Progressive Neighbor-masked Contrastive Learning for Fusion-style Deep Multi-view Clustering.

Fusion-style Deep Multi-view Clustering (FDMC) can efficiently integrate comprehensive feature information from latent embeddings of multiple views and has drawn much attention recently. However, existing FDMC methods suffer from the interference of view-specific information for fusion representation, affecting the learning of discriminative cluster structure. In this paper, we propose a new framework of Progressive Neighbor-masked Contrastive Learning for FDMC (PNCL-FDMC) to tackle the aforementioned issues. Specifically, by using neighbor-masked contrastive learning, PNCL-FDMC can explicitly maintain the local structure during the embedding aggregation, which is beneficial to the common semantics enhancement on the fusion view. Based on the consistent aggregation, the fusion view is further enhanced by diversity-aware cluster structure enhancement. In this process, the enhanced cluster assignments and cluster discrepancies are employed to guide the weighted neighbor-masked contrastive alignment of semantic structure between individual views and the fusion view. Extensive experiments validate the effectiveness of the proposed framework, revealing its ability in discriminative representation learning and improving clustering performance.

Carboxylic acid isomer-directed synthesis of CdS nanocluster isomers.

Selective synthesis of nanocluster (NC) isomers with tailored structures holds significant importance for enhancing their applications. Here, we develop an effective strategy for the selective synthesis of CdS NC isomers through the judicious choice of a pair of carboxylic acid isomer additives. Specifically, CdS NC-312 and NC-323 (denoted by their UV-vis absorption peak position) could be selectively produced by introducing a conventional mixture of Cd and S precursors, with the addition of 2-methylbutyric acid (2-MA) and 3-methylbutyric acid (3-MA), respectively. The synthesized NC isomers demonstrated a precise isomeric relationship, sharing both the isomeric inorganic core and organic surface. Alternatively, the as-synthesized NCs were interconvertible by re-adding the acid isomers. The density functional theory calculations further support that 2-MA and 3-MA have specific selectivity for producing CdS NC isomers by interfacial tuning. Finally, the generality of this methodology was also evidenced with applications in other CdS NC synthetic systems. This study unveils the intriguing correlation between additive structures and the configuration of NCs, providing a foundation for the selective synthesis of NC isomers.

Quantitative ultrasound imaging parameters in patients with cancerous thyroid nodules: development of a diagnostic model.

OBJECTIVE: This study aimed to develop a diagnostic model utilizing quantitative ultrasound parameters to accurately differentiate benign from malignant thyroid nodules. METHODS: A retrospective analysis of 194 patients with thyroid nodules, encompassing 65 malignant and 129 benign cases, was performed. Clinical data, ultrasound characteristics, and hemodynamic indicators were compared. Receiver operating characteristic (ROC) curves and logistic regression analysis identified independent diagnostic markers. RESULTS: No significant differences in clinical data were observed between the groups (P>0.05). Malignant nodules, however, were more likely to exhibit solid composition, hypoechoicity, irregular shapes, calcifications, central blood flow, and unclear margins (P<0.05). Hemodynamic parameters showed that malignant nodules had lower end-diastolic volume (EDV) but higher peak systolic velocity (PSV), resistive index (RI), and vascularization flow index (VFI) (P<0.001). Independent diagnostic factors identified included calcification, margin definition, RI, and VFI. A risk prediction model was formulated, demonstrating significantly lower scores for benign nodules (P<0.0001), achieving an ROC area of 0.964. CONCLUSION: Color Doppler ultrasound effectively distinguishes malignant from benign thyroid nodules. The diagnostic model emphasizes the importance of calcification, margin clarity, RI, and VFI as critical elements, enhancing the accuracy of thyroid nodule characterization and facilitating informed clinical decisions.

Characterizing and identifying of miRNAs involved in berberine modulating glucose metabolism of Megalobrama amblycephala.

The present study, as one part of a larger project that aimed to investigate the effects of dietary berberine (BBR) on fish growth and glucose regulation, mainly focused on whether miRNAs involve in BBR's modulation of glucose metabolism in fish. Blunt snout bream Megalobrama amblycephala (average weight of 20.36 ± 1.44 g) were exposed to the control diet (NCD, 30% carbohydrate), the high-carbohydrate diet (HCD, 43% carbohydrate) and the berberine diet (HCB, HCD supplemented with 50 mg/kg BBR). After 10 weeks' feeding trial, intraperitoneal injection of glucose was conducted, and then, the plasma and liver were sampled at 0 h, 1 h, 2 h, 6 h, and 12 h. The results showed the plasma glucose levels in all groups rose sharply and peaked at 1 h after glucose injection. Unlike the NCD and HCB groups, the plasma glucose in the HCD group did not decrease after 1 h, while remained high level until at 2 h. The NCD group significantly increased liver glycogen content at times 0-2 h compared to the other two groups and then liver glycogen decreased sharply until at times 6-12 h. To investigate the role of BBR that may cause the changes in plasma glucose and liver glycogen, miRNA high-throughput sequencing was performed on three groups of liver tissues at 2 h time point. Eventually, 20 and 12 differentially expressed miRNAs (DEMs) were obtained in HCD vs NCD and HCB vs HCD, respectively. Through function analyzing, we found that HCD may affect liver metabolism under glucose loading through the NF-κB pathway; and miRNAs regulated by BBR mainly play roles in adipocyte lipolysis, niacin and nicotinamide metabolism, and amino acid transmembrane transport. In the functional exploration of newly discovered novel:Chr12_18892, we found its target gene, adenylate cyclase 3 (adcy3), was widely involved in lipid decomposition, amino acid metabolism, and other pathways. Furthermore, a targeting relationship of novel:Chr12_18892 and adcy3 was confirmed by double luciferase assay. Thus, BBR may promote novel:Chr12_18892 to regulate the expression of adcy3 and participate in glucose metabolism.

Protosappanin A Protects DOX-Induced Myocardial Injury and Cardiac Dysfunction by Targeting ACSL4/FTH1 Axis-Dependent Ferroptosis.

Doxorubicin (DOX) is an effective anticancer agent, but its clinical utility is constrained by dose-dependent cardiotoxicity, partly due to cardiomyocyte ferroptosis. However, the progress of developing cardioprotective medications to counteract ferroptosis has encountered obstacles. Protosappanin A (PrA), an anti-inflammatory compound derived from hematoxylin, shows potential against DOX-induced cardiomyopathy (DIC). Here, it is reported that PrA alleviates myocardial damage and dysfunction by reducing DOX-induced ferroptosis and maintaining mitochondrial homeostasis. Subsequently, the molecular target of PrA through proteome microarray, molecular docking, and dynamics simulation is identified. Mechanistically, PrA physically binds with ferroptosis-related proteins acyl-CoA synthetase long-chain family member 4 (ACSL4) and ferritin heavy chain 1 (FTH1), ultimately inhibiting ACSL4 phosphorylation and subsequent phospholipid peroxidation, while also preventing FTH1 autophagic degradation and subsequent release of ferrous ions (Fe2+) release. Given the critical role of ferroptosis in the pathogenesis of ischemia-reperfusion (IR) injury, this further investigation posits that PrA can confer a protective effect against IR-induced cardiac damage by inhibiting ferroptosis. Overall, a novel pharmacological inhibitor is unveiled that targets ferroptosis and uncover a dual-regulated mechanism for cardiomyocyte ferroptosis in DIC, highlighting additional therapeutic options for chemodrug-induced cardiotoxicity and ferroptosis-triggered disorders.

Defect effects on the electronic, valley, and magnetic properties of the two-dimensional ferrovalley material VSi2N4.

Due to their novel spin and valley properties, two-dimensional (2D) ferrovalley materials are expected to be promising candidates for next-generation spintronic and valleytronic devices. However, they are subject to various defects in practical applications. Therefore, the electronic, valley, and magnetic properties may be modified in the presence of the defects. In this work, utilizing first-principles calculations, we systematically studied the effects of defects on the electronic, valley, and magnetic properties of the 2D ferrovalley material VSi2N4. It has been found that C doping, O doping, and N vacancies result in the half-metallic feature, Si vacancies result in the metallic feature, and V vacancies result in a bipolar gapless semiconductor. These defect-induced electronic properties can be effectively tuned by changing defect concentration and layer thickness. Since the impurity bands do not affect the K and K' valleys, valley polarization is well maintained in O-doped and N-defective systems. Importantly, these defects play a crucial role in modifying the magnetic properties of the pristine VSi2N4, especially the magnitude of local magnetic moments and the magnetic anisotropy energy. Detailed analysis of the density of states demonstrates that the variations of the total magnetic moment and magnetic anisotropy energy with biaxial strain are determined by the electronic states near the Fermi level rather than the type of defect, which provides a new understanding of the effects of defects on the magnetic properties of 2D materials. Moreover, the layer thickness can affect the magnetic coupling between defects and surrounding V atoms. Our results offer insight into the electronic, valley, and magnetic properties of VSi2N4 in the presence of various point defects.

Anti-Colon Cancer Activity of Copper-Doped Folate Carbon Dots/MnO2 Complexes Based on Oxygenation and Immune-Enhancing Effects.

In clinical practice, the treatment of colon cancer is faced with the dilemma of metastasis and recurrence, which is related to immunosuppression and hypoxia. Immune checkpoint blockade (ICB) is a negative regulatory pathway of immunity. Immune checkpoint blockade (ICB) is an important immunotherapy method. However, inadequate immunogenicity reduces the overall response rate of ICB. In this study, a tumor microenvironment-responsive nanomedicine (Cu-FACD@MnO2@FA) was prepared to increase host immune response and increase intracellular oxygen levels. Cu-FACD@MnO2@FA preferentially enriched at the tumor site, combined with the immune checkpoint inhibitor alpha PD-L1, induced sufficient immunogenicity to treat colon cancer. Immunofluorescence detection of tumor cells and tissues showed that the expression of hypoxa-inducing factor 1α was significantly down-regulated after treatment and the expression of immunoactivity-related proteins was significantly changed. In vivo treatment in a bilateral tumor mouse model showed complete ablation of the primary tumor and efficient inhibition of the distal tumor. In this study, for the first time, the oxygenation effects of MnO2-coated Cu-doped carbon dots and chemodynamic therapy and a strategy of combining with immuno-blocking therapy were used for treating colon cancer.

Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics.

Introduction: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in motor skills, communication, emotional expression, and social interaction. Accurate diagnosis of ASD remains challenging due to the reliance on subjective behavioral observations and assessment scales, lacking objective diagnostic indicators. Methods: In this study, we introduced a novel approach for diagnosing ASD, leveraging T1-based gray matter and ASL-based cerebral blood flow network metrics. Thirty preschool-aged patients with ASD and twenty-two typically developing (TD) individuals were enrolled. Brain network features, including gray matter and cerebral blood flow metrics, were extracted from both T1-weighted magnetic resonance imaging (MRI) and ASL images. Feature selection was performed using statistical t-tests and Minimum Redundancy Maximum Relevance (mRMR). A machine learning model based on random vector functional link network was constructed for diagnosis. Results: The proposed approach demonstrated a classification accuracy of 84.91% in distinguishing ASD from TD. Key discriminating network features were identified in the inferior frontal gyrus and superior occipital gyrus, regions critical for social and executive functions in ASD patients. Discussion: Our study presents an objective and effective approach to the clinical diagnosis of ASD, overcoming the limitations of subjective behavioral observations. The identified brain network features provide insights into the neurobiological mechanisms underlying ASD, potentially leading to more targeted interventions.

A Novel Drug Candidate for Sepsis Targeting Heparanase by Inhibiting Cytokine Storm.

Sepsis is an infection-triggered, rapidly progressive systemic inflammatory syndrome with a high mortality rate. Currently, there are no promising therapeutic strategies for managing this disease in the clinic. Heparanase plays a crucial role in the pathology of sepsis, and its inhibition can significantly relieve related symptoms. Here, a novel heparanase inhibitor CV122 is rationally designed and synthesized, and its therapeutic potential for sepsis with Lipopolysaccharide (LPS) and Cecal Ligation and Puncture (CLP)-induced sepsis mouse models are evaluated. It is found that CV122 potently inhibits heparanase activity in vitro, protects cell surface glycocalyx structure, and reduces the expression of adhesion molecules. In vivo, CV122 significantly reduces the systemic levels of proinflammatory cytokines, prevents organ damage, improves vitality, and efficiently protects mice from sepsis-induced death. Mechanistically, CV122 inhibits the activity of heparanase, reduces its expression in the lungs, and protects glycocalyx structure of lung tissue. It is also found that CV122 provides effective protection from organ damage and death caused by Crimean-Congo hemorrhagic fever virus (CCHFV) infection. These results suggest that CV122 is a potential drug candidate for sepsis therapy targeting heparanase by inhibiting cytokine storm.

Short-term effects of irrigation and nitrogen management on paddy soil carbon pools under deep placement of basal fertilizer nitrogen.

Active soil organic carbon (SOC) fractions are major driving factors of soil fertility. Understanding the effects of water and fertilizer management on changes in active SOC fractions helps improve soil quality and maintain high agricultural productivity. We conducted a 3-year field experiment in Northeast China. In this experiment, natural soil (CKT) was used as a blank, and two irrigation regimes were established: conventional flooded irrigation (FI) and controlled irrigation (CI). Four nitrogen application levels were set for both irrigation regimes under deep placement of basal fertilizer N: Nd0 (0 kg ha-1), Nd (110 kg ha-1), Nd1 (99 kg ha-1), and Nd2 (88 kg ha-1). After 3 years, at similar N fertilizer application rate, the rice yield, total organic carbon (TOC), and active SOC fraction content of CI were higher under CI than FI. The growth rate of rice yield was 3.8% - 8.63% under CI than FI. Under CI, the rice yield, active SOC fractions contents and carbon pool management index (CPMI) did not decrease with decreasing N application rate but instead reached the highest level in the CNd1 treatment. Overall, CI with Nd1 treatment appears to be the best practice for improving soil fertility and crop productivity in Northeast China.

Halogenated aromatic pollutants in routine animal-derived food of south China: Occurrence, sources, and dietary intake risks.

Halogenated aromatic pollutants (HAPs) including polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs), polychlorinated biphenyls (PCBs), polybrominated dibenzo-p-dioxins/furans (PBDD/Fs), and polybrominated diphenyl ethers (PBDEs) exhibit diverse toxicities and bio-accumulation in animals, thereby imposing risks on human via animal-derived food (ADF) consumption. Here we examined these HAPs in routine ADFs from South China and observed that PBDEs and PCBs showed statistically higher concentrations than PCDD/Fs and PBDD/Fs. PCDD/Fs and PCBs in these ADFs were mainly from the polluted feed and habitat of animals, except PCDD/Fs in egg, which additionally underwent selective biotransformation/progeny transfer after the maternal intake of PCDD/F-polluted stuff. PBDEs and PBDD/Fs were mostly derived from the extensive use of deca-BDE and their polluted environments. Significant interspecific differences were mainly observed for DL-PCBs and partly for PBDD/Fs and PBDEs, which might be caused by their distinct transferability/biodegradability in animals and the different living habit and habitat of animals. The dietary intake doses (DIDs) of these HAPs via ADF consumption were all highest for toddlers, then teenagers and adults. Milk, egg, and fish contributed most to the DIDs and risks for toddlers and teenagers, which results of several cities exceeded the recommended thresholds and illustrated noteworthy risks. Pork, fish, and egg were the top three risk contributors for adults, which carcinogenic and non-carcinogenic risks were both acceptable. Notably, PBDD/Fs showed the lowest concentrations but highest contributions to the total risks of these HAPs, thereby meriting continuous attention.

The crosstalk between macrophages and cancer cells potentiates pancreatic cancer cachexia.

With limited treatment options, cachexia remains a major challenge for patients with cancer. Characterizing the interplay between tumor cells and the immune microenvironment may help identify potential therapeutic targets for cancer cachexia. Herein, we investigate the critical role of macrophages in potentiating pancreatic cancer induced muscle wasting via promoting TWEAK (TNF-like weak inducer of apoptosis) secretion from the tumor. Specifically, depletion of macrophages reverses muscle degradation induced by tumor cells. Macrophages induce non-autonomous secretion of TWEAK through CCL5/TRAF6/NF-κB pathway. TWEAK promotes muscle atrophy by activating MuRF1 initiated muscle remodeling. Notably, tumor cells recruit and reprogram macrophages via the CCL2/CCR2 axis and disrupting the interplay between macrophages and tumor cells attenuates muscle wasting. Collectively, this study identifies a feedforward loop between pancreatic cancer cells and macrophages, underlying the non-autonomous activation of TWEAK secretion from tumor cells thereby providing promising therapeutic targets for pancreatic cancer cachexia.

Deep Imputation Bi-stochastic Graph Regularized Matrix Factorization for Clustering Single-cell RNA-sequencing Data.

By generating massive gene transcriptome data and analyzing transcriptomic variations at the cell level, single-cell RNA-sequencing (scRNA-seq) technology has provided new way to explore cellular heterogeneity and functionality. Clustering scRNA-seq data could discover the hidden diversity and complexity of cell populations, which can aid to the identification of the disease mechanisms and biomarkers. In this paper, a novel method (DSINMF) is presented for single cell RNA sequencing data by using deep matrix factorization. Our proposed method comprises four steps: first, the feature selection is utilized to remove irrelevant features. Then, the dropout imputation is used to handle missing value problem. Further, the dimension reduction is employed to preserve data characteristics and reduce noise effects. Finally, the deep matrix factorization with bi-stochastic graph regularization is used to obtain cluster results from scRNA-seq data. We compare DSINMF with other state-of-the-art algorithms on nine datasets and the results show our method outperformances than other methods.

Immunogenic Cell Death Induction and Oxygenation by Multifunctional Hollow Silica/Copper-Doped Carbon Dots.

The metastasis and recurrence of cancer are related to immunosuppression and hypoxia in the tumor microenvironment. Activating immune activity and improving the hypoxic environment face essential challenges. This paper reports on a multifunctional nanomaterial, HSCCMBC, that induces immunogenic cell death through powerful photodynamic therapy/chemodynamic therapy synergistic antitumor effects. The tumor microenvironment changed from the immunosuppressive type to immune type, activated the immune activity of the system, decomposed hydrogen peroxide to generate oxygen based on Fenton-like reaction, and effectively increased the level of intracellular O2 with the assistance of 3-bromopyruvate, a cell respiratory inhibitor. The structure and composition of HSCCMBC were characterized by transmission electron microscopy, X-ray photoelectron spectroscopy, X-ray diffraction, infrared spectroscopy, etc. Oxygen probe RDPP was used to investigate the oxygen level inside and outside the cell, and hydroxyl radical probe tetramethylbenzidine was used to investigate the Fenton-like reaction ability. The immunofluorescence method investigated the expression of various immune markers and hypoxia-inducing factors in vitro and in vivo after treatment. In vitro and in vivo experiments indicate that HSCCMBC is an excellent antitumor agent and is expected to be a candidate drug for antitumor immunotherapy.

A dual data stream hybrid neural network for classifying pathological images of lung adenocarcinoma.

Lung cancer has seriously threatened human health due to its high lethality and morbidity. Lung adenocarcinoma, in particular, is one of the most common subtypes of lung cancer. Pathological diagnosis is regarded as the gold standard for cancer diagnosis. However, the traditional manual screening of lung cancer pathology images is time consuming and error prone. Computer-aided diagnostic systems have emerged to solve this problem. Current research methods are unable to fully exploit the beneficial features inherent within patches, and they are characterized by high model complexity and significant computational effort. In this study, a deep learning framework called Multi-Scale Network (MSNet) is proposed for the automatic detection of lung adenocarcinoma pathology images. MSNet is designed to efficiently harness the valuable features within data patches, while simultaneously reducing model complexity, computational demands, and storage space requirements. The MSNet framework employs a dual data stream input method. In this input method, MSNet combines Swin Transformer and MLP-Mixer models to address global information between patches and the local information within each patch. Subsequently, MSNet uses the Multilayer Perceptron (MLP) module to fuse local and global features and perform classification to output the final detection results. In addition, a dataset of lung adenocarcinoma pathology images containing three categories is created for training and testing the MSNet framework. Experimental results show that the diagnostic accuracy of MSNet for lung adenocarcinoma pathology images is 96.55 %. In summary, MSNet has high classification performance and shows effectiveness and potential in the classification of lung adenocarcinoma pathology images.

Transformer Monitoring with Electromagnetic Energy Transmission and Wireless Sensing.

To ensure stable and normal transformer operation, light gas protection of the transformer Buchholz relay is essential. However, false alarms related to light gas protection are common, and troubleshooting them often requires on-site gas sampling by personnel. During this time, the transformer's operating state may rapidly deteriorate, posing a safety threat to field staff. To tackle these challenges, this work presents the near-field, thin-sliced transformer monitoring system that uses Electromagnetic Energy Transmission and Wireless Sensing Device (ETWSD). The system leverages external wireless energy input to power gas monitoring sensors. Simultaneously, it employs Near-Field Communication to obtain real-time concentrations of light gases, along with the electrified state and temperature. In field testing conducted on transformer relays' gas collection chambers, the ETWSD effortlessly monitors parameters within warning ranges, encompassing methane gas concentrations around 1000 ppm, leakage voltage ranging from 0-100 V, and relay working temperatures up to 90 °C. Additionally, to facilitate real-time diagnosis for electrical workers, we have developed an Android-based APP software that displays current light gas concentrations, leakage voltage collection values, and temperature, while also enabling threshold judgment, alarms, and data storage. The developed ETWSD is expected to aid on-site personnel in promptly and accurately evaluating transformer light gas protection error alarm faults. It provides a method for simultaneous, contactless, and rapid monitoring of multiple indicators.

Immunoantitumor Activity and Oxygenation Effect Based on Iron-Copper-Doped Folic Acid Carbon Dots.

Cancer metastasis and recurrence are closely associated with immunosuppression and a hypoxic tumor microenvironment. Chemodynamic therapy (CDT) and photothermodynamic therapy (PTT) have been shown to induce immunogenic cell death (ICD), effectively inhibiting cancer metastasis and recurrence when combined with immune adjuvants. However, the limited efficacy of Fenton's reaction and suboptimal photothermal effect present significant challenges for successfully inducing ICD through CDT and PTT. This paper described the synthesis and immunoantitumor activity of the novel iron-copper-doped folic acid carbon dots (CFCFB). Copper-doped folic acid carbon dots (Cu-FACDs) were initially synthesized via a hydrothermal method, using folic acid and copper gluconate as precursors. Subsequently, the nanoparticles CFCFB were obtained through cross-linking and self-assembly of Cu-FACDs with ferrocene dicarboxylic acid (FeDA) and 3-bromopyruvic acid (3BP). The catalytic effect of carbon dots in CFCFB enhanced the activity of the Fenton reaction, thereby promoting CDT-induced ICD and increasing the intracellular oxygen concentration. Additionally, 3BP inhibited cellular respiration, further amplifying the oxygen concentration. The photothermal conversion efficiency of CFCFB reached 55.8%, which significantly enhanced its antitumor efficacy through photothermal therapy. Immunofluorescence assay revealed that treatment with CFCFB led to an increased expression of ICD markers, including calreticulin (CRT) and ATP, as well as extracellular release of HMGB-1, indicating the induction of ICD by CFCFB. Moreover, the observed downregulation of ARG1 expression indicates a transition in the tumor microenvironment from an immunosuppressive state to an antitumor state following treatment with CFCFB. The upregulation of IL-2 and CD8 expression facilitated the differentiation of effector T cells, resulting in an augmented population of CD8+ T cells, thereby indicating the activation of systemic immune response.

The Failure Mechanism of Micro Thermoelectric Devices under the Action of the Temperature Field.

The micro thermoelectric device (m-TED) boasts features such as adjustable volume, straightforward structure, and precise, rapid temperature control, positioning it as the only current solution for managing the temperature of microelectronic systems. It is extensively utilized in 5G optical modules, laser lidars, and infrared detection. Nevertheless, as the size of the m-TED diminishes, the growing proportion of interface damages the device's operational reliability, constraining the advancement of the m-TED. In this study, we used commercially available bismuth telluride materials to construct the m-TED. The device's reliability was tested under various temperatures: -40, 85, 125, and 150 °C. By deconstructing and analyzing the devices that failed during the tests, we discovered that the primary cause of device failure was the degradation of the solder layer. Moreover, we demonstrated that encapsulating the device with polydimethylsiloxane (PDMS) could effectively delay the deterioration of its performance. This study sparks new insights into the service reliability of m-TEDs and paves the way for further optimizing device interface design and enhancing the device manufacturing process.

The stromal microenvironment endows pancreatic neuroendocrine tumors with spatially specific invasive and metastatic phenotypes.

Cancer-associated fibroblasts (CAFs) play an important role in a variety of cancers. However, the role of tumor stroma in nonfunctional pancreatic neuroendocrine tumors (NF-PanNETs) is often neglected. Profiling the heterogeneity of CAFs can reveal the causes of malignant phenotypes in NF-PanNETs. Here, we found that patients with high stromal proportion had poor prognosis, especially for that with infiltrating stroma (stroma and tumor cells that presented an infiltrative growth pattern and no regular boundary). In addition, myofibroblastic CAFs (myCAFs), characterized by FAP+ and α-SMAhigh, were spatially closer to tumor cells and promoted the EMT and tumor growth. Intriguingly, only tumor cells which were spatially closer to myCAFs underwent EMT. We further elucidated that myCAFs stimulate TGF-ß expression in nearby tumor cells. Then, TGF-ß promoted the EMT in adjacent tumor cells and promoted the expression of myCAFs marker genes in tumor cells, resulting in distant metastasis. Our results indicate that myCAFs cause spatial heterogeneity of EMT, which accounts for liver metastasis of NF-PanNETs. The findings of this study might provide possible targets for the prevention of liver metastasis.