DNA Binding Polyamides and the Importance of DNA Recognition in their use as Gene-Specific and Antiviral Agents

There is a long history for the bioorganic and biomedical use of N-methyl-pyrrole-derived polyamides (PAs) that are higher homologs of natural products such as distamycin A and netropsin. This work has been pursued by many groups, with the Dervan and Sugiyama groups responsible for many breakthroughs. We have studied PAs since about 1999, partly in industry and partly in academia. Early in this program, we reported methods to control cellular uptake of polyamides in cancer cell lines and other cells likely to have multidrug resistance efflux pumps induced. We went on to discover antiviral polyamides active against HPV31, where SAR showed that a minimum binding size of about 10 bp of DNA was necessary for activity. Subsequently we discovered polyamides active against two additional high-risk HPVs, HPV16 and 18, a subset of which showed broad spectrum activity against HPV16, 18 and 31. Aspects of our results presented here are incompatible with reported DNA recognition rules. For example, molecules with the same cognate DNA recognition properties varied from active to inactive against HPVs. We have since pursued the mechanism of action of antiviral polyamides, and polyamides in general, with collaborators at NanoVir, the University of Missouri-St. Louis, and Georgia State University. We describe dramatic consequences of β-alanine positioning even in relatively small, 8-ring polyamides; these results contrast sharply with prior reports. This paper was originally presented by JKB as a Keynote Lecture in the 2nd International Conference on Medicinal Chemistry and Computer Aided Drug Design Conference in Las Vegas, NV, October 2013

Heterogeneous Dynamics in DNA Site Discrimination by the Structurally Homologous DNA-Binding Domains of ETS-Family Transcription Factors

The ETS family of transcription factors exemplifies current uncertainty in how eukaryotic genetic regulators with overlapping DNA sequence preferences achieve target site specificity. PU.1 and Ets-1 represent archetypes for studying site discrimination by ETS proteins because their DNA-binding domains are the most divergent in sequence, yet they share remarkably superimposable DNA-bound structures. To gain insight into the contrasting thermodynamics and kinetics of DNA recognition by these two proteins, we investigated the structure and dynamics of site discrimination by their DNA-binding domains. Electrophoretic mobilities of complexes formed by the two homologs with circularly permuted binding sites showed significant dynamic differences only for DNA complexes of PU.1. Free solution measurements by dynamic light scattering showed PU.1 to be more dynamic than Ets-1; moreover, dynamic changes are strongly coupled to site discrimination by PU.1, but not Ets-1. Interrogation of the protein/DNA interface by DNA footprinting showed similar accessibility to dimethyl sulfate for PU.1/DNA and Ets-1/DNA complexes, indicating that the dynamics of PU.1/DNA complexes reside primarily outside that interface. An information-based analysis of the two homologs’ binding motifs suggests a role for dynamic coupling in PU.1\u27s ability to enforce a more stringent sequence preference than Ets-1 and its proximal sequence homologs

TADW: Traceable and Anti-detection Dynamic Watermarking of Deep Neural Networks

Deep neural networks (DNN) with incomparably advanced performance have been extensively applied in diverse fields (e.g., image recognition, natural language processing, and speech recognition). Training a high-performance DNN model requires a lot of training data and intellectual and computing resources, which bring a high cost to the model owners. Therefore, illegal model abuse (model theft, derivation, resale or redistribution, etc.) seriously infringes model owners’ legitimate rights and interests. Watermarking is considered the main topic of DNN ownership protection. However, almost all existing watermarking works apply solely to image data. They do not trace the unique infringing model, and the adversary easily detects these ownership verification samples (trigger set) simultaneously. This paper introduces TADW, a dynamic watermarking scheme with tracking and antidetection abilities in the deep learning (DL) textual domain. Specifically, we propose a new approach to construct trigger set samples for antidetection and innovatively design a mapping algorithm that assigns a unique serial number (SN) to every watermarked model. Furthermore, we implement and detailedly evaluate TADW on 2 benchmark datasets and 3 popular DNNs. Experiment results show that TADW can successfully verify the ownership of the target model at a less than 0.5% accuracy cost and identify unique infringing models. In addition, TADW is excellently robust against different model modifications and can serve numerous users

Retrieval of Grassland Aboveground Biomass through Inversion of the PROSAIL Model with MODIS Imagery

The estimation of aboveground biomass (AGB), an important indicator of grassland production, is crucial for evaluating livestock carrying capacity, understanding the response and feedback to climate change, and achieving sustainable development. Most existing grassland AGB estimation studies were based on empirical methods, in which field measurements are indispensable, hindering their operational use. This study proposed a novel physically-based grassland AGB retrieval method through the inversion of PROSAIL model against MCD43A4 imagery. This method relies on the basic understanding that grassland is herbaceous, and therefore AGB can be represented as the product of leaf dry matter content (Cm) and leaf area index (LAI), i.e., AGB = Cm × LAI. First, the PROSAIL model was parameterized according to the literature regarding grassland parameters retrieval, then Cm and LAI were retrieved using a lookup table (LUT) algorithm, finally, the retrieved Cm and LAI were multiplied to obtain the AGB. The method was assessed in Zoige Plateau, China. Results show that it could reproduce the reference AGB map, which is generated by upscaling the field measurements, in terms of magnitude (with RMSE and R-RMSE of 60.06 g·m−2 and 18.1%, respectively) and spatial distribution. The estimated AGB time series also agreed reasonably well with the expected temporal dynamic trends of the grassland in our study area. The greatest advantage of our method is its fully physical nature, i.e., no field measurement is needed. Our method has the potential for operational monitoring of grassland AGB at regional and even larger scales

Hydrothermal Regime Variation and Ecological Effects on Fish Reproduction in the Yangtze River

Water temperature, as one of the important water environment impact factors, has a significant impact on the survival and development of aquatic organisms. We selected water temperature data (1959–2017) from four key hydrological stations in the Yangtze River: Cuntan, Yichang, Hankou, and Datong. We analyzed the characteristics and variability of the Yangtze River hydrothermal regime by the Mann-Kendall method, wavelet analysis, and by the IHA-RVA method to analyze hydrothermal regime variations of the Yangtze River, and the response mechanisms of fish to variations in hydrothermal regimes were explored. The results show that (1) The annual average water temperature of the Yangtze River is warming, and Cuntan Station, Yichang Station, Hankou Station, and Datong Station have a sudden increase in temperature in 2002, 1995, 2003, and 2004, and the periodicity analysis demonstrates that Cuntan, Yichang, and Datong stations all have main periods of 24~32 years; (2) The overall variations of 32 hydrothermal indicators at Cuntan Station and Yichang Station reached 65% and 61%, which are close to the height variation; (3) With the construction of the Three Gorges Dam, the stagnant cooling effect caused the arrival date of the upper reproduction water temperature of “The four major fish species” to be delayed by about 23 days, and the stagnant heat effect caused the arrival date of the Chinese sturgeon reproduction upper limit water temperature to be delayed by about 30 days

The Influence of Pretreatment on the Preparation of Fuel Ethanol from Corn Stalk

In this research, the effects of three different pretreatment methods, physical pulverizing, steam blasting and hydrogen peroxide oxidizing, on ethanol preparation from corn straw were compared. The results showed that the content of reducing sugar in corn straw briquette with grinding and steam blasting pretreatment were 2 and 1.5 times higher than that without pretreatment. In the final product, the concentration of ethanol and rate of alcohol increased about 3.8 and 2 times, respectively. Besides, the reducing sugar content, ethanol content and alcohol yield in corn stalks soaked in hydrogen peroxide were 7 times higher than the untreated. The cellulose can be effectively isolated after being soaked in hydrogen peroxide with a concentration of 2.5% for 72 hours, as well as better degradation of lignin and hemicellulose. The amount of ethanol and the yield of alcohol were 1.9 and 3.3 times higher than physical pulverization and steam blasting. In brief, it is declared that hydrogen peroxide pretreatment can easily destroy the lignocellulosic cellulose of maize straw and improve the conversion rate of cellulose, which might be beneficial for the production of fuel ethanol