Bioinformatics analysis of HPV associated host microRNA functions and identification of viral microRNA

Human papillomaviruses (HPVs) form a large family among double stranded DNA (dsDNA) viruses, some types of which are the major causes of cervical cancer. HPV 16 is widely distributed and the most common high-risk HPV type and approximately half of the cervical cancers are associated with HPV type 16. Of the three HPV 16 encoded oncogenes, the function of E5 in regulating viral replication and pathogenesis is less well understood than E6 and E7. The microRNAs (miRNAs) are important small noncoding RNA molecules that regulate wide range of cellular functions. Some dsDNA viruses, such as SV40 and human polyomaviruses, have functional viral miRNAs. The functional and molecular similarities among dsDNA viruses suggest that HPV could encode viral miRNAs, which have not been validated thus far. The aim of this thesis was to study the functions of the host miRNAs in HPV 16 oncogene induction and identify novel HPV encoded viral miRNAs. We utilized microarray technology to investigate the effect of E5 on host miRNAs and mRNAs expression in 0 96 hours after E5 induction in a cell line model. Among the differentially expressed cellular miRNAs, we further validated the expression of hsa-mir-146a, hsa-mir-203, and hsa-mir-324-5p and some of their target genes in a time series of 96 hours of E5 induction. Our results indicate that HPV E5 expression has an impact through complex regulatory patterns of gene expression in the host cells, and part of those genes is regulated by the E5 protein. Second, high throughput sequencing was used to identify virus-encoded miRNAs. We prepared small RNA sequencing libraries from ten HPV-associated cervical lesions, including cancer and two HPV-harboring cell lines. For more flexible analysis of the sequencing data we developed miRSeqNovel, an R based workflow for miRNA sequencing data analysis, and applied it to the sequencing data to predict putative viral miRNAs and discovered nine putative papillomavirus encoded miRNAs. Viral miRNA validation was performed for five candidates, four of which were successfully validated by qPCR from cervical tissue samples and cell lines: two were encoded by HPV 16, one by HPV 38, and one by HPV 68. The expression of two HPV 16 miRNAs was further supported by in situ hybridization, and colocalization with p16INK4A staining, a marker of cervical neoplasia. Prediction of cellular target genes of HPV 16 encoded miRNAs suggests that they may play a role in cell cycle, immune functions, cell adhesion and migration, development and cancer, which were also among the functions targeted by the E5 regulated host cell mRNA and miRNAs. Two putative viral target sites for the two validated HPV 16 miRNAs were mapped to the E5 gene, one in the E1 gene, two in the L1 gene, and one in the long control region (LCR).Ihmisen papilloomavirukset (HPV) muodostavat suuren heimon kaksijuosteisen DNA-virusten (dsDNA) joukossa, ja niistä jotkin virustyypit ovat kohdunkaulasyövän pääasiallisia aiheuttajia. HPV 16 on laajalle levinnyt ja yleisin suuren riskin HPV-tyyppi, joka aiheuttaa noin puolet kohdunkaulasyövistä. Kolmesta HPV 16:n koodittamasta onkogeenistä E5:n toiminta viruksen replikaation ja patogeneesin säätelyssä tunnetaan huonommin kuin E6:n ja E7:n. Mikro-RNA:t (miRNA) ovat pieniä ei-koodittaavia RNA-molekyylejä, joilla on tärkeä merkitys solun toimintojen säätelyssä. Jotkin dsDNA-virukset, kuten SV40 ja ihmisen polyoomavirukset, koodittavat omia toiminnallisia mikro-RNA:ita. HPV:n koodittamia mRNAita ei ole aiemmin validoitu, mutta dsDNA-virusten toiminnalliset ja molekulaariset samankaltaisuudet viittaavat siihen, että myös HPV voisi koodittaa omia mikro-RNA:ita. Väitöskirjan tavoitteena oli tutkia isäntäsolun mikro-RNA:iden toimintaa HPV 16 onkogeeni-induktiossa ja löytää uusia, HPV:n koodittamia miRNA:ita. Tutkimme sirutekniikan avulla E5:n vaikutusta isännän miRNA- ja mRNA-ekspressioon solulinjamallissa 0-96 tunnin kuluessa E5:n induktiosta. Eri tavoin ekpressoituneista miRNA tutkimme tarkemmin hsa-mir-146, hsa-mir-203 ja hsa-mir-324-5p sekä muutamien näiden kohdegeenien ekspressiota 96 tunnin aikasarjana E5 induktiosta. Tulokset osoittavat HPV E5 ekspression vaikuttavan isäntäsolun geenien ilmentymiseen monimutkaisen säätelymallin välityksellä ja E5-proteiinin myös säätelevän osaa näistä geeneistä. Next generation sekvensointia käytettiin tunnistamaan virusten koodaamia miRNA:ita. Joustavampaa miRNA sekvenssidatan analysointia varten kehitimme miRSeqNovel-nimisen R-pohjaisen työkalun ja käytimme sitä ennustamaan mahdollisia virusten koodaamia miRNA:ita. Löysimme yhdeksän mahdollisesti HPV:n koodaamaa miRNA:ta, joista viisi otettiin mukaan miRNAn validointiin. Neljä viidestä HPV:n koodaamasta miRNAsta pystyttiin validoimaan qPCR:n avulla kohdunkaulan kudosnäytteistä ja solulonjoista. Näistä kaksi miRNA:ta on HPV 16 koodaamaa ja yhdet HPV38 ja HPV68 koodaamia. Kahden HPV16 koodaaman miRNA:n ekspressiota osoitettiin myös in-situ-hybridisaatiossa kolokalisoituneena värjäyksessä kohdunkaulan neoplasiasta kertovan P16INK4a kanssa. HPV16 mikro-RNA:n kohdegeenien ennusteet viittaavat miRNA:iden mahdolliseen rooliin solusyklissä, immuunijärjestelmän toiminnoissa, soluadheesiossa ja migraatiossa, yksilönkehityksessä ja syövässä. Nämä kohteet löytyvät myös E5:n säätelemien mRNA:iden ja miRNA:iden kohteista. Kaksi HPV16 miRNA:n mahdollista kohdetta löytyvät viruksen E5-geenistä, yksi kohden E1 geenistä, kaksi L1 geenistä ja yksi pitkästä kontrollialueesta (LCR)

Non-Hermitian Maxwell's Demon

Maxwell's demon was first introduced by Maxwell in 1871 to discuss the limitations of the second law of thermodynamics due to addition information flow. In this paper, an alternative type of Maxwell's demon -- non-Hermitian Maxwell's demon is uncovered that shows quite different properties as the original Maxwell's demon and leads to rich physics phenomena in non-Hermitian systems, such as mismatch between single-body and many-body properties, Bose-Einstein condensation at arbitrary high temperature, phase transition that violates the Goldstone theorem. This provides an alternative degree of freedom to tune quantum many-body systems and realize exotic quantum phases and phase transitions

An Online Word Vector Generation Method Based on Incremental Huffman Tree Merging

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Global Convergence of a Nonlinear Conjugate Gradient Method

A modified PRP nonlinear conjugate gradient method to solve unconstrained optimization problems is proposed. The important property of the proposed method is that the sufficient descent property is guaranteed independent of any line search. By the use of the Wolfe line search, the global convergence of the proposed method is established for nonconvex minimization. Numerical results show that the proposed method is effective and promising by comparing with the VPRP, CG-DESCENT, and DL+ methods

Supervised Contrastive Learning for Fine-grained Chromosome Recognition

Chromosome recognition is an essential task in karyotyping, which plays a vital role in birth defect diagnosis and biomedical research. However, existing classification methods face significant challenges due to the inter-class similarity and intra-class variation of chromosomes. To address this issue, we propose a supervised contrastive learning strategy that is tailored to train model-agnostic deep networks for reliable chromosome classification. This method enables extracting fine-grained chromosomal embeddings in latent space. These embeddings effectively expand inter-class boundaries and reduce intra-class variations, enhancing their distinctiveness in predicting chromosome types. On top of two large-scale chromosome datasets, we comprehensively validate the power of our contrastive learning strategy in boosting cutting-edge deep networks such as Transformers and ResNets. Extensive results demonstrate that it can significantly improve models' generalization performance, with an accuracy improvement up to +4.5%. Codes and pretrained models will be released upon acceptance of this work

A Learning-based Discretionary Lane-Change Decision-Making Model with Driving Style Awareness

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Anti-jamming communication in cognitive radio networks with unknown channel Statistics

Abstract-Recently, many opportunistic spectrum sensing and access protocols have been proposed for cognitive radio networks (CRNs). For achieving optimized spectrum usage, existing solutions model the spectrum sensing and access problem as a partially observed Markov decision process (POMDP) and assume that the information states and/or the primary users' (PUs) traffic statistics are known a priori to the secondary users (SUs). While theoretically sound, these existing approaches may not be effective in practice due to two main concerns. First, the assumptions they made are not practical, as before the communication starts, PUs' traffic statistics may not be readily available to the SUs. Secondly and more seriously, existing approaches are extremely vulnerable to malicious jamming attacks. A cognitive attacker can always jam the channels to be accessed by leveraging the same statistic information and stochastic dynamic decision making process that the SUs would follow. To address the above concerns, we formulate the problem of anti-jamming multichannel access in CRNs and solve it as a non-stochastic multiarmed bandit (NS-MAB) problem, where the secondary sender and receiver adaptively choose their arms (i.e., sending and receiving channels) to operate. The proposed protocol enables them to hop to the same set of channels with high probability in the presence of jamming. We analytically show the convergence of the learning algorithms, i.e., the performance difference between the secondary sender and receiver's optimal strategies is no more than O( T n ln n). Extensive simulations are conducted to validate the theoretical analysis and show that the proposed protocol is highly resilient to various jamming attacks