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Abstract Humans can be exposed to multiple pollutants in the air and surface water. These environments are non-static, trans-boundary and correlated, creating a complex network, and significant challenges for research on environmental hazards, especially in real-world cancer research. This article reports on a large study (377 million people in 30 provinces of China) that evaluated the combined impact of air and surface water pollution on cancer. We formulate a spatial evaluation system and a common grading scale for co-pollution measurement, and validate assumptions that air and surface water environments are spatially connected and that cancers of different types tend to cluster in areas where these environments are poorer. We observe “dose–response” relationships in both the number of affected cancer types and the cancer incidence with an increase in degree of co-pollution. We estimate that 62,847 (7.4%) new cases of cancer registered in China in 2016 were attributable to air and surface water pollution, and the majority (69.7%) of these excess cases occurred in areas with the highest level of co-pollution. The findings clearly show that the environment cannot be considered as a set of separate entities. They also support the development of policies for cooperative environmental governance and disease prevention.

Two new species of Eupolyphaga (E. bicolor Han, Che & Wang, sp. nov. and E. nigra Han, Che & Wang, sp. nov.) and six new species of Pseudoeupolyphaga (P. flava Han, Che & Wang, sp. nov., P. deficiens Han, Che & Wang, sp. nov., P. magna Han, Che & Wang, sp. nov., P. longiseta Han, Che & Wang, sp. nov., P. latizona Han, Che & Wang, sp. nov., and P. baimaensis Han, Che & Wang, sp. nov.) are described and illustrated. The female external genitalia and spermathecae of these two genera are reported and the role of these characters in species delimitation is discussed.

Abstract Most of the existing methods for harmonic analysis are from frequency‐domain perspective. In fact, the essential factor for generating harmonics is non‐linear characteristic or time‐varying property. Therefore, the harmonic generation mechanism and the harmonic source location method are investigated from the time domain perspective in this paper. Firstly, a general model of non‐harmonic sources is established. The non‐harmonic sources will match well with the proposed general model while the harmonic source will not. Then correlation coefficient that reflects compliance degree between each device and the general model is defined for distinguishing harmonic sources from non‐harmonic sources. On this basis, a novel time‐domain harmonic source location method is proposed. Numerous simulations and experiments have demonstrated that the proposed method has good performance under fluctuations, saturations, pre‐distortions, transient process, and resonances. The defined correlation coefficient can reflect non‐linearity/time‐varying degree of the harmonic source, which can be used for evaluating harmonic emission level of each harmonic source. On this basis, a simple harmonic responsibility division method is proposed, which is immune to possible fluctuations, pre‐distortions, saturations, resonances, and impedance variation.

Abstract Constant-frequency ultrasonic treatment helped to improve seed germination. However, variable-frequency ultrasonic treatment on maize seed germination were rarely reported. In this study, maize seeds were exposed to 20–40 kHz ultrasonic for 40 s. The germination percentage and radicle length of maize seeds increased by 10.4% and 230.5%. Ultrasonic treatment also significantly increased the acid protease, α-amylase, and β-amylase contents by 96.4%, 73.8%, and 49.1%, respectively. Transcriptome analysis showed that 11,475 differentially expressed genes (DEGs) were found in the ultrasonic treatment and control groups, including 5,695 upregulated and 5,780 downregulated. Metabolic pathways and transcription factors (TFs) were significantly enriched among DEGs after ultrasonic treatment. This included metabolism and genetic information processing, that is, ribosome, proteasome, and pyruvate metabolism, sesquiterpenoid, triterpenoid, and phenylpropanoid biosynthesis, and oxidative phosphorylation, as well as transcription factors in the NAC, MYB, bHLH, WRKY, AP2, bZIP, and ARF families. Variable-frequency ultrasonic treatment increased auxin, gibberellin, and salicylic acid by 5.5%, 37.3%, and 28.9%, respectively. Abscisic acid significantly decreased by 33.2%. The related DEGs were upregulated and downregulated to varying degrees. Seed germination under the abiotic stress conditions of salt stress (NaCl solution), drought (PEG solution), and waterlogging (water-saturated sand bed) under ultrasonic treatment were promoted, radicle length was significantly increased by 30.2%, 30.5%, and 27.3%, respectively; and germination percentage by 14.8%, 20.1%, and 21.6%, respectively. These findings provide new insight into the mechanisms through ultrasonic to promote maize seed germination.

Herein, novel amperometric based biosensor using a MXene-Pt nanocomposite was fabricated and utilized for lactate analysis. MXene-Pt provided a desirable matrix for the anchoring of lactate oxidase (LOD). Excellent electron transfer occurred at the interface between the receptor and glassy carbon electrode (GCE) due to the synergetic effect between MXene layers and Pt nanoparticles (NPs). The uniform distribution of small sized Pt NPs gives rise to superior electron transfer kinetics, thereby maximizing the lactate detection abilities of the LOD-MXene-Pt modified GCE. The novel sensing platform displays this linear response in buffer medium (pH = 7.4) within the range of concentrations of 0.02–0.75 mM, and the detection limit of 10 µM based on 3σ was obtained for lactate detection. The accurate analysis of lactate in physiological samples indicated that the presence method is a very specific tool. It was used for successful measurement of lactate concentration in saliva samples during sport practice. The proposed strategy is convenient and less expensive, quick analysis time and offers an efficient procedure of lactate monitoring in the common clinical tests.

Abstract Diabetic nephropathy (DN) is a critical inflammatory condition linked to diabetes, affecting millions worldwide. This study employs Mendelian randomization (MR) to explore the causal relationship between immune cell signatures and DN, analyzing over 731 immune signatures and incorporating data from 1400 metabolites to investigate potential mediators. Despite no statistically significant influence of DN on immunophenotypes after FDR correction, some phenotypes with unadjusted low P-values warranted mention, including CD34 on Hematopoietic Stem Cell (Myeloid cell Panel), CD45 on CD33− HLA DR− (Myeloid cell Panel). Furthermore, three immunophenotypes were identified to have a significant impact on DN risk: CD16−CD56 on HLA DR+ NK (TBNK Panel), CD45 on HLA DR+ T cell (TBNK Panel), and CD33dim HLA DR+ CD11b+ AC (Myeloid cell Panel). Our findings underscore the critical role of immune cells in DN, highlighting potential mediators and offering new insights into its underlying mechanisms.

Abstract Background Numerous studies have confirmed the involvement of extracellular vesicles (EVs) in various physiological processes, including cellular death and tissue damage. Recently, we reported that EVs derived from ischemia-reperfusion heart exacerbate cardiac injury. However, the role of EVs from healthy heart tissue (heart-derived EVs, or cEVs) on myocardial ischemia-reperfusion (MI/R) injury remains unclear. Results Here, we demonstrated that intramyocardial administration of cEVs significantly enhanced cardiac function and reduced cardiac damage in murine MI/R injury models. cEVs treatment effectively inhibited ferroptosis and maintained mitochondrial homeostasis in cardiomyocytes subjected to ischemia-reperfusion injury. Further results revealed that cEVs can transfer ATP5a1 into cardiomyocytes, thereby suppressing mitochondrial ROS production, alleviating mitochondrial damage, and inhibiting cardiomyocyte ferroptosis. Knockdown of ATP5a1 abolished the protective effects of cEVs. Furthermore, we found that the majority of cEVs are derived from cardiomyocytes, and ATP5a1 in cEVs primarily originates from cardiomyocytes of the healthy murine heart. Moreover, we demonstrated that adipose-derived stem cells (ADSC)-derived EVs with ATP5a1 overexpression showed much better efficacy on the therapy of MI/R injury compared to control ADSC-derived EVs. Conclusions These findings emphasized the protective role of cEVs in cardiac injury and highlighted the therapeutic potential of targeting ATP5a1 as an important approach for managing myocardial damage induced by MI/R injury.

To explore the protective effects of water extracts from different Ganoderma lucidum (G. lucidum) mycelium on ethanol-induced hepatocyte injury in LO2 cells. The effects of water extracts obtained from different G. lucidum mycelium against ethanol-induced damage to LO2 cells were examined in this research. Cell survival rate, alanine aminotransferase (ALT), aspartate aminotransferase (AST), reactive oxygen species (ROS), superoxide dismutase (SOD), glutathione (GSH) and malondialdehyde (MDA) levels were measured in a liver injury model employing ethanol-induced LO2 cells, to assess the preventive effects of G. lucidum mycelium water extracts against ethanol-induced damage. The results showed that water extracts from the mycelium of all seven strains exhibited varying degrees of protective effects. Among them, the water extract from strains G0119 and G0154 had the best protective effect. Compared with the model group, the intervention of water extracts significantly increased LO2 cell survival (P

In recent years, exploration breakthroughs have been successively achieved in the strata deeper than the fifth member of the Lower Ordovician Majiagou Formation in the Ordos Basin, revealing its tremendous exploration potential. With the deployment of high-precision 3D seismic data and the deepening of oil and gas exploration, the control exerted by faults on the gas reservoirs in the deeper layers of the fifth member has become increasingly prominent. Based on high-precision 3D seismic data, this study systematically characterized the geometric features of faults in the Gaojiabao area, dissected typical fault structural patterns, established fault formation and evolution models, and, in conjunction with drilling and testing data, discussed the control of faults on the differential enrichment of gas reservoirs in the deeper layers of the Majiagou Formation. The study yielded the following insights: Faults in the Lower Paleozoic of the Gaojiabao area in the Ordos Basin exhibit distinct stratified deformation characteristics, with the two sets of gypsum-salt rocks in the third and fifth members being major contributors to fault stratification. The Lower Paleozoic in the Gaojiabao area mainly develops strike-slip faults with compressional and torsional properties and thrust faults. Through studying the structural morphology and fault patterns of the Gaojiabao area, it is inferred that the Yanshan tectonic movement was the most significant phase of reformation affecting the faults formed during the Caledonian tectonic movement. The coupling of the structural uplift period with the oil-gas charging period in the Gaojiabao area means that faults play multiple roles, including improving reservoirs, connecting source rocks, and controlling traps.

Abstract Chronic constipation, diarrhea, and fecal incontinence have high incidence, potential disability, and socioeconomic impact, imposing a heavy burden on the quality of life. We aim to explore the association between cardiovascular health (CVH) and bowel health from National Health and Nutrition Survey 2005–2010. CVH is assessed using Life’s Essential 8 (LE8). Chronic constipation, chronic diarrhea, and fecal incontinence are assessed based on Bristol Stool Form Scale classification, bowel movements, and bowel leakage. Better health behaviors (odds ratio [OR]: 0.71, 95% confidence interval [CI] 0.53–0.94, p = 0.02) and worse health factors (OR: 1.45, CI 1.03–2.04, p = 0.04) were associated with less chronic constipation. Less chronic diarrhea is correlated with better CVH (OR: 0.53, 95% CI 0.35–0.79, p = 0.003) and health factors (OR: 0.61, CI 0.46–0.81, p = 0.001). Meanwhile, the proportion of chronic diarrhea significantly decreases when the health behaviors score exceeds 59.42. Lower fecal incontinence was associated with better health behaviors (OR: 0.63, CI 0.44–0.90, p = 0.01) CVH. Better CVH and health behaviors are both linked to lower all-cause mortality in participants with chronic constipation and chronic diarrhea. A higher health behaviors score is also associated with less all-cause mortality in patients with fecal incontinence. Maintaining CVH at the population level contributes to intestinal health, achieving the dual management of both while saving on healthcare costs. However, further prospective research is needed to confirm these associations.

Abstract We aimed to identify the severity and duration of COVID-19 infection on complications after allo-HSCT. Enrolled 179 hospitalized patients with COVID-19 were categorized into long-term infection (> 18 days, n = 90) or short-term infection group (≤ 18 days, n = 89) according to the median duration of COVID-19. The severity of COVID-19 was categorized as asymptomatic infection, mild, moderate, severe, and critical illness according to guidelines of National Institutes of Health. Particularly, severe illness and critical illness were classified as serious infection. Asymptomatic infection, mild illness and moderate illness were classified as non-serious infection. The 150-day probabilities of poor graft function (PGF), cytomegalovirus (CMV) pneumonia and non-relapse mortality (NRM) were significantly higher in long-term infection group. The 150-day probabilities of CMV pneumonia and NRM after COVID-19 were higher in serious infection group. The 150-day probabilities of overall survival (OS) was significantly lower in long-term and serious infection group. In multivariable analysis, the severity of COVID-19 was associated with NRM and OS, and the duration of COVID-19 was associated with PGF. In summary, our data reported that the severity and duration of COVID-19 were associated with several complications and contribute to poor outcomes after allo-HSCT.

Abstract Background Severe pneumonia is one of the most important causes of mortality after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Adenovirus (ADV) is a significant cause of severe viral pneumonia after allo-HSCT, and we aimed to identify the clinical manifestations, prognostic factors, and outcomes of ADV pneumonia after allo-HSCT. Methods Twenty-nine patients who underwent allo-HSCT at the Peking University Institute of Hematology and who experienced ADV pneumonia after allo-HSCT were enrolled in this study. The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Potential prognostic factors for 100-day OS after ADV pneumonia were evaluated through univariate and multivariate Cox regression analyses. Results The incidence rate of ADV pneumonia after allo-HSCT was approximately 0.71%. The median time from allo-HSCT to the occurrence of ADV pneumonia was 99 days (range 17–609 days). The most common clinical manifestations were fever (86.2%), cough (34.5%) and dyspnea (31.0%). The 100-day probabilities of ADV-related mortality and OS were 40.4% (95% CI 21.1%-59.7%) and 40.5% (95% CI 25.2%-64.9%), respectively. Patients with low-level ADV DNAemia had lower ADV-related mortality and better OS than did those with high-level (≥ 106 copies/ml in plasma) ADV DNAemia. According to the multivariate analysis, high-level ADV DNAemia was the only risk factor for intensive care unit admission, invasive mechanical ventilation, ADV-related mortality, and OS after ADV pneumonia. Conclusions We first reported the prognostic factors and confirmed the poor outcomes of patients with ADV pneumonia after allo-HSCT. Patients with high-level ADV DNAemia should receive immediate and intensive therapy.

Abstract Background Mitogen-activated protein kinase (MAPK)signaling-mediated smoking-associated pulmonary vascular remodeling (PVR) plays an important role in the pathogenesis of group 3 pulmonary hypertension (PH). And G protein pathway suppressor 2 (GPS2) could suppress G-protein signaling such as Ras and MAPK, but its role in cigarette smoking -induced PVR (CS-PVR) is unclear. Methods An in vivo model of smoke-exposed rats was constructed to assess the role of GPS2 in smoking-induced PH and PVR. In vitro, the effects of GPS2 overexpression and silencing on the function of human pulmonary arterial smooth cells (HPASMCs) and the underlying mechanisms were explored. Results GPS2 expression was downregulated in rat pulmonary arteries (PAs) and HPASMCs after CS exposure. More importantly, CS-exposed rats with GPS2 overexpression had lower right ventricular systolic pressure (RVSP), right ventricular hypertrophy index (RVHI), and wall thickness (WT%) than those without. And enhanced proliferation and migration of HPASMCs induced by cigarette smoking extract (CSE) can be evidently inhibited by overexpressed GPS2. Besides, GPS2siRNA significantly enhanced the proliferation, and migration of HPASMCs as well as activated Ras and Raf/ERK signaling, while these effects were inhibited by zoledronic acid (ZOL). In addition, GPS2 promoter methylation level in rat PAs and HPASMCs was increased after CS exposure, and 5-aza-2-deoxycytidine (5-aza) inhibited CSE-induced GPS2 hypermethylation and downregulation in vitro. Conclusions GPS2 overexpression could improve the CS-PVR, suggesting that GPS2 might serve as a novel therapeutic target for PH-COPD in the future. Graphical Abstract

Highlights Evaporation and solution two-step hybrid process are used to fabricate conformal growth of perovskite film on textured silicon substrates. F-PMAI additive enlarged the perovskite grains, induced the (111) preferred orientation and passivated interface defects. We obtained a champion efficiency of 30.05% for a monolithic perovskite/silicon tandem solar cell based on a silicon thin film tunneling junction.

Bone morphogenetic protein 4 (BMP4) can induce the formation of chicken primordial germ cells (PGCs) in vitro; however, its regulatory mechanism in poultry remains unknown. This study aimed to use RNA-seq to analyze PGCs in chicken embryos and iPGCs induced by BMP4 in vitro, clarify the internal regulatory factors of PGCs, analyze the mechanism of the formation of PGCs, and lay a theoretical foundation for the further optimization of PGCs induction systems. Embryonic stem cells (ESCs), PGCs and iPGCs induced by BMP4 in vitro were collected. The transcriptional maps of the three cell types were studied using RNA-seq. The results showed 6,142 genes differentially expressed between PGCs and iPGCs, of which 2,728 were upregulated in iPGCs and 3,414 were downregulated in iPGCs. Compared to that in ESCs, BMP4 was significantly upregulated in PGCs and iPGCs. KEGG results showed that both the TGF-β and Wnt signaling pathways were activated during the formation of PGCs in vitro and in vivo, and the activation was more significant during iPGCs induced by BMP4. The expression of Nodal, an inhibitory factor of TGF-β signaling, was significantly decreased in PGCs and iPGCs, but was not expressed in iPGCs, which further supports our conclusion. Additionally, the Lysosome and PI3K-AKT signaling pathways were significantly enriched in PGCs and iPGCs, respectively. Further, transmission electron microscopy (TEM) results showed that the number of autolysosomes was significantly higher after the addition of BMP4, which is consistent with the KEGG results. Furthermore, the number of PGCs was significantly reduced after ATG14 was interfered in vivo and in vitro. In conclusion, this study screened out the key signaling pathways during the formation of PGCs, aiming to provide help for enriching the mechanism network regulating PGCs formation in chicken and laying a theoretical foundation for further improving the efficiency of inducing PGCs in vitro.

Abstract Objective To explore the application and advantages of 5G technology in aeromedical rescue. Methods Through the analysis of 11 rescue cases, especially two cases of 5G rescus cases, such as remote video consultation, 5G module equipment, vital signs data return, and Beidou high‐precision positioning. Results 5G technology significantly optimizes the rescue process, enabling real‐time monitoring, low‐airspace 5G private network coverage, advanced equipment support, collaborative operations, and seamless information connection. Its high‐speed network transmission and high‐precision positioning capabilities have promoted the development of aerial body area network disease perception technology and 5G ground–ground collaborative rapid diagnosis and treatment technology, making telemedicine more convenient, safe, and scalable. Conclusion 5G technology has great potential and promotion value in the field of aeromedical rescue.

Abstract With the development and the application popularization of artificial intelligence robot technology and 5G technology, a robotic arm is designed and developed for rinsing porcelain bushing in high voltage substation in this paper. Firstly, the components and implementation of robotic arm are presented, subsequently, a circular cleaning structure with a 120-degree split is proposed to rinse the porcelain bushing. Secondly, a two-stage simple and effective method to realize automatic orientation is proposed utilizing photoelectric switches. Moreover, a prototype of robotic arm with control system is developed based on the regime switching function, and the result of edge computing is transmitted by 5G technology. Finally, feasibility and effectiveness of the robotic arm are verified in the Nanjing power grid. The case study manifests that the robotic arm developed by the proposed method in the paper can achieve efficient rinsing and all the corresponding information can be transmitted preciously. The proposed method lays a foundation for wide application of cleaning robot in high voltage substation.

Background: Colon cancer is one of the most prevalent digestive cancers worldwide. Results of epidemiological, experimental, and clinical studies suggest that aspirin inhibits the development of colon cancer. This study aimed to systematically elucidate the molecular mechanisms by which aspirin prevents colon carcinogenesis. Methods: We determined the global protein expression profiles of colorectal cancer and aspirin-treated cells using quantitative proteomic analysis. We analyzed the proteomic results using bioinformatics (including differential proteins, protein annotation, Kyoto Encyclopedia of Genes and Genomes [KEGG] pathways, and protein–protein interaction [PPI] network). The viability of the colon cancer cell line and HT29 ​cells treated with aspirin was determined using the cell counting kit-8 assay. The differentially expressed proteins, such as p53 and cyclin-dependent kinase 1 (CDK1), were quantified using real-time polymerase chain reaction (PCR) and Western blotting. We measured cell cycle distribution and apoptosis in HT29 ​cells exposed to aspirin using fluorescence-activated cell sorting (FACS). Results: We found that 552 proteins were significantly dysregulated, of which 208 and 334 were upregulated and downregulated, respectively, in colon cancer cells exposed to 10 ​mmol/L of aspirin (95% confidence interval [CI]: -1.269 to -0.106, P ​

As an important part of the geological environment assessment in recent years, mine interpretation has attracted broad attention in the area of sustainable development. As an object that can be captured by remote sensing of multispectral imageries, the open-pit (OP) mine environment has the characteristics of irregular distribution, diverse shapes, and varied textures and colors, which makes interpretation a challenge and limits the accuracy of OP mine mapping. Moreover, the development of computational vision technology enables efficient and fast interpretation. However, there is a lack of open semantic segmentation datasets for OP mining areas. In this paper, we introduce a dataset for OP mining areas in the West Hubei metallogenic belt (DOWHM) for OP mine element interpretation. DOWHM includes 24 active OP mining zones in China’s Hubei Province, with a total of 1875 satellite images of 224×224 pixels at a resolution of 0.6 m. Second, we design a ConvFormer model for fine classification and mapping in OP mining areas. The ConvFormer model adopts an encoder featuring a large convolutional kernel. The decoder of the ConvFormer model employs a multi-branch approach, integrating modules of convolutional neural network (CNN) and self-attention mechanism. In this manner, ConvFormer effectively captures both global–local information. This solves the problem of the misclassification of elements in the prediction results, and especially has advantages in road classification. In the experiments, ConvFormer achieved mIoU of 68.18% on DOWHM. Compared to other popular semantic segmentation models, ConvFormer improved the overall mIoU by 2%, which is advantageous in the fine classification of OP mining regions, and it can be applied to the mapping of entire mining regions. DOWHM and the code are available at https://github.com/zxy1211/DOWHM.

Summary: A crucial challenge in hydrogen production through electrolysis is developing inexpensive, earth-abundant, and highly efficient Pt-free electrocatalysts for the hydrogen evolution reaction (HER). Molybdenum carbide is ideal for this application because of its special electrical structure, low cost, and advantageous characteristics. Herein, the long-lived electrocatalysts for HER have been synthesized via the direct current (DC) arc discharge plasma method under ambient air conditions, and the relationship between the properties of materials and catalytic characteristics has been established. The samples differed in the ratio of molybdenum, graphite, and melamine. The sample with the highest proportion of melamine in the initial mixture has Mo2C-MoO2 heterointerfaces, which demonstrates the highest and most stable electrocatalytic activity with the overpotential of 148 mV at 10 mA·cm-2 and Tafel slope of 63 mV·dec−1 in alkaline electrolyte. Meanwhile, the electrodes demonstrated long-lived electrochemical durability for two weeks and investigated the features of forming a stable system for HER.

Background Ankylosing spondylitis (AS) is characterized by inflammation and osteoblastic changes in the sacroiliac joint. As a potential imaging method for the early assessment of AS, positron emission tomography (PET) can quantify systemic disease activity, which is conducive to monitoring the progression of disease activity and assisting in evaluating the efficacy of the treatment. Objective The study was to evaluate the diagnostic value of aluminium-[ 18 F]fuoride(Al 18 F)-labelled fibroblast activation protein inhibitor (FAPI) PET/computed tomography (CT) in AS and to investigate its ability to assess disease activity during the development of AS. Material and Methods Twenty AS participants who met the Assessment of SpondyloArthritis international Society criteria and were in an active disease stage were included in this study from May 2022 to April 2023. Sixteen healthy controls were also inrolled. All participants underwent Al 18 F-NOTA-FAPI-04 PET/CT imaging after collecting clinical assessment and laboratory results. The correlation between positive joint count (PJC) and systemic joint standard uptake value ratio (SUVR, the mean SUV max of the 5 highest joints/SUV max of the uninvolved sacrum) on PET and clinical disease activity assessment and various laboratory tests were analyzed. Results A total of 2820 joints were observed in 20 participants (median age 34.5,[21-61]range, 15 men), with a PJC of 1300 (46.7%), and 39 positive uptakes were found in 40 sacroiliac joints (97.5%). PET/CT images revealed FAPI-04 uptake in both sacroiliac joints in 2 participants without radiographic sacroiliitis in the early stages of AS and varying degrees of uptake in the sacroiliac joints and spinal joints in the remaining participants. PJC and SUVR were positively correlated with most clinical assessments and laboratory findings ( P

Abstract Base editors (BEs) are a recent generation of genome editing tools that couple a cytidine or adenosine deaminase activity to a catalytically impaired Cas9 moiety (nCas9) to enable specific base conversions at the targeted genomic loci. Given their strong application potential, BEs are under active developments toward greater levels of efficiency and safety. Here, a previously overlooked nCas9‐centric strategy is explored for enhancement of BE. Based on a cytosine BE (CBE), 20 point mutations associated with nCas9‐target interaction are tested. Subsequently, from the initial positive X‐to‐arginine hits, combinatorial modifications are applied to establish further enhanced CBE variants (1.1–1.3). Parallel nCas9 modifications in other versions of CBEs including A3A‐Y130F‐BE4max, YEE‐BE4max, CGBE, and split‐AncBE4max, as well as in the context of two adenine BEs (ABE), likewise enhance their respective activities. The same strategy also substantially improves the efficiencies of high‐fidelity nCas9/BEs. Further evidence confirms that the stabilization of nCas9‐substrate interactions underlies the enhanced BE activities. In support of their translational potential, the engineered CBE and ABE variants respectively enable 82% and 25% higher rates of editing than the controls in primary human T‐cells. This study thus demonstrates a highly adaptable strategy for enhancing BE, and for optimizing other forms of Cas9‐derived tools.

PM2.5 pollution has been associated with the incidence of lung cancer, but the underlying mechanism is still unclear. PIWI-interacting RNAs (piRNAs), initially identified in germline cells, have emerged as a novel class of small non-coding RNAs (26 – 32 nucleotides) with diverse functions in various diseases, including cancer. However, the role and mechanism of piRNAs in the development of PM2.5-induced lung cancer remain to be clarified. In the presented study, we used a PM2.5-induced malignant transformation cell model to analyze the change of piRNA profiles. Among the disturbed piRNAs, piR-27222 was identified as an oncogene that inhibited cell death in a m6A-dependent manner. Mechanistically, we found that piR-27222 could deubiquitinate and stabilize eIF4B by directly binding to eIF4B and reducing its interaction with PARK2. The enhanced expression of eIF4B, in turn, promoted the expression of WTAP, leading to increased m6A modification in the Casp8 transcript. Consequently, the stability of Casp8 transcripts was reduced, rendering lung cancer cells resistant to PANoptosis. Collectively, our findings reveal that PM2.5 exposure up-regulated piR-27222 expression, which could affect EIF4B/WTAP/m6A axis, thereby inhibiting PANoptosis of cells and promoting lung cancer. Our study provides new insights into understanding the epigenetic mechanisms underlining PM2.5-induced lung cancer.

Rapid global population growth and urbanization have heightened the demand for emergency medical rescue, with helicopter medical rescue emerging as an effective solution. The advent of 5G communication technology, characterized by large bandwidth, low latency, and high reliability, offers substantial promise in enhancing the efficiency and quality of helicopter rescue operations. However, the full integration of 5G technology into helicopter emergency medical services is still in its nascent stages and requires further development. In this viewpoint, we present our experience from the Shenzhen University General Hospital of the application of 5G low-altitude network communication technology, body area network disease sensing technology, and 5G air-ground collaborative rapid diagnosis and treatment technology in aeromedical rescue. We consider that the 5G air-to-ground collaborative rapid diagnosis and treatment technology enables high-quality remote consultation, enhancing emergency medical rescue and providing strong support for future rescue operations.

BackgroundMetastasis remains the leading cause of mortality among colorectal cancer (CRC) patients. Identification of new metastasis-related genes are critical to improve colorectal cancer prognosis.MethodsData on mRNA expression in metastatic and primary CRC was obtained from the Gene Expression Omnibus (GEO) database, including GSE81986, GSE41568, GSE71222, GSE21510, and GSE14333. Additionally, data concerning mRNA expression in colon cancer (COAD) and adjacent normal tissues were acquired from The Cancer Genome Atlas (TCGA) database. Hub genes were identified by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis. Moreover, we assessed the impact of hub gene expression on both overall survival (OS) and disease-free survival (DFS) in patients and identified ZG16 as a potential target. We generated CRC cell lines transfected with lentivirus OE-ZG16 to investigate proliferation, invasion, and migration in vitro. To further elucidate the involvement of ZG16, we utilized gene set enrichment analysis (GSEA) to identify enriched pathways, which were subsequently validated via Western blot analysis.ResultsFive datasets containing primary and metastatic CRC samples from GEO database and CRC samples from TCGA database were included in this study and 29 hub genes were identified by WGCNA and differentially expressed gene (DEG) analysis. Low expression of the hub genes (CLCA1 and ZG16) was associated with poor DFS and OS. We confirmed the low expression of ZG16 in CRC using external database and IHC analysis at both transcriptional and protein levels. In addition, the expression of ZG16 was notably elevated in NCM460 cells in comparison to CRC cell lines. The overexpression of ZG16 in CRC cells has been shown to inhibit the proliferation, invasion, and migration of CRC cells. Furthermore, the overexpression of ZG16 has been found to suppress the activation of the epithelial-mesenchymal transition (EMT) and Wnt/β-catenin signaling pathways in CRC.ConclusionZG16 may serve as a promising therapeutic target for metastatic CRC treatment.

Background: Electroacupuncture (EA) has been shown to promote functional recovery after cerebral ischemia–reperfusion (I/R) injury. However, the contribution of mitochondrial dynamics to recovery remains unclear. The aim of this study was to investigate whether mitochondrial dynamics are involved in the effects of EA on cerebral I/R injury. Methods: The rats with cerebral I/R injury were established by the middle cerebral artery occlusion/reperfusion. Subsequently, EA was applied to Baihui (GV20) and Dazhui (GV14) acupoints, with 2 Hz/5 Hz in frequency, 1.0 mA in intensity, 20 min each time, once a day for seven consecutive days. The therapeutic outcomes were assessed by modified neurological severity score (mNSS), 2,3,5-Triphenyte-trazolium chloride (TTC) staining, and hematoxylin-eosin (HE) staining. Mitochondrial morphology was observed under transmission electron microscopy. Adenosine triphosphate (ATP) content and ATP synthases (ATPases) activity were evaluated to measure mitochondrial function using ELISA. Finally, mitochondrial dynamics-related molecules, including dynamin-related protein 1 (Drp1), fission 1 (Fis1), mitofusin 1 (Mfn1), mitofusin 2 (Mfn2), and optic atrophy 1 (OPA1), were detected by Western blot and immunofluorescence staining. Results: Cerebral I/R injury induced neurological dysfunction, cerebral infarction and neuronal injury, all of which were ameliorated by EA. And EA improved mitochondrial morphology and function. Moreover, EA altered the balance of mitochondrial dynamics. Specifically, the data showed a significant decrease in the expression of Drp1 and Fis1, leading to the inhibition of mitochondrial fission. Additionally, Mfn1, Mfn2 and Opa1, which are related to mitochondrial fusion, were effectively promoted after EA treatment. However, sham EA did not show any neuroprotective effects in rats with cerebral I/R injury. Conclusions: In summary, our study indicates that the balance of mitochondrial dynamics is crucial for EA therapy to treat cerebral I/R injury.

BackgroundSolid pseudopapillary neoplasms of the pancreas with hepatic metastases are infrequent and difficult to diagnose, and treatment is uncertain.MethodsA retrospective analysis of clinical data from patients with pancreatic solid pseudopapillary neoplasm (SPN) hepatic metastases who underwent surgery at the First Hospital of Jilin University from January 2005 to December 2021 was conducted. A total of 287 patients with SPN were included in the study, of which 8 (3%) developed liver metastases, all of whom were treated surgically and recovered well after surgery. The clinical presentation, imaging features, surgical treatment, histopathological examination, and postoperative follow-up data (mean 70 months; range 28–138 months) of the patients were recorded and analyzed. Clinical response strategies can be derived by reviewing previous studies on hepatic metastases of SPNs.ResultsFor resectable hepatic metastases from pancreatic solid pseudopapillary neoplasms, early surgery with total resection of the primary tumor and metastasis has shown great efficiency and is associated with patient good prognosis. In patients presenting unresectable hepatic metastases, aggressive tumor reduction surgery resulted in the alleviation of clinical symptoms and reduction of tumor burden while potentially achieving long-term survival.ConclusionFor hepatic metastases of SPNs, a preoperative liver tissue biopsy is beneficial for a definitive diagnosis. Surgery demonstrates excellent therapeutic efficacy and is considered the preferred curative treatment approach. This paper presents clinical experiences with SPN-related hepatic metastases at the Affiliated Hospital of Jilin University, which can be used to guide patient counseling in clinical practice.

Abstract Background The current guidelines for managing screen‐detected pulmonary nodules offer rule‐based recommendations for immediate diagnostic work‐up or follow‐up at intervals of 3, 6, or 12 months. Customized visit plans are lacking. Purpose To develop individualized screening schedules using reinforcement learning (RL) and evaluate the effectiveness of RL‐based policy models. Methods Using a nested case–control design, we retrospectively identified 308 patients with cancer who had positive screening results in at least two screening rounds in the National Lung Screening Trial. We established a control group that included cancer‐free patients with nodules, matched (1:1) according to the year of cancer diagnosis. By generating 10,164 sequence decision episodes, we trained RL‐based policy models, incorporating nodule diameter alone, combined with nodule appearance (attenuation and margin) and/or patient information (age, sex, smoking status, pack‐years, and family history). We calculated rates of misdiagnosis, missed diagnosis, and delayed diagnosis, and compared the performance of RL‐based policy models with rule‐based follow‐up protocols (National Comprehensive Cancer Network guideline; China Guideline for the Screening and Early Detection of Lung Cancer). Results We identified significant interactions between certain variables (e.g., nodule shape and patient smoking pack‐years, beyond those considered in guideline protocols) and the selection of follow‐up testing intervals, thereby impacting the quality of the decision sequence. In validation, one RL‐based policy model achieved rates of 12.3% for misdiagnosis, 9.7% for missed diagnosis, and 11.7% for delayed diagnosis. Compared with the two rule‐based protocols, the three best‐performing RL‐based policy models consistently demonstrated optimal performance for specific patient subgroups based on disease characteristics (benign or malignant), nodule phenotypes (size, shape, and attenuation), and individual attributes. Conclusions This study highlights the potential of using an RL‐based approach that is both clinically interpretable and performance‐robust to develop personalized lung cancer screening schedules. Our findings present opportunities for enhancing the current cancer screening system.

Inspecting sewage outfall into rivers is significant to the precise management of the ecological environment because they are the last gate for pollutants to enter the river. Unmanned Aerial Vehicles (UAVs) have the characteristics of maneuverability and high-resolution images and have been used as an important means to inspect sewage outfalls. UAVs are widely used in daily sewage outfall inspections, but relying on manual interpretation lacks the corresponding low-altitude sewage outfall images dataset. Meanwhile, because of the sparse spatial distribution of sewage outfalls, problems like less labeled sample data, complex background types, and weak objects are also prominent. In order to promote the inspection of sewage outfalls, this paper proposes a low-attitude sewage outfall object detection dataset, namely UAV-SOD, and an attention-guided feature enhancement network, namely AFENet. The UAV-SOD dataset features high resolution, complex backgrounds, and diverse objects. Some of the outfall objects are limited by multi-scale, single-colored, and weak feature responses, leading to low detection accuracy. To localize these objects effectively, AFENet first uses the global context block (GCB) to jointly explore valuable global and local information, and then the region of interest (RoI) attention module (RAM) is used to explore the relationships between RoI features. Experimental results show that the proposed method improves detection performance on the proposed UAV-SOD dataset than representative state-of-the-art two-stage object detection methods.

Background: High mobility group box 2 (HMGB2) is considered as a biomarker of poor prognosis in various cancers.This study aims to investigate the effect and mechanism of HMGB2 in gliomas. Methods: With the glioma related on-line and our local hospital databases, the expression differences of HMGB2,Kaplan-Meier survival analysis and COX regression analysis were performed.The correlation analysis between the clinicopathological features and imaging parameters with the HMGB2 expression had been done. Then GSEA and PPI networks were carried out to find out the most significant pathway. The pathway inhibitor was applied to verify HMGB2’s participation. CCK8,EDU assays,γ-H2AX immunofluorescence staining and colony formation assay were conducted to observe effects on glioma cells. Results: Available datasets showed that HMGB2 was highly expressed in glioma and patients with high expression of HMGB2 had poorer prognosis and molecular characteristics. Protein level evidence of western blot and immunohistochemistry from our center supported the conclusions above. Analysis on imaging features suggested that HMGB2 expression level had an inverse association with ADCmean but positively with the thickness of enhancing margin. Results from GSEA and PPI network analysis exhibited that HMGB2 was involved in base excision repair (BER) signaling pathway. Experimental evidence demonstrated that the overexpression of HMGB2 promoted the proliferation of glioma cells and enhanced the radio-resistance. Conclusions: HMGB2 could promote glioma development and enhance the radioresistance of glioma cells, potentially related to the BER pathway, suggesting it may serve as an underlying biomarker for patients with glioma.

Purposes The Hutuo Group belongs to the Early Proterozoic strata. As one of the most typical Paleoproterozoic strata in North China, the timing redefinition of the Hutuo Group is of great significance to the establishment of the early Precambrian stratigraphic chronology framework, the discussion of the early Precambrian geological evolution process in North China and the study of plate assembly. Methods This article conducts a detailed study of the Dongye Subgroup strata of the Hutuo Group, collecting 24 detrital zircon samples from the Jian'ancun Formation of the Hutuo Group. From 23 similar age detrital zircons, we define the weighted average age of the bottom boundary of the Hutuo Group is 2 469 Ma, and regional tectonic movements occurred in the Wutai area around 1 855 Ma. According to the 1 109 zircon ages in Hutuo Group from previous studies, we considered that the ages of >2.5 Ga are from underlying Gaofan subgroup and the maximum depositional age of Hutuo Group was early Paleoproterozoic. Findings The results show that the crust of the Wutai area was unstable at 2 376, 2 170, 2 066, 1 988, and 1 825 Ma, resulting in multiple magmatic events. The 1 825 Ma zircon age can further indicate the occurrence of the Lyuliang movement, and provide a basis for the early Proterozoic North China Craton integration.

Abstract Background Pectus excavatum, the most common chest wall deformity, is frequently treated with Nuss procedure. Here we will describe non-invasive procedure and analyze the variables associated vacuum bell therapy for patients with pectus excavatum. Methods Retrospective case–control study in a single center between July 2018 and February 2022, including patients with pectus excavatum treated with vacuum bell. Follow-up was continued to September 2022. The Haller index and Correction index was calculated before and after treatment to analysis the effectiveness of vacuum bell therapy. Results There were 98 patients enrolled in the treatment group, with 72 available for analysis, and the follow-up period ranged from 1.1 to 4.4 years (mean 3.3 years). When analyzing with the Haller Index, 18 patients (25.0%) showed excellent correction, 13 patients (18.1%) achieved good correction, and 4 patients (5.6%) had fair correction. The remaining patients had a poor outcome. Characteristics predicting a non-poor prognosis included initial age ≤ 11 years (OR = 3.94, p = 0.013) and patients with use over 24 consecutive months (OR = 3.95, p = 0.013). A total of 9 patients (12.5%) achieved a CI reduction below 10. Patients who started vacuum bell therapy at age > 11 had significantly less change compared to those who started at age ≤ 11 (P

Abstract Despite the critical role of academic English writing proficiency in higher education, existing research has inadequately addressed the comparative impact of teacher-led and student-involved assessments on writing outcomes. To address the research gap, this study aimed to evaluate the effectiveness of 'Teacher-Only Assessment' compared to 'Combined Teacher and Student Self-Assessment' in English writing at a university in southern Thailand. Additionally, the study examined the viewpoints of students regarding the implementation of these approaches. It utilized a sequential explanatory research design in conjunction with a quasi-experimental design. The research instruments included a series of writing tasks, a teacher assessment rubric, a self-assessment form, and a questionnaire with open-ended questions. A group of 62 first-year English majors was divided into two groups: a control group and an experimental group, consisting of 31 students each. Both groups were taking an English Composition I course for 12 weeks and were assigned the same writing tasks. The experimental group was provided with both self-assessments and teacher evaluations, whereas the control group solely received teacher evaluations. The quantitative data was analyzed using an independent sample, while the qualitative data was examined through a thematic analysis. Quantitatively, the independent t-test results indicated that there was no statistically significant distinction in overall writing performance between both groups, except for narrative paragraphs. Moreover, the qualitative findings emphasized the merits of incorporating teacher-led and student-involved assessments. This study suggests various implications for English as a Foreign Language (EFL) instruction and assessment practices.

Abstract Background Avian pathogenic E. coli (APEC) can cause localized or systemic infections, collectively known as avian colibacillosis, resulting in huge economic losses to poultry industry globally per year. In addition, increasing evidence indicates that long non-coding RNAs (lncRNAs) play a critical role in regulating host inflammation in response to bacterial infection. However, the role of lncRNAs in the host response to APEC infection remains unclear. Results Here, we found 816 differentially expressed (DE) lncRNAs and 1,798 DE mRNAs in APEC infected chicken macrophages by RNAseq. The identified DE lncRNA-mRNAs were involved in Toll like receptor signaling pathway, VEGF signaling pathway, fatty acid metabolism, phosphatidylinositol signaling system, and other types of O-glycan biosynthesis. Furthermore, we found the novel lncRNA TCONS_00007391 as an important immune regulator in APEC infection was able to regulate the inflammatory response by directly targeting CD86. Conclusion These findings provided a better understanding of host response to APEC infection and also offered the potential drug targets for therapy development against APEC infection.

Abstract Background Though (1S, 3R)-RSL3 has been used widely in basic research as a small molecular inducer of ferroptosis, the toxicity on normal cells and poor pharmacokinetic properties of RSL3 limited its clinical application. Here, we investigated the synergism of non-thermal plasma (NTP) and low-concentration RSL3 and attempted to rise the sensitivity of NSCLC cells on RSL3. Methods CCK-8 assay was employed to detect the change of cell viability. Microscopy and flowcytometry were applied to identify lipid peroxidation, cell death and reactive oxygen species (ROS) level respectively. The molecular mechanism was inspected with western blot and RT-qPCR. A xenograft mice model was adopted to investigate the effect of NTP and RSL3. Results We found the synergism of NTP and low-concentration RSL3 triggered severe mitochondria damage, more cell death and rapid ferroptosis occurrence in vitro and in vivo. NTP and RSL3 synergistically induced xCT lysosomal degradation through ROS/AMPK/mTOR signaling. Furthermore, we revealed mitochondrial ROS was the main executor for ferroptosis induced by the combined treatment. Conclusion Our research shows NTP treatment promoted the toxic effect of RSL3 by inducing more ferroptosis rapidly and provided possibility of RSL3 clinical application. Graphical Abstract Video Abstract

As renewable energy continues to grow, more inverter-based distributed generators are being integrated into power grids, in which virtual synchronous generator (VSG) is widely adopted to regulate system voltage and stabilize frequency. However, grid voltage imbalances can cause serious oscillations in active power and system frequency, thus severely limiting the effectiveness of VSGs. Consequently, this study proposes an adaptive control strategy to enhance the dynamic performance of VSG under an imbalanced grid voltage. Compared to conventional VSG control methods, the proposed approach enables dynamic adjustment of the inertia and damping coefficients based on the output angular frequency oscillations, so as to shorten the settling time and reduce active power overshoot. The error-driven adaptive mechanism forms a closed-loop control, which effectively keeps the system stable regardless of parameter variations. Additionally, it combines with balanced output current (BOC), constant active power (CAP), and constant reactive power (CRP) control modes to further improve effectiveness. Finally, verifications have been conducted in the MATLAB/SIMULINK and hardware-in-the-loop (HIL) environment to demonstrate the superiority and feasibility of the proposed method.

Feature representation is a crucial issue in multimodal image registration. The handcrafted features extracted by traditional methods are highly sensitive to nonlinear radiation differences, while supervised learning methods are limited by deficient labeled samples in the remote sensing field. Therefore, this article proposes a consistency feature representation learning method for multimodal image registration, which involves mapping data into a common feature space to realize the accurate alignment of remote sensing images. First, a contrastive network with a spatial attention mechanism is driven to enhance the capability to highlight high-level features of images. Second, a positive sample augmentation strategy is implemented with contrastive loss, which helps the model learn the inherent features better, and imposes constraints on the sample similarity to optimize the feature projection. Finally, a multimodal image registration framework is proposed to enhance the stability of feature matching. The proposed framework achieves accurate feature extraction and consistency feature description for multimodal images, ensuring robustness against nonlinear radiometric differences. Experimental results demonstrate that the proposed method obtains more reliable registration results on the SEN1-2 dataset. Furthermore, the proposed algorithm achieves superior performance on data from other modalities, indicating strong generalization ability.

Geological remote sensing interpretation plays a pivotal role in the field of regional geological mapping, encompassing the analysis of rock, soil, and water features. However, these geological elements can be obscured by the surrounding geographical environment and can undergo modifications caused by geological activities. The former hinders the effectiveness of satellite remote sensing data, resulting in the invisibility of element features, while the latter leads to the complex distribution of element features and significant spatial variations of geological elements. Consequently, existing deep learning-based models for interpreting geological elements often exhibit limited accuracy. To address these issues, this study proposes the contextually enhanced multiscale feature fusion network for the efficient interpretation of geological elements. First, the context enhancement module is employed to extract abundant feature information and reinforce contextual features, aiming to capture essential features and strengthen their interconnections. Second, the multiscale feature fusion module incorporates the SimAM attention mechanism to adaptively learn features from different channels, emphasizing the feature information that contributes to interpretation results and maximizing the comprehensive and crucial feature information for each element. Extensive experiments demonstrate the superior performance of both the context enhancement module and the multiscale feature fusion module compared to several representative deep learning networks in terms of overall interpretation accuracy on two datasets. The model demonstrated improvements in oPA and mIoU of 2.4% and 2.8%, respectively, on the Landsat 8 dataset, and 3.5% and 3.2%, respectively, on the Sentinel-2 dataset.

This study aims addresses the challenge of gesture recognition in smart sports stadiums through the fusion enhancement of YOLOv5 and Copula Bayesian Classifier algorithm. By leveraging FasterNet for YOLOv5 transformation, integrating the Convolutional Block Attention Module (CBAM) as an attention mechanism, and merging it with the Copula Bayesian Classifier, we propose a tandem model for robust gesture recognition in the complex environments of sports venues. Extensive training on a substantial dataset yields an efficient and accurate gesture recognition model. Our findings showcase the effectiveness of the proposed algorithm, achieving a remarkable accuracy rate of 99.2% in identifying gesture categories swiftly. This advancement holds significant implications for future human-computer interaction in smart sports stadiums, offering a more seamless and intelligent mode of interaction for both spectators and athletes. Ultimately, it enhances user experience and management efficiency within smart sports venues.

Few-shot image classification remains a persistent challenge due to the intrinsic difficulty faced by visual recognition models in achieving generalization with limited training data. Existing methods primarily focus on exploiting marginal distributions and overlook the disparity between the product of marginals and the joint characteristic functions. This can lead to less robust feature representations. In this paper, we introduce DBDC-SSL, a method that aims to improve few-shot visual recognition models by learning a feature extractor that produces image representations that are more robust. To improve the robustness of the model, we integrate DeepBDC (DBDC) during the training process to learn better feature embeddings by effectively computing the disparity between product of the marginals and joint characteristic functions of the features. To reduce overfitting and improve the generalization of the model, we utilize an auxiliary rotation loss for self-supervised learning (SSL) in the training of the feature extractor. The auxiliary rotation loss is derived from a pretext task, where input images undergo rotation by predefined angles, and the model classifies the rotation angle based on the features it generates. Experimental results demonstrate that DBDC-SSL is able to outperform current state-of-the-art methods on 4 common few-shot image classification benchmark, which are miniImageNet, tieredImageNet, CUB and CIFAR-FS. For 5-way 1-shot and 5-way 5-shot tasks respectively, the proposed DBDC-SSL achieved the accuracy of 68.64±0.43 and 86.02±0.28 on miniImageNet, 73.88±0.48 and 89.03±0.29 on tieredImageNet, 84.67±0.39 and 94.76±0.16 on CUB, and 75.60±0.44 and 88.49±0.31 on CIFAR-FS.

Few-shot learning continues to pose a challenge as it is inherently difficult for visual recognition models to generalize with limited labeled examples. When the training data is limited, the process of training and fine-tuning the model will be unstable and inefficient due to overfitting. In this paper, we introduce NegCosIC: Negative Cosine Similarity-Invariance-Covariance Regularization, a method that aims to improve the mean accuracy from the perspective of stabilizing the fine-tuning process and regularizing variance. NegCosIC incorporates a negative simple cosine similarity loss to stabilize the parameters of the feature extractor during fine-tuning. In addition, NegCosIC integrates invariance loss and covariance loss to regularize the embeddings in order to reduce overfitting. Experimental results demonstrate that NegCosIC is able to bring substantial improvements over the current state-of-the-art methods. An in-depth worse case analysis is also conducted and shows that NegCosIC is able to outperform state-of-the-art methods on worst case accuracy. The proposed NegCosIC achieved 2.15% and 2.13% higher accuracy on miniImageNet 1-shot and 5-shot tasks, 3.22% and 2.67% higher accuracy on CUB 1-shot and 5-shot tasks, and 2.13% and 7.74% higher accuracy on CIFAR-FS 1-shot and 5-shot tasks in terms of worst-case accuracies.

Condition monitoring of wind turbines is critical for increasing the reliability of the turbines and reducing their operation and maintenance costs. Supervisory control and data acquisition (SCADA) systems have been widely regarded as a promising technique to monitor the health status of turbines due to their abundance and cost-effective operation data. However, SCADA data are fundamentally multivariate time series with inherent spatio-temporal correlations. Therefore, it is still difficult to extract such correlations and then accurately identify the health status. This paper proposes a novel multi-view spatio-temporal feature fusion approach (MVSTCNN) based on convolutional neural networks (CNN) for condition monitoring of wind turbines. Specifically, multiple CNN modules with convolutional kernels of varying sizes are designed to extract correlations among several sensor variables and the temporal dependency concealed in each variable in parallel. A main advantage of the proposed method is its capacity to capture multiscale local information and global information simultaneously in both temporal and spatial dimensions, which improves the performance of condition monitoring. Real SCADA data from a wind farm is utilized to evaluate the effectiveness and superiority of the proposed approach. The SCADA data experiments demonstrate that the proposed approach is effective for early fault detection in wind turbines.

Abstract Background Clustering is a fundamental problem in statistics and has broad applications in various areas. Traditional clustering methods treat features equally and ignore the potential structure brought by the characteristic difference of features. Especially in cancer diagnosis and treatment, several types of biological features are collected and analyzed together. Treating these features equally fails to identify the heterogeneity of both data structure and cancer itself, which leads to incompleteness and inefficacy of current anti-cancer therapies. Objectives In this paper, we propose a clustering framework based on hierarchical heterogeneous data with prior pairwise relationships. The proposed clustering method fully characterizes the difference of features and identifies potential hierarchical structure by rough and refined clusters. Results The refined clustering further divides the clusters obtained by the rough clustering into different subtypes. Thus it provides a deeper insight of cancer that can not be detected by existing clustering methods. The proposed method is also flexible with prior information, additional pairwise relationships of samples can be incorporated to help to improve clustering performance. Finally, well-grounded statistical consistency properties of our proposed method are rigorously established, including the accurate estimation of parameters and determination of clustering structures. Conclusions Our proposed method achieves better clustering performance than other methods in simulation studies, and the clustering accuracy increases with prior information incorporated. Meaningful biological findings are obtained in the analysis of lung adenocarcinoma with clinical imaging data and omics data, showing that hierarchical structure produced by rough and refined clustering is necessary and reasonable.

Abstract Background Gastric cancer is characterized by high invasiveness, heterogeneity, and late diagnosis, leading to high incidence and mortality rates. It is a significant public health concern globally. Early prevention is crucial in reducing the occurrence of gastric cancer, and dietary prevention, particularly focusing on carotenoids, has been considered a convenient and effective approach. However, the association between carotenoid intake and gastric cancer incidence remains controversial. Methods A systematic search was conducted in PubMed, Ovid Embase, Web of Science, and Cochrane databases from inception to January 5, 2023. Two reviewers independently screened search results, extracted relevant data, and evaluated study quality. Statistical analysis was performed using the "metan" command in STATA 16 software. Random-effects or fixed-effects models were chosen based on the magnitude of heterogeneity among studies. Results This study included a total of 35 publications, consisting of 23 case–control studies and 12 cohort studies. Meta-analysis of case–control studies showed that alpha-carotene (OR = 0.71, 95% CI: 0.55–0.92), beta-carotene (OR = 0.62, 95% CI: 0.53–0.72), and lutein (OR = 0.82, 95% CI: 0.69–0.97) significantly reduced the risk of gastric cancer, while beta-cryptoxanthin (OR = 0.88, 95% CI: 0.75–1.04) and lycopene (OR = 0.86, 95% CI: 0.73–1.00) showed no significant correlation. Meta-analysis of cohort studies indicated no significant associations between any of the five carotenoids and gastric cancer incidence (alpha-carotene: RR = 0.81, 95% CI: 0.54–1.23; beta-carotene: RR = 0.86, 95% CI: 0.64–1.16; beta-cryptoxanthin: RR = 0.86, 95% CI: 0.64–1.16; lutein: RR = 0.94, 95% CI: 0.69–1.29; lycopene: RR = 0.89, 95% CI: 0.69–1.14). Conclusions The relationship between carotenoids and gastric cancer incidence may vary depending on the type of study conducted. Considering that evidence from cohort studies is generally considered stronger than evidence from case–control studies, and high-quality randomized controlled trials show no significant association between carotenoids and gastric cancer incidence, current evidence does not support the supplementation of carotenoids for gastric cancer prevention. Further targeted research is needed to explore the association between the two.

Abstract Self-efficacy in English language learning is directly correlated with the success of the students in learning English, the models they follow at each level, the encouragement and suggestions received by their groups, and the evaluations their teachers provide them. As an innovation for the traditional teaching method, the flipped classroom teaching model can affect the formation of self-efficacy in English language learning from the above four aspects. It has a theoretically positive promotion of self-efficacy. The study employed a quasi-experimental approach and semi-structured interviews to investigate whether the flipped classroom teaching model has a positive impact on self-efficacy in English language learning of the students of Chinese higher vocational colleges. The results showed that flipped classroom had a significant positive impact on students’ self-efficacy in English language learning.

The emergence of various high bandwidth services has led to increasing demands for data transmission speed. Nowadays, a single network can no longer meet the diverse business needs of customers at any time. Therefore, utilizing wireless networks to achieve multi-path parallel transmission is an important approach. A multi-path parallel transmission control method is proposed to avoid the congestion and chaos of the receiver, so as to improve the transmission efficiency. Reinforcement learning is used to intelligently select the size and redundancy of code packets to overcome data packets chaos. Meanwhile, considering that network transmission services may become paralyzed after congestion occurs, this study also proposes a Q-learning-based congestion control algorithm. These results indicate that the network resource optimization algorithm proposed by this research can dynamically adjust the length of packets and redundant packets within packets based on network conditions, making it suitable for various network situations. The adaptive linear network coding method is usedtoget a larger buffer space faster, which takes 8 seconds. The congestion control algorithm proposed by the research can maintain a bandwidth utilization rate of nearly 99% while maintaining a high transmission rate. This shows that the proposed linear network coding transmission method can effectively improve the problem of packet disorder in multi-user information fusion and improve the efficiency of multi-user information fusion. A new network congestion control method proposed by the research can ensure the rapid recovery of the network after congestion while ensuring the transmission quality of the network.

Abstract The gas therapy is drawing increasing attention in the treatment of many diseases including cancer. As one of gas signaling molecules, carbon monoxide (CO) has been proved to exert anti-cancer effects via triggering multiple cell death types, such as autophagy, apoptosis and necrosis. Here, we showed that low concentration CO delivered from CO-releasing molecule 3 (CORM-3) effectively induced ferroptosis, known as a novel proinflammatory programmed cell death, in vitro and in vivo. Mechanistically, we found that CO triggered ferroptosis by modulating the ROS/GSK3β/GPX4 signaling pathway, resulting in the accumulation of lipid hydroperoxides and the occurrence of ferroptosis. We think our findings provide novel insights into the anti-cancer mechanisms of CO, and suggest that CO could potentially be exploited as a novel ferroptosis inducer for cancer treatment in the future.

ObjectivesAs the core system of an unmanned surface vehicle, the autonomous control system (ACS) is responsible for coordinating other systems to achieve combat missions, which is the key to unmanned surface ship technology. MethodsFirst, based on the physiological structure and cognitive mechanism of the nervous system, this paper proposes six bionic revelations for the ACS. Furthermore, based on such revelations, a system architecture and its typical ACS case are proposed as the biomimetic of the central and peripheral nervous system. Finally, a design scheme for the ACS architecture that composed of eight functional modules with service-oriented architecture is obtained which draws upon the information processing of the human brain. ResultsThe bionic physical architecture and functional architecture is achieved. ConclusionsThis study can provide useful references for the overall construction, system design and equipment development of the ACS for medium to large unmanned surface ships.