Tracing the origin of alveolar stem cells in lung repair and regeneration.

Alveolar type 2 (AT2) cells are stem cells of the alveolar epithelia. Previous genetic lineage tracing studies reported multiple cellular origins for AT2 cells after injury. However, conventional lineage tracing based on Cre-loxP has the limitation of non-specific labeling. Here, we introduced a dual recombinase-mediated intersectional genetic lineage tracing approach, enabling precise investigation of AT2 cellular origins during lung homeostasis, injury, and repair. We found AT1 cells, being terminally differentiated, did not contribute to AT2 cells after lung injury and repair. Distinctive yet simultaneous labeling of club cells, bronchioalveolar stem cells (BASCs), and existing AT2 cells revealed the exact contribution of each to AT2 cells post-injury. Mechanistically, Notch signaling inhibition promotes BASCs but impairs club cells' ability to generate AT2 cells during lung repair. This intersectional genetic lineage tracing strategy with enhanced precision allowed us to elucidate the physiological role of various epithelial cell types in alveolar regeneration following injury.

Continuous genetic monitoring of transient mesenchymal gene activities in distal tubule and collecting duct epithelial cells during renal fibrosis.

Epithelial cells (ECs) have been proposed to contribute to myofibroblasts or fibroblasts through epithelial-mesenchymal transition (EMT) during renal fibrosis. However, since EMT may occur dynamically, transiently, and reversibly during kidney fibrosis, conventional lineage tracing based on Cre-loxP recombination in renal ECs could hardly capture the transient EMT activity, yielding inconsistent results. Moreover, previous EMT research has primarily focused on renal proximal tubule ECs, with few reports of distal tubules and collecting ducts. Here, we generated dual recombinases-mediated genetic lineage tracing systems for continuous monitoring of transient mesenchymal gene expression in E-cadherin+ and EpCAM+ ECs of distal tubules and collecting ducts during renal fibrosis. Activation of key EMT-inducing transcription factor (EMT-TF) Zeb1 and mesenchymal markers αSMA, vimentin, and N-cadherin, were investigated following unilateral ureteral obstruction (UUO). Our data revealed that E-cadherin+ and EpCAM+ ECs did not transdifferentiate into myofibroblasts, nor transiently expressed these mesenchymal genes during renal fibrosis. In contrast, in vitro a large amount of cultured renal ECs upregulated mesenchymal genes in response to TGF-ß, a major inducer of EMT.

Lenvatinib Suppresses Protein Kinase B Signaling and Induces Apoptosis in Osteosarcoma Cells.

BACKGROUND/AIM: Lenvatinib, an oral multikinase inhibitor, has demonstrated promising activity in patients with osteosarcoma (OS). Therefore, it is worth exploring the inhibitory efficacy and mechanism of action of lenvatinib in osteosarcoma. The primary goal of this study was to examine the inhibitory effectiveness and mechanism of lenvatinib on the growth and invasion of OS cells. MATERIALS AND METHODS: The effects of lenvatinib on cell viability, apoptosis, protein kinase B (AKT) activation, its downstream effector proteins involved in tumor progression, and invasion capability were assessed using MTT assay, flow cytometry, western blotting, and invasion/migration assay on U-2 OS and MG63 cells. RESULTS: Lenvatinib effectively induced cytotoxicity, apoptosis, as well as extrinsic and intrinsic apoptotic signaling in OS cells. Lenvatinib also significantly decreased the invasion/migration capability, AKT activation, and downstream effector proteins. CONCLUSION: The anti-OS effect of lenvatinib may be associated with the induction of apoptosis and the inactivation of AKT.

Transfer learning with CNNs for efficient prostate cancer and BPH detection in transrectal ultrasound images.

Early detection of prostate cancer (PCa) and benign prostatic hyperplasia (BPH) is crucial for maintaining the health and well-being of aging male populations. This study aims to evaluate the performance of transfer learning with convolutional neural networks (CNNs) for efficient classification of PCa and BPH in transrectal ultrasound (TRUS) images. A retrospective experimental design was employed in this study, with 1380 TRUS images for PCa and 1530 for BPH. Seven state-of-the-art deep learning (DL) methods were employed as classifiers with transfer learning applied to popular CNN architectures. Performance indices, including sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), Kappa value, and Hindex (Youden's index), were used to assess the feasibility and efficacy of the CNN methods. The CNN methods with transfer learning demonstrated a high classification performance for TRUS images, with all accuracy, specificity, sensitivity, PPV, NPV, Kappa, and Hindex values surpassing 0.9400. The optimal accuracy, sensitivity, and specificity reached 0.9987, 0.9980, and 0.9980, respectively, as evaluated using twofold cross-validation. The investigated CNN methods with transfer learning showcased their efficiency and ability for the classification of PCa and BPH in TRUS images. Notably, the EfficientNetV2 with transfer learning displayed a high degree of effectiveness in distinguishing between PCa and BPH, making it a promising tool for future diagnostic applications.

Serum ferritin level is an effective prognostic factor for lung cancer immunotherapy.

Immunotherapy of lung cancer has achieved promising clinical results. However, it is urgent to develop predictive biomarkers for effective immunotherapy. While ferroptosis plays a critical role in immunotherapy efficacy, ferritin is an important regulatory factor. We, therefore, hypothesize that basal serum ferritin levels before immunotherapy and their corresponding changes during immunotherapy can be useful predictors of immunotherapy response in patients with lung cancer. We measured serum ferritin levels in 107 patients with lung cancer before and during immune checkpoint blockade treatments and studied the correlation between ferritin levels, response rate, and survival. Moreover, the correlation between basal ferritin and PD-L1 expression, tumor stages and pathological types was also analyzed. Patients with lower basal serum ferritin levels before immunotherapy had longer progression-free survival (PFS) (median 7 vs 4 months, P = .023) and higher disease control rate (DCR) (X2 = 4.837, P = .028), those with downregulated serum ferritin levels during immunotherapy correlated with longer PFS (median 9.5 vs 4 months, P < .001) and higher DCR (X2 = 6.475, P = .011). However, the "integrated factor", which was calculated as the combination of lower basal serum ferritin levels before immunotherapy and downregulated serum ferritin levels during immunotherapy, correlated with prolonged PFS (P < .001). Multivariate analyses revealed that the basal serum ferritin levels before immunotherapy and the corresponding changes during immunotherapy were both strong independent prognostic factors (hazard ratio (HR) = 1.60, P = .041; HR = 2.65, P = .001). These findings suggest that serum ferritin levels can be used as a prognostic biomarker for lung cancer in predicting immunotherapy efficacy.

An inducible hACE2 transgenic mouse model recapitulates SARS-CoV-2 infection and pathogenesis in vivo.

The classical manifestation of COVID-19 is pulmonary infection. After host cell entry via human angiotensin-converting enzyme II (hACE2), the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus can infect pulmonary epithelial cells, especially the AT2 (alveolar type II) cells that are crucial for maintaining normal lung function. However, previous hACE2 transgenic models have failed to specifically and efficiently target the cell types that express hACE2 in humans, especially AT2 cells. In this study, we report an inducible, transgenic hACE2 mouse line and showcase three examples for specifically expressing hACE2 in three different lung epithelial cells, including AT2 cells, club cells, and ciliated cells. Moreover, all these mice models develop severe pneumonia after SARS-CoV-2 infection. This study demonstrates that the hACE2 model can be used to precisely study any cell type of interest with regard to COVID-19-related pathologies.

Intercellular genetic tracing of cardiac endothelium in the developing heart.

Cardiac resident macrophages play vital roles in heart development, homeostasis, repair, and regeneration. Recent studies documented the hematopoietic potential of cardiac endothelium that supports the generation of cardiac macrophages and peripheral blood cells in mice. However, the conclusion was not strongly supported by previous genetic tracing studies, given the non-specific nature of conventional Cre-loxP tracing tools. Here, we develop an intercellular genetic labeling system that can permanently trace heart-specific endothelial cells based on cell-cell interaction in mice. Results from cell-cell contact-mediated genetic fate mapping demonstrate that cardiac endothelial cells do not exhibit hemogenic potential and do not contribute to cardiac macrophages or other circulating blood cells. This Matters Arising paper is in response to Shigeta et al. (2019), published in Developmental Cell. See also the response by Liu and Nakano (2023), published in this issue.

Allyl isothiocyanate inhibits cell migration and invasion in human gastric cancer AGS cells via affecting PI3K/AKT and MAPK signaling pathway in vitro.

Metastasis is commonly occurred in gastric cancer, and it is caused and responsible for one of the major cancer-related mortality in gastric cancer patients. Allyl isothiocyanate (AITC), a natural product, exhibits anticancer activities in human many cancer cells, including gastric cancer. However, no available report shows AITC inhibits gastric cancer cell metastasis. Herein, we evaluated the impact of AITC on cell migration and invasion of human gastric cancer AGS cells in vitro. AITC at 5-20 µM did not induce significant cell morphological damages observed by contrast-phase microscopy but decreased cell viability assayed by flow cytometry. After AGS cells were further examined by atomic force microscopy (AFM), which indicated AITC affected cell membrane and morphology in AGS cells. AITC significantly suppressed cell motility examined by scratch wound healing assay. The results of the gelatin zymography assay revealed that AITC significantly suppressed the MMP-2 and MMP-9 activities. In addition, AITC suppressed cell migration and invasion were performed by transwell chamber assays at 24 h in AGS cells. Furthermore, AITC inhibited cell migration and invasion by affecting PI3K/AKT and MAPK signaling pathways in AGS cells. The decreased expressions of p-AKTThr308 , GRB2, and Vimentin in AGS cells also were confirmed by confocal laser microscopy. Our findings suggest that AITC may be an anti-metastasis candidate for human gastric cancer treatment.

The impact of surgical learning curve on short-term outcomes after bilateral lung transplantation: results from a multidisciplinary surgical team.

OBJECTIVES: The aim of this study was to examine the impact of surgical learning curve on short-term clinical outcomes of patients after bilateral lung transplantation (LTx) performed by a surgical multidisciplinary team (MDT). METHODS: Forty-two patients underwent double LTx from December 2016 to October 2021. All procedures were performed by a surgical MDT in a newly established LTx program. The time required for bronchial, left atrial cuff and pulmonary artery anastomoses was the main end point to assess surgical proficiency. The associations between the surgeon's experience and procedural duration were examined by linear regression analysis. We employed the simple moving average technique to generate learning curves and evaluated short-term outcomes before and after achieving surgical proficiency. RESULTS: Both total operating time and total anastomosis time were inversely associated with the surgeon's experience. On analysing the learning curve for bronchial, left atrial cuff and pulmonary artery anastomoses using moving averages, the inflection points occurred at 20, 15 and 10 cases, respectively. To assess the learning curve effect, the study cohort was divided into early (cases 1-20) and late (cases 21-42) groups. Short-term outcomes-including intensive care unit stay, in-hospital stay and severe complications-were significantly more favourable in the late group. Furthermore, there was a notable tendency for patients in the late group to experience a decreased duration of mechanical ventilation along with reduced instances of grade 3 primary graft dysfunction. CONCLUSIONS: A surgical MDT can perform double LTx safely after 20 procedures.

Bipotent transitional liver progenitor cells contribute to liver regeneration.

Following severe liver injury, when hepatocyte-mediated regeneration is impaired, biliary epithelial cells (BECs) can transdifferentiate into functional hepatocytes. However, the subset of BECs with such facultative tissue stem cell potential, as well as the mechanisms enabling transdifferentiation, remains elusive. Here we identify a transitional liver progenitor cell (TLPC), which originates from BECs and differentiates into hepatocytes during regeneration from severe liver injury. By applying a dual genetic lineage tracing approach, we specifically labeled TLPCs and found that they are bipotent, as they either differentiate into hepatocytes or re-adopt BEC fate. Mechanistically, Notch and Wnt/ß-catenin signaling orchestrate BEC-to-TLPC and TLPC-to-hepatocyte conversions, respectively. Together, our study provides functional and mechanistic insights into transdifferentiation-assisted liver regeneration.

Learning curve for open surgical repair of acute type A aortic dissection.

There is scarce evidence about the surgeon learning curve of acute type A aortic dissection surgery and whether the optimal procedure number exists when training a cardiovascular surgeon. A total of 704 patients with acute type A aortic dissection surgery performed by 17 junior surgeons who can identify their first career surgery from January 1, 2005, to December 31, 2018, are included. The surgeon experience volume is defined as the cumulative number of acute type A aortic dissection surgery of the surgeon since January 1, 2005. The primary outcome was in-hospital mortality. The possibility of non-linearity and cutoffs for surgeon experience volume level was explored using a restricted cubic spline model. The results revealed that more surgeon experience volume is significantly correlated to a lower in-hospital mortality rate (r = - 0.58, P = 0.010). The RCS model shows for an operator who reaches 25 cumulative volumes of acute type A aortic dissection surgery, the average in-hospital mortality rate of the patients can be below 10%. Furthermore, the longer duration from the 1st to 25th operations of the surgeon is significantly correlated to a higher average in-hospital mortality rate of the patients (r = 0.61, p = 0.045). Acute type A aortic dissection surgery has a prominent learning curve in terms of improving clinical outcomes. The findings suggest fostering high-volume surgeons at high-volume hospitals can achieve optimal clinical outcomes.

Effect of Sugammadex During Transcranial Electrical Motor Evoked Potentials Monitoring in Spinal Surgery: A Randomized Controlled Trial.

INTRODUCTION: Neuromuscular blockade suppresses transcranial electrical motor evoked potential (TceMEP) amplitude and is usually avoided during TceMEP monitoring. In this randomized controlled trial, we investigated whether rocuronium-induced suppression of TceMEP amplitude could be reversed by sugammadex in patients undergoing spine surgery. METHODS: Seventy-six patients undergoing spinal surgery were randomly allocated into sugammadex and control groups. In the sugammadex group, a rocuronium infusion was titrated to maintain moderate neuromuscular blockade (2 twitches on train-of-four) until dural opening when the rocuronium infusion was discontinued and 2 mg/kg sugammadex administered. In the control group, no neuromuscular blockade was administered after induction of anesthesia. The primary outcome was a comparison between sugammadex and control groups of mean TceMEP amplitudes in the abductor pollicis brevis muscles of both upper extremities 5 minutes after dural. Secondary outcomes included TceMEP amplitudes at 10, 20, 30, and 60 minutes after dural opening. RESULTS: Sixty-six patients were included in the analysis. TceMEP amplitudes were significantly greater in the sugammadex group (629 µV, interquartile range: 987 µV) than in the control group (502 µV, interquartile range: 577 µV; P =0.033) at 5 minutes after dural opening. TceMEP amplitudes were also greater in the sugammadex group at 10 minutes ( P =0.0010), 20 minutes ( P =0.003), 30 minutes ( P =0.001), and 60 minutes ( P =0.003) after dural opening. CONCLUSIONS: Moderate neuromuscular blockade induced by continuous infusion of rocuronium was effectively reversed by sugammadex. This suggests that sugammadex could be used to enhance TceMEP waveform monitoring during spine surgery requiring muscle relaxation.

Bioprosthetic versus mechanical mitral valve replacements in patients with rheumatic heart disease.

BACKGROUND: Rheumatic heart disease (RHD) remains a critical problem in developed countries. Few studies have compared the long-term outcomes of bioprosthetic valves and mechanical valves in patients with RHD who have received mitral valve (MV) replacement. METHODS: Patients with RHD who received MV replacement with bioprosthetic or mechanical valves were identified between 2000 and 2013 from Taiwan's National Health Insurance Research Database. The primary late outcomes of interest were all-cause mortality and redo MV surgery. Propensity score matching at a 1:1 ratio was performed. RESULTS: We identified 3638 patients with RHD who underwent MV replacement. Among those patients, 1075 (29.5%) and 2563 (70.5%) chose a bioprosthetic valve and mechanical valve, respectively. After matching, 788 patients were assigned to each group. No significant difference in the risk of in-hospital mortality was observed between groups (P = .920). Higher risks of all-cause mortality (10-year actuarial estimates: 50.6% vs 45.5%; hazard ratio, 1.19; 95% confidence interval, 1.01-1.41; P = .040) and MV reoperation (10-year actuarial estimates: 8.9% vs 0.93%; subdistribution hazard ratio, 4.56; 95% confidence interval, 1.71-12.17; P <.01) were observed in the bioprosthetic valve group. Furthermore, the relative mortality benefit associated with mechanical valves was more apparent in younger patients and the beneficial effect persisted until approximately 65 years of age. CONCLUSIONS: In the patients with RHD who underwent MV replacement, mechanical valves were associated with more favorable long-term outcomes in patients younger than the age of 65 years.

Monitoring of cell-cell communication and contact history in mammals.

Monitoring of cell-cell communication in multicellular organisms is fundamental to understanding diverse biological processes such as embryogenesis and tumorigenesis. To track cell-cell contacts in vivo, we developed an intercellular genetic technology to monitor cell-cell contact and to trace cell contact histories by permanently marking contacts between cells. In mice, we engineered an artificial Notch ligand into one cell (the sender cell) and an artificial receptor into another cell (the receiver cell). Contact between the sender and receiver cells triggered a synthetic Notch signaling that activated downstream transcriptional programs in the receiver cell, thereby transiently or permanently labeling it. In vivo cell-cell contact was observed during development, tissue homeostasis, and tumor growth. This technology may be useful for studying dynamic in vivo cell-cell contacts and cell fate plasticity.

Using Deep Neural Network Approach for Multiple-Class Assessment of Digital Mammography.

According to the Health Promotion Administration in the Ministry of Health and Welfare statistics in Taiwan, over ten thousand women have breast cancer every year. Mammography is widely used to detect breast cancer. However, it is limited by the operator's technique, the cooperation of the subjects, and the subjective interpretation by the physician. It results in inconsistent identification. Therefore, this study explores the use of a deep neural network algorithm for the classification of mammography images. In the experimental design, a retrospective study was used to collect imaging data from actual clinical cases. The mammography images were collected and classified according to the breast image reporting and data-analyzing system (BI-RADS). In terms of model building, a fully convolutional dense connection network (FC-DCN) is used for the network backbone. All the images were obtained through image preprocessing, a data augmentation method, and transfer learning technology to build a mammography image classification model. The research results show the model's accuracy, sensitivity, and specificity were 86.37%, 100%, and 72.73%, respectively. Based on the FC-DCN model framework, it can effectively reduce the number of training parameters and successfully obtain a reasonable image classification model for mammography.

Segmentation of liver tumors with abdominal computed tomography using fully convolutional networks.

BACKGROUND: Dividing liver organs or lesions depicting on computed tomography (CT) images could be applied to help tumor staging and treatment. However, most existing image segmentation technologies use manual or semi-automatic analysis, making the analysis process costly and time-consuming. OBJECTIVE: This research aims to develop and apply a deep learning network architecture to segment liver tumors automatically after fine tuning parameters. METHODS AND MATERIALS: The medical imaging is obtained from the International Symposium on Biomedical Imaging (ISBI), which includes 3D abdominal CT scans of 131 patients diagnosed with liver tumors. From these CT scans, there are 7,190 2D CT images along with the labeled binary images. The labeled binary images are regarded as gold standard for evaluation of the segmented results by FCN (Fully Convolutional Network). The backbones of FCN are extracted from Xception, InceptionresNetv2, MobileNetv2, ResNet18, ResNet50 in this study. Meanwhile, the parameters including optimizers (SGDM and ADAM), size of epoch, and size of batch are investigated. CT images are randomly divided into training and testing sets using a ratio of 9:1. Several evaluation indices including Global Accuracy, Mean Accuracy, Mean IoU (Intersection over Union), Weighted IoU and Mean BF Score are applied to evaluate tumor segmentation results in the testing images. RESULTS: The Global Accuracy, Mean Accuracy, Mean IoU, Weighted IoU, and Mean BF Scores are 0.999, 0.969, 0.954, 0.998, 0.962 using ResNet50 in FCN with optimizer SGDM, batch size 12, and epoch 9. It is important to fine tuning the parameters in FCN model. Top 20 FNC models enable to achieve higher tumor segmentation accuracy with Mean IoU over 0.900. The occurred frequency of InceptionresNetv2, MobileNetv2, ResNet18, ResNet50, and Xception are 9, 6, 3, 5, and 2 times. Therefore, the InceptionresNetv2 has higher performance than others. CONCLUSIONS: This study develop and test an automated liver tumor segmentation model based on FCN. Study results demonstrate that many deep learning models including InceptionresNetv2, MobileNetv2, ResNet18, ResNet50, and Xception have high potential to segment liver tumors from CT images with accuracy exceeding 90%. However, it is still difficult to accurately segment tiny and small size tumors by FCN models.

HIVEP3 cooperates with ferroptosis gene signatures to confer adverse prognosis in acute myeloid leukemia.

BACKGROUND: The human immunodeficiency virus type I enhancer binding protein (HIVEP) family, which contains zinc finger and acid-rich (ZAS) domains, has been demonstrated to be implicated in vital biological processes, such as cell survival, tumor necrosis factor (TNF) signaling, and tumor formation. However, its expression patterns, prognostic relevance, and functional implications in acute myeloid leukemia (AML) remain elusive. METHODS: We inspected HIVEP mRNA expression levels in datasets from The Cancer Genome Atlas (TCGA) and GSE24006. Survival analyses were orchestrated using the web-based bioinformatics platforms and R studio in two AML cohorts. Prognostic value and capacity were assessed by Cox regression analyses. Association of HIVEP3 expression levels with clinical characteristics were analyzed with R and UALCAN. Subsequentially, functional enrichment analyses were operated to interpret HIVEP3 co-expressed gene clusters. A prognostic gene signature was created by the least absolute shrinkage and selection operator (LASSO) regression algorithm. Moreover, bone marrow aspirate smears of AML patients were stained for HIVEP3 by immunohistochemistry (IHC). HIVEP3 expression was examined by qRT-PCR in leukemia cell lines treated with ferroptosis compounds in vitro. RESULTS: Augmented transcriptional levels of HIVEP2 and 3 were noted in AML patients (p<0.001). HIVEP3 not only could confer adverse prognosis independently in AML patients, but also was associated with AML subtypes, age, cytogenetic risk, and disease-related molecules. Co-expressed gene clusters of HIVEP3 were enriched in functional pathways related to AML leukemogenesis, such as ribosome, metabolism, and calcium signaling. Combined with multiple tumorigenesis signaling pathways, we proposed an integrated LASSO model with HIVEP3 and ferroptosis regulators AIFM2 and LPCAT3, to predict the outcome for AML patients. Furthernore, altered HIVEP3 expression at the mRNA or protein level was confirmed in sorted leukemia cells and blast cells in bone marrow tissues. In vitro experiments authenticated the involvement of HIVEP3 in ferroptosis signaling pathways. CONCLUSIONS: Our findings suggest that HIVEP3 is a de novo independent prognostic indicator, and the crosstalk between HIVEP3 and ferroptosis signaling pathways may inspire a specific perspective on the oncological network of AML.

Lineage tracing clarifies the cellular origin of tissue-resident macrophages in the developing heart.

Tissue-resident macrophages play essential functions in the maintenance of tissue homeostasis and repair. Recently, the endocardium has been reported as a de novo hemogenic site for the contribution of hematopoietic cells, including cardiac macrophages, during embryogenesis. These observations challenge the current consensus that hematopoiesis originates from the hemogenic endothelium within the yolk sac and dorsal aorta. Whether the developing endocardium has such a hemogenic potential requires further investigation. Here, we generated new genetic tools to trace endocardial cells and reassessed their potential contribution to hematopoietic cells in the developing heart. Fate-mapping analyses revealed that the endocardium contributed minimally to cardiac macrophages and circulating blood cells. Instead, cardiac macrophages were mainly derived from the endothelium during primitive/transient definitive (yolk sac) and definitive (dorsal aorta) hematopoiesis. Our findings refute the concept of endocardial hematopoiesis, suggesting that the developing endocardium gives rise minimally to hematopoietic cells, including cardiac macrophages.

Inactivation of AKT/ERK Signaling and Induction of Apoptosis Are Associated With Amentoflavone Sensitization of Hepatocellular Carcinoma to Lenvatinib.

BACKGROUND/AIM: AKT/ERK signaling transduction and anti-apoptosis effects have both been recognized as important mediators of hepatocellular carcinoma (HCC) progression. Targeting AKT/ERK signaling and mediating apoptosis may be beneficial for alleviating HCC growth. Lenvatinib, a tyrosine kinase inhibitor, has been approved by the FDA to treat HCC since 2018 as a monotherapy with limited efficacy. Amentoflavone, a biflavonoid in natural plants, has been shown to have the potential to suppress HCC progression in previous studies. Whether the combination of lenvatinib and amentoflavone may show superior HCC suppression is unclear. MATERIALS AND METHODS: We used MTT, flow cytometry and western blotting assays to identify the role of lenvatinib and amentoflavone in both Hep3B and Huh7 cells. RESULTS: We found that amentoflavone enhances the suppressive effect of AKT/ERK signaling induced by lenvatinib and, thus, sensitizes HCC to lenvatinib. The intrinsic/extrinsic apoptosis pathways induced by lenvatinib were also boosted by amentoflavone. CONCLUSION: Amentoflavone sensitization of HCC to lenvatinib is associated with AKT/ERK inactivation and apoptosis induction.

Genetic Lineage Tracing of Pericardial Cavity Macrophages in the Injured Heart.

BACKGROUND: Macrophages play an important role in cardiac repair after myocardial infarction (MI). In addition to the resident macrophages and blood-derived monocytes, Gata6+ cavity macrophages located in the pericardial space were recently reported to relocate to the injured myocardium and prevent cardiac fibrosis. However, there is no direct genetic evidence to support it. METHODS: We used dual recombinases (Cre and Dre) to specifically label Gata6+ pericardial macrophages (GPCMs) in vivo. For functional study, we generated genetic systems to specifically ablate GPCMs by induced expression of DTR (diphtheria toxin receptor) or knockout of Gata6 (GATA binding protein 6) gene in GPCMs. We used these genetic systems to study GPCMs in pericardium intact MI model. RESULTS: Dual recombinases-mediated genetic system targeted GPCMs specifically and efficiently. Lineage tracing study revealed accumulation of GPCMs on the surface of MI heart without deep penetration into the myocardium. We did not detect significant change of cardiac fibrosis or function of MI hearts after cell ablation or Gata6 knockout in GPCMs. CONCLUSIONS: GPCMs minimally invade the injured heart after MI. Nor do they prevent cardiac fibrosis and exhibit reparative function on injured heart. This study also underlines the importance of using specific genetic tool for studying in vivo cell fates and functions.