Metabolic Heterogeneity and Potential Immunotherapeutic Responses Revealed by Single-Cell Transcriptomics of Breast Cancer.

BACKGROUND: Breast cancer (BC) exhibits remarkable heterogeneity. However, the transcriptomic heterogeneity of BC at the single-cell level has not been fully elucidated. METHODS: We acquired BC samples from 14 patients. Single-cell RNA sequencing (scRNA-seq), bioinformatic analyses, along with immunohistochemistry (IHC) and immunofluorescence (IF) assays were carried out. RESULTS: According to the scRNA-seq results, 10 different cell types were identified. We found that Cancer-Associated Fibroblasts (CAFs) exhibited distinct biological functions and may promote resistance to therapy. Metabolic analysis of tumor cells revealed heterogeneity in glycolysis, gluconeogenesis, and fatty acid synthetase reprogramming, which led to chemotherapy resistance. Furthermore, patients with multiple metastases and progression were predicted to benefit from immunotherapy based on a heterogeneity analysis of T cells and tumor cells. CONCLUSIONS: Our findings provide a comprehensive understanding of the heterogeneity of BC, provide comprehensive insight into the correlation between cancer metabolism and chemotherapy resistance, and enable the prediction of immunotherapy responses based on T-cell heterogeneity.

Myogenic exosome miR-140-5p modulates skeletal muscle regeneration and injury repair by regulating muscle satellite cells.

Muscle satellite cells (SCs) play a crucial role in the regeneration and repair of skeletal muscle injuries. Previous studies have shown that myogenic exosomes can enhance satellite cell proliferation, while the expression of miR-140-5p is significantly reduced during the repair process of mouse skeletal muscle injuries induced by BaCl2. This study aims to investigate the potential of myogenic exosomes carrying miR-140-5p inhibitors to activate SCs and influence the regeneration of injured muscles. Myogenic progenitor cell exosomes (MPC-Exo) and contained miR-140-5p mimics/inhibitors myogenic exosomes (MPC-Exo140+ and MPC-Exo140-) were employed to treat SCs and use the model. The results demonstrate that miR-140-5p regulates SC proliferation by targeting Pax7. Upon the addition of MPC-Exo and MPC-Exo140-, Pax7 expression in SCs significantly increased, leading to the transition of the cell cycle from G1 to S phase and an enhancement in cell proliferation. Furthermore, the therapeutic effect of MPC-Exo140- was validated in animal model, where the expression of muscle growth-related genes substantially increased in the gastrocnemius muscle. Our research demonstrates that MPC-Exo140- can effectively activate dormant muscle satellite cells, initiating their proliferation and differentiation processes, ultimately leading to the formation of new skeletal muscle cells and promoting skeletal muscle repair and remodeling.

Oleanolic acid alleviates obesity-induced skeletal muscle atrophy via the PI3K/Akt signaling pathway.

Oleanolic acid (OA) is a pentacyclic triterpene with reported protective effects against various diseases, including diabetes, hepatitis, and different cancers. However, the effects of OA on obesity-induced muscle atrophy remain largely unknown. This study investigated the effects of OA on skeletal muscle production and proliferation of C2C12 cells. We report that OA significantly increased skeletal muscle mass and improved glucose intolerance and insulin resistance. OA inhibited dexamethasone (Dex)-induced muscle atrophy in C2C12 myoblasts by regulating the PI3K/Akt signaling pathway. In addition, it also inhibited expression of MuRF1 and Atrogin1 genes in skeletal muscle of obese mice suffering from muscle atrophy, and increased the activation of PI3K and Akt, thereby promoting protein synthesis, and eventually alleviating muscle atrophy. Taken together, these findings suggest OA may have potential for the prevention and treatment of muscle atrophy.

Exercise-inducible circulating extracellular vesicle irisin promotes browning and the thermogenic program in white adipose tissue.

AIM: Exercise can reduce body weight and promote white fat browning, but the underlying mechanisms remain largely unknown. This study investigated the role of fibronectin type III domain-containing protein 5 (FNDC5)/Irisin, a hormone released from exercising muscle, in the browning of white fat in circulating extracellular vesicles (EVs). METHODS: Mice were subjected to a 4 weeks of running table exercise, and fat browning was analyzed via histology, protein blotting and qPCR. Circulating EVs were extracted by ultrahigh-speed centrifugation, and ELISA was used to measure the irisin concentration in the circulating EVs. Circulating EVs that differentially expressed irisin were applied to adipocytes, and the effect of EV-irisin on adipocyte energy metabolism was analyzed by immunofluorescence, protein blotting, and cellular oxygen consumption rate analysis. RESULTS: During sustained exercise, the mice lost weight and developed fat browning. FNDC5 was induced, cleaved, and secreted into irisin, and irisin levels subsequently increased in the plasma during exercise. Interestingly, irisin was highly expressed in circulating EVs that effectively promoted adipose browning. Mechanistically, the circulating EV-irisin complex is transported intracellularly by the adipocyte membrane receptor integrin αV, which in turn activates the AMPK signaling pathway, which is dependent on mitochondrial uncoupling protein 1 to cause mitochondrial plasmonic leakage and promote heat production. After inhibition of the AMPK signaling pathway, the effects of the EV-irisin on promoting fat browning were minimal. CONCLUSION: Exercise leads to the accumulation of circulating EV-irisin, which enhances adipose energy metabolism and thermogenesis and promotes white fat browning in mice, leading to weight loss.

MiR-222-3p suppresses C2C12 myoblast proliferation and differentiation via the inhibition of IRS-1/PI3K/Akt pathway.

Numerous studies have revealed the profound impact of microRNAs on regulating skeletal muscle development and regeneration. However, the biological function and regulation mechanism of miR-222-3p in skeletal muscle remains largely unknown. In this study, miR-222-3p was found to be abundantly expressed in the impaired skeletal muscles, indicating that it might have function in the development and regeneration process of the skeletal muscle. MiR-222-3p overexpression impeded C2C12 myoblast proliferation and myogenic differentiation, whereas inhibition of miR-222-3p got the opposite results. The dual-luciferase reporter assay showed that insulin receptor substrate-1 (IRS-1) was the target gene of miR-222-3p. We next found that knockdown of IRS-1 could obviously suppress C2C12 myoblast proliferation and differentiation. Additionally, miR-222-3p-induced repression of myoblast proliferation and differentiation was verified to be associated with a decrease in phosphoinositide 3-kinase (PI3K)-Akt signaling. Overall, we demonstrated that miR-222-3p inhibited C2C12 cells myogenesis via IRS-1/PI3K/Akt pathway. Therefore, miR-222-3p may be used as a therapeutic target for alleviating muscle loss caused by inherited and nonhereditary diseases.

Endurance Exercise-Induced Fgf21 Promotes Skeletal Muscle Fiber Conversion through TGF-ß1 and p38 MAPK Signaling Pathway.

Fgf21 has been identified as playing a regulatory role in muscle growth and function. Although the mechanisms through which endurance training regulates skeletal muscle have been widely studied, the contribution of Fgf21 remains poorly understood. Here, muscle size and function were measured, and markers of fiber type were evaluated using immunohistochemistry, immunoblots, or qPCR in endurance-exercise-trained wild-type and Fgf21 KO mice. We also investigated Fgf21-induced fiber conversion in C2C12 cells, which were incubated with lentivirus and/or pathway inhibitors. We found that endurance exercise training enhanced the Fgf21 levels of liver and GAS muscle and exercise capacity and decreased the distribution of skeletal muscle fiber size, and fast-twitch fibers were observed converting to slow-twitch fibers in the GAS muscle of mice. Fgf21 promoted the markers of fiber-type transition and eMyHC-positive myotubes by inhibiting the TGF-ß1 signaling axis and activating the p38 MAPK signaling pathway without apparent crosstalk. Our findings suggest that the transformation and function of skeletal muscle fiber types in response to endurance training could be mediated by Fgf21 and its downstream signaling pathways. Our results illuminate the mechanisms of Fgf21 in endurance-exercise-induced fiber-type conversion and suggest a potential use of Fgf21 in improving muscle health and combating fatigue.

CCE and EODF as two distinct non-shivering thermogenesis models inducing weight loss.

Increasing energy expenditure and reducing energy intake are considered two classical methods to induce weight loss. Weight loss through physical methods instead of drugs has been a popular research topic nowadays, but how these methods function in adipose and cause weight loss in body remains unclear. In this study, we set up chronic cold exposure (CCE) and every-other-day fasting (EODF) as two distinct models in long-term treatment to induce weight loss, recording their own characteristics in changes of body temperature and metabolism. We investigated the different types of non-shivering thermogenesis induced by CCE and EODF in white and brown adipose tissue through sympathetic nervous system (SNS), creatine-driven pathway, and fibroblast growth factor 21 (FGF21)-adiponectin axis. CCE and EODF could reduce body weight, lipid composition, increase insulin sensitivity, promote the browning of white fat, and increase the expression of endogenous FGF21 in adipose tissue. CCE stimulated the SNS and increased the thermogenic function of brown fat, and EODF increased the activity of protein kinase in white fat. In this study, we further explained the thermogenic mechanism function in adipose and metabolic benefits of the stable phenotype through physical treatments used for weight loss, providing more details for the literature on weight loss models. The influence on metabolism, non-shivering thermogenesis, endogenous FGF21, and ADPN changes in the long-term treatment of distinct methods (increasing energy expenditure and decreasing energy intake) to induce weight loss.

Generalizability and Diagnostic Performance of AI Models for Thyroid US.

Background Artificial intelligence (AI) models have improved US assessment of thyroid nodules; however, the lack of generalizability limits the application of these models. Purpose To develop AI models for segmentation and classification of thyroid nodules in US using diverse data sets from nationwide hospitals and multiple vendors, and to measure the impact of the AI models on diagnostic performance. Materials and Methods This retrospective study included consecutive patients with pathologically confirmed thyroid nodules who underwent US using equipment from 12 vendors at 208 hospitals across China from November 2017 to January 2019. The detection, segmentation, and classification models were developed based on the subset or complete set of images. Model performance was evaluated by precision and recall, Dice coefficient, and area under the receiver operating characteristic curve (AUC) analyses. Three scenarios (diagnosis without AI assistance, with freestyle AI assistance, and with rule-based AI assistance) were compared with three senior and three junior radiologists to optimize incorporation of AI into clinical practice. Results A total of 10 023 patients (median age, 46 years [IQR 37-55 years]; 7669 female) were included. The detection, segmentation, and classification models had an average precision, Dice coefficient, and AUC of 0.98 (95% CI: 0.96, 0.99), 0.86 (95% CI: 0.86, 0.87), and 0.90 (95% CI: 0.88, 0.92), respectively. The segmentation model trained on the nationwide data and classification model trained on the mixed vendor data exhibited the best performance, with a Dice coefficient of 0.91 (95% CI: 0.90, 0.91) and AUC of 0.98 (95% CI: 0.97, 1.00), respectively. The AI model outperformed all senior and junior radiologists (P < .05 for all comparisons), and the diagnostic accuracies of all radiologists were improved (P < .05 for all comparisons) with rule-based AI assistance. Conclusion Thyroid US AI models developed from diverse data sets had high diagnostic performance among the Chinese population. Rule-based AI assistance improved the performance of radiologists in thyroid cancer diagnosis. © RSNA, 2023 Supplemental material is available for this article.

A deep learning model for the differential diagnosis of benign and malignant salivary gland tumors based on ultrasound imaging and clinical data.

Background: The preoperative differentiation between benign parotid gland tumors (BPGTs) and malignant parotid gland tumors (MPGTs) is of great significance for therapeutic decision-making. Deep learning (DL), an artificial intelligence algorithm based on neural networks, can help overcome inconsistencies in conventional ultrasonic (CUS) examination outcomes. Therefore, as an auxiliary diagnostic tool, DL can support accurate diagnosis using massive ultrasonic (US) images. This current study developed and validated a DL-based US diagnosis for the preoperative differentiation of BPGT from MPGT. Methods: A total of 266 patients, including 178 patients with BPGT and 88 patients with MPGT, were consecutively identified from a pathology database and enrolled in this study. Ultimately, considering the limitations of the DL model, 173 patients were selected from the 266 patients and divided into 2 groups: a training set, and a testing set. US images of the 173 patients were used to construct the training set (including 66 benign and 66 malignant PGTs) and testing set (consisting of 21 benign and 20 malignant PGTs). These were then preprocessed by normalizing the grayscale of each image and reducing noise. Processed images were imported into the DL model, which was then trained to predict the images from the testing set and evaluated for performance. Based on the training and validation datasets, the diagnostic performance of the 3 models was assessed and verified using receiver operating characteristic (ROC) curves. Ultimately, before and after combining the clinical data, we compared the area under the curve (AUC) and diagnostic accuracy of the DL model with the opinions of trained radiologists to evaluate the application value of the DL model in US diagnosis. Results: The DL model showed a significantly higher AUC value compared to doctor 1 + clinical data, doctor 2 + clinical data, and doctor 3 + clinical data (AUC =0.9583 vs. 0.6250, 0.7250, and 0.8025 respectively; all P<0.05). In addition, the sensitivity of the DL model was higher than the sensitivities of the doctors combined with clinical data (97.2% vs. 65%, 80%, and 90% for doctor 1 + clinical data, doctor 2 + clinical data, and doctor 3 + clinical data, respectively; all P<0.05). Conclusions: The DL-based US imaging diagnostic model has excellent performance in differentiating BPGT from MPGT, supporting its value as a diagnostic tool for the clinical decision-making process.

Bone marrow mesenchymal stem cell-derived exosomes reduce insulin resistance and obesity in mice via the PI3K/AKT signaling pathway.

Obesity is a common chronic metabolic disease that induces chronic systemic inflammation in the body, eventually leading to related complications such as insulin resistance (IR), type 2 diabetes mellitus, and metabolic syndromes such as cardiovascular disease. Exosomes transfer bioactive substances to neighboring or distal cells through autosomal, paracrine, or distant secretion, regulating the gene and protein expression levels of receptor cells. In this study, we investigated the effect of mouse bone marrow mesenchymal stem cell-derived exosomes (BMSC-Exos) on high-fat diet obese mice and mature 3T3-L1 adipocyte models of IR. BMSC-Exo treatment of obese mice promoted their metabolic homeostasis, including reduction of obesity, inhibition of M1-type proinflammatory factor expression, and improvement of insulin sensitivity. In vitro analysis revealed that BMSC-Exos improved IR and lipid droplet accumulation in mature 3T3-L1 adipocytes treated with palmitate (PA). Mechanistically, BMSC-Exos cause increased glucose uptake and improved IR in high-fat chow-fed mice and PA-acting 3T3-L1 adipocytes by activating the phosphoinositide 3-kinases/protein kinase B (PI3K/AKT) signaling pathway and upregulating glucose transporter protein 4 (GLUT4) expression. This study offers a new perspective for the development of treatments for IR in obese and diabetic patients.

Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis.

Elastography ultrasound (EUS) imaging is a vital ultrasound imaging modality. The current use of EUS faces many challenges, such as vulnerability to subjective manipulation, echo signal attenuation, and unknown risks of elastic pressure in certain delicate tissues. The hardware requirement of EUS also hinders the trend of miniaturization of ultrasound equipment. Here we show a cost-efficient solution by designing a deep neural network to synthesize virtual EUS (V-EUS) from conventional B-mode images. A total of 4580 breast tumor cases were collected from 15 medical centers, including a main cohort with 2501 cases for model establishment, an external dataset with 1730 cases and a portable dataset with 349 cases for testing. In the task of differentiating benign and malignant breast tumors, there is no significant difference between V-EUS and real EUS on high-end ultrasound, while the diagnostic performance of pocket-sized ultrasound can be improved by about 5% after V-EUS is equipped.

An MRI-based Radiomics Approach to Improve Breast Cancer Histological Grading.

RATIONALE AND OBJECTIVES: Nottingham histological grade (NHG) 2 breast cancer has an intermediate risk of recurrence, which is not informative for therapeutic decision-making. We sought to develop and independently validate an MRI-based radiomics signature (Rad-Grade) to improve prognostic re-stratification of NHG 2 tumors. MATERIALS AND METHODS: Nine hundred-eight subjects with invasive breast cancer and preoperative MRI scans were retrospectively obtained. The NHG 1 and 3 tumors were randomly split into training and independent test cohort, with the NHG 2 as the prognostic validation set. From MRI image features, a radiomics-based signature predictive of the histological grade was built by use of the LASSO logistic regression algorithm. The model was developed for identifying NHG 1 and 3 radiological patterns, followed with re-stratification of NHG 2 tumors into Rad-Grade (RG)2-low (NHG 1-like) and RG2-high (NHG 3-like) subtypes using the learned patterns, and the prognostic value was assessed in terms of recurrence-free survival (RFS). RESULTS: The Rad-Grade showed independent prognostic value for re-stratification of NHG 2 tumors, where RG2-high had an increased risk for recurrence (HR 2.20, 1.10-4.40, p = 0.026) compared with RG2-low after adjusting for established risk factors. RG2-low shared similar phenotypic characteristics and RFS outcomes with NHG 1, and RG2-high with NHG 3, revealing that the model captures radiomic features in NHG 2 that are associated with different aggressiveness. The prognostic value of Rad-Grade was further validated in the NHG2 ER+ (HR 2.53, 1.13-5.56, p = 0.023) and NHG 2 ER+LN- (HR 5.72, 1.24-26.44, p = 0.025) subgroups, and in specific treatment contexts. CONCLUSION: The radiomics-based re-stratification of NHG 2 tumors offers a cost-effective promising alternative to gene expression profiling for tumor grading and thus may improve clinical decisions.

Safety findings after intravenous administration of sulfur hexafluoride microbubbles to 463,434 examinations at 24 centers.

OBJECTIVES: We aimed to evaluate the safety of the ultrasound contrast agent sulfur hexafluoride microbubbles in a large group of patients referred for routine contrast-enhanced ultrasound (CEUS). METHODS: A retrospective assessment was made of all patients that received sulfur hexafluoride microbubbles intravenously for CEUS at 24 centers between January 2006 and April 2019. Patient demographic details, examination type, and the dose of sulfur hexafluoride microbubbles administered were recorded with specific adverse events (AEs) documentation tools at each center. All AEs were recorded as serious or non-serious. Non-serious AEs were classified by intensity as mild, moderate, or severe according to ACR criteria. The frequencies of AEs across patient subgroups were compared using the chi-square test. RESULTS: A total of 463,434 examinations were evaluated. Overall, 157 AEs (153 [0.033%] non-serious; 4 [0.001%] serious) were reported after sulfur hexafluoride microbubbles administration, giving an AE frequency of 0.034% (157/463,434). Among the non-serious AEs, 66 (0.014%) were mild, 70 (0.015%) moderate, and 17 (0.004%) severe in intensity. The liver was the most common examination site, presenting an AE frequency of 0.026%. The highest AE frequency (0.092%) was for patients undergoing CEUS for vascular disease. There were no significant gender differences in either the total number or the severity of non-serious AEs (chi-square = 2.497, p = 0.287). The onset of AEs occurred within 30 min of sulfur hexafluoride microbubbles administration in 91% of cases. CONCLUSION: The frequency of AEs to sulfur hexafluoride microbubbles is very low and severe reactions are rare, confirming that sulfur hexafluoride microbubbles are appropriate for routine CEUS applications. KEY POINT: • The frequency of AEs to sulfur hexafluoride microbubbles is very low and severe reactions are rare.

Expression analysis of irisin during different development stages of skeletal muscle in mice.

BACKGROUND: As a newly discovered muscle factor secreted by skeletal muscle cells, irisin is a polypeptide fragment formed from hydrolysis of fibronectin type Ⅲ domain-containing protein 5 (FNDC5). Irisin can promote beigeing of white adipose tissue (WAT) and regulate glucose and lipid metabolisms. However, the functions of irisin in skeletal muscle development remain largely unknown. In order to characterize the expression of irisin, this study investigated the expression of irisin precursor FNDC5 in myoblasts and skeletal muscles during different developmental stages of SPF mice. RESULTS: The Western blot, quantitative real-time PCR (qRT-PCR), and immunofluorescence assay results showed that FNDC5 was expressed in all the developmental stages of myoblasts and gastrocnemius, but its expression differed at different stages. FNDC5 protein exhibited the highest expression in gastrocnemius of sexually mature mice, followed by elderly mice and adolescent mice, and it displayed the lowest expression in pups. Additionally, FNDC5 protein was mainly expressed in cytoplasm, and it had the highest expression in primary myoblasts, followed by the myotubes with the lowest expression in C2C12 myogenic cells. CONCLUSIONS: Overall, FNDC5 was mainly expressed in cytoplasm and extracellular matrix with different expression levels at different developmental stages of skeletal muscle cells and tissues in mice. This study will provide new strategies for promoting skeletal muscle development and treating muscle- and metabolism-related disease by using irisin.

Myoblast-derived exosomes promote the repair and regeneration of injured skeletal muscle in mice.

When skeletal muscle is damaged, satellite cells (SCs) are activated to proliferate rapidly and fuse with the damaged muscle fibers to form new muscle fibers, thereby promoting muscle growth and remodeling and repair of trauma. Exosomes from differentiating human skeletal muscle cells trigger myogenesis of stem cells and provide biochemical cues for skeletal muscle regeneration. Therefore, we hypothesized that, when muscles are injured, myoblast-derived exosomes may regulate muscle repair and regeneration. Here, we investigated the underlying mechanism by applying C2C12-derived exosomes to injured mouse skeletal muscles. The expression levels of skeletal muscle regeneration factors paired box 7 and lipid-promoting factor peroxisome proliferator-activated receptor γ were upregulated, whereas the expression levels of fibrosis factors collagen-1 and α-smooth muscle actin decreased. The expression of proliferating cell nuclear antigen was elevated after applying C2C12-derived exosomes to SCs. Application of C2C12-derived exosomes to fibro-adipogenic progenitors resulted in an increase in peroxisome proliferator-activated receptor γ expression and adipogenesis capacity, whereas α-smooth muscle actin expression and fibrosis capacity decreased. Analysis of the transcriptome and proteome of SCs after treatment with exosomes showed the involvement of multiple biological processes, including proliferation and differentiation of SCs, muscle regeneration, skeletal muscle atrophy, and the inflammatory response after muscle injury. Hence, our data suggest that C2C12-derived exosomes can promote the regeneration of skeletal muscle fibers, accelerate the production of fat from damaged muscles, inhibit the fibrosis of damaged muscles, and accelerate injury repair, which is related to exosome-mediated regulation of the proliferation of SCs, differentiation of fibro-adipogenic progenitors, and modulation of SC mRNA expression and protein formation and decomposition.

Three-dimensional ultrasound integrating nomogram and the blood flow image for prostate cancer diagnosis and biopsy: A retrospective study.

Backgrounds: Prostate cancer (PCa) is the second most common male cancer in the world and based on its high prevalence and overwhelming effect on patients, more precise diagnostic and therapeutic methods are essential research topics. As such, this study aims to evaluate the value of three-dimensional transrectal ultrasound (3D-TRUS) in the detection, diagnosis and biopsy of PCa, and to provide a basis for clinical practice of PCa. Methods: Retrospective analysis and comparison of a total of 401 male patients who underwent prostate TRUS in our hospital from 2019 to 2020 were conducted, with all patients having prostate biopsy. Nomogram was used to estimate the probability of different ultrasound signs in diagnosing prostate cancer. The ROC curve was used to estimate the screening and diagnosis rates of 3D-TRUS, MRI and TRUS for prostate cancer. Results: A total of 401 patients were randomly divided into two groups according to different methods of prostate ultrasonography, namely the TRUS group (251 patients) and the 3D-TRUS group (150 patients). Of these cases, 111 patients in 3D-TRUS group underwent MRI scan. The nomogram further determined the value of 3D-TRUS for prostate cancer. The ROC AUC of prostate cancer detected by TRUS, MRI and 3D-TRUS was 0.5580, 0.6216 and 0.6267 respectively. Biopsy complications were lower in 3D-TRUS group than TRUS group, which was statistically significant (P<0.005). Conclusions: The accuracy of 3D-TRUS was higher in diagnosis and biopsy of prostate cancer. Meanwhile, the positive rate of biopsy could be improved under direct visualization of 3D-TRUS, and the complications could be decreased markedly. Therefore, 3D-TRUS was of high clinical value in diagnosis and biopsy of prostate cancer.

Irisin promotes the browning of white adipocytes tissue by AMPKα1 signaling pathway.

The development of white adipose tissue (WAT) browning helps to protect animals from cold conditions and prevent obesity. AMPKα1 has been involved in the process of white adipocytes browning. Although Irisin plays a vital role in the browning of WAT, the detailed regulatory mechanism of Irisin inducing the browning of WAT remains unclear. Herein, we firstly investigated the potential roles of differentiation and Irisin in regulating the browning of 3T3-L1 cells. The results found that they could significantly increase the number of lipid droplets and upregulate the expression levels of UCP1, PGC-1α, PRDM16, and p-AMPKα1. Then we proved the effectiveness of the AMPKα1 signaling pathway in the process of Irisin inducing the browning of 3T3-L1 cells. Compared with si-NC, si-AMPKα1 not only decreased the number of Irisin-induced lipid droplets, but also attenuated the expression of Irisin-induced UCP1, PGC-1α, and PRDM16 protein and mRNA levels in 3T3-L1 cells. Furthermore, the results showed that Irisin increased the positive distribution of UCP1 and PGC-1α, and upregulated the expression of UCP1, PGC-1α, and PRDM16 at both protein and mRNA levels in WAT. Once siRNA treated mice, the facilitation of Irisin on UCP1 and PGC-1α in si-AMPKα1-injected mice was lower than that in si-NC-injected mice. Compared with si-NC, si-AMPKα1 significantly downregulated the expression of UCP1, PGC-1α, and PRDM16 in Irisin-injected mice. Taken together, our results demonstrate that Irisin activates the AMPKα1 pathway to promote the browning of WAT by upregulating the mRNA and protein levels of UCP1, PGC-1α, and PRDM16.

Novel Human Artificial Intelligence Hybrid Framework Pinpoints Thyroid Nodule Malignancy and Identifies Overlooked Second-Order Ultrasonographic Features.

We present a Human Artificial Intelligence Hybrid (HAIbrid) integrating framework that reweights Thyroid Imaging Reporting and Data System (TIRADS) features and the malignancy score predicted by a convolutional neural network (CNN) for nodule malignancy stratification and diagnosis. We defined extra ultrasonographical features from color Doppler images to explore malignancy-relevant features. We proposed Gated Attentional Factorization Machine (GAFM) to identify second-order interacting features trained via a 10 fold distribution-balanced stratified cross-validation scheme on ultrasound images of 3002 nodules all finally characterized by postoperative pathology (1270 malignant ones), retrospectively collected from 131 hospitals. Our GAFM-HAIbrid model demonstrated significant improvements in Area Under the Curve (AUC) value (p-value < 10−5), reaching about 0.92 over the standalone CNN (~0.87) and senior radiologists (~0.86), and identified a second-order vascularity localization and morphological pattern which was overlooked if only first-order features were considered. We validated the advantages of the integration framework on an already-trained commercial CNN system and our findings using an extra set of ultrasound images of 500 nodules. Our HAIbrid framework allows natural integration to clinical workflow for thyroid nodule malignancy risk stratification and diagnosis, and the proposed GAFM-HAIbrid model may help identify novel diagnosis-relevant second-order features beyond ultrasonography.

Diagnosis of rectal cancer based on the Xception-MS network.

Objective. Accurate T staging of rectal cancer based on ultrasound images is convenient for doctors to determine the appropriate treatment. To effectively solve the problems of low efficiency and accuracy of traditional methods for T staging diagnosis of rectal cancer, a deep-learning-based Xception-MS diagnostic model is proposed in this paper.Approach. The proposed diagnostic model consists of three steps. First, the model preprocesses rectal cancer images to solve the problem of data imbalance and deficiency of sample size, and reduces the risk of model overfitting. Second, a new Xception-MS network with stronger feature extraction capability, which is a combination of the Xception network and MS module, is proposed. The MS module is a new function module that can more effectively extract multi-scale information from rectal cancer images. In addition, to solve the deficiency of the small sample size of rectal cancer, the proposed network is combined with transfer learning technology. At last, the output layer of the network is modified, in which the global average pooling and a fully connected softmax layer are employed to replace the original ones, and then the rectal cancer 4 classification (T1, T2, T3, T4 staging) is output.Main results. Experiments of rectal cancer T staging are conducted on a dataset of 1078 rectal cancer images in 4 categories collected from the Department of Colorectal Surgery of the Third Affiliated Hospital of Kunming Medical University. The experimental results show that the accuracy, precision, recall andF1 values obtained by the model are 94.66%, 94.70%, 94.65%, and 94.67%, respectively.Significance. The experimental results show that our model is superior to the existing classification models, can effectively and automatically classify ultrasound images of rectal cancer, and can better assist doctors in the diagnosis of rectal cancer.