Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network.

Emerging evidence has proved that circular RNAs (circRNAs) are implicated in pathogenic processes. They are regarded as promising biomarkers for diagnosis due to covalently closed loop structures. As opposed to traditional experiments, computational approaches can identify circRNA-disease associations at a lower cost. Aggregating multi-source pathogenesis data helps to alleviate data sparsity and infer potential associations at the system level. The majority of computational approaches construct a homologous network using multi-source data, but they lose the heterogeneity of the data. Effective methods that use the features of multi-source data are considered as a matter of urgency. In this paper, we propose a model (CDHGNN) based on edge-weighted graph attention and heterogeneous graph neural networks for potential circRNA-disease association prediction. The circRNA network, micro RNA network, disease network and heterogeneous network are constructed based on multi-source data. To reflect association probabilities between nodes, an edge-weighted graph attention network model is designed for node features. To assign attention weights to different types of edges and learn contextual meta-path, CDHGNN infers potential circRNA-disease association based on heterogeneous neural networks. CDHGNN outperforms state-of-the-art algorithms in terms of accuracy. Edge-weighted graph attention networks and heterogeneous graph networks have both improved performance significantly. Furthermore, case studies suggest that CDHGNN is capable of identifying specific molecular associations and investigating biomolecular regulatory relationships in pathogenesis. The code of CDHGNN is freely available at https://github.com/BioinformaticsCSU/CDHGNN.

CRMSS: predicting circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features.

Circular RNAs (circRNAs) are reverse-spliced and covalently closed RNAs. Their interactions with RNA-binding proteins (RBPs) have multiple effects on the progress of many diseases. Some computational methods are proposed to identify RBP binding sites on circRNAs but suffer from insufficient accuracy, robustness and explanation. In this study, we first take the characteristics of both RNA and RBP into consideration. We propose a method for discriminating circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features, called CRMSS. For circRNAs, we use sequence ${k}\hbox{-}{mer}$ embedding and the forming probabilities of local secondary structures as features. For RBPs, we combine sequence and structure frequencies of RNA-binding domain regions to generate features. We capture binding patterns with multi-scale residual blocks. With BiLSTM and attention mechanism, we obtain the contextual information of high-level representation for circRNA-RBP binding. To validate the effectiveness of CRMSS, we compare its predictive performance with other methods on 37 RBPs. Taking the properties of both circRNAs and RBPs into account, CRMSS achieves superior performance over state-of-the-art methods. In the case study, our model provides reliable predictions and correctly identifies experimentally verified circRNA-RBP pairs. The code of CRMSS is freely available at https://github.com/BioinformaticsCSU/CRMSS.

Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks.

MOTIVATION: Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited. RESULTS: Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes. AVAILABILITY AND IMPLEMENTATION: DISHyper is freely available for download at https://github.com/genemine/DISHyper.

PDMDA: predicting deep-level miRNA-disease associations with graph neural networks and sequence features.

MOTIVATION: Many studies have shown that microRNAs (miRNAs) play a key role in human diseases. Meanwhile, traditional experimental methods for miRNA-disease association identification are extremely costly, time-consuming and challenging. Therefore, many computational methods have been developed to predict potential associations between miRNAs and diseases. However, those methods mainly predict the existence of miRNA-disease associations, and they cannot predict the deep-level miRNA-disease association types. RESULTS: In this study, we propose a new end-to-end deep learning method (called PDMDA) to predict deep-level miRNA-disease associations with graph neural networks (GNNs) and miRNA sequence features. Based on the sequence and structural features of miRNAs, PDMDA extracts the miRNA feature representations by a fully connected network (FCN). The disease feature representations are extracted from the disease-gene network and gene-gene interaction network by GNN model. Finally, a multilayer with three fully connected layers and a softmax layer is designed to predict the final miRNA-disease association scores based on the concatenated feature representations of miRNAs and diseases. Note that PDMDA does not take the miRNA-disease association matrix as input to compute the Gaussian interaction profile similarity. We conduct three experiments based on six association type samples (including circulations, epigenetics, target, genetics, known association of which their types are unknown and unknown association samples). We conduct fivefold cross-validation validation to assess the prediction performance of PDMDA. The area under the receiver operating characteristic curve scores is used as metric. The experiment results show that PDMDA can accurately predict the deep-level miRNA-disease associations. AVAILABILITY AND IMPLEMENTATION: Data and source codes are available at https://github.com/27167199/PDMDA.

Sex-based clinical and immunological differences in COVID-19.

BACKGROUND: Males and females differ in their immunological responses to foreign pathogens. However, most of the current COVID-19 clinical practices and trials do not take the sex factor into consideration. METHODS: We performed a sex-based comparative analysis for the clinical outcomes, peripheral immune cells, and severe acute respiratory syndrome coronavirus (SARS-CoV-2) specific antibody levels of 1558 males and 1499 females COVID-19 patients from a single center. The lymphocyte subgroups were measured by Flow cytometry. The total antibody, Spike protein (S)-, receptor binding domain (RBD)-, and nucleoprotein (N)- specific IgM and IgG levels were measured by chemiluminescence. RESULTS: We found that male patients had approximately two-fold rates of ICU admission (4.7% vs. 2.7% in males and females, respectively, P = 0.005) and mortality (3% vs. 1.4%, in males and females, respectively, P = 0.004) than female patients. Survival analysis revealed that the male sex is an independent risk factor for death from COVID-19 (adjusted hazard ratio [HR] = 2.22, 95% confidence interval [CI]: 1.3-3.6, P = 0.003). The level of inflammatory cytokines in peripheral blood was higher in males during hospitalization. The renal (102/1588 [6.5%] vs. 63/1499 [4.2%], in males and females, respectively, P = 0.002) and hepatic abnormality (650/1588 [40.9%] vs. 475/1499 [31.7%], P = 0.003) were more common in male patients than in female patients. By analyzing dynamic changes of lymphocyte subsets after symptom onset, we found that the percentage of CD19+ B cells and CD4+ T cells was generally higher in female patients during the disease course of COVID-19. Notably, the protective RBD-specific IgG against SARS-CoV-2 sharply increased and reached a peak in the fourth week after symptom onset in female patients, while gradually increased and reached a peak in the seventh week after symptom onset in male patients. CONCLUSIONS: Males had an unfavorable prognosis, higher inflammation, a lower percentage of lymphocytes, and indolent antibody responses during SARS-CoV-2 infection and recovery. Early medical intervention and close monitoring are important, especially for male COVID-19 patients.

Micro "Hyper-Channels" on Laser-Refined Cellulose Structures.

Controlled liquid transportation is widely applied in both academia and industry. However, liquid transport applications are limited by parameters such as driving forces, precision, and velocity. Herein, a simple laser-refining technology is presented to produce micro "hyper-channels". A cellulose substrate is rendered hydrophobic through silanization and refined with a laser to produce both hierarchical nanostructures and a wettability contrast simultaneously. Such a method enables faster ("hyper"-channel) aqueous liquid transportation (≈25X, 50 mm s-1 ) compared to conventional methods. Complex patterns can be readily produced at different scales with spatial resolution as low as 50 µm. This technique also controls the refining depth on the thin paper substrate. Shallow channels can be fabricated on thin paper substrates that enable fluidic channel-crossover without liquid mixing. With certain parameters, the technique creates "portals" through the substrate, allowing trans-dimensional liquid transportation between two layers of a single sheet of substrate. The fluid throughput can be increased, while also permitting fluidic channel crossover without liquid mixing. By introducing multiple portals, the controlled fluid can transfer trans-dimensionally several times, enabling further fluidic complexity. The real-life utility of the method is demonstrated by creating a trans-dimensional microfluidic device for colorimetric detection.

RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction.

Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the mechanisms of biological processes, developing PPI networks, and detecting protein functions. Currently, most computational methods primarily concentrate on sequence context features and rarely consider the spatial neighborhood features. To address this limitation, we propose a novel residual graph convolutional network for structure-based PPI site prediction (RGCNPPIS). Specifically, we use a GCN module to extract the global structural features from all spatial neighborhoods, and utilize the GraphSage module to extract local structural features from local spatial neighborhoods. To the best of our knowledge, this is the first work utilizing local structural features for PPI site prediction. We also propose an enhanced residual graph connection to combine the initial node representation, local structural features, and the previous GCN layer's node representation, which enables information transfer between layers and alleviates the over-smoothing problem. Evaluation results demonstrate that RGCNPPIS outperforms state-of-the-art methods on three independent test sets. In addition, the results of ablation experiments and case studies confirm that RGCNPPIS is an effective tool for PPI site prediction.

Molecular Cloning and Characterization of WRKY12, A Pathogen Induced WRKY Transcription Factor from Akebia trifoliata.

WRKY transcription factors (TFs), which are plant-specific TFs, play significant roles in plant defense. Here, a pathogen-induced WRKY gene, named AktWRKY12, which was the homologous gene of AtWRKY12, was isolated from Akebia trifoliata. The AktWRKY12 gene has a total length of 645 nucleotides and an open reading frame (ORF) encoding 214 amino acid polypeptides. The characterizations of AktWRKY12 were subsequently performed with the ExPASy online tool Compute pI/Mw, PSIPRED and SWISS-MODEL softwares. The AktWRKY12 could be classified as a member of WRKY group II-c TFs based on sequence alignment and phylogenetic analysis. The results of tissue-specific expression analysis revealed that the AktWRKY12 gene was expressed in all the tested tissues, and the highest expression level was detected in A. trifoliata leaves. Subcellular localization analysis showed that AktWRKY12 was a nuclear protein. Results showed that the expression level of AktWRKY12 significantly increased in A. trifoliata leaves with pathogen infection. Furthermore, heterologous over-expression of AktWRKY12 in tobacco resulted in suppressed expression of lignin synthesis key enzyme genes. Based on our results, we speculate that AktWRKY12 might play a negative role in A. trifoliata responding to biotic stress by regulating the expression of lignin synthesis key enzyme genes during pathogen infection.

Single-cell analysis reveals the chemotherapy-induced cellular reprogramming and novel therapeutic targets in relapsed/refractory acute myeloid leukemia.

Chemoresistance and relapse are the leading cause of AML-related deaths. Utilizing single-cell RNA sequencing (scRNA-seq), we dissected the cellular states of bone marrow samples from primary refractory or short-term relapsed AML patients and defined the transcriptional intratumoral heterogeneity. We found that compared to proliferating stem/progenitor-like cells (PSPs), a subpopulation of quiescent stem-like cells (QSCs) were involved in the chemoresistance and poor outcomes of AML. By performing longitudinal scRNA-seq analyses, we demonstrated that PSPs were reprogrammed to obtain a QSC-like expression pattern during chemotherapy in refractory AML patients, characterized by the upregulation of CD52 and LGALS1 expression. Flow cytometric analysis further confirmed that the preexisting CD99+CD49d+CD52+Galectin-1+ (QSCs) cells at diagnosis were associated with chemoresistance, and these cells were further enriched in the residual AML cells of refractory patients. Interaction of CD52-SIGLEC10 between QSCs and monocytes may contribute to immune evading and poor outcomes. Furthermore, we identified that LGALS1 was a promising target for chemoresistant AML, and LGALS1 inhibitor could help eliminate QSCs and enhance the chemotherapy in patient-derived primary AML cells, cell lines, and AML xenograft models. Our results will facilitate a better understanding of the AML chemoresistance mechanism and the development of novel therapeutic strategies for relapsed/refractory AML patients.

Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer.

Male breast cancer (MBC) is a rare but aggressive malignancy with cellular and immunological characteristics that remain unclear. Here, we perform transcriptomic analysis for 111,038 single cells from tumor tissues of six MBC and thirteen female breast cancer (FBC) patients. We find that that MBC has significantly lower infiltration of T cells relative to FBC. Metastasis-related programs are more active in cancer cells from MBC. The activated fatty acid metabolism involved with FASN is related to cancer cell metastasis and low immune infiltration of MBC. T cells in MBC show activation of p38 MAPK and lipid oxidation pathways, indicating a dysfunctional state. In contrast, T cells in FBC exhibit higher expression of cytotoxic markers and immune activation pathways mediated by immune-modulatory cytokines. Moreover, we identify the inhibitory interactions between cancer cells and T cells in MBC. Our study provides important information for understanding the tumor immunology and metabolism of MBC.

Single-cell RNA sequencing unveils the communications between malignant T and myeloid cells contributing to tumor growth and immunosuppression in cutaneous T-cell lymphoma.

Cutaneous T cell lymphoma (CTCL) is characterized by the accumulation of malignant T cells in the skin. However, advanced CTCL pathophysiology remains elusive and therapeutic options are limited due to the high intratumoral heterogeneity and complicated tumor microenvironment (TME). By comparing the single-cell RNA-seq (scRNA-seq) data from advanced CTCL patients and healthy controls (HCs), we showed that CTCL had a higher enrichment of T/NK and myeloid cells. Subpopulations of T cells (CXCR3+, GNLY+, CREM+, and MKI67+ T cells), with high proliferation, stemness, and copy number variation (CNV) levels, contribute to the malignancy of CTCL. Besides, CCL13+ monocytes/macrophages and LAMP3+ cDC cells were enriched and mediated the immunosuppression via inhibitory interactions with malignant T cells, such as CD47-SIRPA, MIF-CD74, and CCR1-CCL18. Notably, elevated expressions of S100A9 and its receptor TLR4, as well as the activation of downstream toll-like receptor and NF-κB pathway were observed in both malignant cells and myeloid cells in CTCL. Cell co-culture experiments further confirmed that the interaction between malignant CTCL cells and macrophages contributed to tumor growth via S100A9 upregulation and NF-kb activation. Our results showed that blocking the S100A9-TLR4 interaction using tasquinimod could inactivate the NF-κB pathway and inhibit the growth of CTCL tumor cells, and trigger cell apoptosis. Collectively, our study revealed a landscape of immunosuppressive TME mediated by interactions between malignant T cells and myeloid cells, and provided novel targets and potential treatment strategies for advanced CTCL patients.

EBV miRNAs BART11 and BART17-3p promote immune escape through the enhancer-mediated transcription of PD-L1.

Epstein-Barr virus (EBV) is reportedly the first identified human tumor virus, and is closely related to the occurrence and development of nasopharyngeal carcinoma (NPC), gastric carcinoma (GC), and several lymphomas. PD-L1 expression is elevated in EBV-positive NPC and GC tissues; however, the specific mechanisms underlying the EBV-dependent promotion of PD-L1 expression to induce immune escape warrant clarification. EBV encodes 44 mature miRNAs. In this study, we find that EBV-miR-BART11 and EBV-miR-BART17-3p upregulate the expression of PD-L1 in EBV-associated NPC and GC. Furthermore, EBV-miR-BART11 targets FOXP1, EBV-miR-BART17-3p targets PBRM1, and FOXP1 and PBRM1 bind to the enhancer region of PD-L1 to inhibit its expression. Therefore, EBV-miR-BART11 and EBV-miR-BART17-3p inhibit FOXP1 and PBRM1, respectively, and enhance the transcription of PD-L1 (CD274, http://www.ncbi.nlm.nih.gov/gene/29126 ), resulting in the promotion of tumor immune escape, which provides insights into potential targets for EBV-related tumor immunotherapy.

Functional and versatile superhydrophobic coatings via stoichiometric silanization.

Superhydrophobic coatings have tremendous potential for applications in different fields and have been achieved commonly by increasing nanoscale roughness and lowering surface tension. Limited by the availability of either ideal nano-structural templates or simple fabrication procedures, the search of superhydrophobic coatings that are easy to manufacture and are robust in real-life applications remains challenging for both academia and industry. Herein, we report an unconventional protocol based on a single-step, stoichiometrically controlled reaction of long-chain organosilanes with water, which creates micro- to nano-scale hierarchical siloxane aggregates dispersible in industrial solvents (as the coating mixture). Excellent superhydrophobicity (ultrahigh water contact angle >170° and ultralow sliding angle <1°) has been attained on solid materials of various compositions and dimensions, by simply dipping into or spraying with the coating mixture. It has been demonstrated that these complete waterproof coatings hold excellent properties in terms of cost, scalability, robustness, and particularly the capability of encapsulating other functional materials (e.g. luminescent dyes).

CircARHGAP12 promotes nasopharyngeal carcinoma migration and invasion via ezrin-mediated cytoskeletal remodeling.

An increasing number of studies have shown that circular RNAs (circRNAs) play important roles in malignant tumor initiation and progression; however, many circRNAs are yet unidentified, and the role of circRNAs in nasopharyngeal carcinoma (NPC) is unclear. Using RNA sequencing, we discovered a novel circRNA, termed circARHGAP12, that was processed from the pre-mRNA of the ARHGAP12 gene. CircARHGAP12 was significantly upregulated in NPC tissues and cell lines and promoted NPC cell migration and invasion. Overexpression or knockdown experiments revealed that circARHGAP12 regulates the expression of cytoskeletal remodeling-related proteins EZR, TPM3, and RhoA. CircARHGAP12 was found to bind directly to the 3' UTR of EZR mRNA and promote its stability; moreover, EZR protein interacted with TPM3 and RhoA and formed a complex to promote NPC cell invasion and metastasis. This study identified the novel circRNA circARHGAP12, characterized its biological function and mechanism, and increased our understanding of circRNAs in NPC pathogenesis. In particular, circARHGAP12 was found to promote the malignant biological phenotype of NPC via cytoskeletal remodeling, thus providing a clue for targeted therapy of NPC.

circSETD3 regulates MAPRE1 through miR-615-5p and miR-1538 sponges to promote migration and invasion in nasopharyngeal carcinoma.

Circular RNAs (circRNAs) play an essential role in tumorigenesis and development. However, they have rarely been investigated in nasopharyngeal carcinoma (NPC). This study aimed to investigate the role of circRNA in the invasion and metastasis of NPC. We screened and verified the high expression of circSETD3 in NPC cell lines using RNA sequencing (RNA-Seq) and verified the results of NPC biopsy samples using real-time quantitative polymerase chain reaction (qRT-PCR) and in situ hybridization (ISH). In vivo and in vitro experiments indicated that circSETD3 could promote NPC cell invasion and migration. We compared the proteomic data of NPC cells before and after the overexpression or knockdown of circSETD3 in combination with bioinformatics prediction and experimental verification. It was found that circSETD3 competitively adsorbs to miR-615-5p and miR-1538 and negates their inhibitory effect on MAPRE1 mRNA, thereby upregulating the expression of MAPRE1. The upregulated MAPRE1 then inhibits the acetylation of α-tubulin, promotes the dynamic assembly of microtubules, and enhances the invasion and migration capabilities of NPC cells. The results of this study suggest that circSETD3 is a novel molecular marker and a potential target for NPC diagnosis and treatment.

Superhydrophobic Glass Microfiber Filter as Background-Free Substrate for Quantitative Fluorometric Assays.

We have discovered herein that commonly used laboratory glass microfiber filters can be functionalized as background-free superhydrophobic substrates for quantitative fluorometric assays. In particular, glass microfiber filters (Whatman GF/A) can be treated with low-concentration (20 mM) methyltrichlorosilane/toluene solution to be superhydrophobic (water contact angle >150°) in less than 5 min; the modified glass microfiber filter can be readily patterned with UV/ozone irradiation to create hydrophilic reaction zones on the otherwise superhydrophobic substrate. Compared with traditional cellulose filter paper, the glass microfiber filter has extremely low fluorescence background, which makes it an excellent substrate for preparing quantitative fluorometric assays. In conjunction with smartphone imaging and color analysis, we have showcased a copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC)-based fluorometric assay for copper quantitation on these patterned, superhydrophobic glass microfiber filter substrates. Both the limit of detection and linear response range are comparable with the standard spectrophotometric quantitation in solution and commercial copper detection kits, which augments the application potential of superhydrophobic glass microfiber filters as ideal (e.g., background-free) substrates for the preparation of multiplex microassays and other advanced microanalytical devices based on fluorescence readout.

Long non-coding RNA expression profiles and related regulatory networks in areca nut chewing-induced tongue squamous cell carcinoma.

Areca nut chewing is an important risk factor for developing tongue squamous cell carcinoma (TSCC), although the underlying molecular mechanism is unknown. To determine the potential molecular mechanisms of areca nut chewing-induced TSCC, the present study performed whole-genome detection with five pairs of TSCC and adjacent normal tissues, via mRNA- and long non-coding (lnc)RNA-gene chip analysis. A total of 3,860 differentially expressed genes were identified, including 2,193 lncRNAs and 1,667 mRNAs. Gene set-enrichment analysis revealed that the differentially expressed mRNAs were enriched in chromosome 22q13, 8p21 and 3p21 regions, and were regulated by nuclear factor kappa B (NF-κB) and interferon regulatory factors (IRFs). The results of ingenuity pathway analysis revealed that these mRNAs were significantly enriched for inflammatory immune-related signaling pathways. A co-expression network of mRNAs and lncRNAs was constructed by performing weighted gene co-expression network analysis. The present study focused on NF-κB-, IRF- and Th cell-signaling pathway-related lncRNAs and the corresponding mRNA-lncRNA regulatory networks. To the best of our knowledge, the present study was the first to investigate differential mRNA- and lncRNA-expression profiles in TSCCs induced by areca nut chewing. Inflammation-related mRNA-lncRNA regulatory networks driven by IRFs and NF-κB were identified, as well as the Th cell-related signaling pathways that play important carcinogenic roles in areca nut chewing-induced TSCC. These differentially expressed mRNAs and lncRNAs, and their regulatory networks provide insight for further analysis on the molecular mechanism of areca nut chewing-induced TSCC, candidate molecular markers and targets for further clinical intervention.

Binary Silanization and Silver Nanoparticle Encapsulation to Create Superhydrophobic Cotton Fabrics with Antimicrobial Capability.

Cotton fabrics are functionalized with a binary solution of fluorine-free organosilanes and "encapsulated" with silver nanoparticles to achieve both superhydrophobic and antimicrobial properties. Derived from cellulose, cotton is one of the most abundant biologically generated materials and has been used in a wide variety of consumer goods. Nonetheless, cotton fabrics are not waterproof and prone to microbial contamination. Herein we report the rapid functionalization of cotton fabrics with a binary hexane solution of methyltrichlorosilane (MTS) and octadecyltrichlorosilane (OTS) at low concentration (0.17% v/v) followed by coating with colloidal silver nanoparticles (AgNP). The combined effects of binary silanization and AgNP encapsulation produced a surface that has remarkable water contact angle of 153 ± 2° and antimicrobial properties (against gram-negative Escherichia coli). The superior performance of the modified cotton fabrics produced with fluorine-free organosilanes and silver nanoparticles augments the potential of improving the functionality of abundant biopolymers to be waterproof and contamination-resistant.

From kirigami to three-dimensional paper-based micro-analytical device: cut-and-paste fabrication and mobile app quantitation.

Nowadays quantitative chemical analysis is usually costly, instrument-dependent, and time-consuming, which limits its implementation for remote locations and resource-limited regions. Inspired by the ancient papercutting art (kirigami), we herein introduce a novel cut-and-paste protocol to fabricate 3D microfluidic paper-based analytical devices (µPADs) that are suitable for on-site quantitative assay applications. The preparation of the device is fast, simple, and independent of any lithographic devices or masks. Particularly designed reaction "channels" were pre-cut from a piece of filter paper, then assembled back to the silanized, superhydrophobic paper pads. The different layers of the device were assembled using a chemically-inert adhesive spray. The fabricated device has high efficiency of liquid handling (up to 60 times faster than conventional methods) and it is particularly inexpensive. Beyond the benchtop fabrication advantage, in conjunction with a custom mobile app developed for colorimetric analysis, we were able to quantify representative environmental contaminants (i.e., the amount of Cr(vi) and nitrite ions) in various water samples with the cut-and-paste µPADs (namely kPADs). Their detection limits (0.7 µg mL-1 for Cr(vi) and 0.4 µg mL-1 for nitrite ions, respectively) are comparable with conventional spectrophotometric methods, which confirm the potential of kPADs for on-site environmental/sanitary monitoring and food toxin pre-screening.

The role of Wnt signaling pathway in tumor metabolic reprogramming.

The occurrence and development of tumors is a complex process involving long-term multi-factor participation. In this process, tumor cells from a set of abnormal metabolic patterns that are different from normal cells. This abnormal metabolic change is called metabolic reprogramming of tumors. Wnt signaling pathway is one of the critical signaling pathways regulating cell proliferation and differentiation. In recent years, it has been found that Wnt signaling participates in the occurrence and development of malignant tumors by affecting metabolic reprogramming. This paper reviews the role of Wnt signaling in tumor metabolic reprogramming to provide crucial theoretical guidance for targeted therapy and drug response of tumors.