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The issues of the degradation of the visual sensor's image quality in foggy weather and the loss of information after defogging have brought great challenges to obstacle detection during autonomous driving. Therefore, this paper proposes a method for detecting driving obstacles in foggy weather. The driving obstacle detection in foggy weather was realized by combining the GCANet defogging algorithm with the detection algorithm-based edge and convolution feature fusion training, with a full consideration of the reasonable matching between the defogging algorithm and the detection algorithm on the basis of the characteristics of obvious target edge features after GCANet defogging. Based on the YOLOv5 network, the obstacle detection model is trained using clear day images and corresponding edge feature images to realize the fusion of edge features and convolution features, and to detect driving obstacles in a foggy traffic environment. Compared with the conventional training method, the method improves the mAP by 12% and recall by 9%. In contrast to conventional detection methods, this method can better identify the image edge information after defogging, which significantly enhances detection accuracy while ensuring time efficiency. This is of great practical significance for improving the safe perception of driving obstacles under adverse weather conditions, ensuring the safety of autonomous driving. [ABSTRACT FROM AUTHOR]

Polyketides are a large class of structurally and functionally diverse natural products with important bioactivities. Many polyketides are synthesized by reducing type II polyketide synthases (PKSs), containing transiently interacting standalone enzymes. During synthesis, ketoreductase (KR) catalyzes regiospecific carbonyl to hydroxyl reduction, determining the product outcome, yet little is known about what drives specific KR–substrate interactions. In this study, computational approaches were used to explore KR–substrate interactions based on previously solved apo and mimic cocrystal structures. We found five key factors guiding KR–substrate binding. First, two major substrate binding motifs were identified. Second, substrate length is the key determinant of substrate binding position. Third, two key residues in chain length specificity were confirmed. Fourth, phosphorylation of substrates is critical for binding. Finally, packing/hydrophobic effects primarily determine the binding stability. The molecular bases revealed here will help further engineering of type II PKSs and directed biosynthesis of new polyketides. [ABSTRACT FROM AUTHOR]

Target deconvolution is a crucial but costly and time-consuming task that hinders large-scale profiling for drug discovery. We present a m atrix-augmented p ooling s trategy (MAPS) which mixes multiple drugs into samples with optimized permutation and delineates targets of each drug simultaneously with mathematical processing. We validated this strategy with thermal proteome profiling (TPP) testing of 15 drugs concurrently, increasing experimental throughput by 60x while maintaining high sensitivity and specificity. Benefiting from the lower cost and higher throughput of MAPS, we performed target deconvolution of the 15 drugs across 5 cell lines. Our profiling revealed that drug-target interactions can differ vastly in targets and binding affinity across cell lines. We further validated BRAF and CSNK2A2 as potential off-targets of bafetinib and abemaciclib, respectively. This work represents the largest thermal profiling of structurally diverse drugs across multiple cell lines to date. [Display omitted] • MAPS strategy boosts throughput of derivatization-free target deconvolution by 15x • MAPS profiling across multiple cell lines reveals cell-specific drug targets • BRAF and CSNK2A2 were validated as target of bafetinib and abemaciclib, respectively Ji et al. develop a high-throughput strategy and algorithms for large-scale derivatization-free drug target deconvolution. The strategy is validated experimentally on large set of diverse drugs across multiple cell lines revealing drug-protein interactions that differ across cell lines. [ABSTRACT FROM AUTHOR]

• Australian agricultural TFP is sensitive to climate variability and long-term change. • A new framework is proposed to disentangle climate variability from agricultural TFP. • The new 'climate-adjusted TFP' enables observation of industry progress in productivity. • The climate-adjusted TFP is valuable for both statistical agencies and policy makers. Estimates of agricultural Total Factor Productivity (TFP) can be highly sensitive to both short-run climate variability and long-term climate change. This is particularly true in Australia where drought impacts are responsible for most of the annual volatility in official farm TFP statistics. While climate variability can obscure short-term productivity trends, researchers have typically assumed that long run TFP trends are largely unaffected. However, in the presence of global climate change this assumption becomes problematic. For example, in Australia, shifts to higher temperatures and lower winter season rainfall over the last 20–30 years have had a significant negative impact on agricultural productivity. This study presents a framework to account for the effects of climate variability on TFP estimates. In contrast with previous work, this approach applies a reduced form machine learning based model of farm production to generate synthetic (climate-adjusted) farm-level input and output data sets. It therefore has advantages in terms of flexibility—since the synthetic datasets can be combined with any existing TFP estimation framework. In this study, the approach is applied to estimate climate-adjusted TFP indices (TFP under an assumption of constant long-run average climate conditions) for a range of Australian agricultural sectors. [ABSTRACT FROM AUTHOR]

In order to develop a secure and competent technique to express the human immune gene for fighting infections, we cloned and expressed the BD2/3 using VR1020 (a eukaryotic expression plasmid). BD2/3 contains human β-defensin 2 (BD2) and human BD3. To explore safe and effective DNA delivery molecules in vitro and in vivo, the fusion genes of BD2/3 were used as an immune-labelled gene to verify transfection effectivness of modified chitosan (CS). Plasmid of VR1020-BD2/3 was packed with biomaterials: CS, average molecular weight: 25000D; polyethylene glycol-O-chitosan-polyethylenimine (PEG-O-CS-PEI); liposomes (LP); polyamine cationic liposomes (PCL); polyamine cationic liposomes of protamine (PCL-protamine) by ionotropic gelation. We observed that BD2/3 fusion gene showed high bioactivity in vitro and in vivo. The BD2/3 fusion protein inhibited the proliferation of bacteria (S. aureus, S. pneumoniae, P. aeruginosa and E. coli). The Kunming mice were immune to these nanoparticles and we analyzed their delivery efficiency and gene expression effect. BD2/3 results in multiple changes of innate and required immune system of mice. BD2/3 increases expression of IgG, IgG1, IgG2a, IL-2, IL-6, IFN-γ, as well as of lymphocytes and monocytes. Following challenge with virulent E. coli, CD4+ and CD8+ positive T-cell counts were highly elevated in the BD2/3 immunized mice, resulting in higher survival rates of mice. These results indicate that nanoparticles containing modified CS and BD2/3 are potentially safe and effective drugs in vivo to improve the immunity against bacterial infection and enhance innate immunity and adaptive immunity against infectious diseases. [ABSTRACT FROM AUTHOR]

The Hippo pathway, which plays a critical role in organ size control and cancer, features numerous WW domain‐based protein–protein interactions. However, ~100 WW domains and 2,000 PY motif‐containing peptide ligands are found in the human proteome, raising a "WW‐PY" binding specificity issue in the Hippo pathway. In this study, we have established the WW domain binding specificity for Hippo pathway components and uncovered a unique amino acid sequence required for it. By using this criterion, we have identified a WW domain‐containing protein, STXBP4, as a negative regulator of YAP. Mechanistically, STXBP4 assembles a protein complex comprising α‐catenin and a group of Hippo PY motif‐containing components/regulators to inhibit YAP, a process that is regulated by actin cytoskeleton tension. Interestingly, STXBP4 is a potential tumor suppressor for human kidney cancer, whose downregulation is correlated with YAP activation in clear cell renal cell carcinoma. Taken together, our study not only elucidates the WW domain binding specificity for the Hippo pathway, but also reveals STXBP4 as a player in actin cytoskeleton tension‐mediated Hippo pathway regulation. Synopsis: Interactions between the Hippo pathway components are often mediated by WW domain binding to PY motifs. Identification of a conserved WW domain sequence that mediates specific interactions with Hippo pathway components uncovers syntaxin‐binding protein 4 (STXBP4) as an inhibitor of YAP activity and a potential tumor suppressor in kidney cancer. A "WW‐PY" binding specificity exists within the Hippo pathway protein‐protein interaction network.A unique 9‐amino acid sequence defines the specificity of WW domain‐containing protein interactions with Hippo pathway components.WW domain‐containing protein STXBP4 inhibits YAP activity via LATS1‐mediated phosphorylation.STXBP4 sequesters YAP in a complex with α‐catenin and several PY motif‐containing Hippo pathway members.STXBP4 functions as a potential tumor suppressor in clear cell renal cell carcinoma. [ABSTRACT FROM AUTHOR]