System Analysis Based on Pancreatic Cancer Progression Identifies BRINP2 as a Novel Prognostic Biomarker.

Pancreatic adenocarcinoma (PAAD) is a malignant tumor of the digestive system, which develops rapidly and has no obvious early symptoms. This study aims to discover the biomarkers associated with PAAD development. We obtained RNA expression of PAAD patient samples and corresponding clinical data from The cancer genome atlas (TCGA), and screened out BMP/RA-inducible neural-specific protein 2 (BRINP2) gene which is highly associated with PAAD severity. Then, gene ontology (GO) enrichment, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis and single-sample gene set enrichment analysis (ssGSEA) analysis were performed to explore the biological functions of BRINP2. Subsequently, long non-coding RNA (lncRNAs) associated with BRINP2 were screened out via correlation analysis, and Cox regression analysis and least absolute shrinkage selection operator (LASSO) regression analysis were used to construct the risk prediction model. We further validated the expression level of BRINP2 and its associated lncRNAs in BRINP2-associated lncRNAs prognostic model in vitro. We proposed that BRINP2 might be correlated to the tumor immune microenvironment and could also be used as a biomarker for PAAD progression. GO enrichment analysis and KEGG pathway analysis showed that the prognostic model was highly correlated to immune microenvironment-related pathways. Additionally, we established a BRINP2-associated lncRNAs prognostic model consisting of three lncRNAs. We validated the expression trends of BRINP2 and its associated lncRNAs in BRINP2-associated lncRNAs prognostic model in PAAD cells with various severity of metastatic potential using the quantitative real-time PCR (qRT-PCR). Meanwhile, pRRophetic R package was employed to predict potential therapeutic drugs for BRINP2-associated lncRNAs prognostic model of PAAD. The results suggest that BRINP2 can be used as a novel prognostic biomarker for PAAD.

Identification and validation of a fatty acid metabolism-related lncRNA signature as a predictor for prognosis and immunotherapy in patients with liver cancer.

BACKGROUND: Fatty acid (FA) metabolism is considered the emerging cause of tumor development and metastasis, driving poor prognosis. Long non-coding RNAs (lncRNAs) are closely related to cancer progression and play important roles in FA metabolism. Thus, the discovery of FA metabolism-related lncRNA signatures to predict outcome and immunotherapy response is critical in improving the survival of patients with hepatocellular carcinoma (HCC). METHODS: FA metabolism scores and a FA metabolism-related lncRNA signature were constructed using a single-sample gene set enrichment analysis based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. "ConsensusClusterPlus" was used to screen molecular subtypes. Chi-squared test and Fisher's exact test were applied to explore the relationship between clinical, genomic mutation characteristics and subtypes. Transcription factor (TF) activity scores, cellular distributions, immune cell infiltration, and immunotherapy response were employed to investigate the functions of FA metabolism-related lncRNA signatures. FA metabolism microarray and western blot were performed to detect the biological function of candidate lncRNAs. RESULTS: A total of 70 lncRNAs that highly correlated with FA metabolism scores in two cohorts were used to construct two distinct clusters. Patients in cluster 2 had lower FA metabolism scores and worse survival than those in cluster 1. Patients in cluster 2 exhibited a high frequency of DNA damage, gene mutations, oncogenic signaling such as epithelial-to-mesenchymal transition, and a high degree of immune cell infiltration. Moreover, the lncRNA signature could predict the effects of immunotherapy in patients with HCC. Furthermore, three lncRNAs (SNHG1, LINC00261, and SNHG7) were identified that were highly correlated with FA metabolism. Additionally, SNHG1 and SNHG7 were found to regulate various FA metabolism-related genes and ferroptosis-related genes in vitro experiments. GSEA analysis revealed that SNHG1 and SNHG7 promote fatty acid beta-oxidation. SNHG1 and SNHG7 silencing dramatically reduced lipid droplets in HCC cells. Many immune-infiltration genes and TFs were overexpressed in HCC tissues with SNHG1 and SNHG7 high expression. CONCLUSIONS: A novel molecular model of FA metabolism-related lncRNAs was developed, which has significantly prognostic potential in HCC diagnosis and aids in clinical decision making.

Proteomics reveals the potential mechanism of Mrps35 controlling Listeria monocytogenes intracellular proliferation in macrophages.

Macrophages are sentinels in the organism which can resist and destroy various bacteria through direct phagocytosis. Here, we reported that expression level of mitochondrial ribosomal protein S35 (Mrps35) continued to decrease over infection time after Listeria monocytogenes (L. monocytogenes) infected macrophages. Our results indicated that knockdown Mrps35 increased the load of L. monocytogenes in macrophages. This result supported that Mrps35 played the crucial roles in L. monocytogenes infection. Moreover, we performed the comprehensive proteomics to analyze the differentially expressed protein of wild type and Mrps35 Knockdown Raw264.7 cells by L. monocytogenes infection over 6 h. Based on the results of mass spectrometry, we presented a wide variety of hypotheses about the mechanism of Mrps35 controlling the L. monocytogenes intracellular proliferation. Among them, experiments confirmed that Mrps35 and 60S ribosomal protein L22-like 1 (Rpl22l1) were a functional correlation or potentially a compensatory mechanism during L. monocytogenes infection. This study provided new insights into understanding that L. monocytogenes infection changed the basic synthesis or metabolism-related proteins of host cells.

TAK1 is involved in sodium L-lactate-stimulated p38 signaling and promotes apoptosis.

In the present study, we found that the phosphorylation of p38 mitogen-activated protein kinase (p38) was significantly increased in L-lactate-treated HeLa cells, which is under concentration- and time-dependent manner. The protein level of Bcl-2 was significantly reduced and Bax and C-caspase3 were significantly increased in L-lactate-treated cells. qRT-PCR analysis suggested that the expression level of apoptosis-related genes Bax, C-myc, and FasL were significantly upregulated by L-lactate treatment. In addition, p38 inhibitor SB203580 blocked the L-lactate-stimulated phosphorylation of p38 (p-p38) and apoptosis, which suggested that L-lactate-stimulated apoptosis may be related to the activation of p38. Moreover, TAK1 inhibitor Takinib reduced L-lactate-triggered phosphorylation of p38 and also apoptosis; however, ASK1 inhibitor NQDI-1 did not. Cells transfected with siRNA of TAK1(siTAK1) showed similar results with Takinib inhibitor. These results suggested that the L-lactate treatment elevated activation of p38 and apoptosis was related to TAK1. In this study, we suggested that TAK1 plays an important role in L-lactate-stimulated activation of p38 affecting apoptosis in HeLa cells.

Correlations between CYP3A4 polymorphism and susceptibility to breast cancer in Chinese Han population.

BACKGROUND: CYP3A4 is a major enzyme catalyzing the metabolism of endogenous steroids that play an important role in the etiology of carcinogenesis. This study was designed to investigate the contribution of CYP3A4 polymorphism to breast cancer in Chinese Han female population. METHODS: To examine whether variants of CYP3A4 contribute to breast cancer, 5 single-nucleotide polymorphisms (SNPs) of CYP3A4 were genotyped by Sequenom MassARRAY in 267 breast cancer patients and 302 healthy controls. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated by unconditional logistic regression adjusted for age. RESULTS: We found that the TT genotype of CYP3A4*1G (rs2242480) polymorphism was associated with increased risk of breast cancer using the fixed effects model (recessive model: OR = 2.34, p = 0.018). Stratified according to age, CYP3A4*1G increased the risk of breast cancer especially in less than 50-year-old group (codominant model OR = 3.68, p = 0.041; recessive model: OR = 3.55, p = 0.012). Furthermore, TT genotype of rs2242480 was associated with Cerb-B2 positive (recessive model: OR = 2.47, p = 0.025) and stage I/II (recessive model: OR = 2.32, p = 0.041). However, no statistically significant associations in other polymorphisms and haploview analysis were observed. CONCLUSIONS: This study provides an evidence for polymorphism of CYP3A4 gene associated with the development of breast cancer, also a new insight into etiology of breast cancer. However, the underlying mechanism of the CYP3A4 gene in breast cancer is necessary for further study.

Upregulation of LncDQ is Associated with Poor Prognosis and Promotes Tumor Progression via Epigenetic Regulation of the EMT Pathway in HCC.

BACKGROUND/AIMS: Long noncoding RNAs (lncRNAs) are key regulators of cancer initiation and progression. In this study, we investigated the clinical value and functional role of LncRNA DQ786243 (LncDQ) in the pathogenesis of hepatocellular carcinoma (HCC). METHODS: To investigate the expression level of LncDQ in HCC, we performed quantitative real-time PCR using total RNA extracted from HCC tumor tissues and their matched non-neoplastic counterparts, as well as from the serum of HCC patients and healthy volunteers. The correlation of LncDQ expression with clinicopathologic features and prognosis was analyzed. The functional role of LncDQ in cell proliferation, migration, and invasion were evaluated by MTT cell viability, wound healing, and transwell assays in vitro and in vivo. RNA immunoprecipitation and chromatin immunoprecipitation assays were performed to analyze the potential mechanism of LncDQ in HCC cells. RESULTS: LncDQ was upregulated in both HCC tissue samples and serum and was correlated with low survival rate and adverse clinical pathological characteristics. Multivariate analysis demonstrated that LncDQ expression was an independent prognostic factor for HCC. The area under the receiver operating characteristic curve was 0.804 with a sensitivity of 0.72 and a specificity of 0.8. Knockdown of LncDQ induced inhibition of cell proliferation, migration, and invasion in vitro and in vivo. Mechanistically, LncDQ regulated the epithelial-mesenchymal transition pathway by interacting with EZH2, to epigenetically repress the expression of E-cadherin in HCC cells. CONCLUSIONS: Taken together, the results of our study indicate that LncDQ plays a critical role in HCC progression, and may serve as a potential diagnostic and prognostic biomarker for HCC.

Cuffless Blood Pressure Estimation Using Pressure Pulse Wave Signals.

Pulse transit time (PTT) has received considerable attention for noninvasive cuffless blood pressure measurement. However, this approach is inconvenient to deploy in wearable devices because two sensors are required for collecting two-channel physiological signals, such as electrocardiogram and pulse wave signals. In this study, we investigated the pressure pulse wave (PPW) signals collected from one piezoelectric-induced sensor located at a single site for cuffless blood pressure estimation. Twenty-one features were extracted from PPW that collected from the radial artery, and then a linear regression method was used to develop blood pressure estimation models by using the extracted PPW features. Sixty-five middle-aged and elderly participants were recruited to evaluate the performance of the constructed blood pressure estimation models, with oscillometric technique-based blood pressure as a reference. The experimental results indicated that the mean ± standard deviation errors for the estimated systolic blood pressure and diastolic blood pressure were 0.70 ± 7.78 mmHg and 0.83 ± 5.45 mmHg, which achieved a decrease of 1.33 ± 0.37 mmHg in systolic blood pressure and 1.14 ± 0.20 mmHg in diastolic blood pressure, compared with the conventional PTT-based method. The proposed model also demonstrated a high level of robustness in a maximum 60-day follow-up study. These results indicated that PPW obtained from the piezoelectric sensor has great feasibility for cuffless blood pressure estimation, and could serve as a promising method in home healthcare settings.

An Assisted Diagnosis System for Detection of Early Pulmonary Nodule in Computed Tomography Images.

Lung cancer is still the most concerned disease around the world. Lung nodule generates in the pulmonary parenchyma which indicates the latent risk of lung cancer. Computer-aided pulmonary nodules detection system is necessary, which can reduce diagnosis time and decrease mortality of patients. In this study, we have proposed a new computer aided diagnosis (CAD) system for detection of early pulmonary nodule, which can help radiologists quickly locate suspected nodules and make judgments. This system consists of four main sections: pulmonary parenchyma segmentation, nodule candidate detection, features extraction (total 22 features) and nodule classification. The publicly available data set created by the Lung Image Database Consortium (LIDC) is used for training and testing. This study selects 6400 slices from 80 CT scans containing totally 978 nodules, which is labeled by four radiologists. Through a fast segmentation method proposed in this paper, pulmonary nodules including 888 true nodules and 11,379 false positive nodules are segmented. By means of an ensemble classifier, Random Forest (RF), this study acquires 93.2, 92.4, 94.8, 97.6% of accuracy, sensitivity, specificity, area under the curve (AUC), respectively. Compared with support vector machine (SVM) classifier, RF can reduce more false positive nodules and acquire larger AUC. With the help of this CAD system, radiologist can be provided with a great reference for pulmonary nodule diagnosis timely.

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies.

Objective: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy. Methods: We retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the "one-class logistic regression (OCLR)" algorithm to obtain the mRNAsi of patients with HCC. We performed "unsupervised consensus clustering" to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient's prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC. Results: We screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient's prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines. Conclusion: The novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

An Ultra-Low Modulus of Ductile TiZrHfTa Biomedical High-Entropy Alloys through Deformation Induced Martensitic Transformation/Twinning/Amorphization.

Biomedical alloys are paramount materials in biomedical applications, particularly in crafting biological artificial replacements. In traditional biomedical alloys, a significant challenge is simultaneously achieving an ultra-low Young's modulus, excellent biocompatibility, and acceptable ductility. A multi-component body-centered cubic (BCC) biomedical high-entropy alloy (Bio-HEA), which is composed of non-toxic elements, is noteworthy for its outstanding biocompatibility and compositional tuning capabilities. Nevertheless, the aforementioned challenges still remain. Here, a method to achieve a single phase with the lowest Young's modulus among the constituent phases by precisely tuning the stability of the BCC phase in the Bio-HEA, is proposed. The subtle tuning of the BCC phase stability also enables the induction of stress-induced martensite transformation with extremely low trigger stress. The transformation-induced plasticity and work hardening capacity are achieved via the stress-induced martensite transformation. Additionally, the hierarchical stress-induced martensite twin structure and crystalline-to-amorphous phase transformation provide robust toughening mechanisms in the Bio-HEA. The cytotoxicity test confirms that this Bio-HEA exhibits excellent biocompatibility without cytotoxicity. In conclusion, this study provides new insights into the development of biomedical alloys with a combination of ultra-low Young's modulus, excellent biocompatibility, and decent ductility.

Inactivation of ERK1/2 in cancer-associated hepatic stellate cells suppresses cancer-stromal interaction by regulating extracellular matrix in fibrosis.

The ERK1/2 pathway is involved in epithelial-mesenchymal transformation and cell cycle of tumor cells in hepatocellular carcinoma (HCC). In the present study, we investigated the involvement of ERK1/2 activation on hepatic stellate cells (HSCs). We identified ERK1/2 phosphorylation in activated HSCs of HCC samples. We found that tumor cells promoted the migration and invasion capacity of HSCs by activating ERK1/2 phosphorylation. Using high throughput transcriptome sequencing analysis, we found that ERK1/2 inhibition altered genes significantly correlated to signaling pathways involved in extracellular matrix remodeling. We screened genes and demonstrated that the ERK1/2 inhibition-related gene set significantly correlated to cancer-associated fibroblast infiltration in TCGA HCC tumor samples. Moreover, inhibition of ERK1/2 suppressed tumor cell-induced enhancement of HSC migration and invasion by regulating expression of fibrosis markers FAP, FN1 and COL1A1. In a tumor cell and HSC splenic co-transplanted xenograft mouse model, inhibition of ERK1/2 suppressed liver tumor formation by downregulating fibrosis, indicating ERK1/2 inhibition suppresses tumor-stromal interactions in vivo. Taken together, our data indicate that inhibition of ERK1/2 in tumor-associated HSCs suppresses tumor-stromal interactions and progression. Furthermore, inhibition of ERK1/2 may be a potential target for HCC treatment.

HGCTNet: Handcrafted Feature-Guided CNN and Transformer Network for Wearable Cuffless Blood Pressure Measurement.

Biosignals collected by wearable devices, such as electrocardiogram and photoplethysmogram, exhibit redundancy and global temporal dependencies, posing a challenge in extracting discriminative features for blood pressure (BP) estimation. To address this challenge, we propose HGCTNet, a handcrafted feature-guided CNN and transformer network for cuffless BP measurement based on wearable devices. By leveraging convolutional operations and self-attention mechanisms, we design a CNN-Transformer hybrid architecture to learn features from biosignals that capture both local information and global temporal dependencies. Then, we introduce a handcrafted feature-guided attention module that utilizes handcrafted features extracted from biosignals as query vectors to eliminate redundant information within the learned features. Finally, we design a feature fusion module that integrates the learned features, handcrafted features, and demographics to enhance model performance. We validate our approach using two large wearable BP datasets: the CAS-BP dataset and the Aurora-BP dataset. Experimental results demonstrate that HGCTNet achieves an estimation error of 0.9 ± 6.5 mmHg for diastolic BP (DBP) and 0.7 ± 8.3 mmHg for systolic BP (SBP) on the CAS-BP dataset. On the Aurora-BP dataset, the corresponding errors are -0.4 ± 7.0 mmHg for DBP and -0.4 ± 8.6 mmHg for SBP. Compared to the current state-of-the-art approaches, HGCTNet reduces the mean absolute error of SBP estimation by 10.68% on the CAS-BP dataset and 9.84% on the Aurora-BP dataset. These results highlight the potential of HGCTNet in improving the performance of wearable cuffless BP measurements.

Effect of Bioactive Black Phosphorus Nanomaterials on Cancer-Associated Fibroblast Heterogeneity in Pancreatic Cancer.

Tumor-stromal interactions and stromal heterogeneity in the tumor microenvironment are critical factors that influence the progression, metastasis, and chemoresistance of pancreatic ductal adenocarcinoma (PDAC). Here, we used spatial transcriptome technology to profile the gene expression landscape of primary PDAC and liver metastatic PDAC after bioactive black phosphorus nanomaterial (bioactive BP) treatment using a murine model of PDAC (LSL-KrasG12D/+; LSL-Trp53R172H/+; and Pdx-1-Cre mice). Bioinformatic and biochemical analyses showed that bioactive BP contributes to the tumor-stromal interplay by suppressing cancer-associated fibroblast (CAF) activation. Our results showed that bioactive BP contributes to CAF heterogeneity by decreasing the amount of inflammatory CAFs and myofibroblastic CAFs, two CAF subpopulations. Our study demonstrates the influence of bioactive BP on tumor-stromal interactions and CAF heterogeneity and suggests bioactive BP as a potential PDAC treatment.

[Corrigendum] lncRNA DQ786243 promotes hepatocellular carcinoma cell invasion and proliferation by regulating the miR­15b­5p/Wnt3A axis.

Following the publication of this article, an interested reader drew to the authors' attention that the primer sequences written for lncRNA DQ786243 and miR­15b­5p on p. 2 in the study were incorrect. Upon requesting an explanation of these errors from the authors, they realized that, regarding the sequence of the reverse primer for lncRNA DQ786243, three nucleotides were omitted from its 3'­end [the sequence of this primer on p. 2, right­hand column, line 25 should have been written as 5'­CTTCTGCTGGGCTGTTGAGTG­3' (with the omitted nucleotides highlighted in bold)]. Regarding the primers of miR­15b­5p, the authors used the mature miR­15b­5p sequence as the forward primer; however, they inadvertently overlooked replacing U with T in the description of the forward primer of miR­15b­5p, and therefore the sequence of the forward primer of miR­15b­5p on line 27 should have been written as 5'­TAGCAGCACATCATGGTTTACA­3'. Moreover, a universal reverse primer was used for the reverse primer of miR­15b­5p, as provided by the kit [specifically, the authors used an Mir­X miRNA qRT­PCR TB Green Kit (Takara Bio USA, Inc.) for detecting the expression of miR­15b­5p, and the reverse primer was supplied in the kit]; however, a different primer sequence used in the authors' lab was erroneously written as the reverse primer of miR­15b­5p in the manuscript. Finally, note that the title was published with a typographical error: "miR­15p­5p" in the title should have been written as "miR­15b­5p", as appeared elsewhere throughout the paper, and the corrected title is presented above.  The authors are grateful to the Editor of Molecular Medicine Reports for allowing them the opportunity to publish this corrigendum, and all the authors agree with its publication. The authors also regret the inconvenience that these mistakes have caused. [Molecular Medicine Reports 23: 318, 2021; DOI: 10.3892/mmr.2021.11957].

Exploring the effects and mechanisms of Guizhigancao Decoction on heart failure using an integrated approach based on experimental support and network pharmacology strategy.

Background and aim: HF (Heart Failure) is the leading cause of mortality and is a significant clinical problem affecting millions of patients worldwide. To date, the mechanisms of HF remain largely elusive. The effective treatments contributing to HF remain incompletely understood. Therefore, the development of an effective strategy for HF is urgently needed. Experimental procedure: In the present study, we devoted to investigating the effective treatments and sought to systematically decipher the related molecular mechanisms of Guizhigancao Decoction (GZGCD, Cinnamomum cassia Presl and Glycyrrhizae Radix Et Rhizoma Praeparata Cum Melle) for treating HF. We examined the therapeutic effect of GZGCD on HF in vivo. An integrative approach combining biomarker examination, echocardiography, myocardial fibrosis and cardiac apoptosis condition using Masson and TUNEL staining was performed to assess the efficacy of GZGCD against HF. Subsequently, comprehensive network pharmacology analyses were performed to explore the mechanisms involved in GZGCD therapeutic effects on HF. Results and conclusions: The results showed that GZGCD could reverse cardiac function in rats with HF by reducing NT-proBNP, increasing EF, decreasing LVESV, LVEDV, LVIDs, LVIDd, increasing running time, and ameliorate myocardial collagen fiber hyperplasia and cardiomyocyte apoptosis. We showed that GZGCD might contribute to HF treatment via oxidative related pathways through bioinformatics. Eventually, promising compound quercetin in GZGCD for HF therapeutics was proposed in database-based analysis. Collectively, our findings indicate that GZGCD has a treatment effect on HF. We proposed that GZGCD might contribute HF treatment via oxidative response-related pathways.

Long noncoding RNA LINC00665 is a diagnostic biomarker that enhances cell proliferation and migration in hepatocellular carcinoma.

BACKGROUND: This study aimed to evaluate the relationship between LINC00665 expression levels and the risk of hepatocellular carcinoma (HCC) in Chinese Han nationality patients and to explore the influence of LINC00665 dysregulation on the proliferation and migration potential of HCC cells. PATIENTS AND METHODS: We investigated the expression of LINC00665 in The Cancer Genome Atlas (TCGA) database. Then, we confirmed the expression of LINC00665 in 54 pairs of surgical tissues from HCC patients and in liver cancer cell lines by quantitative real-time polymerase chain reaction. Furthermore, we manipulated the expression level of LINC00665 and examined the cell proliferation and migration abilities of HCC cells. RESULTS: In the TCGA cohort, a high level of LINC00665 in patients with HCC was significantly associated with tumor stage, tumor differentiation grade, and overall survival. In our HCC patient cohort, overexpression of LINC00665 in patients showed positive correlations with alpha-fetoprotein level, Barcelona Clinic Liver Cancer stage, and tumor differentiation grade. In addition, LINC00665 was upregulated in HCC cells, especially in cells with rapid growth rates and high migration abilities. A new LINC00665 isoform with a length of 1,371 nucleotides was identified in MHCC-97H cells. Interfering with LINC00665 expression weakened the proliferation and migration abilities of HCC cells. In contrast, LINC00665 overexpression enhanced proliferation and migration abilities. CONCLUSION: LINC00665 was upregulated in HCC tissues and cells and might be used to predict a poor prognosis of HCC patients. In addition, LINC00665 may promote the malignant progression of HCC by enhancing proliferation and migration capacities.

CDCA8 induced by NF-YA promotes hepatocellular carcinoma progression by regulating the MEK/ERK pathway.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors. Cell division cycle associated 8 (CDCA8) is an important multifactorial regulator in cancers. However, its up and downstream targets and effects in HCC are still unclear. METHODS: A comprehensive bioinformatics analysis was performed using The Cancer Genome Atlas dataset (TCGA) to explore novel core oncogenes. We quantified CDCA8 levels in HCC tumors using qRT-PCR. HCC cell's proliferative, migratory, and invasive abilities were detected using a Cell Counting Kit-8 (CCK-8) assay, 5-ethynyl-2'-deoxyuridine (EdU) assay, clone formation, and a Transwell assay. An orthotopic tumor model and tail vein model were constructed to determine the effects of CDCA8 inhibition in vivo. The mechanism underlying CDCA8 was investigated using RNA sequencing. The prognostic value of CDCA8 was assessed with immunohistochemical staining of the tissue microarrays. RESULTS: CDCA8 was identified as a novel oncogene during HCC development. The high expression of CDCA8 was an independent predictor for worse HCC outcomes both in publicly available datasets and in our cohort. We found that CDCA8 knockdown inhibited HCC cell proliferation, colony formation, and migration by suppressing the MEK/ERK pathway in vitro. Moreover, CDCA8 deficiency significantly inhibited tumorigenesis and metastasis. Next-generation sequencing and laboratory validation showed that CDCA8 silencing inhibited the expression of TPM3, NECAP2, and USP13. Furthermore, NA-YA overexpression upregulated the expression of CDCA8. CDCA8 knockdown could attenuate NF-YA-mediated cell invasion in vitro. The expression of NF-YA alone or in combined with CDCA8 were validated as significant independent risk factors for patient survival. CONCLUSION: Our findings revealed that the expression of CDCA8 alone or in combined with NF-YA contributed to cancer progression, and could serve as novel potential therapeutic targets for HCC patients.

Cuffless Blood Pressure Measurement Using Smartwatches: A Large-Scale Validation Study.

This study aimed to evaluate the performance of cuffless blood pressure (BP) measurement techniques in a large and diverse cohort of participants. We enrolled 3077 participants (aged 18-75, 65.16% women, 35.91% hypertensive participants) and conducted followed-up for approximately 1 month. Electrocardiogram, pulse pressure wave, and multiwavelength photoplethysmogram signals were simultaneously recorded using smartwatches; dual-observer auscultation systolic BP (SBP) and diastolic BP (DBP) reference measurements were also obtained. Pulse transit time, traditional machine learning (TML), and deep learning (DL) models were evaluated with calibration and calibration-free strategy. TML models were developed using ridge regression, support vector machine, adaptive boosting, and random forest; while DL models using convolutional and recurrent neural networks. The best-performing calibration-based model yielded estimation errors of 1.33 ± 6.43 mmHg for DBP and 2.31 ± 9.57 mmHg for SBP in the overall population, with reduced SBP estimation errors in normotensive (1.97 ± 7.85 mmHg) and young (0.24 ± 6.61 mmHg) subpopulations. The best-performing calibration-free model had estimation errors of -0.29 ± 8.78 mmHg for DBP and -0.71 ± 13.04 mmHg for SBP. We conclude that smartwatches are effective for measuring DBP for all participants and SBP for normotensive and younger participants with calibration; performance degrades significantly for heterogeneous populations including older and hypertensive participants. The availability of cuffless BP measurement without calibration is limited in routine settings. Our study provides a large-scale benchmark for emerging investigations on cuffless BP measurement, highlighting the need to explore additional signals or principles to enhance the accuracy in large-scale heterogeneous populations.

Long non-coding RNA colon cancer-associated transcript 1-Vimentin axis promoting the migration and invasion of HeLa cells.

BACKGROUND: Long non-coding RNA colon cancer-associated transcript 1 (CCAT1) is involved in transforming multiple cancers into malignant cancer types. Previous studies underlining the mechanisms of the functions of CCAT1 primarily focused on its decoy for miRNAs (micro RNAs). However, the regulatory mechanism of CCAT1-protein interaction associated with tumor metastasis is still largely unknown. The present study aimed to identify proteome-wide CCAT1 partners and explored the CCAT1-protein interaction mediated tumor metastasis. METHODS: CCAT1-proteins complexes were purified and identified using RNA antisense purification coupled with the mass spectrometry (RAP-MS) method. The database for annotation, visualization, and integrated discovery and database for eukaryotic RNA binding proteins (EuRBPDB) websites were used to bioinformatic analyzing CCAT1 binding proteins. RNA pull-down and RNA immunoprecipitation were used to validate CCAT1-Vimentin interaction. Transwell assay was used to evaluate the migration and invasion abilities of HeLa cells. RESULTS: RAP-MS method worked well by culturing cells with nucleoside analog 4-thiouridine, and cross-linking was performed using 365 nm wavelength ultraviolet. There were 631 proteins identified, out of which about 60% were RNA binding proteins recorded by the EuRBPDB database. Vimentin was one of the CCAT1 binding proteins and participated in the tumor metastasis pathway. Knocked down vimetin ( VIM ) and rescued the downregulation by overexpressing CCAT1 demonstrated that CCAT1 could enhance tumor migration and invasion abilities by stabilizing Vimentin protein. CONCLUSION: CCAT1 may bind with and stabilize Vimentin protein, thus enhancing cancer cell migration and invasion abilities.