UV-induced cyclobutane pyrimidine dimers (CPDs) in the template DNA strand stall transcription elongation by RNA polymerase II (Pol II). If the nucleotide excision repair machinery does not promptly remove the CPDs, stalled Pol II creates a roadblock for DNA replication and subsequent rounds of transcription. Here we present evidence that Pol II has an intrinsic capacity for translesion synthesis (TLS) that enables bypass of the CPD with or without repair. Translesion synthesis depends on the trigger loop and bridge helix, the two flexible regions of the Pol II subunit Rpb1 that participate in substrate binding, catalysis, and translocation. Substitutions in Rpb1 that promote lesion bypass in vitro increase UV resistance in vivo and substitutions that inhibit lesion bypass decrease cell survival after UV irradiation. Thus, translesion transcription becomes essential for cell survival upon accumulation of the unrepaired CPD lesions in genomic DNA.
Plate-tectonic processes have long been thought to be the major cause of the Cenozoic global carbon cycle, and global cooling by uplift of the Tibetan Plateau through enhancing silicate weathering and organic carbon burial and/or by weathering of obducted ophiolites during the closure of the Neo-Tethys Ocean. However, the imbalance resulting from accelerated CO2 consumption and a relatively stable CO2 input from volcanic degassing during the Cenozoic should have depleted atmospheric CO2 within a few million years; therefore, a negative feedback mechanism must have stabilized the carbon cycle. Here, we present the first almost-complete Paleogene silicate weathering intensity (SWI) records from continental rocks in the northern Tibetan Plateau showing that silicate weathering in this tectonically inactive area was modulated by global temperature. These findings suggest that Paleogene global cooling was also strongly influenced by a temperature feedback mechanism, which regulated silicate weathering rates and hydrological cycles and maintained a nearly stable carbon cycle. It acted as a negative feedback by decreasing CO2 consumption resulting from the lower SWI and the kinetic limitations in tectonically inactive areas.
Phishing attack is now a big threat to people's daily life and networking environment. Through disguising illegal URLs as legitimate ones, attackers can induce users to visit the phishing URLs to get private information and other benefits. Effective methods of detecting the phishing websites are urgently needed to alleviate the threats posed by the phishing attacks. As the active learning capability from massive data sets, the neural network is widely used to detect the phishing attacks. However, in the stage of training data sets, many useless and small influence features will trap the neural network model into the problem of over-fitting. This problem usually causes the trained model that cannot effectively detect phishing websites. In order to alleviate this problem, this paper proposes OFS-NN, an effective phishing websites detection model based on the optimal feature selection method and neural network. In the proposed OFS-NN, a new index, feature validity value (FVV), is first introduced to evaluate the impact of sensitive features on the phishing websites detection. Then, based on the new FVV index, an algorithm is designed to select the optimal features from the phishing websites. This algorithm is able to alleviate the over-fitting problem of the underlying neural network to a large extent. The selected optimal features are used to train the underlying neural network, and finally, an optimal classifier is constructed to detect the phishing websites. The experimental results show that the OFS-NN model is accurate and stable in detecting many types of phishing websites. INDEX TERMS Information security, intrusion detection, machine learning, neural network.
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