Research advances in serum chitinase-3-like protein 1 in liver fibrosis.

While liver fibrosis remains a serious, progressive, chronic liver disease, and factors causing damage persist, liver fibrosis may develop into cirrhosis and liver cancer. However, short-term liver fibrosis is reversible. Therefore, an early diagnosis of liver fibrosis in the reversible transition phase is important for effective treatment of liver diseases. Chitinase-3-like protein 1 (CHI3L1), an inflammatory response factor that participates in various biological processes and is abundant in liver tissue, holds promise as a potential biomarker for liver diseases. Here, we aimed to review research developments regarding serum CHI3L1 in relation to the pathophysiology and diagnosis of liver fibrosis of various etiologies, providing a reference for the diagnosis, treatment, and prognosis of liver diseases.

CPSS: Fusing consistency regularization and pseudo-labeling techniques for semi-supervised deep cardiovascular disease detection using all unlabeled electrocardiograms.

BACKGROUND AND OBJECTIVE: Deep learning usually achieves good performance in the supervised way, which requires a large amount of labeled data. However, manual labeling of electrocardiograms (ECGs) is laborious that requires much medical knowledge. Semi-supervised learning (SSL) provides an effective way of leveraging unlabeled data to improve model performance, providing insight for solving this problem. The objective of this study is to improve the performance of cardiovascular disease (CVD) detection by fully utilizing unlabeled ECG. METHODS: A novel SSL algorithm fusing consistency regularization and pseudo-labeling techniques (CPSS) is proposed. CPSS consists of supervised learning and unsupervised learning. For supervised learning, the labeled ECGs are mapped into prediction vectors by the classifier. The cross-entropy loss function is used to optimize the classifier. For unsupervised learning, the unlabeled ECGs are weakly and strongly augmented, and a consistency loss is used to minimize the difference between the classifier's predictions for the two augmentations. Pseudo-labeling techniques include positive pseudo-labeling (PL) and ranking-based negative pseudo-labeling (RNL). PL introduces pseudo-labels for data with high prediction confidence. RNL assigns negative pseudo-labels to the lower-ranked categories in the prediction vectors to leverage data with low prediction confidence. In this study, VGGNet and ResNet are used as classifiers, which are jointly optimized by labeled and unlabeled ECGs. RESULTS: CPSS has been validated on several databases. With the same number of labeled ECGs (10%), it improves the accuracies over pure supervised learning by 13.59%, 4.60%, and 5.38% in the CPSC2018, PTB-XL, and Chapman databases, respectively. CPSS achieves comparable results to the fully supervised method with only 10% of labeled ECGs, which reduces the labeling workload by 90%. In addition, to verify the practicality of CPSS, a cardiovascular disease monitoring system is designed by heterogeneously deploying the trained classifiers on an SoC (system-on-a-chip), which can detect CVD in real time. CONCLUSION: The results of this study indicate that the proposed CPSS can significantly improve the performance of CVD detection using unlabeled ECG, which reduces the burden of ECG labeling in deep learning. In addition, the designed monitoring system makes the proposed CPSS promising for real-world applications.

Sleep and mental health during the COVID-19 pandemic: findings from an online questionnaire survey in China.

Introduction: The online study investigated the sleep, psychological conditions, and risk factors during the wave of transmission of COVID-19 since December 7, 2022. Methods: We distributed questionnaires through networking mediums to residents to gather information about COVID-19 infection, sleep, and mental status. Results: During the extraordinary period in China, 91.9% of 1094 participants claimed to be infected with COVID-19, 36.8% reported poor sleep quality, 75.9% reported anxiety, and 65.5% reported depression. In retrospect, people have experienced lower sleep quality, longer sleep latency, enhanced rising time, and decreased sleep efficiency after the infection wave. After adjusting confounding factors, the elderly, women, urban residents, people with comorbidity, anxiety, depression, stress state, and COVID-19 infection have high risks for sleep disorders during the period. Discussion: The survey indicates that sleep disturbance caused by COVID-19 involves multiple dimensions, such as physiology, psychology, and society. The COVID-19 infection-related sleep problem should be taken seriously. Apart from conventional treatment, psychological issues of insomnia can not be ignored.

Protective effects of chlorogenic acid on the intestinal barrier of broiler chickens: an immunological stress model study.

This study was conducted to investigate the protective effects of chlorogenic acid (CGA) on inflammatory responses and intestinal health of lipopolysaccharide (LPS)-challenged broilers. One hundred and forty-four 1-day-old male broiler chicks were divided into 3 groups with 6 replicates of 8 birds each. The groups were as follows: 1) Control group: birds fed a basal diet; 2) LPS group: LPS-challenged birds fed a basal diet; 3) CGA group: LPS-challenged birds fed a CGA-supplemented diet. The LPS was intraperitoneally administered at a dose of 1 mg/kg of body weight. CGA increased the weight gain and feed intake of LPS-challenged birds by 37.05% and 24.29%, respectively (P < 0.05). CGA also alleviated LPS-induced inflammation, as evidenced by lower levels of pro-inflammatory cytokines in the serum and jejunum (tumor necrosis factor-α, interferon-γ, interleukin-1ß, and interleukin-6), and the decreased myeloperoxidase activity in the jejunum (P < 0.05). These effects were accompanied by a decrease in the mRNA abundance of toll-like receptor 4 and myeloid differentiation factor 88 and an inhibition of nuclear factor kappa-B translocation in the jejunum (P < 0.05). CGA reduced circulating diamine oxidase activity and levels of D-lactate and endotoxin, and positively regulated the expression of jejunal claudin-3 and zonula occludens-1 in LPS-challenged broilers (P < 0.05). Compared to the LPS group, CGA reduced the apoptotic rate of epithelial cells and cytochrome c concentration in the jejunum, and normalized the expression of genes responsible for proliferation and apoptosis in jejunal epithelial cells, including cysteine aspartate-specific protease-9, B cell lymphoma-2, and proliferating cell nuclear antigen (P < 0.05). Furthermore, CGA normalized the altered phosphorylation of protein kinase B and glycogen synthase kinase-3ß, as well as the translocation of nuclear ß-catenin in the jejunum of LPS-challenged broilers (P < 0.05). These results suggested that CGA supplementation improved growth performance, alleviated inflammation, and helped maintain intestinal integrity and barrier function in LPS-challenged broilers, possibly through the regulation of the toll-like receptor 4/nuclear factor kappa-B and protein kinase B/Wnt/ß-catenin pathways.

TLR3 activation enhances abscopal effect of radiotherapy in HCC by promoting tumor ferroptosis.

Radiotherapy (RT) has been reported to induce abscopal effect in advanced hepatocellular carcinoma (HCC), but such phenomenon was only observed in sporadic cases. Here, we demonstrated that subcutaneous administration of Toll-like receptor 3 (TLR3) agonist poly(I:C) could strengthen the abscopal effect during RT through activating tumor cell ferroptosis signals in bilateral HCC subcutaneous tumor mouse models, which could be significantly abolished by TLR3 knock-out or ferroptosis inhibitor ferrostatin-1. Moreover, poly(I:C) could promote the presentation of tumor neoantigens by dendritic cells to enhance the recruitment of activated CD8+ T cells into distant tumor tissues for inducing tumor cell ferroptosis during RT treatment. Finally, the safety and feasibility of combining poly(I:C) with RT for treating advanced HCC patients were further verified in a prospective clinical trial. Thus, enhancing TLR3 signaling activation during RT could provide a novel strategy for strengthening abscopal effect to improve the clinical benefits of advanced HCC patients.

Risk of Esophageal Adenocarcinoma After Bariatric Surgery: A Meta-Analysis of Retrospective Studies.

PURPOSE: This study aims to systematically review and meta-analyze the evidence on the risk of esophageal adenocarcinoma (EAC) following metabolic and bariatric surgery (MBS). MATERIALS AND METHODS: A systematic literature search was conducted on the China National Knowledge Infrastructure (CNKI), Wanfang, EMBASE, MEDLINE, Web of Science, The Cochrane Library, and PubMed databases. Meta-analysis utilized odds ratios (ORs) and 95% confidence intervals (CIs) to analyze the correlation between MBS and the risk of EAC. Meta-analysis was performed using STATA software (version 12.0). RESULTS: Fourteen studies involving patients with obesity undergoing bariatric surgery and control groups receiving conventional treatment were included. The meta-analysis indicated a reduction in the overall incidence of esophageal cancer after bariatric surgery (OR = 0.69, 95% CI: 0.51-0.95, P = 0.022). Subgroup analysis results demonstrated a decreased risk of EAC in European patients with obesity undergoing MBS treatment (OR: 0.60, 95% CI: 0.38-0.95, P = 0.028). In studies with a sample size greater than or equal to 100,000 patients, the risk of EAC in patients with obesity undergoing MBS was significantly lower than the non-surgery group (OR: 0.59, 95% CI: 0.42-0.83, P = 0.003). Articles published before 2020 and those published in 2020 or earlier showed a significant difference in the incidence of EAC between the surgery and non-surgery groups (OR: 0.57, 95% CI: 0.43-0.75, P < 0.001). The risk of EAC in patients with obesity with a follow-up time of less than 5 years was statistically significant (OR: 0.46, 95% CI: 0.25-0.82, P = 0.009). CONCLUSION: Our meta-analysis results suggest a reduced risk of esophageal cancer in patients with obesity after bariatric surgery. PROSPERO REGISTRATION: CRD 42024505177.

Short-Chain Sulfur Confined into Nitrogen-Doped Hollow Carbon Nanospheres for High-Capacity Potassium Storage.

Carbon-based materials are one of the ideal negative electrode materials for potassium ion batteries. However, the limited active sites and sluggish diffusion ion kinetics still hinder its commercialization process. To address these problems, we design a novel carbon composite anode, by confining highly reactive short-chain sulfur molecules into nitrogen-doped hollow carbon nanospheres (termed SHC-450). The formation process involves the controlled synthesis of hollow polyaniline (PANI) nanospheres as precursors via an Ostwald ripening mechanism and subsequent sulfuration treatment. The high content of constrained short-chain sulfur molecules (20.94 wt%) and considerable N (7.15 wt%) ensure sufficient active sites for K+ storage in SHC-450. Accordingly, the SHC-450 electrode exhibits a high reversible capacity of 472.05 mAh g-1 at 0.1 A g-1 and good rate capability (172 mAh g-1 at 2 A g-1). Thermogravimetric analysis shows that SHC-450 has impressive thermal stability to withstand a high temperature of up to 640 °C. Ex situ spectroscopic characterizations reveal that the short-chain sulfur provides high capacity through reversible formation of K2S. Moreover, its special hollow structure not only provides ample space for highly active short-chain sulfur reactants but also effectively mitigates volume expansion during the sulfur conversion process. This work offers new perspectives on enhanced K+ storage performance from an interesting anode design and the space-limited domain principle.

ST-ReGE: A Novel Spatial-Temporal Residual Graph Convolutional Network for CVD.

Recently, deep learning (DL) has enabled rapid advancements in electrocardiogram (ECG)-based automatic cardiovascular disease (CVD) diagnosis. Multi-lead ECG signals have lead systems based on the potential differences between electrodes placed on the limbs and the chest. When applying DL models, ECG signals are usually treated as synchronized signals arranged in Euclidean space, which is the abstraction and generalization of real space. However, conventional DL models typically merely focus on temporal features when analyzing Euclidean data. These approaches ignore the spatial relationships of different leads, which are physiologically significant and useful for CVD diagnosis because different leads represent activities of specific heart regions. These relationships derived from spatial distributions of electrodes can be conveniently created in non-Euclidean data, making multi-lead ECGs better conform to their nature. Considering graph convolutional network (GCN) adept at analyzing non-Euclidean data, a novel spatial-temporal residual GCN for CVD diagnosis is proposed in this work. ECG signals are firstly divided into single-channel patches and transferred into nodes, which will be connected by spatial-temporal connections. The proposed model employs residual GCN blocks and feed-forward networks to alleviate over-smoothing and over-fitting. Moreover, residual connections and patch dividing enable the capture of global and detailed spatial-temporal features. Experimental results reveal that the proposed model achieves at least a 5.85% and 6.80% increase in F1 over other state-of-the-art algorithms with similar parameters and computations in both PTB-XL and Chapman databases. It indicates that the proposed model provides a promising avenue for intelligent diagnosis with limited computing resources.

The toxic mechanism of tetracycline on root tips in hulless barley (Hordeum vulgare L. var. nudum).

Tetracycline (TC) is a commonly used antibiotic that affects various physiological processes in plants. However, its negative effects on plants remain poorly understood at the molecular level. To ascertain the TC toxicity in the roots, transcriptomic, cytological, and physiological analyses were performed to explore the molecular mechanisms of TC influencing the growth of hulless barley root. At a low concentration (1 mg/L), TC promoted root growth by upregulating the genes related to the flavonoid pathway. At high concentrations (10, 100, and 200 mg/L), TC downregulated genes related to homologous recombination in the root meristem zone and inhibited the mitosis index by 16.4%. Disruption of the DNA repair process can lead to chromosomal aberrations, resulting in a 6.8% C-mitosis rate in the most severe cases. Finally, root growth was inhibited by TC, as evidenced by a reduction in root viability, an increase in reactive oxygen species content, and an inhibition of root length. Cross-comparison of physiological and cytological characterizations and transcriptomic information revealed changes in genetic processes under TC stress. Overall, we present an early genetic strategy to study the significant influence of TC stress on roots.

Optimized Solutions of Electrocardiogram Lead and Segment Selection for Cardiovascular Disease Diagnostics.

Most of the existing multi-lead electrocardiogram (ECG) detection methods are based on all 12 leads, which undoubtedly results in a large amount of calculation and is not suitable for the application in portable ECG detection systems. Moreover, the influence of different lead and heartbeat segment lengths on the detection is not clear. In this paper, a novel Genetic Algorithm-based ECG Leads and Segment Length Optimization (GA-LSLO) framework is proposed, aiming to automatically select the appropriate leads and input ECG length to achieve optimized cardiovascular disease detection. GA-LSLO extracts the features of each lead under different heartbeat segment lengths through the convolutional neural network and uses the genetic algorithm to automatically select the optimal combination of ECG leads and segment length. In addition, the lead attention module (LAM) is proposed to weight the features of the selected leads, which improves the accuracy of cardiac disease detection. The algorithm is validated on the ECG data from the Huangpu Branch of Shanghai Ninth People's Hospital (defined as the SH database) and the open-source Physikalisch-Technische Bundesanstalt diagnostic ECG database (PTB database). The accuracy for detection of arrhythmia and myocardial infarction under the inter-patient paradigm is 99.65% (95% confidence interval: 99.20-99.76%) and 97.62% (95% confidence interval: 96.80-98.16%), respectively. In addition, ECG detection devices are designed using Raspberry Pi, which verifies the convenience of hardware implementation of the algorithm. In conclusion, the proposed method achieves good cardiovascular disease detection performance. It selects the ECG leads and heartbeat segment length with the lowest algorithm complexity while ensuring classification accuracy, which is suitable for portable ECG detection devices.

Adjustment of impact phenolic compounds, antioxidant activity and aroma profile in Cabernet Sauvignon wine by mixed fermentation of Pichia kudriavzevii and Saccharomyces cerevisiae.

Mixed fermentation using saccharomyces cerevisiae and non-saccharomyces cerevisiae has become one of the main research strategies to improve wine aroma. Hence, this study applied the mixed fermentation technique using Pichia kudriavzevii and Saccharomyces cerevisiae to brew Cabernet Sauvignon wine and to investigate the effects of inoculation timing and inoculation ratio on the polyphenolics, antioxidant activity and aroma of the resulting wine. The results showed that mixed fermentation significantly improved the amounts of flavan-3-ols. In particular, S1:5 had the highest amounts of (-)-catechin and procyanidin B1 (73.23 mg/L and 46.59 mg/L), while S1:10 had the highest (-)-epicatechin content (57.95 mg/L). Meanwhile, S1:10 showed the strongest FRAP, CUPRAC and ABTS + activities (31.46 %, 25.38 % and 13.87 % higher than that of CK, respectively). In addition, mixed fermentation also increased the amounts of phenylethanol, isoamyl alcohol and ethyl esters, which enhanced the rose-like and fruity flavor of wine. This work used a friendly non-saccharomyces cerevisiae alongside appropriate inoculation strategies to provide an alternative approach for improved wine aroma and phenolic profile.

A fully-mapped and energy-efficient FPGA accelerator for dual-function AI-based analysis of ECG.

In this paper, a fully-mapped field programmable gate array (FPGA) accelerator is proposed for artificial intelligence (AI)-based analysis of electrocardiogram (ECG). It consists of a fully-mapped 1-D convolutional neural network (CNN) and a fully-mapped heart rate estimator, which constitute a complementary dual-function analysis. The fully-mapped design projects each layer of the 1-D CNN to a hardware module on an Intel Cyclone V FPGA, and a virtual flatten layer is proposed to effectively bridge the feature extraction layers and fully-connected layer. Also, the fully-mapped design maximizes computational parallelism to accelerate CNN inference. For the fully-mapped heart rate estimator, it performs pipelined transformations, self-adaptive threshold calculation, and heartbeat count on the FPGA, without multiplexed usage of hardware resources. Furthermore, heart rate calculation is elaborately analyzed and optimized to remove division and acceleration, resulting in an efficient method suitable for hardware implementation. According to our experiments on 1-D CNN, the accelerator can achieve 43.08× and 8.38× speedup compared with the software implementations on ARM-Cortex A53 quad-core processor and Intel Core i7-8700 CPU, respectively. For the heart rate estimator, the hardware implementations are 25.48× and 1.55× faster than the software implementations on the two aforementioned platforms. Surprisingly, the accelerator achieves an energy efficiency of 63.48 GOPS/W, which obviously surpasses existing studies. Considering its power consumption is only 67.74 mW, it may be more suitable for resource-limited applications, such as wearable and portable devices for ECG monitoring.

Effects of dietary supplementation with chlorogenic acid on growth performance, antioxidant capacity, and hepatic inflammation in broiler chickens subjected to diquat-induced oxidative stress.

This study was conducted to investigate the protective effects of chlorogenic acid (CGA) on broilers subjected to (DQ)-induced oxidative stress. In experiment 1, one hundred and ninety-two male one-day-old Ross 308 broiler chicks were distributed into 4 groups and fed a basal diet supplemented with 0, 250, 500, or 1,000 mg/kg CGA for 21 d. In experiment 2, an equivalent number of male one-day-old chicks were allocated to 4 treatments for a 21-d trial: 1) Control group, normal birds fed a basal diet; 2) DQ group, DQ-challenged birds fed a basal diet; and 3) and 4) CGA-treated groups: DQ-challenged birds fed a basal diet supplemented with 500 or 1,000 mg/kg CGA. The intraperitoneal DQ challenge was performed at 20 d. In experiment 1, CGA administration linearly increased 21-d body weight, and weight gain and feed intake during 1 to 21 d (P < 0.05). CGA linearly and/or quadratically increased total antioxidant capacity, catalase, superoxide dismutase, and glutathione peroxidase activities, elevated glutathione level, and reduced malondialdehyde accumulation in serum, liver, and/or jejunum (P < 0.05). In experiment 2, compared with the control group, DQ challenge reduced body weight ratio (P < 0.05), which was reversed by CGA administration (P < 0.05). DQ challenge increased serum total protein level, aspartate aminotransferase activity, and total bilirubin concentration (P < 0.05), which were normalized when supplementing 500 mg/kg and/or 1,000 mg/kg CGA (P < 0.05). DQ administration elevated hepatic interleukin-1ß, tumor necrosis factor-α, and interleukin-6 levels (P < 0.05), and the values of interleukin-1ß were normalized to control values when supplementing CGA (P < 0.05). DQ injection decreased serum superoxide dismutase activity, hepatic catalase activity, and serum and hepatic glutathione level, but increased malondialdehyde concentration in serum and liver (P < 0.05), and the values of these parameters (except hepatic catalase activity) were reversed by 500 and/or 1,000 mg/kg CGA. The results suggested that CGA could improve growth performance, alleviate oxidative stress, and ameliorate hepatic inflammation in DQ-challenged broilers.

A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC.

The utilization of unlabeled electrocardiogram (ECG) data is always a critical topic in artificial intelligence healthcare, as the manual annotation for ECG data is a time-consuming task that requires much medical expertise. The recent development of self-supervised learning, especially contrastive learning, has provided helpful inspirations to solve this problem. In this paper, a joint cross-dimensional contrastive learning algorithm for unlabeled 12-lead ECGs is proposed. Unlike existing studies about ECG contrastive learning, our algorithm can simultaneously exploit unlabeled 1-dimensional ECG signals and 2-dimensional ECG images. A cross-dimensional contrastive learning method enhances the interaction between 1-dimensional and 2-dimensional ECG data, resulting in a more effective self-supervised feature learning. Combining this cross-dimensional contrastive learning, a 1-dimensional contrastive learning with ECG-specific transformations is employed to constitute a joint model. To pre-train this joint model, a new hybrid contrastive loss balances the 2 algorithms and uniformly describes the pre-training target. In the downstream classification task, the features learned by our algorithm shows impressive advantages. Compared with other representative methods, it achieves a at least 5.99% increase in accuracy. For real-world applications, an efficient heterogenous deployment on a "system-on-a-chip" (SoC) is designed. According to our experiments, the model can process 12-lead ECGs in real-time on the SoC. Furthermore, this heterogenous deployment can achieve a 14 × faster inference than the pure software deployment on the same SoC. In summary, our algorithm is a good choice for unlabeled 12-lead ECG utilization, the proposed heterogenous deployment makes it more practical in real-world applications.

An evaluation of graded levels of beta-sitosterol supplementation on growth performance, antioxidant status, and intestinal permeability-related parameters and morphology in broiler chickens at an early age.

This study was designed to examine the effects of different levels of beta-sitosterol (BS) supplementation on growth performance, serum biochemical indices, redox status, and intestinal permeability-related parameters and morphology of young broilers. Two hundred and forty male Arbor Acres broiler chicks were allocated into 5 groups of 6 replicates with 8 birds each, and fed a basal diet supplemented with 0, 25, 50, 75, and 100 mg/kg BS for 21-d, respectively. The BS quadratically decreased feed conversion ratio during 1 to 14 d and 1 to 21 d, with its effect being more prominent at 25 or 50 mg/kg (P < 0.05). The BS linearly and quadratically reduced 14-d plasma diamine oxidase activity and D-lactate level, and this effect was more pronounced when its supplemental level was 25 or 50 mg/kg (P < 0.05). The BS linearly increased duodenal villus height (VH) and quadratically increased jejunal VH and ratio of VH and crypt depth (CD) at 14 d, and these effects in 25 mg/kg group were more remarkable (P < 0.05). Similarly, BS linearly or quadratically increased VH and ratio of VH and CD, but decreased CD in the jejunum and ileum at 21 d, with these effects being more pronounced at 50 mg/kg (P < 0.05). The BS supplementation especially at 50 or 75 mg/kg linearly or quadratically reduced 14-d serum and 21-d hepatic malondialdehyde concentration, and increased serum glutathione peroxidase and catalase activities at 14 and 21 d (P < 0.05). Moreover, the BS administration linearly and/or quadratically increased glutathione peroxidase, catalase, and superoxide dismutase activities and glutathione level, and reduced malondialdehyde accumulation in the intestinal mucosa at 14 and/or 21 d, and these consequences were more significant in 50 to 100 mg/kg BS-supplemented groups (P < 0.05). The results demonstrated that BS administration could improve growth performance, intestinal barrier function, and antioxidant status of broilers at an early age, with these effects being more pronounced at a level of 50 mg/kg.

Personalized neoantigen vaccine combined with PD-1 blockade increases CD8+ tissue-resident memory T-cell infiltration in preclinical hepatocellular carcinoma models.

BACKGROUND: Personalized neoantigen vaccine could induce a robust antitumor immune response in multiple cancers, whose efficacy could be further enhanced by combining with programmed cell death 1 blockade (α-PD-1). However, the corresponding immune response and synergistic mechanisms remain largely unclear. Here, we aimed to develop clinically available combinational therapeutic strategy and further explore its potential antitumor mechanisms in hepatocellular carcinoma (HCC). METHODS: Neoantigen peptide vaccine (NeoVAC) for murine HCC cell line Hepa1-6 was developed and optimized by neoantigen screening and adjuvant optimization. Then the synergistic efficacy and related molecular mechanisms of NeoVAC combined with α-PD-1 in HCC were evaluated by orthotopic HCC mouse model, single-cell RNA sequencing, tetramer flow cytometry, immunofluorescence, etc. The tumor-killing capacity of CD8+ tissue-resident memory T cells (CD8+ TRMs) was assessed by orthotopic HCC mouse model, and autologous patient-derived cells. RESULTS: NeoVAC, which consisted of seven high immunogenic neoantigen peptides and clinical-grade Poly(I:C), could generate a strong antitumor immune response in HCC mouse models. Significantly, its efficacy could be further improved by combining with α-PD-1, with 80% of durable tumor regression and long-term immune memory in orthotopic HCC models. Moreover, in-depth analysis of the tumor immune microenvironment showed that the percentage of CD8+ TRMs was remarkedly increased in NeoVAC plus α-PD-1 treatment group, and positively associated with the antitumor efficacy. In vitro and in vivo T-cell cytotoxicity assay further confirmed the strong tumor-killing capacity of CD8+ TRMs sorting from orthotopic mouse HCC or patient's HCC tissue. CONCLUSIONS: This study showed that NeoVAC plus α-PD-1 could induce a strong antitumor response and long-term tumor-specific immune memory in HCC by increasing CD8+ TRMs infiltration, which might serve as a potential immune-therapeutic target for HCC.

Pien Tze Huang Inhibits Migration and Invasion of Hepatocellular Carcinoma Cells by Repressing PDGFRB/YAP/CCN2 Axis Activity.

OBJECTIVE: To investigate the effects of Pien Tze Huang (PZH) on the migration and invasion of HCC cells and underlying molecular mechanism. METHODS: Cell counting kit-8 (CCK-8) was applied to evaluate the cell viabilities of SMMC-7721, SK-Hep-1, C3A and HL-7702 (6 × 103 cells/well) co-incubated with different concentrations of PZH (0, 0.2, 0.4, 0.6, 0.8 mg/mL) for 24 h. Transwell, wound healing assay, CCK-8 and Annexin V-FITC/PI staining were conducted to investigate the effects of PZH on the migration, invasion, proliferation and apoptosis of SK-Hep-1 and SMMC-7721 cells (650 µ g/mL for SK-Hep-1 cells and 330 µ g/mL for SMMC-7721 cells), respectively. In vivo, lung metastasis mouse model constructed by tail vein injection of HCC cells was used for evaluating the anti-metastasis function of PZH. SK-Hep-1 cells (106 cells/200 µ L per mice) were injected into B-NDG mice via tail vein. Totally 8 mice were randomly divided into PZH and control groups, 4 mice in each group. After 2-d inoculation, mice in the PZH group were administered with PZH (250 mg/kg, daily) and mice in the control group received only vehicle (PBS) from the 2nd day after xenograft to day 17. Transcriptome analysis based on RNA-seq was subsequently used for deciphering anti-tumor mechanism of PZH. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were applied to verify RNA-seq results. Luciferase reporter assay was performed to examine the transcriptional activity of yes-associated protein (YAP). RESULTS: PZH treatment significantly inhibited the migration, invasion, proliferation and promoted the apoptosis of HCC cells in vitro and in vivo (P<0.01). Transcriptome analysis indicated that Hippo signaling pathway was associated with anti-metastasis function of PZH. Mechanical study showed PZH significantly inhibited the expressions of platelet derived growth factor receptor beta (PDGFRB), YAP, connective tissue growth factor (CCN2), N-cadherin, vimentin and matrix metallopeptidase 2 (MMP2, P<0.01). Meanwhile, the phosphorylation of YAP was also enhanced by PZH treatment in vitro and in vivo. Furthermore, PZH played roles in inhibiting the transcriptional activity of YAP. CONCLUSION: PZH restrained migration, invasion and epithelial-mesenchymal transition of HCC cells through repressing PDGFRB/YAP/CCN2 axis.