Smart-Plexer: a breakthrough workflow for hybrid development of multiplex PCR assays.

Developing multiplex PCR assays requires extensive experimental testing, the number of which exponentially increases by the number of multiplexed targets. Dedicated efforts must be devoted to the design of optimal multiplex assays ensuring specific and sensitive identification of multiple analytes in a single well reaction. Inspired by data-driven approaches, we reinvent the process of developing and designing multiplex assays using a hybrid, simple workflow, named Smart-Plexer, which couples empirical testing of singleplex assays and computer simulation to develop optimised multiplex combinations. The Smart-Plexer analyses kinetic inter-target distances between amplification curves to generate optimal multiplex PCR primer sets for accurate multi-pathogen identification. In this study, the Smart-Plexer method is applied and evaluated for seven respiratory infection target detection using an optimised multiplexed PCR assay. Single-channel multiplex assays, together with the recently published data-driven methodology, Amplification Curve Analysis (ACA), were demonstrated to be capable of classifying the presence of desired targets in a single test for seven common respiratory infection pathogens.

Expression of ALG3 in Hepatocellular Carcinoma and Its Clinical Implication.

Background: Recent studies have shown that alpha-1,3-mannosyltransferase (ALG3) promoted tumorigenesis and progression in multiple cancer types. Our study planned to explore the clinical implication and potential function of ALG3 in hepatocellular carcinoma. Materials and Methods: Data from public databases were used to analyze the ALG3 expression and its impact on the clinical significance of patients with HCC. The ALG3 expression was confirmed by qRT-PCR and Western blot. Immunohistochemistry was used to confirm the ALG3 expression and explore its clinical implication in HCC. KEGG, GO, and GSEA enrichment analyses were utilized to explore the biological pathways related to ALG3 in HCC. TIMER2.0 was applied to assess the association between ALG3 and immune infiltration. CCK8, MTT, and transwell assays were used to investigate the role of ALG3 downregulation in HCC cell lines. Results: qRT-PCR, WB, and IHC proved ALG3 was highly overexpressed in HCC tissues. The Kaplan-Meier analysis verified the overexpression of ALG3 was related to poor overall survival (p < 0.001). Multivariate cox regression analysis showed that the high ALG3 expression was an independent risk prognostic factor. GSEA and TIMER2.0 predicted that ALG3 participates in cell differentiation and cycle and correlates with immune cell infiltration. Transwell assay results showed that ALG3 silencing also impaired the invasion ability of HCC cells. Conclusion: ALG3 was overexpressed and considered a potential indicator of survival in HCC, and our findings provided a novel therapeutic target for HCC.

Microvascular Invasion in Hepatocellular Carcinoma: A Review of Its Definition, Clinical Significance, and Comprehensive Management.

Hepatocellular carcinoma (HCC) is one of the most common types of malignancies in the world, and most HCC patients undergoing liver resection relapse within five years. Microvascular invasion (MVI) is an independent factor for both the disease-free survival and overall survival of HCC patients. At present, the definition of MVI is still controversial, and a global consensus on how to evaluate MVI precisely is needed. Moreover, this review summarizes the current knowledge and clinical significance of MVI for HCC patients. In terms of management, antiviral therapy, wide surgical margins, and postoperative transcatheter arterial chemoembolization (TACE) could effectively reduce the incidence of MVI or improve the disease-free survival and overall survival of HCC patients with MVI. However, other perioperative management practices, such as anatomical resection, radiotherapy, targeted therapy and immune therapy, should be clarified in future investigations.

Single-channel digital LAMP multiplexing using amplification curve analysis.

Loop-mediated isothermal amplification assays are currently limited to one target per reaction in the absence of melting curve analysis, molecular probes or restriction enzyme digestion. Here, we demonstrate multiplexing of five targets in a single fluorescent channel using digital LAMP and the machine learning-based method amplification curve analysis, resulting in a classification accuracy of 91.33% on 54 186 positive amplification events.

Development of a novel prognostic nomogram for the early recurrence of liver cancer after curative hepatectomy.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant cancers worldwide. Curative resection is an effective treatment but HCC recurrence rates remain high. This study aimed to establish a novel prognostic nomogram to assess the risk of recurrence in patients following curative resection. METHODS: A total of 410 patients undergoing HCC curative resection were recruited from the Guangdong Provincial People's Hospital (GDPH). The cohort was divided into a training group (n=291) and a validation group (n=97). The risk factors for HCC early recurrence within 1 year of curative hepatectomy were identified. Finally, a multivariate prognostic nomogram was developed and validated. RESULTS: Age, tumor number, tumor capsule, portal vein tumor thrombi, pathological grade, vascular tumor emboli, activated partial thromboplastin time (APTT), and tumor size were identified as independent prognostic risk factors for HCC early recurrence within 1 year of curative hepatectomy. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.806 [95% confidence interval (CI): 0.755 to 0.857; P<0.001], and no AUC/ROC statistical difference was detected between the training and validation sets. CONCLUSIONS: The nomogram effectively predicted postoperative HCC recurrence within 1 year after curative hepatectomy, which may be a useful tool for the postoperative treatment or follow up for HCC patients.

circRPS16 Promotes Proliferation and Invasion of Hepatocellular Carcinoma by Sponging miR-876-5p to Upregulate SPINK1.

The roles of serine protease inhibitor Kazal type 1 (SPINK1) in multiple types of cancers have been significantly documented. However, its specific roles in hepatocellular carcinoma (HCC) remain to be investigated. This study found that SPINK1 is upregulated in HCC and its upregulation correlates with poor prognosis. Besides, functional assays revealed that SPINK1 promotes cell proliferation, cell cycle, and invasion in vitro. Through bioinformatics analysis, we speculate that circRPS16 regulates SPINK1 expression by sponging miR-876-5p. This was further verified by the dual-luciferase reporter and fluorescent in situ hybridization (FISH) assays. Subsequently, rescue assays verified that circRPS16 promotes cell proliferation, cell cycle, and invasion through miR-876-5p. Importantly, silencing circRPS16 inhibited tumor growth by downregulating SPINK1 expression in vivo. Collectively, our results confirm that SPINK1 is a downstream target of circRPS16. Besides, circRPS16 and SPINK1 are oncogenic factors in HCC progression; they provide novel diagnostic and therapeutic targets for HCC patients.

Tumor Cell-Derived Exosomal Circ-0072088 Suppresses Migration and Invasion of Hepatic Carcinoma Cells Through Regulating MMP-16.

Background: Tumor-derived exosomes (EXOs), commonly differentially expressed in circular RNAs, have been shown to be crucial determinants of tumor progression and may regulate the development and metastasis of hepatic carcinoma (HCC). Methods: Possibly differentially expressed circRNAs in patients with HCC were screened out from the Gene Expression Omnibus (GEO). EXOs were isolated from the culture medium of HCC cells and plasma of patients with HCC, followed by characterization by transmission electron microscope, NanHCCight, and western blotting. Additionally, RNA immunoprecipitation and luciferase reporter gene assays were carried out to explore the molecular mechanism of hsa_circRNA_103809 (circ-0072088) in HCC cells. Results: The screening results showed that circ-0072088 was highly expressed in patients with HCC, and its increase indicated unfavorable prognosis of patients according to quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Additionally, circ-0072088 was mainly secreted by HCC cells via EXOs in plasma of such patients, and its high level in plasma EXOs was closely associated with tumor node metastasis (TNM) staging and tumor size. Moreover, HCC-secreted EXOs mediated the degradation of miR-375 via circ-0072088 and upregulated MMP-16, thus suppressing the metastasis of HCC. Conclusion: Upregulated in patients with HCC, circ-0072088 may be an index for diagnosis and prognosis of HCC. In addition, HCC-derived EXOs coated with circ-0072088 might be a treatment for HCC, with the ability to inhibit the metastasis of HCC cells.

Simulating Large Quantum Circuits on a Small Quantum Computer.

Limited quantum memory is one of the most important constraints for near-term quantum devices. Understanding whether a small quantum computer can simulate a larger quantum system, or execute an algorithm requiring more qubits than available, is both of theoretical and practical importance. In this Letter, we introduce cluster parameters K and d of a quantum circuit. The tensor network of such a circuit can be decomposed into clusters of size at most d with at most K qubits of inter-cluster quantum communication. We propose a cluster simulation scheme that can simulate any (K,d)-clustered quantum circuit on a d-qubit machine in time roughly 2^{O(K)}, with further speedups possible when taking more fine-grained circuit structure into account. We show how our scheme can be used to simulate clustered quantum systems-such as large molecules-that can be partitioned into multiple significantly smaller clusters with weak interactions among them. By using a suitable clustered ansatz, we also experimentally demonstrate that a quantum variational eigensolver can still achieve the desired performance for estimating the energy of the BeH_{2} molecule while running on a physical quantum device with half the number of required qubits.

The expression and prognostic value of GLYATL1 and its potential role in hepatocellular carcinoma.

BACKGROUND: Glycine-N-acyltransferase-like 1 (GLYATL1), which is involved in the detoxification of endogenous and exogenous acyl-CoA, promotes glutamine metabolism in xenobiotic metabolism. Recent evidence suggests an association between GLYATL1 and tumors. However, there are few comprehensive analyses of GLYATL1 in cancers. We evaluated the expression and prognostic value of GLYATL1 and explored the mechanism underlying the association between GLYATL1 and cancers. METHODS: GLYATL1 mRNA expression across cancers was investigated in the Oncomine database and confirmed in the UALCAN and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Next, its prognostic value in different cancers was revealed by PrognoScan and Kaplan-Meier plotter. According to clinicopathologic features, we conducted a subgroup analysis of the prognosis of GLYATL1 in a cohort of hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) and the GSE116174 dataset. We further investigated the GLYATL1 promoter methylation profile in HCC. Next, a protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. Finally, we utilized gene set enrichment analysis (GSEA) to identify significantly enriched pathways and confirmed their associations using the Tumor Immune Estimation Resource (TIMER) and GEPIA databases. RESULTS: GLYATL1 is downregulated in many cancers and indicates a poor prognosis. Specifically, low GLYATL1 expression was associated with short overall survival (OS) in HCC patients. Interestingly, GLYATL1 expression was associated with poor OS in stage I-II HCC patients and was revealed as an independent prognostic factor. The promoter methylation level of GLYATL1 in HCC tissue was significantly higher than that in normal liver tissue. The PPI network suggested that GLYATL1 is co-expressed with ten genes, including CNGA3 and GNB5. GSEA revealed that GLYATL1 is predominantly negatively enriched in xenobiotic metabolism, and the gene association analysis in TIMER and GEPIA showed a significantly negative association between the expression of GLYATL1 and the expression of most genes involved in mitochondrial glutamine metabolism, including SLC1A5 and SLC1A11. CONCLUSIONS: Our study is the first to shed light on the expression and prognostic value of GLYATL1 in cancers and provide a potential regulatory mechanism underlying HCC development.

High-Speed Device-Independent Quantum Random Number Generation without a Detection Loophole.

Quantum mechanics provides the means of generating genuine randomness that is impossible with deterministic classical processes. Remarkably, the unpredictability of randomness can be certified in a manner that is independent of implementation devices. Here, we present an experimental study of device-independent quantum random number generation based on a detection-loophole-free Bell test with entangled photons. In the randomness analysis, without the independent identical distribution assumption, we consider the worst case scenario that the adversary launches the most powerful attacks against the quantum adversary. After considering statistical fluctuations and applying an 80 Gb×45.6 Mb Toeplitz matrix hashing, we achieve a final random bit rate of 114 bits/s, with a failure probability less than 10^{-5}. This marks a critical step towards realistic applications in cryptography and fundamental physics tests.