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Abstract In this study, we successfully established a novel gallbladder cancer cell line, designated as GBC-X1, derived from a primary tumor of a gallbladder cancer patient. By comprehensively analyzing the cell line’s phenotype, molecular characteristics, biomarkers, and histological characteristics, we confirmed that GBC-X1 serves as a valuable model for investigating the pathogenesis of gallbladder cancer and developing therapeutic agents. GBC-X1 has been continuously cultured for one year, with over 60 stable passages. Morphologically, GBC-X1 exhibits typical features of epithelial tumors. The population doubling time of GBC-X1 is 32 h. STR analysis validated a high consistency between GBC-X1 and the patient’s primary tumor. Karyotype analysis revealed an abnormal hypertetraploid karyotype for GBC-X1, characterized by representative karyotypes of 98, XXXX del (4) p (12) del (5) p (21) der (10). Under suspension culture conditions, GBC-X1 efficiently forms tumor balls, while subcutaneous inoculation of GBC-X1 cells into NXG mice leads to xenograft formation with a rate of 80%. Drug sensitivity testing demonstrated that GBC-X1 is resistant to oxaliplatin and sensitive to 5-FU, gemcitabine, and paclitaxel. Immunohistochemistry revealed positive expression of CK7, CK19, E-cadherin, MMP-2, CD44, SOX2, and TP53 in GBC-X1 cells, weak positive expression of Vimentin, and a Ki67 positive rate of 35%. Our research highlights GBC-X1 as a novel gallbladder cancer cell line and emphasizes its potential as an effective experimental model for investigating the pathogenesis of gallbladder cancer and drug development.

Abstract. Background:. Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients' recovery. Methods:. This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group (n = 665) and fasting group (n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results:. The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P

Abstract Chemotherapy resistance poses clinical challenges in pancreatic cancer treatment. Developing cell lines resistant to chemotherapy is crucial for investigating drug resistance mechanisms and identifying alternative treatment pathways. The genetic and biological attributes of pancreatic cancer depend on its aetiology, racial demographics and anatomical origin, underscoring the need for models that comprehensively represent these characteristics. Here, we introduce PDAC-X2, a pancreatic cancer cell line derived from Chinese patients. We conducted a comprehensive analysis encompassing the immune phenotype, biology, genetics, molecular characteristics and tumorigenicity of the cell line. PDAC-X2 cells displayed epithelial morphology and expressed cell markers (CK7 and CK19) alongside other markers (E-cadherin, Vimentin, Ki-67, CEA and CA19-9). The population doubling time averaged around 69 h. In vivo, PDAC-X2 cells consistently maintained their tumorigenicity, achieving a 100% tumour formation rate. Characterised by a predominantly tetraploid karyotype, this cell line exhibited a complex genetic markup. Notably, PDAC-X2 cells demonstrated resistance to multiple drugs, including gemcitabine, paclitaxel, 5-fluorouracil and oxaliplatin. In conclusion, PDAC-X2 presents an invaluable preclinical model. Its utility lies in facilitating the study of drug resistance mechanisms and the exploration of alternative therapeutic approaches aimed at enhancing the prognosis of this tumour type.

Non-small cell lung cancer (NSCLC) is the predominant form of lung cancer and is characterized by rapid metastasis and high mortality, presenting a challenge for early-stage treatment modalities. The heterogeneity of NSCLC’s tumor microenvironment (TME) significantly influences the efficacy of anti-PD-1 immune checkpoint inhibitors (ICIs) therapy, leading to varied patient responses. This review characterized different strains of oncolytic viruses in NSCLC and the different gene edits in pre-existing oncolytic viruses. This study also aimed to provide strategies to enhance anti-PD-1 therapy in NSCLC by engineering oncolytic viruses (OVs). This study offers insights into the genomic adaptations necessary for OVs targeting NSCLC, identify genetic determinants of anti-PD-1 response variability, and propose genomic edits to bolster therapy effectiveness. The primary goal of this study is to present a theoretically designed OV with a detailed genomic framework capable of enhancing the response to anti-PD-1 therapy, thereby advancing the field of cancer immunotherapy.

The long non-coding RNA MIR4435-2HG has been confirmed to play a crucial regulatory role in various types of tumors. As a novel type of non-coding RNA, MIR4435-2HG plays a key role in regulating the expression of tumor-related genes, interfering with cellular signaling pathways, and affecting tumor immune evasion. Its unique structure allows it to regulate the expression of various tumor-related genes through different pathways, participating in the regulation of tumor signaling pathways, such as regulating the expression of oncogenes and tumor suppressor genes, influencing the biological behaviors of proliferation, metastasis, and apoptosis in tumors. Numerous studies have found a high expression of MIR4435-2HG in various tumor tissues, closely related to the clinical pathological characteristics of tumors, such as staging, lymph node metastasis and prognosis. Some studies have discovered that MIR4435-2HG can regulate the sensitivity of tumor cells to chemotherapy drugs, affecting tumor cell drug resistance. This provides new insights into overcoming tumor drug resistance by regulating MIR4435-2HG. Therefore, studying its molecular mechanisms, expression regulation, and its relationship with the clinical features of tumors is of great significance for revealing the mechanisms of tumor occurrence and developing new therapeutic targets.

Thaumatin-like proteins (TLPs), including osmotins, are multifunctional proteins related to plant biotic and abiotic stress responses. TLPs are often present as large multigene families. Tetragonia tetragonoides (Pall.) Kuntze (Aizoaceae, 2n = 2x = 32), a vegetable used in both food and medicine, is a halophyte that is widely distributed in the coastal areas of the tropics and subtropics. Saline–alkaline soils and drought are two major abiotic stress factors significantly affecting the distribution of tropical coastal plants. The expression of stress resistance genes would help to alleviate the cellular damage caused by abiotic stress factors such as high temperature, salinity–alkalinity, and drought. This study aimed to better understand the functions of TLPs in the natural ecological adaptability of T. tetragonoides to harsh habitats. In the present study, we used bioinformatics approaches to identify 37 TtTLP genes as gene family members in the T. tetragonoides genome, with the purpose of understanding their roles in different developmental processes and the adaptation to harsh growth conditions in tropical coral regions. All of the TtTLPs were irregularly distributed across 32 chromosomes, and these gene family members were examined for conserved motifs of their coding proteins and gene structure. Expression analysis based on RNA sequencing and subsequent qRT-PCR showed that the transcripts of some TtTLPs were decreased or accumulated with tissue specificity, and under environmental stress challenges, multiple TtTLPs exhibited changeable expression patterns at short (2 h), long (48 h), or both stages. The expression pattern changes in TtTLPs provided a more comprehensive overview of this gene family being involved in multiple abiotic stress responses. Furthermore, several TtTLP genes were cloned and functionally identified using the yeast expression system. These findings not only increase our understanding of the role that TLPs play in mediating halophyte adaptation to extreme environments but also improve our knowledge of plant TLP evolution. This study also provides a basis and reference for future research on the roles of plant TLPs in stress tolerance and ecological environment suitability.

Abstract The diverse bacterial populations within the symbiotic microbiota play a pivotal role in both health and disease. Microbiota modulates critical aspects of tumor biology including cell proliferation, invasion, and metastasis. This regulation occurs through mechanisms like enhancing genomic damage, hindering gene repair, activating aberrant cell signaling pathways, influencing tumor cell metabolism, promoting revascularization, and remodeling the tumor immune microenvironment. These microbiota‐mediated effects significantly impact overall survival and the recurrence of tumors after surgery by affecting the efficacy of chemoradiotherapy. Moreover, leveraging the microbiota for the development of biovectors, probiotics, prebiotics, and synbiotics, in addition to utilizing antibiotics, dietary adjustments, defensins, oncolytic virotherapy, and fecal microbiota transplantation, offers promising alternatives for cancer treatment. Nonetheless, due to the extensive and diverse nature of the microbiota, along with tumor heterogeneity, the molecular mechanisms underlying the role of microbiota in cancer remain a subject of intense debate. In this context, we refocus on various cancers, delving into the molecular signaling pathways associated with the microbiota and its derivatives, the reshaping of the tumor microenvironmental matrix, and the impact on tolerance to tumor treatments such as chemotherapy and radiotherapy. This exploration aims to shed light on novel perspectives and potential applications in the field.

Prostate cancer: stem cell treatment targets microRNA A microRNA shown to promote prostate cancer growth can be targeted through a treatment derived from stem cells. Prostate cancer is lethal for many men, and its growth is promoted by testosterone. However, some “castration-resistant” strains keep growing even after treatments that reduce testosterone levels. Xiaoyi Huang at Harbin Medical University Cancer Hospital, China, and co-workers examined the role of microRNA-375 in the progression of castration-resistant prostate cancer. They found that microRNA-375 was over-expressed in cancer tissue samples and promoted tumor growth by interfering with a specific signaling pathway. The team applied a treatment comprising extracellular vesicles called exosomes that are derived from human stem cells and loaded with molecules that suppress microRNA-375. The treatment inhibited microRNA-375 and thereby repressed the cancer growth, while also reducing the cancer’s resistance to the testosterone-blocking drug enzalutamide.

Pancreatic cancer is a strongly malignant gastrointestinal carcinoma characterized by late detection, high mortality rates, poor patient prognosis and lack of effective treatments. Consequently, there is an urgent need to identify novel therapeutic strategies for this disease. Pancreatic stellate cells, which constitute a significant component of the mesenchymal cellular layer within the pancreatic tumor microenvironment, play a pivotal role in modulating this environment through their interactions with pancreatic cancer cells. This paper reviews the mechanisms by which pancreatic stellate cells inhibit antitumor immune responses and promote cancer progression. We also discuss preclinical studies focusing on these cells, with the goal of providing some theoretical references for the development of new therapeutic approaches for pancreatic cancer.

The electrode microstructure and interface stability play an important role during thermal cycles and reversible cycles for protonic reversible solid oxide cells (P-rSOCs). In this work, the effects of microstructural change of air electrodes on the performance and cycling stability are investigated by using tubular cells with large active area (7.5 cm2). The BaCe0.5Zr0.4In0.1O3@ La0.6Sr0.4CoO3 (BCZI@LSC) composite air electrode is prepared through a wet chemical procedure based on infiltration of the LSC precursor solution into the BCZI electrolyte skeleton. The LSC nanoparticles attach to the electrolyte skeleton in a continuous film-forming morphology, affording abundant three-phase reaction boundaries (TPBs) and the continuous conducting phase. Compared to the BCZI + LSC composite air electrode prepared by conventional mechanical mixing, the cell with the BCZI@LSC electrode demonstrates an increased current density of 51%. The cell with the BCZI + LSC electrode shows acceptable stability during 14 reversible FC-EC cycles and 4 thermal cycles (between 650 °C and room temperature) for 360 h in 20% H2O-air atmosphere. The differences in stability for cells prepared by the two processes are compared and discussed.

The interactions between the microbiota and the human host can affect the physiological functions of organs (such as the brain, liver, gut, etc.). Accumulating investigations indicate that the imbalance of microbial community is closely related to the occurrence and development of diseases. Thus, the identification of potential links between microbes and diseases can provide insight into the pathogenesis of diseases. In this study, we propose a deep learning framework (MDAGCAN) based on graph convolutional attention network to identify potential microbe-disease associations. In MDAGCAN, we first construct a heterogeneous network consisting of the known microbe-disease associations and multi-similarity fusion networks of microbes and diseases. Then, the node embeddings considering the neighbor information of the heterogeneous network are learned by applying graph convolutional layers and graph attention layers. Finally, a bilinear decoder using node embedding representations reconstructs the unknown microbe-disease association. Experiments show that our method achieves reliable performance with average AUCs of 0.9778 and 0.9454 ± 0.0038 in the frameworks of Leave-one-out cross validation (LOOCV) and 5-fold cross validation (5-fold CV), respectively. Furthermore, we apply MDAGCAN to predict latent microbes for two high-risk human diseases, i.e., liver cirrhosis and epilepsy, and results illustrate that 16 and 17 out of the top 20 predicted microbes are verified by published literatures, respectively. In conclusion, our method displays effective and reliable prediction performance and can be expected to predict unknown microbe-disease associations facilitating disease diagnosis and prevention.

Early and accurate diagnosis and treatment of pancreatic cancer (PC) remain challenging endeavors globally. Late diagnosis lag, high invasiveness, chemical resistance, and poor prognosis are unresolved issues of PC. The concept of metabolic reprogramming is a hallmark of cancer cells. Increasing evidence shows that PC cells alter metabolic processes such as glucose, amino acids, and lipids metabolism and require continuous nutrition for survival, proliferation, and invasion. Glucose metabolism, in particular, regulates the tumour microenvironment (TME). Furthermore, the link between glucose metabolism and TME also plays an important role in the targeted therapy, chemoresistance, radiotherapy ineffectiveness, and immunosuppression of PC. Altered metabolism with the TME has emerged as a key mechanism regulating PC progression. This review shed light on the relationship between TME, glucose metabolism, and various aspects of PC. The findings of this study provide a new direction in the development of PC therapy targeting the metabolism of cancer cells.

IntroductionEpichloë bromicola is a cultivable fungal endophyte that lives in symbiosis with wild barley (Hordeum brevisubulatum) to which it confers salt tolerance. This study tested the hypothesis that E. bromicola derived from wild barley has the potential to increase salt tolerance in cultivated barley under salt stress.MethodsTo test this hypothesis, the growth response, physiological parameters, and metabolic profiles of barley plants inoculated with E. bromicola (E+) and those not inoculated with E. bromicola (E–) were compared under salt stress.ResultsCompared with E– barley plants, E+ barley plants had significantly increased plant height, shoot biomass, total biomass, chlorophyll content, osmotic synthesis, and accumulation of stress adaptation metabolites. E. bromicola increased the salt stress tolerance of cultivated barley, and the positive effects correlated with different salt stress conditions.DiscussionThese results suggest that E. bromicola has promising potential for enhancing the salt tolerance of barley. New insights into the mechanisms underlying this barley–fungal endophyte association are provided, and interesting questions regarding the role of E. bromicola in fungus-enhanced tolerance to salt stress in this symbiosis are raised.

Introduction: Tremendous evidence indicates that N6-methyladenosine (m6A) epigenetic modification and m6A-related enzymes constitute a complex network, which jointly regulates prevailing pathological processes and various signaling pathways in humankind. Currently, the role of the m6A-mediated molecular regulatory network in hepatocellular carcinoma (HCC) remains elusive.Methods: We recruited expression and pathological files of 368 HCC patients from The Cancer Genome Atlas cohort. Four public datasets serve as external authentication sets for nearest template prediction (NTP) validation. The correlation between 35 regulators and their prognostic value was compared. Gene set variation analysis (GSVA) was used to explore the latent mechanism. Four independent algorithms (ssGSEA, xCell, MCP-counter, and TIMER) were used to calculate the ratio of tumor cells and non-tumor cells to evaluate the tumor immune microenvironment. The m6Ascore model was established by principal component analysis (PCA). Prediction of immunotherapy and potential drugs was performed using TIDE and SubMap.Results: A total of 35 m6A regulators were widely associated, most of which were risk factors for HCC patients. The m6A phenotypic-cluster revealed differences in regulator transcriptional level, gene mutation frequency, functional pathways, and immune cell infiltration abundance under distinct m6A patterns. As expected, the m6A gene cluster confirmed the aforementioned results. The m6Ascore model further found that patients in the high-m6Ascore group were associated with lower tumor purity, higher enrichment of immune and stromal cells, upregulation of metabolic pathways, lower expression of m6A regulators, and favorable outcomes. Low-m6Ascore patients were associated with adverse outcomes. Notably, low-m6Ascore patients might be more sensitive to anti-PD-L1 therapy.Conclusion: This study found that a classification model based on the m6A manner could predict HCC prognosis and response to immunotherapy for HCC patients, which might improve prognosis and contribute to clinical individualized decision-making.

Abstract Background Canavalia rosea (Sw.) DC. (bay bean) is an extremophile halophyte that is widely distributed in coastal areas of the tropics and subtropics. Seawater and drought tolerance in this species may be facilitated by aquaporins (AQPs), channel proteins that transport water and small molecules across cell membranes and thereby maintain cellular water homeostasis in the face of abiotic stress. In C. rosea, AQP diversity, protein features, and their biological functions are still largely unknown. Results We describe the action of AQPs in C. rosea using evolutionary analyses coupled with promoter and expression analyses. A total of 37 AQPs were identified in the C. rosea genome and classified into five subgroups: 11 plasma membrane intrinsic proteins, 10 tonoplast intrinsic proteins, 11 Nod26-like intrinsic proteins, 4 small and basic intrinsic proteins, and 1 X-intrinsic protein. Analysis of RNA-Seq data and targeted qPCR revealed organ-specific expression of aquaporin genes and the involvement of some AQP members in adaptation of C. rosea to extreme coral reef environments. We also analyzed C. rosea sequences for phylogeny reconstruction, protein modeling, cellular localizations, and promoter analysis. Furthermore, one of PIP1 gene, CrPIP1;5, was identified as functional using a yeast expression system and transgenic overexpression in Arabidopsis. Conclusions Our results indicate that AQPs play an important role in C. rosea responses to saline-alkaline soils and drought stress. These findings not only increase our understanding of the role AQPs play in mediating C. rosea adaptation to extreme environments, but also improve our knowledge of plant aquaporin evolution more generally.

With the increasing of renewable energy penetration, adequate reserve capacity is more important to modern power system facing with various uncertain factors. Mobilizing the enthusiasm of units and demand response to participate in reserve auxiliary service can reduce the reserve providing pressure of conventional power supplies, which is conducive to the reliable and economical operation of system. The uncertain factors such as system random failure, prediction error of both load and renewable energy output are considered, and taking unit reserve, demand response such as flexible loads as system reserve resources, this paper establishes the risk cost models to optimize system up and down reserve requirement and make optimal allocation among units and flexible loads. A joint market clearing model of day-ahead electric energy and reserve auxiliary service is established in which both the units and flexible loads participate, and is solved by the robust optimization theory. The joint market clearing model takes the reliability and the economy of the system operation into account, and optimizes the clearing scheme for market decision makers, which can provide a decision reference for the market to resist the risk of uncertainty. Finally, the effectiveness of the model and method proposed in this paper is verified by a modified 10-machine 39-bus simulation example system.

Abstract Background Circular RNAs (circRNAs) are widely expressed in cells and tissues and are involved in biological processes and human diseases. Recent studies have demonstrated that circRNAs can interact with RNA-binding proteins (RBPs), which is considered an important aspect for investigating the function of circRNAs. Results In this study, we design a slight variant of the capsule network, called circRB, to identify the sequence specificities of circRNAs binding to RBPs. In this model, the sequence features of circRNAs are extracted by convolution operations, and then, two dynamic routing algorithms in a capsule network are employed to discriminate between different binding sites by analysing the convolution features of binding sites. The experimental results show that the circRB method outperforms the existing computational methods. Afterwards, the trained models are applied to detect the sequence motifs on the seven circRNA-RBP bound sequence datasets and matched to known human RNA motifs. Some motifs on circular RNAs overlap with those on linear RNAs. Finally, we also predict binding sites on the reported full-length sequences of circRNAs interacting with RBPs, attempting to assist current studies. We hope that our model will contribute to better understanding the mechanisms of the interactions between RBPs and circRNAs. Conclusion In view of the poor studies about the sequence specificities of circRNA-binding proteins, we designed a classification framework called circRB based on the capsule network. The results show that the circRB method is an effective method, and it achieves higher prediction accuracy than other methods.

Abstract Background Circular RNA (circRNA) has been extensively identified in cells and tissues, and plays crucial roles in human diseases and biological processes. circRNA could act as dynamic scaffolding molecules that modulate protein-protein interactions. The interactions between circRNA and RNA Binding Proteins (RBPs) are also deemed to an essential element underlying the functions of circRNA. Considering cost-heavy and labor-intensive aspects of these biological experimental technologies, instead, the high-throughput experimental data has enabled the large-scale prediction and analysis of circRNA-RBP interactions. Results A computational framework is constructed by employing Positive Unlabeled learning (P-U learning) to predict unknown circRNA-RBP interaction pairs with kernel model MFNN (Matrix Factorization with Neural Networks). The neural network is employed to extract the latent factors of circRNA and RBP in the interaction matrix, the P-U learning strategy is applied to alleviate the imbalanced characteristics of data samples and predict unknown interaction pairs. For this purpose, the known circRNA-RBP interaction data samples are collected from the circRNAs in cancer cell lines database (CircRic), and the circRNA-RBP interaction matrix is constructed as the input of the model. The experimental results show that kernel MFNN outperforms the other deep kernel models. Interestingly, it is found that the deeper of hidden layers in neural network framework does not mean the better in our model. Finally, the unlabeled interactions are scored using P-U learning with MFNN kernel, and the predicted interaction pairs are matched to the known interactions database. The results indicate that our method is an effective model to analyze the circRNA-RBP interactions. Conclusion For a poorly studied circRNA-RBP interactions, we design a prediction framework only based on interaction matrix by employing matrix factorization and neural network. We demonstrate that MFNN achieves higher prediction accuracy, and it is an effective method.

We, the Editors and Publisher of the journal Artificial Cells, Nanomedicine, and Biotechnology, have retracted the following article:Kexiang Zhu, Zhengcong Zhang, Hui Zhang, Zhengfeng Wang & Fanghong Wang (2020) MiR-142-3p targeting NUCKS1 inhibits proliferation and invasion of pancreatic cancer cells. Artificial Cells, Nanomedicine, and Biotechnology, 48(1), 415–424, DOI: 10.1080/21691401.2019.1652629Since publication, concerns have been raised about the integrity of the data in the article. In addition, during the course of our investigation it has come to our attention that the authorship list and affiliations for this manuscript were significantly changed after the article was accepted. We have contacted the corresponding author for an explanation, but we have not received a response. As determining authorship is core to the integrity of published work, and we have also been unable to verify the original data, we are retracting the article. The corresponding author listed in this publication has been notified.We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as ‘Retracted’.

The Chinese mugwort (Artemisia argyi Lév. et Vaniot) is an important traditional Chinese medicine plant that is ubiquitously disturbed in Asia. However, the molecular mechanisms that reflect the natural evolution of Artemisia argyi remain unclear. In this study, a high-quality draft assembly of the allotetraploid A. argyi (ArteW1-Tongbai) was conducted utilizing PacBio long-read sequencing and Hi-C technologies. The assembly is about 7.20 Gb with a contig N50 length of 0.87 Mb. The allotetraploid genome of ArteW1-Tongbai is highly heterozygous and rich in repeat sequences (the heterozygous ratio is 1.36%, and the repeat rate is 86.26%). A total of 139,245 protein-coding genes were identified. The KEGG enrichment analysis revealed that 846 species-specific genes were related to the biosynthesis of secondary metabolites. The plants with allopolyploid genomes can potentially exhibit a better adaptive capacity to environmental stresses and accumulation of secondary metabolites. Therefore, the genome assembly serves as a valuable reference for Artemisia, the genus characterized by species richness and diverse specialized metabolites.

The development of temozolomide (TMZ) resistance in glioma leads to poor patient prognosis. Sorafenib, a novel diaryl urea compound and multikinase inhibitor, has the ability to effectively cross the blood-brain barrier. However, the effect of sorafenib on glioma cells and the molecular mechanism underlying the ability of sorafenib to enhance the antitumor effects of TMZ remain elusive. Here, we found that sorafenib could enhance the cytotoxic effects of TMZ in glioma cells in vitro and in vivo. Mechanistically, the combination of sorafenib and TMZ induced mitochondrial depolarization and apoptosis inducing factor (AIF) translocation from mitochondria to nuclei, and this process was dependent on STAT3 inhibition. Moreover, the combination of sorafenib and TMZ inhibited JAK2/STAT3 phosphorylation and STAT3 translocation to mitochondria. Inhibition of STAT3 activation promoted the autophagy-associated apoptosis induced by the combination of sorafenib and TMZ. Furthermore, the combined sorafenib and TMZ treatment induced oxidative stress while reactive oxygen species (ROS) clearance reversed the treatment-induced inhibition of JAK2/STAT3. The results indicate that sorafenib enhanced the temozolomide sensitivity of human glioma cells by inducing oxidative stress-mediated autophagy and JAK2/STAT3-AIF axis.

Intermediate between apoptosis and necrosis, necroptosis is a regulated caspase-independent programmed cell death that induces an inflammatory response and mediates cancer development. As our understanding improves, its role in the physiopathology of numerous diseases, including pancreatic diseases, has been reconsidered, and especially in pancreatitis and pancreatic cancer. However, the exact pathogenesis remains elusive, even though some studies have been conducted on these diseases. Its unique mechanisms of action in diseases are expected to bring prospects for the treatment of pancreatic diseases. Therefore, it is imperative to further explore its molecular mechanism in pancreatic diseases in order to identify novel therapeutic options. This article introduces recent related research on necroptosis and pancreatic diseases, explores necroptosis-related molecular pathways, and provides a theoretical foundation for new therapeutic targets for pancreatic diseases.

Hordeum vulgare is an important source of feed and forage for livestock, and of food and drink for humans, but its utilization rate is lower than that of other cereal crops, thus it is crucial to improve barley agronomic traits and production. Epichloë bromicola is an endophyte that was isolated from wild barley (Hordeum brevisubulatum). Previous studies have found that Epichloë can indirectly influence the growth of host plants by affecting soil chemical characteristics, the microbial community, and by producing a range of secondary metabolites. However, underlying effects of Epichloë on the abundance and diversity of soil and root microbes have not been well-studied. In addition, there is a question regarding the relationship between endophyte-produced alkaloids and effects on the root and rhizosphere microbial communities. The objective of this study was to investigate changes in agronomic traits, nutritional properties, peramine, soil chemical and microbial community in the fourth generation of new barley symbionts EI (E. bromicola-infection) and EF (E. bromicola-free) in LQ+4 and LZ+4. We understand the plant height and biomass of EI in LZ+4 were significantly higher than those of EF. The HPLC analysis showed that the peramine content of EI in LQ+4 and LZ+4 was 0.085 and 0.1 mg/g, respectively. We compared the bacterial and fungal communities by analyzing the 16s rRNA (for bacteria) and ITS rDNA regions (for fungi). Our data revealed that the composition of fungal communities in rhizosphere soil of LZ+4 EI are higher than EF. In addition, the diversity and richness of fungal communities in root and rhizosphere soil of LQ+4 EI and LZ+4 EI are significantly higher than EF. Rhizosphere soil microbial community composition was higher than that in roots in LQ+4 and LZ+4. Peramine was significantly and positively correlated with the richness of the soil fungal community. Moreover, the principal component analysis (PCoA) results indicated that E. bromicola significantly influenced the community composition of root and rhizosphere soil microbes in both LQ+4 and LZ+4. Our results illustrate that E. bromicola can influence barley growth, peramine production and microbial communities associated with barley.

Summary: HPV infections are common in healthy women and only rarely cause cervical cancer, suggesting that individual genetic susceptibility may play a critical role in the establishment of persistent HPV infection and the development of cervical cancer. Here, we provide convincing in vitro and in vivo evidence showing that differential expression and activation of YAP1 oncogene determine individual susceptibility to HPV infection and cervical carcinogenesis. We found that hyperactivation of YAP1 in mouse cervical epithelium was sufficient to induce invasive cervical cancer. Cervical epithelial cell-specific HPV16 E6/E7 and YAP1 double-knockin mouse model demonstrated that high-risk HPV synergized with hyperactivated YAP1 to promote the initiation and progression of cervical cancer. Our mechanistic studies indicated that hyperactivation of YAP1 in cervical epithelial cells facilitated HPV infection by increasing the putative HPV receptor molecules and disrupting host cell innate immunity. Our finding reveals an unconventional mechanism for cervical carcinogenesis. : HPV infections are common in healthy women and only rarely cause cervical cancer. He et al. provide evidence that hyperactivation of the YAP1 oncogene can drive cervical cancer initiation and progression. YAP1 hyperactivation in cervical epithelial cells increases the HPV receptors and disrupts host cell innate immunity, facilitating HPV infection. Keywords: Hippo pathway, YAP1 oncogene, HPV infection, cervical carcinogenesis, cervical cancer mouse model, innate immunity, molecular mechanism, HPV receptor molecules, type I interferon, interferon-stimulated genes

Plant metal tolerance proteins (MTPs) play key roles in heavy metal absorption and homeostasis in plants. By using genome-wide and phylogenetic approaches, the origin and diversification of MTPs from Canavalia rosea (Sw.) DC. was explored. Canavalia rosea (bay bean) is an extremophile halophyte with strong adaptability to seawater and drought and thereby shows specific metal tolerance with a potential phytoremediation ability. However, MTP genes in leguminous plants remain poorly understood. In our study, a total of 12 MTP genes were identified in C. rosea. Multiple sequence alignments showed that all CrMTP proteins possessed the conserved transmembrane domains (TM1 to TM6) and could be classified into three subfamilies: Zn-CDFs (five members), Fe/Zn-CDFs (five members), and Mn-CDFs (two members). Promoter cis-acting element analyses revealed that a distinct number and composition of heavy metal regulated elements and other stress-responsive elements existed in different promoter regions of CrMTPs. Analysis of transcriptome data revealed organ-specific expression of CrMTP genes and the involvement of this family in heavy metal stress responses and adaptation of C. rosea to extreme coral reef environments. Furthermore, the metal-specific activity of several functionally unknown CrMTPs was investigated in yeast. These results will contribute to uncovering the potential functions and molecular mechanisms of heavy metal absorption, translocation, and accumulation in C. rosea plants.

Seasonal precipitation changes are increasingly severe in subtropical areas. However, the responses of soil nitrogen (N) cycle and its associated functional microorganisms to such precipitation changes remain unclear. In this study, two projected precipitation patterns were manipulated: intensifying the dry-season drought (DD) and extending the dry-season duration (ED) but increasing the wet-season storms following the DD and ED treatment period. The effects of these two contrasting precipitation patterns on soil net N transformation rates and functional gene abundances were quantitatively assessed through a resistance index. Results showed that the resistance index of functional microbial abundance (-0.03 ± 0.08) was much lower than that of the net N transformation rate (0.55 ± 0.02) throughout the experiment, indicating that microbial abundance was more responsive to precipitation changes compared with the N transformation rate. Spring drought under the ED treatment significantly increased the abundances of both nitrifying (amoA) and denitrifying genes (nirK, nirS, and nosZ), while changes in these gene abundances overlapped largely with control treatment during droughts in the dry season. Interestingly, the resistance index of the ammonia-oxidizing archaea (AOA) amoA abundance was significantly higher than that of the denitrifying gene abundances, suggesting that AOA were more resistant to the precipitation changes. This was attributed to the stronger environmental adaptability and higher resource utilization efficiency of the AOA community, as indicated by the lack of correlations between AOA gene abundance and environmental factors [i.e., soil water content, ammonium (NH4+) and dissolved organic carbon concentrations] during the experiment.

Circular RNAs (circRNAs) are extensively expressed in cells and tissues, and play crucial roles in human diseases and biological processes. Recent studies have reported that circRNAs could function as RNA binding protein (RBP) sponges, meanwhile RBPs can also be involved in back-splicing. The interaction with RBPs is also considered an important factor for investigating the function of circRNAs. Hence, it is necessary to understand the interaction mechanisms of circRNAs and RBPs, especially in human cancers. Here, we present a novel method based on deep learning to identify cancer-specific circRNA−RBP binding sites (CSCRSites), only using the nucleotide sequences as the input. In CSCRSites, an architecture with multiple convolution layers is utilized to detect the features of the raw circRNA sequence fragments, and further identify the binding sites through a fully connected layer with the softmax output. The experimental results show that CSCRSites outperform the conventional machine learning classifiers and some representative deep learning methods on the benchmark data. In addition, the features learnt by CSCRSites are converted to sequence motifs, some of which can match to human known RNA motifs involved in human diseases, especially cancer. Therefore, as a deep learning-based tool, CSCRSites could significantly contribute to the function analysis of cancer-associated circRNAs.

The control of cerebral blood flow is complex, and only beginning to be elucidated. Studies have identified three key regulatory paradigms. The first is cerebral pressure autoregulation, which maintains a constant flow in the face of changing cerebral perfusion pressure. Flow-metabolism coupling refers to the brains ability to vary blood flow to match metabolic activity. An extensive arborization of perivascular nerves also serves to modulate cerebral blood flow, so-called neurogenic regulation. Central to these three paradigms are two cell types: endothelium and astrocytes. The endothelium produces several vasoactive factors that are germane to the regulation of cerebral blood flow: nitric oxide, endothelium-dependent hyperpolarization factor, the eicosanoids, and the endothelins. Astrocytic foot processes directly abut the blood vessels, and play a key role in regulation of cerebral blood flow. Lastly, new research has been investigating cell-cell communication at the microvascular level. Several lines of evidence point to the ability of the larger proximal vessels to coordinate vasomotor responses downstream.

Vascular endothelial cell premature senescence plays an important part in stroke. Many microRNAs (miRNAs) are known to be involved in the pathological process of vascular endothelial cell premature senescence. The present study aimed to investigate the mechanism of hydrogen peroxide (H~2O2)-induced premature senescence in human umbilical vein endothelial cells (HUVECs) and effect of miR-142-3p on hydrogen peroxide (H2O2)-induced premature senescence. HUVECs were exposed to H2O2 to establish a model premature senescence in endothelial cells. CCK-8 assay was performed to detect cell viability. Senescence-associated ß-galactosidase staining assay and senescence-related proteins p16 and p21 were used to detect changes in the degree of cell senescence. RT-qPCR and Western blot were conducted to measure mRNA and protein levels, respectively. The scratch wound-healing assay, transwell assay, and EdU assay were performed to evaluate the ability of migration and proliferation, respectively. miRNA-142-3p and silencing information regulator 2 related enzyme 1 (SIRT1) binding was verified using Targetscan software and a dual-luciferase assay. We found that miRNA-142-3p is abnormally up-regulated in HUVECs treated with H2O2. Functionally, miRNA-142-3p inhibition may mitigate the degree of HUVEC senescence and improve HUVEC migration and proliferation. Mechanistically, SIRT1 was validated to be targeted by miRNA-142-3p in HUVECs. Moreover, SIRT1 inhibition reversed the effects of miRNA-142-3p inhibition on senescent HUVECs exposed to H2O2. To our knowledge, this is the first study to show that miRNA-142-3p ameliorates H2O2-induced HUVECs premature senescence by targeting SIRT1 and may shed light on the role of the miR-142-3p/SIRT1 axis in stroke treatment. [ABSTRACT FROM AUTHOR]

The Shanghai Fish Market (1936), initiated by Republican China's Ministry of Industry, was briefly a linchpin for producers and distributors, facilitating state intervention in the supply chain of the treaty port city. The market's modernist design by Su, Yang & Lei Architects departed from the Beaux-Arts-inspired practices often associated with Nationalist China's self-presentation. Influenced by foreign precedents, it incorporated rationalized trading procedures into its spatial layout. This article examines the market's construction, which was guided by fishery expertise and aimed to harness natural resources for societal and national benefits. Technopolitical dynamics surrounding the reconfiguration of food provisioning logistics generated power struggles among stakeholders at the local and international levels. Despite the obstacles that constantly challenged the technocrats' ambition to revolutionize the fishery industry, the Shanghai Fish Market's historical and architectural significance lies in its efforts to integrate the built and natural environments into a national system of governance. [ABSTRACT FROM AUTHOR]

The high overlap of participants in the carbon emissions trading and electricity markets couples the operations of the two markets. The carbon emission cost (CEC) of coal-fired units becomes part of the power generation cost through market coupling. The accuracy of CEC calculation affects the clearing capacity of coal-fired units in the electric power market. Study of carbon-electricity market interaction and CEC calculations is still in its initial stages. This study analyzes the impact of carbon emissions trading and compliance on the operation of the electric power market and defines the cost transmission mode between the carbon emissions trading and electric power markets. A long-period interactive operation simulation mechanism for the carbon-electricity market is established, and operation and trading models of the carbon emissions trading market and electric power market are established. A daily rolling estimation method for the CEC of coalfired units is proposed, along with the CEC per unit electric quantity of the coal-fired units. The feasibility and effectiveness of the proposed method are verified through an example simulation, and the factors influencing the CEC are analyzed. [ABSTRACT FROM AUTHOR]