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Abstract Background Colorectal cancer, a prevalent malignancy worldwide, poses a significant challenge due to the lack of effective prognostic tools. In this study, we aimed to develop a functional gene signature to stratify colorectal cancer patients into different groups with distinct characteristics, which will greatly facilitate disease prediction. Results Patients were stratified into high- and low-risk groups using a prediction model built based on the functional gene signature. This innovative approach not only predicts clinicopathological features but also reveals tumor immune microenvironment types and responses to immunotherapy. The study reveals that patients in the high-risk group exhibit poorer pathological features, including invasion depth, lymph node metastasis, and distant metastasis, as well as unfavorable survival outcomes in terms of overall survival and disease-free survival. The underlying mechanisms for these observations are attributed to upregulated tumor-related signaling pathways, increased infiltration of pro-tumor immune cells, decreased infiltration of anti-tumor immune cells, and a lower tumor mutation burden. Consequently, patients in the high-risk group exhibit a diminished response to immunotherapy. Furthermore, the high-risk group demonstrates enrichment in extracellular matrix-related functions and significant infiltration of cancer-associated fibroblasts (CAFs). Single-cell transcriptional data analysis identifies CAFs as the primary cellular type expressing hub genes, namely ACTA2, TPM2, MYL9, and TAGLN. This finding is further validated through multiple approaches, including multiplex immunohistochemistry (mIHC), polymerase chain reaction (PCR), and western blot analysis. Notably, TPM2 emerges as a potential biomarker for identifying CAFs in colorectal cancer, distinguishing them from both colorectal cancer cell lines and normal colon epithelial cell lines. Co-culture of CAFs and colorectal cancer cells revealed that CAFs could enhance the tumorigenic biofunctions of cancer cells indirectly, which could be partially inhibited by knocking down CAF original TPM2 expression. Conclusions This study introduces a functional gene signature that effectively and reliably predicts clinicopathological features and the tumor immune microenvironment in colorectal cancer. Moreover, the identification of TPM2 as a potential biomarker for CAFs holds promising implications for future research and clinical applications in the field of colorectal cancer.

Abstract Background Diabetic wounds present significant challenges, specifically in terms of bacterial infection and delayed healing. Therefore, it is crucial to address local bacterial issues and promote accelerated wound healing. In this investigation, we utilized electrospinning to fabricate microgel/nanofiber membranes encapsulating MXene-encapsulated microgels and chitosan/gelatin polymers. Results The film dressing facilitates programmed photothermal therapy (PPT) and mild photothermal therapy (MPTT) under near-infrared (NIR), showcasing swift and extensive antibacterial and biofilm-disrupting capabilities. The PPT effect achieves prompt sterilization within 5 min at 52 °C and disperses mature biofilm within 10 min. Concurrently, by adjusting the NIR power to induce local mild heating (42 °C), the dressing stimulates fibroblast proliferation and migration, significantly enhancing vascularization. Moreover, in vivo experimentation successfully validates the film dressing, underscoring its immense potential in addressing the intricacies of diabetic wounds. Conclusions The MXene microgel-loaded nanofiber dressing employs temperature-coordinated photothermal therapy, effectively amalgamating the advantageous features of high-temperature sterilization and low-temperature promotion of wound healing. It exhibits rapid, broad-spectrum antibacterial and biofilm-disrupting capabilities, exceptional biocompatibility, and noteworthy effects on promoting cell proliferation and vascularization. These results affirm the efficacy of our nanofiber dressing, highlighting its significant potential in addressing the challenge of diabetic wounds struggling to heal due to infection. Graphical Abstract

Abstract Background Primary sclerosing cholangitis (PSC) is a complex disease with pathogenic mechanisms that remain to be elucidated. Previous observational studies with small sample sizes have reported associations between PSC, dyslipidemia, and gut microbiota dysbiosis. However, the causality of these associations is uncertain, and there has been no systematic analysis to date. Methods The datasets comprise data on PSC, 179 lipid species, and 412 gut microbiota species. PSC data (n = 14,890) were sourced from the International PSC Study Group, while the dataset pertaining to plasma lipidomics originated from a study involving 7174 Finnish individuals. Data on gut microbiota species were derived from the Dutch Microbiome Project study, which conducted a genome-wide association study involving 7738 participants. Furthermore, we employed a two-step Mendelian randomization (MR) analysis to quantify the proportion of the effect of gut microbiota-mediated lipidomics on PSC. Results Following a rigorous screening process, our MR analysis revealed a causal relationship between higher levels of gene-predicted Phosphatidylcholine (O-16:1_18:1) (PC O-16:1_18:1) and an increased risk of developing PSC (inverse variance-weighted method, odds ratio (OR) 1.30, 95% confidence interval (CI) 1.03–1.63). There is insufficient evidence to suggest that gene-predicted PSC impacts the levels of PC O-16:1_18:1 (OR 1.01, 95% CI 0.98–1.05). When incorporating gut microbiota data into the analysis, we found that Eubacterium rectale-mediated genetic prediction explains 17.59% of the variance in PC O-16:1_18:1 levels. Conclusion Our study revealed a causal association between PC O-16:1_18:1 levels and PSC, with a minor portion of the effect mediated by Eubacterium rectale. This study aims to further explore the pathogenesis of PSC and identify promising therapeutic targets. For patients with PSC who lack effective treatment options, the results are encouraging.

Abstract Diabetic wounds pose a challenge to healing due to increased bacterial susceptibility and poor vascularization. Effective healing requires simultaneous bacterial and biofilm elimination and angiogenesis stimulation. In this study, we incorporated polyaniline (PANI) and S-Nitrosoglutathione (GSNO) into a polyvinyl alcohol, chitosan, and hydroxypropyltrimethyl ammonium chloride chitosan (PVA/CS/HTCC) matrix, creating a versatile wound dressing membrane through electrospinning. The dressing combines the advantages of photothermal antibacterial therapy and nitric oxide gas therapy, exhibiting enduring and effective bactericidal activity and biofilm disruption against methicillin-sensitive Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, and Escherichia coli. Furthermore, the membrane’s PTT effect and NO release exhibit significant synergistic activation, enabling a nanodetonator-like burst release of NO through NIR irradiation to disintegrate biofilms. Importantly, the nanofiber sustained a uniform release of nitric oxide, thereby catalyzing angiogenesis and advancing cellular migration. Ultimately, the employment of this membrane dressing culminated in the efficacious amelioration of diabetic-infected wounds in Sprague–Dawley rats, achieving wound closure within a concise duration of 14 days. Upon applying NIR irradiation to the PVA-CS-HTCC-PANI-GSNO nanofiber membrane, it swiftly eradicates bacteria and biofilm within 5 min, enhancing its inherent antibacterial and anti-biofilm properties through the powerful synergistic action of PTT and NO therapy. It also promotes angiogenesis, exhibits excellent biocompatibility, and is easy to use, highlighting its potential in treating diabetic wounds. Graphical Abstract

Abstract Background Long noncoding RNAs (lncRNAs) have emerged as key players in tumorigenesis and tumour progression. However, the biological functions and potential mechanisms of lncRNAs in colorectal cancer (CRC) are unclear. Methods The novel lncRNA POU6F2-AS1 was identified through bioinformatics analysis, and its expression in CRC patients was verified via qRT–PCR and FISH. In vitro and in vivo experiments, such as BODIPY staining, Oil Red O staining, triglyceride (TAG) assays, and liquid chromatography mass spectrometry (LC-MS) were subsequently performed with CRC specimens and cells to determine the clinical significance, and functional roles of POU6F2-AS1. Biotinylated RNA pull-down, RIP, Me-RIP, ChIP, and patient-derived organoid (PDO) culture assays were performed to confirm the underlying mechanism of POU6F2-AS1. Results The lncRNA POU6F2-AS1 is markedly upregulated in CRC and associated with adverse clinicopathological features and poor overall survival in CRC patients. Functionally, POU6F2-AS1 promotes the growth and lipogenesis of CRC cells both in vitro and in vivo. Mechanistically, METTL3-induced m6A modification is involved in the upregulation of POU6F2-AS1. Furthermore, upregulated POU6F2-AS1 could tether YBX1 to the FASN promoter to induce transcriptional activation, thus facilitating the growth and lipogenesis of CRC cells. Conclusions Our data revealed that the upregulation of POU6F2-AS1 plays a critical role in CRC fatty acid metabolism and might provide a novel promising biomarker and therapeutic target for CRC.

The failure or delay in healing of critical bone defects is primarily due to early local anoxic conditions and reduced osteogenic activity. In this research, we integrated calcium peroxide (CPO) embedded polycaprolactone (PCL) microspheres and osteoinductive nanoparticles (Hydroxyapatite/Laponite) into a thermosensitive hydrogel (Pluronic F127), thereby formulating an injectable oxygen-releasing osteogenic thermosensitive hydrogel. Notably, the oxygen-releasing microspheres (ORMs) within the composite hydrogel provide stable oxygen release for up to 21 days, ensuring the survival, migration, and bioactivity of both mesenchymal stem cells and endothelial cells under anoxic conditions. Additionally, the composite hydrogel significantly augments the osteogenic potential of bone marrow mesenchymal stem cells by providing a biomimetic microenvironment with the incorporation of nano-hydroxyapatite/laponite. Ultimately, the injectable composite hydrogel successfully stimulated bone regeneration within a cranial defect in a rat model after 8 weeks, with enhanced vascularization and bone quality. The engineered hydrogel provides a minimally invasive approach to stimulate bone regeneration with a sustained oxygen supply and osteogenic microenvironment provision, underlining its potential for treating critical bone defects.

Abstract Peripheral nerve block is performed for precise pain control and lesser side effects after surgery by reducing opioid consumption. Injectable hydrogel delivery systems with high biosafety and moisture content have good clinical application prospects for local anesthetic delivery. However, how to achieve high drug loading and long‐term controlled release of water‐soluble narcotic drugs remains a big challenge. In this study, heterogeneous microspheres and an injectable gel‐matrix composite drug delivery system are designed in two steps. First, heterogeneous hydrogel microspheres loaded with ropivacaine (HMS‐ROP) are prepared using a microfluidic chip and in situ alkalization. An injectable self‐healing hydrogel matrix (Gel) is then prepared from modified carboxymethylcellulose (CMC‐ADH) and oxidized hyaluronic acid (OHA). A local anesthetic delivery system, Gel/HMS‐ROP/dexmedetomidine (DEX), with long‐term retention and drug release in vivo is prepared by combining HMS‐ROP and Gel/DEX. The drug loading of HMS‐ROP reached 41.1%, with a drug release time of over 160 h in vitro, and sensory and motor blockade times in vivo of 48 and 36 h, respectively. In summary, the sequential release and synergistic analgesic effects of the two anesthetics are realized using core‐shell microspheres, DEX, and an injectable gel, providing a promising strategy for long‐acting postoperative pain management.

Abstract Epidermal electronics that can monitor physiological signals such as surface electromyogram (sEMG) signals attract widespread attentions in personalized healthcare, human–machine interfaces (HMI) and virtual/augmented reality (AR/VR). However, conventional electromyographic electrodes suffer from skin discomfort, susceptibility to motion artifact interference, and short service lifetime. Here, an organohydrogel‐based sEMG electrode endows with high conductivity, low modulus and long‐term stability is developed by doping partially reduced graphene oxide (pRGO) into highly cross‐linked organohydrogel network. The as‐fabricated polyacrylamide/sodium alginate/tannic acid/partially reduced graphene oxide (PAM/SA/TA/pRGO) organohydrogel possesses farewell conductivity (4.22 S m−1) while preserving tissue‐like compliance (Young's modulus ≈32 KPa), excellent stretchability (≈600%), high adhesion as well as superior anti‐drying properties. In addition, a stretchable sEMG electrode for long‐term reliable service is fabricated via immobilizing the organohydrogel electrodes onto a flexible very high bond (VHB) substrate. As a result, the integrated electrodes show high signal‐to‐noise ratio (SNR) (35.15 db) comparable to that of the commercial electrodes. Furthermore, with assistance of deep learning, the proposed sEMG electrodes obtain high identification accuracy of 97.11% in distinguishing sophisticated gestures. This system can be further exploited for real‐time tele‐operations and offers broad prospects in human–machine immersive interactive application.

Abstract China has implemented a series of ecological engineering projects to help achieve the 2060 carbon neutrality target. However, the lack of quantitative research on ecological engineering and the contribution of climate change to terrestrial carbon sinks limits this goal. This study uses robust statistical models combined with multiple terrestrial biosphere models to quantify the impact of China's ecological engineering on terrestrial ecosystem carbon sink trends and their differences according to the difference between reality and nonpractice assumptions. The main conclusions include the following: (1) since 1901, 84% of terrestrial ecosystem carbon sinks in China have shown an increasing trend, and approximately 45% of regional carbon sinks have increased by more than 0.1 g C/m2 every 10 years. (2) Considering the impact of human activities and the implementation of ecological engineering in China, approximately 56% of carbon sinks have improved, and approximately 10% of the regions whose carbon sink growth exceeds 50 g C m−2 yr−1 are mainly in the southeast coastal of China. (3) The carbon sequestration potential and effect of the Sanjiangyuan ecological protection and construction project are better than others, at 1.26 g C m−2 yr−1 and 14.13%, respectively. The Beijing–Tianjin sandstorm source comprehensive control project helps alleviate the reduction in carbon sinks, while the southwest karst rocky desertification comprehensive control project may aggravate the reduction in carbon sinks. This study clarifies the potential of China's different ecological engineering to increase carbon sink potential, and distinguishes and quantifies the contribution of climate and human activity factors to it, which is of great significance to the system management optimization scheme of terrestrial ecosystems and can effectively serve the national carbon neutral strategy. Graphical Abstract

Abstract Recent technological breakthroughs in single-particle cryo-electron microscopy (cryo-EM) enable rapid atomic structure determination of biological macromolecules. A major bottleneck in the current single particle cryo-EM pipeline is the preparation of good quality frozen cryo-EM grids, which is mostly a trial-and-error process. Among many issues, preferred particle orientation and sample damage by air–water interface (AWI) are common practical problems. Here we report a method of applying metallo-supramolecular branched polymer (MSBP) in the cryo-sample preparation for high-resolution single-particle cryo-EM. Our data shows that MSBP keeps a majority of particles away from air–water interface and mitigates preferred orientation as verified by the analyses of apoferritin, hemagglutinin) trimer and various sample proteins. The use of MSBP is a simple method to improve particle distribution for high-resolution structure determination in single-particle cryo-EM.

Abstract Acute lung injury (ALI) as well as its more severe form, acute respiratory distress syndrome (ARDS), frequently leads to an uncontrolled inflammatory response. N6-methyladenosine (m6A) modification was associated with the progression of several inflammatory diseases. However, the role of methyltransferase-like 14 (METTL14)-mediated m6A methylation in ALI/ARDS remains unclear. Here, we reported an increase in overall expression levels of m6A and METTL14 in circulating monocyte-derived macrophages recruited to the lung following ALI, which is correlated with the severity of lung injury. We further demonstrated the critical function of METTL14 in activating NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome in vitro and in mouse models of ALI/ARDS, and validated NLRP3 as the downstream target of METTL14 by the m6A RNA immunoprecipitation (MeRIP) and RIP assays. Mechanistically, METTL14-methylated NLRP3 transcripts were subsequently recognized by insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), an m6A reader, which stabilized NLRP3 mRNA. Furthermore, we observed that IGF2BP2 knockdown diminished LPS-induced ALI in mice by downregulating NLRP3 expression. In summation, our study revealed that the molecular mechanism underlying the pathogenesis of ALI/ARDS involves METTL14-mediated activation of NLRP3 inflammasome in an IGF2BP2 dependent manner, thereby demonstrating the potential of METTL14 and IGF2BP2 as promising biomarkers and therapeutic targets for ALI/ARDS treatment.

Abstract Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128 × 128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows ~22.6×/~14.1× increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes.

ObjectiveThe objective of this study was to provide a multi-modal deep learning framework for forecasting the survival of rectal cancer patients by utilizing both digital pathological images data and non-imaging clinical data.Materials and methodsThe research included patients diagnosed with rectal cancer by pathological confirmation from January 2015 to December 2016. Patients were allocated to training and testing sets in a randomized manner, with a ratio of 4:1. The tissue microarrays (TMAs) and clinical indicators were obtained. Subsequently, we selected distinct deep learning models to individually forecast patient survival. We conducted a scanning procedure on the TMAs in order to transform them into digital pathology pictures. Additionally, we performed pre-processing on the clinical data of the patients. Subsequently, we selected distinct deep learning algorithms to conduct survival prediction analysis using patients’ pathological images and clinical data, respectively.ResultsA total of 292 patients with rectal cancer were randomly allocated into two groups: a training set consisting of 234 cases, and a testing set consisting of 58 instances. Initially, we make direct predictions about the survival status by using pre-processed Hematoxylin and Eosin (H&E) pathological images of rectal cancer. We utilized the ResNest model to extract data from histopathological images of patients, resulting in a survival status prediction with an AUC (Area Under the Curve) of 0.797. Furthermore, we employ a multi-head attention fusion (MHAF) model to combine image features and clinical features in order to accurately forecast the survival rate of rectal cancer patients. The findings of our experiment show that the multi-modal structure works better than directly predicting from histopathological images. It achieves an AUC of 0.837 in predicting overall survival (OS).ConclusionsOur study highlights the potential of multi-modal deep learning models in predicting survival status from histopathological images and clinical information, thus offering valuable insights for clinical applications.

Abstract Background The Qinghai-Tibet Plateau is the “sensitive area” of climate change, and also the “driver” and “amplifier” of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale. Results Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30–70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source). Conclusions The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community’s understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve “carbon neutrality” by 2060.

Forest age is one of most important biological factors that determines the magnitude of vegetation carbon sequestration. A spatially explicit forest age dataset is crucial for forest carbon dynamics modeling at the regional scale. However, owing to the high spatial heterogeneity in forest age, accurate high-resolution forest age data are still lacking, which causes uncertainty in carbon sink potential prediction. In this study, we obtained a 1 km resolution forest map based on the fusion of multiscale age information, i.e., the ninth (2014–2018) forest inventory statistics of China, with high accuracy at the province scale, and a field-observed dataset covering 6779 sites, with high accuracy at the site scale. Specifically, we first constructed a random forest (RF) model based on field-observed data. Utilizing this model, we then generated a spatially explicit forest age map with a 1 km resolution (random forest age map, RF map) using remotely sensed data such as tree height, elevation, meteorology, and forest distribution. This was then used as the basis for downscaling the provincial-scale forest inventory statistics of the forest ages and retrieving constrained maps of forest age (forest inventory constrained age maps, FIC map), which exhibit high statistical accuracy at both the province scale and site scale. The main results included the following: (1) RF can be used to estimate the site-scale forest age accurately (R2 = 0.89) and has the potential to predict the spatial pattern of forest age. However, (2) owing to the impacts of sampling error (e.g., field-observed sites are usually located in areas exhibiting relatively favorable environmental conditions) and the spatial mismatch among different datasets, the regional-scale forest age predicted by the RF model could be overestimated by 71.6%. (3) The results of the downscaling of the inventory statistics indicate that the average age of forests in China is 35.1 years (standard deviation of 21.9 years), with high spatial heterogeneity. Specifically, forests are older in mountainous and hilly areas, such as northeast, southwest, and northwest China, than in southern China. The spatially explicit dataset of the forest age retrieved in this study encompasses synthesized multiscale forest age information and is valuable for the research community in assessing the carbon sink potential and modeling carbon dynamics.

Differential privacy, a cornerstone of privacy-preserving techniques, plays an indispensable role in ensuring the secure handling and sharing of sensitive data analysis across domains such as in census, healthcare, and social networks. Histograms, serving as a visually compelling tool for presenting analytical outcomes, are widely employed in these sectors. Currently, numerous algorithms for publishing histograms under differential privacy have been developed, striving to balance privacy protection with the provision of useful data. Nonetheless, the pivotal challenge concerning the effective enhancement of precision for small bins (those intervals that are narrowly defined or contain a relatively small number of data points) within histograms has yet to receive adequate attention and in-depth investigation from experts. In standard DP histogram publishing, adding noise without regard for bin size can result in small data bins being disproportionately influenced by noise, potentially severely impairing the overall accuracy of the histogram. In response to this challenge, this paper introduces the SReB_GCA sanitization algorithm designed to enhance the accuracy of small bins in DP histograms. The SReB_GCA approach involves sorting the bins from smallest to largest and applying a greedy grouping strategy, with a predefined lower bound on the mean relative error required for a bin to be included in a group. Our theoretical analysis reveals that sorting bins in ascending order prior to grouping effectively prioritizes the accuracy of smaller bins. SReB_GCA ensures strict ϵ-DP compliance and strikes a careful balance between reconstruction error and noise error, thereby not only initially improving the accuracy of small bins but also approximately optimizing the mean relative error of the entire histogram. To validate the efficiency of our proposed SReB_GCA method, we conducted extensive experiments using four diverse datasets, including two real-life datasets and two synthetic ones. The experimental results, quantified by the Kullback–Leibler Divergence (KLD), show that the SReB_GCA algorithm achieves substantial performance enhancement compared to the baseline method (DP_BASE) and several other established approaches for differential privacy histogram publication.

Microbial contamination has profoundly impacted human health, and the effective eradication of widespread microbial issues is essential for addressing serious hygiene concerns. Taking polystyrene (PS) membrane as an example, we herein developed report a robust strategy for the in situ preparation of chlorine-regenerable antimicrobial polymer molecular sieve membranes through combining post-crosslinking and nucleophilic substitution reaction. The cross-linking PS membranes underwent a reaction with 5,5-dimethylhydantoin (DMH), leading to the formation of polymeric N-halamine precursors (PS-DMH). These hydantoinyl groups within PS-DMH were then efficiently converted into biocidal N-halamine structures (PS-DMH-Cl) via a simple chlorination process. ATR-FTIR and XPS spectra were recorded to confirm the chemical composition of the as-prepared PS-DMH-Cl membranes. SEM analyses revealed that the chlorinated PS-DMH-Cl membranes displayed a rough surface with a multitude of humps. The effect of chlorination temperature and time on the oxidative chlorine content in the PS-DMH-Cl membranes was systematically studied. The antimicrobial assays demonstrated that the PS-DMH-Cl membranes could achieve a 6-log inactivation of E. coli and S. aureus within just 4 min of contact time. Additionally, the resulting PS-DMH-Cl membranes exhibited excellent stability and regenerability of the oxidative chlorine content.

Abstract Long noncoding RNAs (lncRNAs) play critical roles in tumorigenesis and tumor metastasis. However, the underlying mechanisms of lncRNAs in colorectal cancer (CRC) need further exploration. By using data from The Cancer Genome Atlas (TCGA) and GEO databases, we identified a novel CRC-related lncRNA, LINC01594, that is significantly upregulated in CRC and associated with poor prognosis. In vitro and in vivo, gain- and loss-of-function experiments demonstrated that LINC01594 promotes metastasis in CRC. LINC01594 functions as a DNMT1 scaffold, increasing the level of CELF6 promoter methylation. LINC01594 also competitively binds the transcription factor p53, decreasing CELF6 expression. This inhibited the exon skipping of CD44 V4–V7 induced by CELF6. In summary, this study highlights a novel CRC biomarker and therapeutic target, LINC01594, and the findings suggest that the LINC01594-CELF6-CD44 axis might serve as a biomarker and therapeutic target in CRC.

BackgroundChronic obstructive pulmonary disease (COPD) has become one of the most significant chronic diseases in China. According to conventional wisdom, smoking is the pathogenic factor. However, current research indicates that the pathophysiology of COPD may be associated with prior respiratory system events (e.g., childhood hospitalization for pneumonia, chronic bronchitis) and environmental exposure (e.g., dust from workplace, indoor combustion particles). Dyspnea, persistent wheezing, and other respiratory symptoms further point to the need for pulmonary function tests in this population. Reducing the burden of chronic diseases in China requires a thorough understanding of the various factors that influence the occurrence of COPD.MethodsUsing a cohort from the natural population, this study used nested case-control analysis. We carried out a number of researches, including questionnaire surveys and pulmonary function testing, in the Northwest and Southeast cohorts of China between 2014 and 2021. After removing any variations in the baseline data between patients and control subjects using propensity score matching analysis, the risk factors were examined using univariate or multivariate regression.ResultIt was discovered that prior history of chronic bronchitis, long-term wheezing symptoms, and environmental exposure—including smoking and biofuel combustion—were risk factors for COPD. Dyspnea, symptoms of mobility limitation, organic matter, and a history of hospitalization for pneumonia at an early age were not significant in the clinical model but their incidence in COPD group is higher than that in healthy population.DiscussionCOPD screening effectiveness can be increased by looking for individuals with chronic respiratory symptoms. Smokers should give up as soon as they can, and families that have been exposed to biofuels for a long time should convert to clean energy or upgrade their ventilation. Individuals who have previously been diagnosed with emphysema and chronic bronchitis ought to be extra mindful of the prevention or advancement of COPD.

Abstract Introduction As a CGM-derived indicator, ‘time in range’ (TIR) is emerging as a key indicator for accurate assessment of glycaemic control. However, there is few report focusing on the correlation of TIR with albumuria and renal fuction. The aim of this work was to investigate whether TIR, as well as nocturnal TIR and hypoglycaemic events is related to the presence and severity of albuminuria and decrease of eGFR in type 2 diabetes. Research design and methods A total of 823 patients were enrolled in this study. All patients received continuous glucose monitoring, TIR indicating the percentage of time that blood glucose was in the range of 3.9–10.0 mmol/L. The Spearman analysis was applied to analyze the relationship between TIR (or nocturnal TIR) and ACR. Logistic regression was used to explore whether TIR (or nocturnal TIR) is an independent risk factor for albuminuria. Results The prevalence of albuminuria decreased with increasing TIR quartiles. Binary logistic regression revealed that TIR as well as nocturnal TIR was obviously related to the presence of albuminuria. Multiple regression analysis found that only nocturnal TIR was obviously related to the severity of albuminuria. In our study, eGFR was significantly associated with the number of hypoglycemic events. Conclusions In T2DM patients, TIR and nocturnal TIR is associated with the presence of albuminuria independent of HbA1c and GV metrics. Nocturnal TIR shows better correlation than TIR. The role of TIR especially nocturnal TIR in the evaluation of diabetes kidney disease should be emphasized.

Abstract Background Mitogen‐activated protein kinase 4 (MAPK4) is an atypical member of the mitogen‐activated protein kinase (MAPK) family. We report here that MAPK4 is overexpressed in glioma. The clinical significance, biological roles and underlying molecular mechanisms through which MAPK4 acts in glioma remain unclear. Methods Analysis of MAPK4 expression and associated survival in glioma patients was performed based on data obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases and confirmed in human glioma tissue by immunohistochemistry. MAPK4 function and pathway enrichment were analyzed through Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO). The viability and migration ability of MAPK4‐silenced glioblastoma multiforme (GBM) cells were evaluated using CCK8 and transwell assays, respectively, and cell cycle and apoptosis analyses were performed using flow cytometry. Immunoblotting was used to analyze the protein level in MAPK4 knockdown glioma cells. We also analyzed the correlation of MAPK4 expression with immune infiltration and immune checkpoints in glioma. Results MAPK4 was overexpressed in IDH wild‐type (wt) and 1p/19q non‐codeletion gliomas. MAPK4 expression predicted poor prognosis of glioma patients. MAPK4 was significantly related to functional states, including stemness, metastasis, cell cycle, differentiation and proliferation, in glioma at single‐cell resolution. MAPK4 silencing inhibited proliferation and migration and induced G1 cell cycle arrest in glioma cells via the AKT/mTOR pathway. In vivo, MAPK4 knockdown markedly suppressed the growth of primary glioma. In addition, MAPK4 expression correlated negatively with the infiltration of plasmacytoid DC cells, CD8+ T cells and T helper cells. Moreover, MAPK4 expression correlated positively with expression of the main immunoinhibitor checkpoint molecules and some chemokines in glioma. Conclusion MAPK4 functions as a prognostic indicator in glioma and promotes the proliferation and migration of GBM cells through the AKT/mTOR pathway. MAPK4 may participate in immune infiltration and the expression of immune checkpoints in the glioma microenvironment.

Abstract Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981–2021), high-resolution (4 km) improved vegetation health index (VHI) dataset integrating climate, vegetation and soil moisture was developed. Based on drought records from the Emergency Event Database, we compared the detection efficiency of the VHI before and after its improvement in the occurrence and scope of observed drought events. The global drought detection efficiency of the improved high-resolution VHI dataset reached values as high as 85%, which is 14% higher than the original VHI dataset. The improved VHI dataset was also more sensitive to mild droughts and more accurate regarding the extent of droughts. This improved dataset can play an important role in long-term drought monitoring but also has the potential to assess the impact of drought on the agricultural, forestry, ecological and environmental sectors.

Summary: Upregulation of FGL1 helps tumors escape from immune surveillance, and therapeutic antibodies targeting FGL1 have potential as another immune checkpoint inhibitor. However, the underlying mechanism of high FGL1 protein level in cancers is not well defined. Here, we report that FBXO38 interacts with and ubiquitylates FGL1 to negatively regulate its stability and to mediate cancer immune response. Depletion of FBXO38 markedly augments FGL1 abundance, not only suppressing CD8+ T cell infiltration and enhancing immune evasion of tumor but also increasing inflammation in mice. Importantly, we observe a negative correlation of FBXO38 with FGL1 and IL-6 in non-small cell lung cancer specimens. FGL1 and IL-6 levels positively correlate with TNM (tumor, lymph node, metastasis) stages, while FBXO38 and the infiltrating CD8+ T cells negatively correlate with TNM stages. Our study identifies a mechanism regulating FGL1 stability and a target to enhance the immunotherapy and suggests that the combination of anti-FGL1 and anti-IL-6 is a potential therapeutic strategy for cancer immunotherapy.

Time-varying effects simulation plays a critical role in computer graphics. Fruit diseases are typical time-varying phenomena. Due to the biological complexity, the existing methods fail to represent the biodiversity and biological law of symptoms. To this end, this paper proposes a biology-aware, physically-based framework that respects biological knowledge for realistic simulation of fruit mildew diseases. The simulated symptoms include skin discoloration, fungus growth, and volume shrinkage. Specifically, we take advantage of both the zero-order kinetic model and reaction–diffusion model to represent the complex fruit skin discoloration related to skin biological characteristics. To reproduce 3D mildew growth, we employ the Poisson-disk sampling technique and propose a template model instancing method. One can flexibly change hyphal template models to characterize the fungal biological diversity. To model the fruit’s biological structure, we fill the fruit mesh interior with particles in a biologically-based arrangement. Based on this structure, we propose a turgor pressure and a Lennard-Jones force-based adaptive mass–spring system to simulate the fruit shrinkage in a biological manner. Experiments verified that the proposed framework can effectively simulate mildew diseases, including gray mold, powdery mildew, and downy mildew. Our results are visually compelling and close to the ground truth. Both quantitative and qualitative experiments validated the proposed method.

The accumulation, transport and distribution of photosynthates within plants not only affect the ratio of shoot-to-root biomass, but also change the distribution pattern of nutrient elements in different organs and tissues. A full understanding of the allocation patterns of biomass and nutrient elements within plants, is helpful to strengthen our understanding of the above- and belowground ecosystem functions. However, at present, we do not know enough about the aboveground–belowground allocation of biomass, carbon (C) and nitrogen (N) contents, and, in particular, the corresponding vertical distribution pattern belowground and its environmental impact. At the community scale, the changes in vegetation community attributes measured in the field can reflect the long-term adaptation and subsequent adaptation strategies of vegetation to the regional environment and environmental changes. In this study, the vertical distribution patterns of community biomass and the carbon and nitrogen contents with soil depth in an alpine grassland on the eastern Qinghai–Tibet Plateau were investigated based on the transect method. Our results show the following: (1) Alpine grasslands can respond to differences in hydrothermal resource availability by changing biomass allocation patterns. In low-temperature and high-humidity environments, aboveground and belowground biomass allocation supports the isometric growth hypothesis. However, in environments with less soil moisture or high temperature and humidity, the aboveground and belowground biomass distributions support the allometric allocation hypothesis. (2) The vertical distribution patterns of the C content, N content and carbon: nitrogen ratio (C:N) within plants are different. From the leaves to the root system, with the increase in root depth, the C content demonstrated a vertical distribution pattern of first decreasing and then increasing, and the N% demonstrated a gradual decreasing distribution pattern, while the C:N ratio demonstrated an exponential increasing distribution pattern. (3) The change rate in C%, N% and C:N related to the soil depth was affected by environmental hydrothermal conditions. C% and C:N ratio changed more rapidly with root depth under low temperature and high humidity. The change rate of N% was mainly affected by temperature and changed more rapidly with root depth at low temperatures. (4) When exploring the relationship between the content of elements within plants, it is necessary to combine both the above- and belowground compartments. There was a nonlinear quadratic relationship between the carbon and nitrogen contents within plants.

The photoactive metal-organic frameworks (MOFs) are good candidates for photocatalysts, but the quick electron-hole pairs recombination has greatly restricted the photocatalytic ability of MOFs. To improve the photoactivity of MOFs, MOFs-based composite materials have been extensively studied. Here, we successfully integrated MoS2 quantum dots (QDs) with UiO-66-NH2 for the first time under hydrothermal conditions. The as-prepared MoS2 QDs/UiO-66-NH2 (MS-U) had good visible light response ability (absorption edge at 445 nm), and charge separation and transfer ability, which lays the foundation for the photocatalytic Cr(VI) reduction. Photocatalytic studies revealed that MoS2 QDs-5/UiO-66-NH2 (MS-U-5) had superior Cr(VI) reduction activity than pure MoS2 QDs and UiO-66-NH2. MS-U-5 could remove 98% Cr(VI) at pH= 2 with visible light irradiation for 20 min, which is the fastest visible light driven Cr(VI) reduction rate among the reported MOFs-based composite photocatalysts without the presence of any cocatalysts or scavengers as far as we know. Importantly, MS-U-5 could be reused at least three times. In the end, the possible electron transfer path and mechanism of Cr(VI) reduction was also investigated.

Abstract Background Microsatellite instability‐high (MSI‐H) subgroup of gastric cancer (GC) is characterized by a high tumor mutational burden, increased lymphocytic infiltration, and enhanced inflammatory cytokines. GC patients with MSI‐H status have a good response to immune checkpoint blockade management. However, heterogeneity within the subtype and the underlying mechanisms of shaping tumor microenvironments remain poorly understood. Methods RNA expression levels and clinical parameters of GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The data were analyzed using single‐sample Gene Set Enrichment Analysis (ssGSEA), univariate Cox regression, multivariate Cox regression, and Least Absolute Shrinkage Selection Operator (LASSO) regression. In addition, multiplex immunohistochemistry (mIHC) was used in our clinical cohort for the tumor microenvironment study. Results By ssGSEA and survival analysis, the EMT signaling pathway was identified as a representative pathway, which can stratify the patients with MSI‐H GC with significant survival predictive power. Then, a novel representative EMT‐related five‐gene signature (namely CALU, PCOLCE2, PLOD2, SGCD, and THBS2) was established from EMT signaling gene set, which sensitivity and specificity were further validated in the independent GEO database (GSE62254) cohort for disease outcome prediction. Based on public single‐cell data and in situ immunohistochemistry, we found that most of these five genes were abundantly expressed in cancer‐associated fibroblasts. Furthermore, patients with high or low risk divided by this five‐gene signature exhibited a strong correlation of the distinct patterns of tumor immune microenvironment. By mIHC staining of sections from 30 patients with MSI‐H status, we showed that the patients with better prognoses had the increased infiltration of CD8+ cells in the primary tumoral tissue. Conclusion Our study developed a simple five‐gene signature for stratifying MSI‐H GC patients with survival predictive power.

Abstract Realizing compact and scalable Ising machines that are compatible with CMOS-process technology is crucial to the effectiveness and practicality of using such hardware platforms for accelerating computationally intractable problems. Besides the need for realizing compact Ising spins, the implementation of the coupling network, which describes the spin interaction, is also a potential bottleneck in the scalability of such platforms. Therefore, in this work, we propose an Ising machine platform that exploits the novel behavior of compact bi-stable CMOS-latches (cross-coupled inverters) as classical Ising spins interacting through highly scalable and CMOS-process compatible ferroelectric-HfO2-based Ferroelectric FETs (FeFETs) which act as coupling elements. We experimentally demonstrate the prototype building blocks of this system, and evaluate the scaling behavior of the system using simulations. Our work not only provides a pathway to realizing CMOS-compatible designs but also to overcoming their scaling challenges.

With the progress of society, the health problems of pets have attracted more and more attention. Recent studies have shown that intestinal microflora and related fecal metabolites play a crucial role in the healthy growth of cats. However, the potential role and related metabolic characteristics of gut microbiota in different age groups of pet cats need to be further clarified. 16S rRNA gene sequencing was used to analyze the intestinal microbial composition of young and old cats. LC-MS metabonomic analysis is used to characterize the changes in the metabolic spectrum in feces. The potential relationship between intestinal microorganisms and metabolites, as well as the differences in different age groups, were studied. The species composition of intestinal microflora in the young group and old group is significantly different, T-test algorithm shows 36 different ASVs and 8 different genuses, while the Wilcoxon algorithm shows 81 different ASVs and 17 different genuses. The metabolomics analysis identified 537 kinds of fecal metabolites, which are rich in differences between young and old cats, and may be potential biomarkers indicating the health of cats. 16S rRNA analysis showed significant differences in fructose and mannose metabolism, while metabonomics KEGG analysis showed significant difference in choline metabolism in cancer. Our study compared the differences between the intestinal microbiome and fecal metabolites in young and old cats. This difference provides a new direction for further exploring the relationship between the composition and metabolism of intestinal microbiota in cats of different age groups. It also provides a reference for cat health research.

Polyglycolic acid (PGA) is an emerging biodegradable plastic material. Together with polylactic acid (PLA), PGA is considered a suitable alternative to conventional plastics and has been widely used in biomedical and food packaging industries. However, degradable plastics continue to face the drawbacks of harsh degradation environment and long degradation time, and may harm the environment and the human body. Therefore, our study focused on assessing the effects of degradable microplastics PGA and PLA on the development and neurobehavior of zebrafish. The results showed that PGA and PLA had little effect on 3–10 hpf embryos. However, developmental stunting was observed in a100 mg/L PGA and PLA-exposed group at 24 hpf. In addition, PGA and PLA exposure decreased the survival and hatching rates, increased wakefulness, and reduced sleep in zebrafish. This indicates that PGA and PLA may affect the circadian behavior of zebrafish by affecting the brain–derived neurotrophic factor (BDNF). Therefore, our results suggest that PGA and PLA exposure induces developmental toxicity, reduces voluntary locomotion, induces of anxiety–like behaviors, and impairs sleep/wake behaviors in zebrafish larvae. This also suggests that the potentially toxic effects of degradable plastics cannot be ignored and that the biological effects of PGA require further research.

Surfactants are widely used in the synthesis of nanoparticles, as they have a remarkable ability to direct their growth to obtain well-defined shapes and sizes. However, their post-synthesis removal is a challenge, and the methods used often result in morphological changes that defeat the purpose of the initial controlled growth. Moreover, after the removal of surfactants, the highly active surfaces of nanomaterials may undergo structural reconstruction by exposure to a different environment. Thus, ex situ characterization after air exposure may not reflect the effect of the cleaning methods. Here, combining X-ray photoelectron spectroscopy, in situ infrared reflection absorption spectroscopy, and environmental transmission electron microscopy measurements with CO probe experiments, we investigated different surfactant-removal methods to produce clean metallic Pt nanoparticles from surfactant-encapsulated ones. It was demonstrated that both ultraviolet-ozone (UV-ozone) treatment and room temperature O2 plasma treatment led to the formation of Pt oxides on the surface after the removal of the surfactant. On the other hand, when H2 was used for plasma treatment, both the Pt0 oxidation state and nanoparticle size distribution were preserved. In addition, H2 plasma treatment can reduce Pt oxides after O2-based treatments, resulting in metallic nanoparticles with clean surfaces. These findings provide a better understanding of the various options for surfactant removal from metal nanoparticles and point toward non-thermal plasmas as the best route if the integrity of the nanoparticle needs to be preserved.

Abstract Background Intestinal obstruction caused by endometriosis maybe easily misdiagnosed as a tumor or other occupying disease in emergency condition. How to deal with it depending on the clarity of the preoperative diagnosis and the experience of the surgeon. Case presentation A 47-year-old woman, admitted to our emergency service with abdominal pain and distension for 5 days, anal stop exhausting and defecating for 3 days. Based on imaging and laboratory examination, we made a preoperative diagnosis of rectal endometriosis probably. After 7 days of colon decompression with a intestinal obstruction catheter, an operation of laparoscopic partial rectal and sigmoid resection without protective stoma and total hysterectomy was performed successfully. The patient obtained a smooth postoperative course and doing well after 12-weeks follow up. Conclusions Obstruction caused by rectal endometriosis is very rare and easily overlooked by surgeon and gynecologist. Appropriate preoperative diagnosis and preoperative management can reduce the trauma and incidence of complications.

A tin disulfide and multi-walled carbon nanotube (SnS2/CNTs) electrochemical sensor was constructed for the sensitive and selective determination of rutin in plants. Tin disulfide nanoflowers with various particle sizes were prepared by controlling the reaction time and composited with multi-walled CNTs. The morphology, crystal structure, and chemical composition of these SnS2/CNTs composites were characterized using XRD, XPS, and SEM-EDS. Results illustrated that the SnS2/CNTs had a large specific surface area, good conductivity, and remarkable electrocatalytic performance. The pH of the buffer solution, the scanning rate, and the amount of modified material were also optimized for the rapid detection of rutin. A 2-electron-2-proton mechanism, involving a few rapid and consecutive stages, was speculated to occur during rutin oxidation, based on the observed slope of -53 mV/pH. There was an appreciable linear relationship between the reductive peak current from DPV and the rutin concentration, ranging from 0.005-0.05 µmol/L and 0.1-6 µmol/L, with a detection limit of 0.22 nmol/L (S/N = 3). The sensor also demonstrated good selectivity, excellent sensitivity, and reproducibility when analyzing rutin in real plant samples, with satisfactory recovery, and was also highly consistent with results of HPLC, and thus could be used to evaluate the medicinal value of natural vegetation.

As the second leading cause of cancer worldwide, colorectal cancer (CRC) is associated with a poor prognosis. Although recent studies have explored prognostic markers in patients with CRC, whether tissue microbes carry prognostic information remains unknown. Here, by assessing the colorectal tissue microbes of 533 CRC patients, we found that Proteobacteria (43.5%), Firmicutes (25.3%), and Actinobacteria (23.0%) dominated the colorectal tissue microbiota, which was different from the gut microbiota. Moreover, two clear clusters were obtained by clustering based on the tissue microbes across all samples. By comparison, the relative abundances of Proteobacteria and Bacteroidetes in cluster 1 were significantly higher than those in cluster 2; while compared with cluster 1, Firmicutes and Actinobacteria were more abundant in cluster 2. In addition, the Firmicutes/Bacteroidetes ratios in cluster 1 were significantly lower than those in cluster 2. Further, compared with cluster 2, patients in cluster 1 had relatively poor survival (Log-rank test, p = 0.0067). By correlating tissue microbes with patient survival, we found that the relative abundance of dominant phyla, including Proteobacteria, Firmicutes, and Bacteroidetes, was significantly associated with survival in CRC patients. Besides, the co-occurrence network of tissue microbes at the phylum level of cluster 2 was more complicated than that of cluster 1. Lastly, we detected some pathogenic bacteria enriched in cluster 1 that promote the development of CRC, thus leading to poor survival. In contrast, cluster 2 showed significant increases in the abundance of some probiotics and genera that resist cancer development. Altogether, this study provides the first evidence that the tissue microbiome of CRC patients carries prognostic information and can help design approaches for clinically evaluating the survival of CRC patients.

Abstract Background Quantifying the stock of soil organic carbon (SOC) and evaluating its potential impact factors is important to evaluating global climate change. Human disturbances and past climate are known to influence the rates of carbon fixation, soil physiochemical properties, soil microbial diversity and plant functional traits, which ultimately affect the current SOC storage. However, whether and how the paleoclimate and human disturbances affect the distribution of SOC storage on the high-altitude Tibetan Plateau remain largely unknown. Here, we took the Qinghai Plateau, the main component of the Tibetan Plateau, as our study region and applied three machine learning models (random forest, gradient boosting machine and support vector machine) to estimate the spatial and vertical distributions of the SOC stock and then evaluated the effects of the paleoclimate during the Last Glacial Maximum and the mid-Holocene periods as well as the human footprint on SOC stock at 0 to 200 cm depth by synthesizing 827 soil observations and 71 environmental factors. Results Our results indicate that the vegetation and modern climate are the determinant factors of SOC stocks, while paleoclimate (i.e., paleotemperature and paleoprecipitation) is more important than modern temperature, modern precipitation and the human footprint in shaping current SOC stock distributions. Specifically, the SOC stock was deeply underestimated in near natural ecosystems and overestimated in the strongly human disturbance ecosystems if the model did not consider the paleoclimate. Overall, the total SOC stock of the Qinghai Plateau was underestimated by 4.69%, 12.25% and 6.67% at depths of 0 to 100 cm, 100 to 200 cm and 0 to 200 cm, respectively. In addition, the human footprint had a weak influence on the distributions of the SOC stock. We finally estimated that the total and mean SOC stock at 200 cm depth by including the paleoclimate effects was 11.36 Pg C and 16.31 kg C m−2, respectively, and nearly 40% SOC was distributed in the top 30 cm. Conclusion The paleoclimate is relatively important for the accurate modeling of current SOC stocks. Overall, our study provides a benchmark for predicting SOC stock patterns at depth and emphasizes that terrestrial carbon cycle models should incorporate information on how the paleoclimate has influenced SOC stocks.

Hardware security is importance with outsourcing of integrated circuit fabrication to various foundries. Here, the authors propose a compact encryption logic based on the active interconnects constructed with ferroelectric field-effect transistors.

Due to the asymmetry of quantum errors, phase-shift errors are more likely to occur than qubit-flip errors. Consequently, there is a need to develop asymmetric quantum error-correcting (QEC) codes that can safeguard quantum information transmitted through asymmetric channels. Currently, a significant body of literature has investigated the construction of asymmetric QEC codes. However, the asymmetry of most QEC codes identified in the literature is limited by the dual-containing condition within the Calderbank-Shor-Steane (CSS) framework. This limitation restricts the exploration of their full potential in terms of asymmetry. In order to enhance the asymmetry of asymmetric QEC codes, we utilize entanglement-assisted technology and exploit the algebraic structure of cyclotomic cosets of constacyclic codes to achieve this goal. In this paper, we generalize the decomposition method of the defining set for constacyclic codes and apply it to count the number of pre-shared entangled states in order to construct four new classes of asymmetric entanglement-assisted quantum maximal-distance separable (EAQMDS) codes that satisfy the asymmetric entanglement-assisted quantum Singleton bound. Compared with the codes existing in the literature, the lengths of the constructed EAQMDS codes and the number of pre-shared entangled states are more general, and the codes constructed in this paper have greater asymmetry.