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"Kui Wang"
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Searchable encryption : from concepts to systems
This book comprehensively reviews searchable encryption, which represents a series of research developments that directly enable search functionality over encrypted data. The book majorly covers: 1) the design and implementation of encrypted search algorithms, data structures, and systems that facilitate various forms of search over always-encrypted databases; 2) different threat models, assumptions, and the related security guarantees, when using searchable encryption in the real-world settings; and 3) latest efforts in building full-fledged encrypted database systems that draw insights from searchable encryption constructions. The book fits in the timely context, where the necessity of safeguarding important and sensitive data has been globally recognized. Traditional security measures, such as storing data behind network firewalls and layers of access control mechanisms to keep attackers out, are no longer sufficient to cope with the expanding landscape of surging cyber threats. There is an urgent call to keep sensitive data always encrypted to protect the data at rest, in transit, and in use. Doing so guarantees data confidentiality for owners, even if the data is out of their hands, e.g., hosted at in-the-cloud databases. The daunting challenge is how to perform computation over encrypted data. As we unfold in this book, searchable encryption, as a specific line of research in this broadly defined area, has received tremendous advancements over the past decades. This book is majorly oriented toward senior undergraduates, graduate students, and researchers, who want to work in the field and need extensive coverage of encrypted database research. It also targets security practitioners who want to make well-informed deployment choices of the latest advancements in searchable encryption for their targeted applications. Hopefully, this book will be beneficial in both regards.
Book
Activator-type R2R3-MYB genes induce a repressor-type R2R3-MYB gene to balance anthocyanin and proanthocyanidin accumulation
• Anthocyanin and proanthocyanidin (PA) accumulation is regulated by both myeloblastosis (MYB) activators and repressors, but little information is available on hierarchical interactions between the positive and negative regulators. Here, we report on a R2R3-MYB repressor in peach, designated PpMYB18, which acts as a negative regulator of anthocyanin and PA accumulation.
• PpMYB18 can be activated by both anthocyanin- and PA-related MYB activators, and is expressed both at fruit ripening and juvenile stages when anthocyanins or PAs, respectively, are being synthesized.
• The PpMYB18 protein competes with MYB activators for binding to basic Helix Loop Helixes (bHLHs), which develops a fine-tuning regulatory loop to balance PA and anthocyanin accumulation. In addition, the bHLH binding motif in the R3 domain and the C1 and C2 repression motifs in the C-terminus of PpMYB18 both confer repressive activity of PpMYB18.
• Our study also demonstrates a modifying negative feedback loop, which prevents cells from excess accumulation of anthocyanin and PAs, and serves as a model for balancing secondary metabolite accumulation at the transcriptional level.
Journal Article
Constructive molecular configurations for surface-defect passivation of perovskite photovoltaics
Surface trap–mediated nonradiative charge recombination is a major limit to achieving high-efficiency metal-halide perovskite photovoltaics. The ionic character of perovskite lattice has enabled molecular defect passivation approaches through interaction between functional groups and defects. However, a lack of in-depth understanding of how the molecular configuration influences the passivation effectiveness is a challenge to rational molecule design. Here, the chemical environment of a functional group that is activated for defect passivation was systematically investigated with theophylline, caffeine, and theobromine. When N-H and C=O were in an optimal configuration in the molecule, hydrogen-bond formation between N-H and I (iodine) assisted the primary C=O binding with the antisite Pb (lead) defect to maximize surface-defect binding. A stabilized power conversion efficiency of 22.6% of photovoltaic device was demonstrated with theophylline treatment.
Journal Article
PpGST1, an anthocyanin‐related glutathione S‐transferase gene, is essential for fruit coloration in peach
Summary Anthocyanins have crucial biological functions and affect quality of horticultural produce. Anthocyanins accumulate in ripe peach fruit; differential accumulation is observed in deep coloured cultivar ‘Hujingmilu’ and lightly pigmented cultivar ‘Yulu’. The difference was not fully explained by accumulation of total flavonoids and expression of anthocyanin biosynthetic genes. Expression analysis was conducted on a glutathione S‐transferase gene (PpGST1), and it was found that the expression correlated well with anthocyanin accumulation in peach fruit tissues. Functional complementation of the Arabidopsis tt19 mutant indicated that PpGST1 was responsible for transport of anthocyanins but not proanthocyanidins. PpGST1 was localized in nuclei and the tonoplast, including the sites at which anthocyanin vacuolar sequestration occurred. Transient overexpression of PpGST1 together with PpMYB10.1 in tobacco leaves and peach fruit significantly increased anthocyanin accumulation as compared with PpMYB10.1 alone. Furthermore, virus‐induced gene silencing of PpGST1 in a blood‐fleshed peach not only resulted in a reduction in anthocyanin accumulation but also a decline in expression of anthocyanin biosynthetic and regulatory genes. Cis‐element analysis of the PpGST1 promoter revealed the presence of four MYB binding sites (MBSs). Dual‐luciferase assays indicated that PpMYB10.1 bound to the promoter and activated the transcription of PpGST1 by recognizing MBS1, the one closest to the ATG start codon, with this trans‐activation being stronger against the promoter of deep coloured ‘Hujingmilu’ compared with lightly coloured cultivar ‘Yulu’. Altogether, our data provided molecular evidence supporting coordinative regulatory roles of PpGST1 and PpMYB10.1 in anthocyanin accumulation in peach.
Journal Article
Targeted inhibition of tumor-derived exosomes as a novel therapeutic option for cancer
Mounting evidence indicates that tumor-derived exosomes (TDEs) play critical roles in tumor development and progression by regulating components in the tumor microenvironment (TME) in an autocrine or paracrine manner. Moreover, due to their delivery of critical molecules that react to chemotherapy and immunotherapy, TDEs also contribute to tumor drug resistance and impede the effective response of antitumor immunotherapy, thereby leading to poor clinical outcomes. There is a pressing need for the inhibition or removal of TDEs to facilitate the treatment and prognosis of cancer patients. Here, in the present review, we systematically overviewed the current strategies for TDE inhibition and clearance, providing novel insights for future tumor interventions in translational medicine. Moreover, existing challenges and potential prospects for TDE-targeted cancer therapy are also discussed to bridge the gaps between progress and promising applications.
Cancer therapy: Interrupting messages sent by tumors
Inhibiting or removing tumor-derived exosomes (TDEs), tiny membrane-bound packets of DNA, RNA, and proteins secreted by tumors, may improve cancer therapies. TDEs can suppress the body’s immune response, promote tumor progression and spread, and reduce efficacy of cancer drugs and immunotherapy. Gang Chen at Wuhan University, China, and co-workers have reviewed ways to remove or inhibit production of TDEs. They report that disruption of the genes for production of TDEs, drugs that inhibit TDE secretion, and removal of TDEs via plasma exchange or dialysis are all being investigated and show promise for reducing patient TDE load, thereby increasing the efficacy of anti-cancer drugs and immunotherapy. Future challenges include reducing side effects and finding less invasive ways to filter out TDEs. Gaining a better understanding of TDEs may help to improve therapies for many types of cancer.
Journal Article
flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions
Identification of intrinsic disorder in proteins relies in large part on computational predictors, which demands that their accuracy should be high. Since intrinsic disorder carries out a broad range of cellular functions, it is desirable to couple the disorder and disorder function predictions. We report a computational tool, flDPnn, that provides accurate, fast and comprehensive disorder and disorder function predictions from protein sequences. The recent Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment and results on other test datasets demonstrate that flDPnn offers accurate predictions of disorder, fully disordered proteins and four common disorder functions. These predictions are substantially better than the results of the existing disorder predictors and methods that predict functions of disorder. Ablation tests reveal that the high predictive performance stems from innovative ways used in flDPnn to derive sequence profiles and encode inputs. flDPnn’s webserver is available at
http://biomine.cs.vcu.edu/servers/flDPnn/
The authors present flDPnn, a computational tool for disorder and disorder function predictions from protein sequences. flDPnn was assessed with the data from the “Critical Assessment of Protein Intrinsic Disorder Prediction” experiment and on an independent and low-similarity test dataset, which show that flDPnn offers accurate predictions of disorder, fully disordered proteins and four common disorder functions.
Journal Article
Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis
Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised clustering, but the ever increasing number of cells and batch effect impose computational challenges. We present DESC, an unsupervised deep embedding algorithm that clusters scRNA-seq data by iteratively optimizing a clustering objective function. Through iterative self-learning, DESC gradually removes batch effects, as long as technical differences across batches are smaller than true biological variations. As a soft clustering algorithm, cluster assignment probabilities from DESC are biologically interpretable and can reveal both discrete and pseudotemporal structure of cells. Comprehensive evaluations show that DESC offers a proper balance of clustering accuracy and stability, has a small footprint on memory, does not explicitly require batch information for batch effect removal, and can utilize GPU when available. As the scale of single-cell studies continues to grow, we believe DESC will offer a valuable tool for biomedical researchers to disentangle complex cellular heterogeneity.
Increasingly large scRNA-seq datasets demand better and more scalable analysis tools. Here, the authors introduce a scalable unsupervised deep embedding algorithm that clusters scRNA-seq data by iteratively optimizing a clustering objective function and enables removal of batch effects.
Journal Article
Mechanical Insights into Aggregation‐Induced Delayed Fluorescence Materials with Anti‐Kasha Behavior
Organic materials with aggregation‐induced delayed fluorescence (AIDF) have exhibited impressive merits for improving electroluminescence efficiency and decreasing efficiency roll‐off of nondoped organic light‐emitting diodes (OLEDs). However, the lack of comprehensive insights into the underlying mechanism may impede further development and application of AIDF materials. Herein, AIDF materials consisting of benzoyl serving as an electron acceptor, and phenoxazine and fluorene derivatives as electron donors are reported. They display greatly enhanced fluorescence with increased delayed component upon aggregate formation. Experimental and theoretical investigations reveal that this AIDF phenomenon can be rationally ascribed to the suppression of internal conversion and the promotion of intersystem crossing in solid. Moreover, the theoretical calculations disclose that the efficient solid‐state delayed fluorescence originates from the higher energy electronic excited state (e.g., S2) rather than the lowest energy‐excited state (S1), demonstrating an anti‐Kasha behavior. The excellent AIDF property allows high exciton utilization and thus superb performance of OLEDs using these new materials as light‐emitting layers. Aggregation‐induced delayed fluorescence (AIDF) can be interpreted as a consequence of the suppression of internal conversion and the promotion of intersystem crossing in the aggregated state. Moreover, efficient solid‐state delayed fluorescence of some AIDF molecules can originate from the higher energy electronic excited state rather than the lowest energy one, demonstrating an anti‐Kasha behavior.
Journal Article
Targeting the Interplay of Autophagy and ROS for Cancer Therapy: An Updated Overview on Phytochemicals
Autophagy is an evolutionarily conserved self-degradation system that recycles cellular components and damaged organelles, which is critical for the maintenance of cellular homeostasis. Intracellular reactive oxygen species (ROS) are short-lived molecules containing unpaired electrons that are formed by the partial reduction of molecular oxygen. It is widely known that autophagy and ROS can regulate each other to influence the progression of cancer. Recently, due to the wide potent anti-cancer effects with minimal side effects, phytochemicals, especially those that can modulate ROS and autophagy, have attracted great interest of researchers. In this review, we afford an overview of the complex regulatory relationship between autophagy and ROS in cancer, with an emphasis on phytochemicals that regulate ROS and autophagy for cancer therapy. We also discuss the effects of ROS/autophagy inhibitors on the anti-cancer effects of phytochemicals, and the challenges associated with harnessing the regulation potential on ROS and autophagy of phytochemicals for cancer therapy.
Journal Article
PHGDH arginine methylation by PRMT1 promotes serine synthesis and represents a therapeutic vulnerability in hepatocellular carcinoma
Serine synthesis is crucial for tumor growth and survival, but its regulatory mechanism in cancer remains elusive. Here, using integrative metabolomics and transcriptomics analyses, we show a heterogeneity between metabolite and transcript profiles. Specifically, the level of serine in hepatocellular carcinoma (HCC) tissues is increased, whereas the expression of phosphoglycerate dehydrogenase (PHGDH), the first rate-limiting enzyme in serine biosynthesis pathway, is markedly downregulated. Interestingly, the increased serine level is obtained by enhanced PHGDH catalytic activity due to protein arginine methyltransferase 1 (PRMT1)-mediated methylation of PHGDH at arginine 236. PRMT1-mediated PHGDH methylation and activation potentiates serine synthesis, ameliorates oxidative stress, and promotes HCC growth in vitro and in vivo. Furthermore, PRMT1-mediated PHGDH methylation correlates with PHGDH hyperactivation and serine accumulation in human HCC tissues, and is predictive of poor prognosis of HCC patients. Notably, blocking PHGDH methylation with a TAT-tagged nonmethylated peptide inhibits serine synthesis and restrains HCC growth in an HCC patient-derived xenograft (PDX) model and subcutaneous HCC cell-derived xenograft model. Overall, our findings reveal a regulatory mechanism of PHGDH activity and serine synthesis, and suggest PHGDH methylation as a potential therapeutic vulnerability in HCC.
The role of protein arginine methylation in serine metabolism of cancer cells in hepatocellular carcinoma (HCC) remains to be explored. Here, the authors show that phosphoglycerate dehydrogenase (PHGDH) is activated by PRMT1-mediated R236 methylation, promoting serine synthesis, redox homeostasis and HCC growth.
Journal Article