper avoids the day-boundary jumps problem of IGS ZTD products by grouping based on single-day data. Secondly, this paper introduces discrete point areas (DPAs) to measure the magnitude of the ZTD values and uses comprehensive indicators to reflect the variation of ZTD. Next, based on the Köppen-Geiger climate classification, this study selected five different climate classifications with a total of 20 IGS stations as experimental data. The data assessed span from day of year (DOY) 001 to DOY 365 in 2022. This paper then applied 26 different parameter estimation strategies for static precise point positioning (PPP) data processing, and the parameter estimation strategies that were used include the RW and PWC (with the piece-wise constant ranging from twenty minutes to five hundred minutes at twenty-minute intervals). Finally, ZTD and positioning results were obtained using various parameter estimation methods, and a combined strategy model was established. We selected five different climate classifications of IGS stations as validation data and designed three sets of comparative experiments: RW, PWC120, and the combined strategy model, to verify the effectiveness of the combined strategy model. The experimental results revealed that: RW and the combined strategy model have a comparable ZTD accuracy and both are superior to PWC120. The combined strategy model improves the positioning accuracy in the U direction compared to RW and PWC120. In arid (B) and polar (E) regions with a small variation of TD, the PWC120 strategy displayed a better positioning accuracy than the RW strategy; in equatorial (A) and warm-temperate (C) regions, where there are large variations of TD, the RW strategy exhibited a better positioning accuracy than the PWC120 strategy. The combined strategy model can flexibly select the optimal parameter estimation method according to the comprehensive indicator while ensuring ZTD estimation accuracy; it enhances positioning accuracy.

In order to reveal the migration process of chromium-contaminated sites, COMSOL5.6 software was used to build the initial model of the chromium pollution source and analyze the migration change characteristics over time based on the rule of groundwater movement and Convection–Dispersion equation. COMSOL provides fully coupled multiphysics modeling for most engineering fields. The results show that: the permeable layer with a high permeability coefficient during the migration of chromium pollutants has a strong adsorption effect on the heavily polluted part, and it will enhance the lateral diffusion of the polluted area within a short period. Based on the migration model, the intermediate gradient and the symmetrical quadrupole sounding model are built. The variation law of apparent amplitude frequency and apparent resistivity under flat and undulating terrain is analyzed based on the dual frequency IP (Induced Polarization) method. The results show that: The intermediate gradient detection is better than the symmetrical quadrupole sounding in the correspondence between the peak value of apparent amplitude frequency and the valley value of apparent resistivity. The arrangement of the bathymetric measurement point in the center of the projected edge of the pollution field can be a better way to monitor the pollution. Monitoring with the intermediate gradient detection device and the symmetrical quadrupole sounding device creates “multiple peaks” in the curve as it passes through the valley. Arranging the power supply electrodes on the mountain frontiers on both sides of the raised peaks and synthesizes the apparent amplitude frequency and apparent resistivity curves of the pollution field, which can effectively determine the specific orientation of the heavily polluted area of the pollution field. This research makes theoretical additions to the migration characteristics of the Cr pollution field. It provides technical guidance for the real-time monitoring of the pollution field, which is of positive significance for promoting ecological and environmental protection.

Introduction: Hyperglycemic conditions achieved during pregnancy have been shown to have detrimental effects to fetal development and increase the prevalence of childhood comorbidities. However, the mechanisms in which diabetic pregnancies affect placental development and subsequently contribute to adverse health effects on the mother and offspring remain unclear. Research design and methods: Streptozotocin was used to induce gestational diabetes in mice. In this model, hyperglycemia was established at embryonic day 3.5 (E3.5). Pregnancy mass was collected at E10.5, E12.5, E14.5, and E16.5 for different assessments. Results: Both placental and embryonic weights were found to be significantly elevated at E16.5. At E14.5, a significantly larger junctional zone with increased number of glycogen trophoblasts was found in the placentas from hyperglycemic pregnancies (HG group) compared to the placentas from normoglycemic pregnancies (NG group). Importantly, the HG placenta exhibited decreased trophoblast giant cell (TGC) association and TUNEL+ cells, and increased expression of α-SMA on the spiral artery, suggesting arterial remodeling was impacted. Moreover, the interhemal membrane of the labyrinth layer, was found to be thicker in the HG placentas. Furthermore, hyperglycemia resulted in more offspring congenital defects, which were associated with a thicker interhemal membrane. Conclusions: Together, these results suggest that gestational diabetes perturbs proper placental development and function, specifically spiral artery remodeling and angiogenesis, thereby negatively impacting embryonic development.

Abstract Design of experiments (DOE)-based analytical quality by design (AQbD) method evaluation, development, and validation is gaining momentum and has the potential to create robust chromatographic methods through deeper understanding and control of variability. In this paper, a case study is used to explore the pros, cons, and pitfalls of using various chromatographic responses as modeling targets during a DOE-based AQbD approach. The case study involves evaluation of a reverse phase gradient HPLC method by a modified circumscribed central composite (CCC) response surface DOE. Solid models were produced for most responses and their validation was assessed with graphical and numeric statistics as well as chromatographic mechanistic understanding. The five most relevant responses with valid models were selected for multiple responses method optimization and the final optimized method was chosen based on the Method Operable Design Region (MODR). The final method has a much larger MODR than the original method and is thus more robust. This study showcases how to use AQbD to gain deep method understanding and make informed decisions on method suitability. Discoveries and discussions in this case study may contribute to continuous improvement of AQbD chromatography practices in the pharmaceutical industry.

Abstract Background High levels of physical activity (PA) and heart rate variability (HRV) are associated with cardiovascular benefits in patients with cardiovascular diseases. HRV, representing cardiac autonomic function, is positively associated with PA. However, the impacts of PA and cardiac autonomic function on cardiovascular outcomes were not analysed in the same study population. This lack of evidence supported our hypothesis that PA might contribute to cardiovascular benefits via enhanced cardiac autonomic function. Methods Patients with implantable cardioverter defibrillator (ICD) or cardiac resynchronisation therapy defibrillator (CRT-D) implantation were included from the SUMMIT registry. HRV and PA values were assessed during the first 30–60 days post device implantation using a continuous home monitoring system. Causal mediation analysis was conducted to explore the possible mediation function of HRV in the association of PA with long-term cardiac death and all-cause mortality in patients at a high risk of sudden cardiac death. Results Over a mean follow-up period of 47.7 months, 63 cardiac deaths (18.9%) and 85 all-cause death events (25.5%) were observed among 342 patients with ICD/CRT-D implantation. A positive linear association between HRV and PA was demonstrated and the β value of HRV was 0.842 (95% confidence interval [CI]: 0.261–1.425, P = 0.005) in the multiple linear regression analysis. Multivariable Cox proportional hazards analysis revealed that high levels of PA (≥11.0%) and HRV (≥75.9 ms) were independent protective factors against cardiac death (PA: hazard ratio [HR] = 0.273; 95% CI, 0.142–0.526, P

BackgroundPhysical activity (PA) and resting heart rate (RHR) are connected with all-cause mortality. Moreover, there was an inverse correlation between PA and RHR. However, the causal relationship between PA, RHR, and long-term mortality has been rarely evaluated and quantified, particularly the mediation effect of RHR in the association between PA and all-cause mortality.ObjectiveTo describe the relationship between PA and RHR when consistently measured via cardiac implantable electronic devices (CIED) and further explore the mediation effect of PA on all-cause mortality through RHR.Materials and methodsPatients who underwent CIED implantation and received remote home monitoring services were included. During the first 30–60 days after CIED implantation, daily PA and RHR were continuously measured and automatically transmitted by CIED. The primary endpoint was all-cause mortality. The multiple linear regression model was used to confirm the relationship between PA and RHR. The predictive values of both PA and RHR for all-cause mortality were assessed by multivariable Cox proportional hazards models. The causal mediation model was further established to verify and quantify the mediation effect of RHR in the association between PA and all-cause mortality.ResultsA total of 730 patients with CIED were included. The mean daily PA and RHR were 10.7 ± 5.7% and 61.3 ± 9.1 bpm, respectively. During a mean follow-up period of 55.8 months, 187 (26.5%) death was observed. A negative linear relationship between PA and RHR was demonstrated in the multiple regression model (β = −0.260; 95% CI: −0.377 to −0.143, p < 0.001). Multivariable Cox proportional hazards analysis showed that both lower levels of PA (HR = 0.907; 95% CI: 0.878–0.936, p < 0.001) and higher RHR (HR = 1.016; 95% CI: 1.001–1.032, P = 0.031) were independent risk factors of all-cause mortality. Causal mediation analysis further confirmed and quantified the mediation function of RHR in the process of PA improving all-cause mortality (mediation proportion = 3.9%; 95% CI: 0.2–10.0%, p = 0.036).ConclusionThe effects of the higher level of PA on improving life prognosis may be partially mediated through RHR among patients with CIED. It indicates that changes in the autonomic nervous function during postoperative rehabilitation exercises should get more attention.

Objectives This study aimed to investigate the differentiation state and clinical significance of colorectal cancer cells, as well as to predict the immune response and prognosis of patients based on differentiation-related genes of colorectal cancer. Introduction Colorectal cancer cells exhibit different differentiation states under the influence of the tumor microenvironment, which determines the cell fates. Methods We combined single-cell sequencing (scRNA-seq) data from The Cancer Genome Atlas source with extensive transcriptome data from the Gene Expression Omnibus database. We obtained colorectal cancer differentiation-related genes using cell trajectory analysis and developed a colorectal cancer differentiation-related gene based molecular typing and prognostic model to predict the immune response and prognosis of patients with colorectal cancer. Results We identified 5 distinct cell differentiation subsets and 620 colorectal cancer differentiation-related genes. Colorectal cancer differentiation-related genes were significantly associated with metabolism, angiogenesis, and immunity. We separated patients into 3 subtypes based on colorectal cancer differentiation-related gene expression in the tumor and found differences among the different subtypes in immune infiltration status, immune checkpoint gene expression, clinicopathological features, and overall survival. Immunotherapeutic interventions involving a highly expressed immune checkpoint blockade may be selectively effective in the corresponding cancer subtypes. We built a risk score prediction model (5-year AUC: .729) consisting of the 4 most important predictors of survival (TIMP1, MMP1, LGALS4, and ITLN1). Finally, we generated and validated a nomogram consisting of the risk score and clinicopathological variables. Conclusion This study highlights the significance of genes involved in cell differentiation for clinical prognosis and immunotherapy in patients and provides prospective therapeutic targets for colorectal cancer.