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Abstract Anion exchange membrane fuel cells (AEMFCs) are one of the ideal energy conversion devices. However, platinum (Pt), as the benchmark catalyst for the hydrogen oxidation reaction (HOR) of AEMFCs anodes, still faces issues of insufficient performance and susceptibility to CO poisoning. Here, we report the Joule heating-assisted synthesis of a small sized Ru1Pt single-atom alloy catalyst loaded on nitrogen-doped carbon modified with single W atoms (s-Ru1Pt@W1/NC), in which the near-range single Ru atoms on the Ru1Pt nanoparticles and the long-range single W atoms on the support simultaneously modulate the electronic structure of the active Pt-site, enhancing alkaline HOR performance of s-Ru1Pt@W1/NC. The mass activity of s-Ru1Pt@W1/NC is 7.54 A mgPt+Ru -1 and exhibits notable stability in 1000 ppm CO/H2-saturated electrolyte. Surprisingly, it can operate stably in H2-saturated electrolyte for 1000 h with only 24.60 % decay. Theoretical calculations demonstrate that the proximal single Ru atoms and the remote single W atoms synergistically optimize the electronic structure of the active Pt-site, improving the HOR activity and CO tolerance of the catalyst.

Abstract The emergence of single-atom catalysts offers exciting prospects for the green production of hydrogen peroxide; however, their optimal local structure and the underlying structure–activity relationships remain unclear. Here we show trace Fe, up to 278 mg/kg and derived from microbial protein, serve as precursors to synthesize a variety of Fe single-atom catalysts containing FeN5−x O x (1 ≤ x ≤ 4) moieties through controlled pyrolysis. These moieties resemble the structural features of nonheme Fe-dependent enzymes while being effectively confined on a microbe-derived, electrically conductive carbon support, enabling high-current density electrolysis. A comparative analysis involving catalysts derived from eleven representative microbes reveals that the presence of 0.05 wt% Fe single-atom sites leads to a significant 26% increase in hydrogen peroxide selectivity. Remarkably, the optimal catalyst featuring FeN3O2 sites demonstrates a selectivity of up to 93.7% and generates hydrogen peroxide in a flow cell at an impressive rate of 29.6 mol g−1 h−1 at 200 mA cm−2. This work achieves structural fine-tuning of metal single-atom sites at the trace level and provides topological insights into single-atom catalyst design to achieve cost-efficient hydrogen peroxide production.

Abstract Chemical recycling of plastic waste could reduce its environmental impact and create a more sustainable society. Hydrogenolysis is a viable method for polyolefin valorization but typically requires high hydrogen pressures to minimize methane production. Here, we circumvent this stringent requirement using dilute RuPt alloy to suppress the undesired terminal C–C scission under hydrogen-lean conditions. Spectroscopic studies reveal that PE adsorption takes place on both Ru and Pt sites, yet the C–C bond cleavage proceeds faster on Ru site, which helps avoid successive terminal scission of the in situ-generated reactive intermediates due to the lack of a neighboring Ru site. Different from previous research, this method of suppressing methane generation is independent of H2 pressure, and PE can be converted to fuels and waxes/lubricant base oils with only

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.

Background: Colorectal cancer (CRC) remains a significant health burden globally, necessitating a deeper understanding of its molecular landscape and prognostic markers. This study characterized ferroptosis-related genes (FRGs) to construct models for predicting overall survival (OS) across various CRC datasets. Methods: In TCGA-COAD dataset, differentially expressed genes (DEGs) were identified between tumor and normal tissues using DESeq2 package. Prognostic genes were identified associated with OS, disease-specific survival, and progression-free interval using survival package. Additionally, FRGs were downloaded from FerrDb website, categorized into unclassified, marker, and driver genes. Finally, multiple models (Coxboost, Elastic Net, Gradient Boosting Machine, LASSO Regression, Partial Least Squares Regression for Cox Regression, Ridge Regression, Random Survival Forest [RSF], stepwise Cox Regression, Supervised Principal Components analysis, and Support Vector Machines) were employed to predict OS across multiple datasets (TCGA-COAD, GSE103479, GSE106584, GSE17536, GSE17537, GSE29621, GSE39084, GSE39582, and GSE72970) using intersection genes across DEGs, OS, disease-specific survival, and progression-free interval, and FRG categories. Results: Six intersection genes (ASNS, TIMP1, H19, CDKN2A, HOTAIR, and ASMTL-AS1) were identified, upregulated in tumor tissues, and associated with poor survival outcomes. In the TCGA-COAD dataset, the RSF model demonstrated the highest concordance index. Kaplan-Meier analysis revealed significantly lower OS probabilities in high-risk groups identified by the RSF model. The RSF model exhibited high accuracy with AUC values of 0.978, 0.985, and 0.965 for 1-, 3-, and 5-year survival predictions, respectively. Calibration curves demonstrated excellent agreement between predicted and observed survival probabilities. Decision curve analysis confirmed the clinical utility of the RSF model. Additionally, the model’s performances were validated in GSE29621 dataset. Conclusions: The study underscores the prognostic relevance of 6 intersection genes in CRC, providing insights into potential therapeutic targets and biomarkers for patient stratification. The RSF model demonstrates robust predictive performance, suggesting its utility in clinical risk assessment and personalized treatment strategies.

BackgroundHepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide. PANoptosis is a recently unveiled programmed cell death pathway, Nonetheless, the precise implications of PANoptosis within the context of HCC remain incompletely elucidated.MethodsWe conducted a comprehensive bioinformatics analysis to evaluate both the expression and mutation patterns of PANoptosis-related genes (PRGs). We categorized HCC into two clusters and identified differentially expressed PANoptosis-related genes (DEPRGs). Next, a PANoptosis risk model was constructed using LASSO and multivariate Cox regression analyses. The relationship between PRGs, risk genes, the risk model, and the immune microenvironment was studies. In addition, drug sensitivity between high- and low-risk groups was examined. The expression profiles of these four risk genes were elucidate by qRT-PCR or immunohistochemical (IHC). Furthermore, the effect of CTSC knock down on HCC cell behavior was verified using in vitro experiments.ResultsWe constructed a prognostic signature of four DEPRGs (CTSC, CDCA8, G6PD, and CXCL9). Receiver operating characteristic curve analyses underscored the superior prognostic capacity of this signature in assessing the outcomes of HCC patients. Subsequently, patients were stratified based on their risk scores, which revealed that the low-risk group had better prognosis than those in the high-risk group. High-risk group displayed a lower Stromal Score, Immune Score, ESTIMATE score, and higher cancer stem cell content, tumor mutation burden (TMB) values. Furthermore, a correlation was noted between the risk model and the sensitivity to 56 chemotherapeutic agents, as well as immunotherapy efficacy, in patient with. These findings provide valuable guidance for personalized clinical treatment strategies. The qRT−PCR analysis revealed that upregulated expression of CTSC, CDCA8, and G6PD, whereas downregulated expression of CXCL9 in HCC compared with adjacent tumor tissue and normal liver cell lines. The knockdown of CTSC significantly reduced both HCC cell proliferation and migration.ConclusionOur study underscores the promise of PANoptosis-based molecular clustering and prognostic signatures in predicting patient survival and discerning the intricacies of the tumor microenvironment within the context of HCC. These insights hold the potential to advance our comprehension of the therapeutic contribution of PANoptosis plays in HCC and pave the way for generating more efficacious treatment strategies.

The development of urban underground space is a crucial aspect of current urban development. However, various factors pose challenges during the development process. In particular, in the valley cities of western China, groundwater has a significant impact on the utilization of underground space. This study focuses on understanding the influence of hydrogeological characteristics on the development of underground space in Ledu District, Haidong. Firstly, the hydrogeological characteristics of the aquifer in the study area are analyzed to determine the recharge and discharge characteristics. The dynamic changes in the groundwater table over time are then examined. Subsequently, the hydrochemical characteristics of groundwater are investigated to expound on the influence mechanism of groundwater on the development of underground space resources in Ledu District. The study reveals that the hydrodynamic effect of groundwater in the study area is substantial and has a significant physical scouring effect on underground structures. The fluctuation of groundwater levels affects the stability of buildings by increasing groundwater buoyancy. Additionally, this fluctuation also leads to engineering and environmental problems such as differential settlement and land salinization. The chemical characteristics of groundwater primarily impact the stability of building foundations through the corrosive effects of groundwater composition. This research clarifies the influence mechanism of groundwater on the development of underground space in typical valley cities of western China. The findings have practical significance for the evaluation, planning, development, and utilization of urban underground space resources in Haidong.

Abstract Pancreatic cancer (PC) is among the most aggressive malignancies associated with a 5-year survival rate of

Abstract Background Appendicitis is the most common abdominal surgical emergency worldwide, and its burden has been changing. We report the level and trends of appendicitis prevalence, and incidence; and years lived with disability (YLD) in 204 countries and territories from 1990 to 2019, based on data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods The numbers and age-standardized prevalence, incidence, and YLD rates per 100,000 population of appendicitis were estimated across regions and countries by age, sex, and sociodemographic index (SDI). All the estimates were reported with 95% uncertainty intervals (UIs). Results Globally, the age-standardized prevalence and incidence rates of appendicitis in 2019 were 8.7 (95% UI 6.9 to 11.0) and 229.9 (95% UI 180.9 to 291.0) per 100,000 population, with increases of 20.8% (95% UI 18.9 to 23.0%) and 20.5% (95% UI 18.7 to 22.8%) from 1990 to 2019, respectively. Additionally, the age-standardized YLDs rate was 2.7 (95% UI 1.8 to 3.9) in 2019, with an increase of 20.4% (95% UI 16.2 to 25.1%) from 1990 to 2019. In 2019, the age-standardized prevalence, incidence, and YLD rates peaked in the 15-to-19-year age groups in both male and female individuals. However, no statistically significant differences were observed between the male and female individuals in all groups. Ethiopia, India, and Nigeria showed the largest increases in the age-standardized prevalence rate between 1990 and 2019. Generally, positive associations were found between the age-standardized YLD rates and SDI at the regional and national levels. Conclusions Appendicitis remains a major public health challenge globally. Increasing awareness of appendicitis and its risk factors and the importance of early diagnosis and treatment is warranted to reduce its the burden.

Background: Magnetically controlled capsule endoscopy (MCCE) is a non-invasive, painless, comfortable, and safe equipment to diagnose gastrointestinal diseases (GID), partially overcoming the shortcomings of conventional endoscopy and wireless capsule endoscopy (WCE). With advancements in technology, the main technical parameters of MCCE have continuously been improved, and MCCE has become more intelligent. Objectives: The aim of this systematic review was to summarize the research progress of MCCE and artificial intelligence (AI) in the diagnosis and treatment of GID. Data Sources and Methods: We conducted a systematic search of PubMed and EMBASE for published studies on GID detection of MCCE, physical factors related to MCCE imaging quality, the application of AI in aiding MCCE, and its additional functions. We synergistically reviewed the included studies, extracted relevant data, and made comparisons. Results: MCCE was confirmed to have the same performance as conventional gastroscopy and WCE in detecting common GID, while it lacks research in detecting early gastric cancer (EGC). The body position and cleanliness of the gastrointestinal tract are the main factors affecting imaging quality. The applications of AI in screening intestinal diseases have been comprehensive, while in the detection of common gastric diseases such as ulcers, it has been developed. MCCE can perform some additional functions, such as observations of drug behavior in the stomach and drug damage to the gastric mucosa. Furthermore, it can be improved to perform a biopsy. Conclusion: This comprehensive review showed that the MCCE technology has made great progress, but studies on GID detection and treatment by MCCE are in the primary stage. Further studies are required to confirm the performance of MCCE.

Automatic segmentation of early esophagus cancer (EEC) in gastrointestinal endoscopy (GIE) images is a critical and challenging task in clinical settings, which relies primarily on labor-intensive and time-consuming routines. EEC has often been diagnosed at the late stage since early signs of cancer are not obvious, resulting in low survival rates. This work proposes a deep learning approach based on the U-Net++ method to segment EEC in GIE images. A total of 2690 GIE images collected from 617 patients at the Digestive Endoscopy Center, West China Hospital of Sichuan University, China, have been utilized. The experimental result shows that our proposed method achieved promising results. Furthermore, the comparison has been made between the proposed and other U-Net-related methods using the same dataset. The mean and standard deviation (SD) of the dice similarity coefficient (DSC), intersection over union (IoU), precision (Pre), and recall (Rec) achieved by the proposed framework were DSC (%) ​= ​94.62 ​± ​0.02, IoU (%) ​= ​90.99 ​± ​0.04, Pre ​(%) = ​94.61 ​± ​0.04, and Rec (%) ​= ​95.00 ​± ​0.02, respectively, outperforming the others. The proposed method has the potential to be applied in EEC automatic diagnoses.

Abstract In order to clean the mislabeled images in the esophageal endoscopy image data set, we designed a new neural network VGG_NIN. Based on the new neural network structure, we developed a method to clean the mislabeled images in the esophageal endoscopy image data set. To verify the effectiveness of the proposed method, we designed two experiments using 3835 esophageal endoscopy images provided by West China Hospital of Sichuan University. The experimental results showed that the proposed method could clean about 93% of the mislabeled images in the data set, which was the first time in the cleaning of esophageal endoscopy image data set. Finally, in order to verify the generalization ability of this method, we cleaned the Kaggle open cat and dog data set, and cleaned out about 167 mislabeled images. Therefore, the proposed method can effectively screen the mislabeled images in the esophageal endoscopy image data set and has good generalization ability, which can provide great help for the development of high-performance gastrointestinal endoscopy image analysis model.

Activation of O2 is a critical step in heterogeneous catalytic oxidation. Here, the authors adopt the concept of increased electron donors induced by nitrogen vacancy to develop an efficient strategy for preparing highly active and stable catalysts for molecular O2 activation.

This paper takes the weak basement of the outside dump of Jiangjun Gobi No.2 Open-pit Coal Mine of Xinjiang Tianchi Energy Company as the research object. Through the routine mechanical experiment and rheological test of the geotechnical soil in the study area, the physical and mechanical indexes of the basement and the abandoned material of the open pit mine are determined. Combined with theoretical analysis, it is determined that the slope landslide mode of the dump is located-shifted and the landslide mechanism is analyzed. The numerical simulation model of the stability analysis of the dump is established, and the deformation and failure modes of the dump slope are simulated. The stability of the dump slope is calculated and analyzed. When the drainage height is 120 m, the potential slip surface penetrates the interior of the dump and the weak basement, and the slope stability coefficient is slightly lower than the safety reserve coefficient.

Green tea (Camellia sinensis, Theaceace), has been extensively studied for its putative effects in prevention of age related diseases. Here, we discuss the increasing evidence that consumption of green tea has preventative effects in obesity, hypertension, insulin resistance, type II diabetes, atherosclerosis, coronary heart disease and Metabolic Syndrome (MetS). The catechins in green tea has been found to be beneficial in obesity induced by a high-fat diet. These effects are mainly attributable to the gallate esters of catechins, (-)-epicatechin gallate (ECG) and (-)-epigallocatechin-3- gallate (EGCG).

Several research studies have been conducted on N-formylation of amines using phenylsilane and CO2. However, most of these studies involved tedious processes of catalyst preparation or complex procedures. In the present study, we describe the use of a simple and commercially available ZnO catalyst for selective N-formylation of amines under mild condition. High-yielding N-formylation products with good recyclability and wide substrate scope were obtained, which can promote fine chemical synthesis and CO2 capture.

Ancylostomiasis is a fairly common small bowel parasite disease identified by capsule endoscopy (CE) for which a computer-aided clinical detection method has not been established. We sought to develop an artificial intelligence system with a convolutional neural network (CNN) to automatically detect hookworms in CE images. We trained a deep CNN system based on a YOLO-V4 (You Look Only Once-Version4) detector using 11236 CE images of hookworms. We assessed its performance by calculating the area under the receiver operating characteristic curve and its sensitivity, specificity, and accuracy using an independent test set of 10,529 small-bowel images including 531 images of hookworms. The trained CNN system required 403 seconds to evaluate 10,529 test images. The area under the curve for the detection of hookworms was 0.972 (95% confidence interval (CI), 0.967-0.978). The sensitivity, specificity, and accuracy of the CNN system were 92.2%, 91.1%, and 91.2%, respectively, at a probability score cut-off of 0.485. We developed and validated a CNN-based system for detecting hookworms in CE images. By combining this high-accuracy, high-speed, and oversight-preventing system with other CNN systems, we hope it will become an important supplement for detecting intestinal abnormalities in CE images. This trial is registered with ChiCTR2000034546 (a clinical research of artificial-intelligence-aided diagnosis for hookworms in small intestine by capsule endoscope images).

A tumorigenic microenvironment can give rise to neoplasm. A shift from this condition to a tumor-suppressive microenvironment is of significant benefit to susceptible individuals. The carbonyl groups of glycine and valine have long bond lengths, consequently generating potent affinities to divalent cations such as calcium. We hypothesize that the formation of insoluble and rigid calcium oxalate augmented by glycine and valine counteracts strong acids such as HCl chemically, thus reducing cancer risks. The anticancer effects of the 2 amino acids can be explained from a chemical and biochemical perspective. A tumor-suppressive microenvironment could be established via the modification of the proteome without genome editing at the DNA level.

Numerous cases of checkpoint inhibitor–triggered cancer hyperprogression have been documented. A previous hypothesis attributes cancer onset to the local buildup of hydrogen chloride, jointly mediated by hydrogen bond donors and acceptors and basic amino acids. The anti-PD1/PD-L1 immunotherapies may have caused a surge of protons or chloride ions for the effective treatment of neoplasm, thus giving rise to the local formation of hydrogen chloride and subsequently cancer hyperprogression in some susceptible individuals. It was postulated that the local strength of acidity is critical for tumor growth and metastasis, as the intake of weak organic acids reduces cancer risks. The anti-PD1/PD-L1 immunotherapies can be integrated with weak organic acids to reduce adverse reactions and generate better anticancer outcomes.

Background: Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide. PANoptosis is a recently unveiled programmed cell death pathway, Nonetheless, the precise implications of PANoptosis within the context of HCC remain incompletely elucidated. Methods: We conducted a comprehensive bioinformatics analysis to evaluate both the expression and mutation patterns of PANoptosis-related genes (PRGs). We categorized HCC into two clusters and identified differentially expressed PANoptosis-related genes (DEPRGs). Next, a PANoptosis risk model was constructed using LASSO and multivariate Cox regression analyses. The relationship between PRGs, risk genes, the risk model, and the immune microenvironment was studies. In addition, drug sensitivity between high- and low-risk groups was examined. The expression profiles of these four risk genes were elucidate by qRT-PCR or immunohistochemical (IHC). Furthermore, the effect of CTSC knock down on HCC cell behavior was verified using in vitro experiments. Results: We constructed a prognostic signature of four DEPRGs (CTSC, CDCA8, G6PD, and CXCL9). Receiver operating characteristic curve analyses underscored the superior prognostic capacity of this signature in assessing the outcomes of HCC patients. Subsequently, patients were stratified based on their risk scores, which revealed that the low-risk group had better prognosis than those in the high-risk group. High-risk group displayed a lower Stromal Score, Immune Score, ESTIMATE score, and higher cancer stem cell content, tumor mutation burden (TMB) values. Furthermore, a correlation was noted between the risk model and the sensitivity to 56 chemotherapeutic agents, as well as immunotherapy efficacy, in patient with. These findings provide valuable guidance for personalized clinical treatment strategies. The qRT-PCR analysis revealed that upregulated expression of CTSC, CDCA8, and G6PD, whereas downregulated expression of CXCL9 in HCC compared with adjacent tumor tissue and normal liver cell lines. The knockdown of CTSC significantly reduced both HCC cell proliferation and migration. Conclusion: Our study underscores the promise of PANoptosis-based molecular clustering and prognostic signatures in predicting patient survival and discerning the intricacies of the tumor microenvironment within the context of HCC. These insights hold the potential to advance our comprehension of the therapeutic contribution of PANoptosis plays in HCC and pave the way for generating more efficacious treatment strategies. [ABSTRACT FROM AUTHOR]

Gastrointestinal (GI) diseases constitute a leading problem in the human digestive system. Consequently, several studies have explored automatic classification of GI diseases as a means of minimizing the burden on clinicians and improving patient outcomes, for both diagnostic and treatment purposes. The challenge in using deep learning-based (DL) approaches, specifically a convolutional neural network (CNN), is that spatial information is not fully utilized due to the inherent mechanism of CNNs. This paper proposes the application of spatial factors in improving classification performance. Specifically, we propose a deep CNN-based spatial attention mechanism for the classification of GI diseases, implemented with encoder–decoder layers. To overcome the data imbalance problem, we adapt data-augmentation techniques. A total of 12,147 multi-sited, multi-diseased GI images, drawn from publicly available and private sources, were used to validate the proposed approach. Furthermore, a five-fold cross-validation approach was adopted to minimize inconsistencies in intra- and inter-class variability and to ensure that results were robustly assessed. Our results, compared with other state-of-the-art models in terms of mean accuracy (ResNet50 = 90.28, GoogLeNet = 91.38, DenseNets = 91.60, and baseline = 92.84), demonstrated better outcomes (Precision = 92.8, Recall = 92.7, F1-score = 92.8, and Accuracy = 93.19). We also implemented t-distributed stochastic neighbor embedding (t–SNE) and confusion matrix analysis techniques for better visualization and performance validation. Overall, the results showed that the attention mechanism improved the automatic classification of multi-sited GI disease images. We validated clinical tests based on the proposed method by overcoming previous limitations, with the goal of improving automatic classification accuracy in future work.

Summary: Single-atom catalysts (SACs) have attracted broad interest recently due to their superior catalytic properties. However, a facile fabrication method for the large-scale synthesis of SACs is still in demand. This study reports a mechanochemical approach for the mass production of noble metal SACs. The successful formation of atomically dispersed palladium species on zinc oxide (Pd1/ZnO) was verified by aberration-corrected high-angle annular dark-field scanning transmission electron microscopy and X-ray absorption spectroscopy. Furthermore, our method exhibited little scaling-up effect on the mass production of Pd1/ZnO at ranges of 10–1,000 g, in which the catalyst structure and catalytic performance were retained. Meanwhile, the versatility of this approach was demonstrated by the large-scale fabrication of Rh and Ru SACs, and Pd1/Cu single-atom alloys. Thus, this promising strategy provides the potential for cost-effective mass production of SACs and subsequently may open a window for their industrial application.