Molecular basis for recognition of Gly/N-degrons by CRL2ZYG11B and CRL2ZER1.

N-degron pathways are a set of proteolytic systems that target the N-terminal destabilizing residues of substrates for proteasomal degradation. Recently, the Gly/N-degron pathway has been identified as a new branch of the N-degron pathway. The N-terminal glycine degron (Gly/N-degron) is recognized by ZYG11B and ZER1, the substrate receptors of the Cullin 2-RING E3 ubiquitin ligase (CRL2). Here we present the crystal structures of ZYG11B and ZER1 bound to various Gly/N-degrons. The structures reveal that ZYG11B and ZER1 utilize their armadillo (ARM) repeats forming a deep and narrow cavity to engage mainly the first four residues of Gly/N-degrons. The α-amino group of the Gly/N-degron is accommodated in an acidic pocket by five conserved hydrogen bonds. These structures, together with biochemical studies, decipher the molecular basis for the specific recognition of the Gly/N-degron by ZYG11B and ZER1, providing key information for future structure-based chemical probe design.

C-terminal glutamine acts as a C-degron targeted by E3 ubiquitin ligase TRIM7.

The exposed N-terminal or C-terminal residues of proteins can act, in cognate sequence contexts, as degradation signals (degrons) that are targeted by specific E3 ubiquitin ligases for proteasome-dependent degradation by N-degron or C-degron pathways. Here, we discovered a distinct C-degron pathway, termed the Gln/C-degron pathway, in which the B30.2 domain of E3 ubiquitin ligase TRIM7 (TRIM7B30.2) mediates the recognition of proteins bearing a C-terminal glutamine. By determining crystal structures of TRIM7B30.2 in complexes with various peptides, we show that TRIM7B30.2 forms a positively charged binding pocket to engage the "U"-shaped Gln/C-degron. The four C-terminal residues of a substrate play an important role in C-degron recognition, with C-terminal glutamine as the principal determinant. In vitro biochemical and cellular experiments were used to further analyze the substrate specificity and selective degradation of the Gln/C-degron by TRIM7.

Flower color polymorphism of a wild Iris on the Qinghai-Tibet plateau.

BACKGROUND: Flower color plays a crucial role in attracting pollinators and facilitating environmental adaptation. Investigating the causes of flower color polymorphism and understanding their potential effects on both ecology and genetics can enhance our understanding of flower color polymorphism in wild plant. RESULTS: In this study, we examined the differences of potential male and female fitness between purple- and yellow- flower individuals in Iris potaninii on the Qinghai-Tibet Plateau, and screened key genes and positively selective genes involved in flower color change. Our results showed that yellow flower exhibited a higher pollen-to-ovule ratio. Yellow flowers were derived from purple flowers due to the loss of anthocyanins, and F3H could be an essential gene affecting flower color variation though expression regulation and sequence polymorphism in this species. Furthermore, our findings suggest that genes positively selected in yellow-flowered I. potaninii might be involved in nucleotide excision repair and plant-pathogen interactions. CONCLUSIONS: These results suggest that F3H induces the flower color variation of Iris potaninii, and the subsequent ecological and additive positive selection on yellow flowers may further enhance plant adaptations to alpine environments.

Hydrogen Peroxide-Inducible PROTACs for Targeted Protein Degradation in Cancer Cells.

Proteolysis-targeting chimeras (PROTACs) provide a powerful technique to degrade targeted proteins utilizing the cellular ubiquitin-proteasome system. The major concern is the host toxicity resulting from their poor selectivity. Inducible PROTACs responding to exogenous stimulus, such as light, improve their specificity, but it is difficult for photo-activation in deep tissues. Herein, we develop H2 O2 -inducible PROTAC precursors 2/5, which can be activated by endogenous H2 O2 in cancer cells to release the active PROTACs 1/4 to effectively degrade targeted proteins. This results in the intended cytotoxicity towards cancer cells while targeted protein in normal cells remains almost unaffected. The higher Bromodomain-containing protein 4 (BRD4) degradation activity and cytotoxicity of 2 towards cancer cells is mainly due to the higher endogenous concentration of H2 O2 in cancer cells (A549 and H1299), characterized by H2 O2 -responsive fluorescence probe 3. Western blot assays and cytotoxicity experiments demonstrate that 2 degrades BRD4 more effectively and is more cytotoxic in H2 O2 -rich cancer cells than in H2 O2 -deficient normal cells. This method is also extended to estrogen receptor (ER)-PROTAC precursor 5, showing H2 O2 -dependent ER degradation ability. Thus, we establish a novel strategy to induce targeted protein degradation in a H2 O2 -dependent way, which has the potential to improve the selectivity of PROTACs.

Glutathione-responsive PROTAC for targeted degradation of ERα in breast cancer cells.

ERα (estrogen receptor-α)-targeting PROTACs (PROteolysis TArgeting Chimeras) have emerged as a novel and promising modality for breast cancer therapeutics. However, ERα PROTACs-induced degradation in normal tissues raises concerns about potential off-tissue toxicity. Tumor microenvironment-responsive strategy provides potential for specific control of the PROTAC's on-target degradation activity. The glutathione (GSH) level has been reported to be significantly increased in tumor cells. Here, we designed a GSH-responsive ERα PROTAC, which is generated by conjugating an o-nitrobenzenesulfonyl group to the hydroxyl group of VHL-based ERα PROTAC through a nucleophilic substitution reaction. The o-nitrobenzenesulfonyl group as a protecting group blocks the bioactivity of ERα PROTAC (ER-P1), and that can be specifically recognized and removed by highly abundant GSH in cancer cells. Consequently, the GSH-responsive ERα PROTAC (GSH-ER-P1) exhibits significantly enhanced degradation of ERα in cancer cells compared to that in normal cells, leading to a remarkable inhibition of breast cancer cell proliferation and less toxic effects on normal cells. This study provides a potentially valuable strategy for breast cancer treatment using tumor microenvironment-responsive PROTACs.

Selective degradation of BRD4 suppresses lung cancer cell proliferation using GSH-responsive PROTAC precursors.

BRD4,as a transcriptional and epigenetic regulator to mediate cellular functions, plays an important role in cancer development.Targeting BRD4 with conventional inhibitors in cancer therapy requires high doses, which often leads to off-target and adverse effects. BRD4-targeted proteolysis-targeting chimeras (PROTACs) can catalytically degrade BRD4 utilizing the endogenous proteasome system, and exhibit promising anti-tumor activity. However, most of the developed PROTACs are non-cancer specific and relatively toxic towards normal cells, limiting their practical applications in cancer treatment. By taking advantage of higher glutathione (GSH) levels in cancer cells than that in normal cells, we developed several GSH-responsive PROTAC precursors 1a-c via the attachment of a GSH-trigger unit on the hydroxyl group of the VHL (von Hippel-Lindau) ligand for the recruitment of E3 ligase. Among the precursors, 1a can be efficiently activated by the innately higher concentrations of GSH in lung cancer cells (A549 and H1299) to release active PROTAC 1, degrading intracellular BRD4 and resulting in cytotoxicity, which is confirmed by mechanistic investigation. On the other hand, 1a cannot be efficiently triggered in normal lung cells (WI38 and HULEC-5a) containing lower levels of GSH, therefore reducing the adverse effects on normal cells. This work provides an alternative proof of concept approach for developing stimuli-responsive PROTAC precursors, and affords a novel insight to improve the selectivity and minimize the adverse effects of current PROTACs, hence enhancing their clinical potential.

Skin/muscle incision and retraction regulates the persistent postoperative pain in rats by the Epac1/PKC-ßII pathway.

Persistent postoperative pain causes influence the life quality of many patients. The Epac/PKC pathway has been indicated to regulate mechanical hyperalgesia. The present study used skin/muscle incision and retraction (SMIR) to induce postoperative pain in rats and evaluated the Epac/PKC pathway in postoperative pain. Mechanical allodynia was assessed by paw withdrawal threshold before and after incision. The levels of Epac, PKC, proinflammatory cytokines, and blood-nerve barrier-related proteins were assessed using Western blotting. We found that SMIR induced the activation of the Epac/PKC pathway, mechanical allodynia, and upregulation of Glut1, VEGF, and PGP9.5 proteins in dorsal root ganglia. Under the influence of agonists of Epac/PKC, normal rats showed mechanical allodynia and increased Glut1, VEGF, and PGP9.5 proteins. After inhibition of Epac1 in rats with SMIR, mechanical allodynia was alleviated, and proinflammatory cytokines and Glut1, VEGF, and PGP9.5 proteins were decreased. Moreover, dorsal root ganglia neurons showed abnormal proliferation under the activation of the Epac/PKC pathway. Using Captopril to protect vascular endothelial cells after SMIR had a positive effect on postoperative pain. In conclusion, SMIR regulates the persistent postoperative pain in rats by the Epac/PKC pathway.

Uncovering the role of a positive selection site of wax ester synthase/diacylglycerol acyltransferase in two closely related Stipa species in wax ester synthesis under drought stress.

Natural selection drives local adaptations of species to biotic or abiotic environmental stresses. As a result, adaptive phenotypic divergence can evolve among related species living in different habitats. However, the genetic foundation of this divergence process remains largely unknown. Two closely related alpine grass species, Stipa capillacea and Stipa purpurea, are distributed in different rainfall regions of northern Tibet. Here, we analyzed the drought tolerance of these two closely related Stipa species, and found that S. purpurea was more resistance to drought stress than S. capillacea. To further understand the genetic diversity behind their adaptation to drought environments, a comprehensive gene repertoire was generated using PacBio isoform and Illumina RNA sequencing technologies. Bioinformatics analyses revealed that differential transcripts were mainly enriched in the wax synthetic pathway, and a threonine residue at position 239 of WSD1 was identified as having undergone positive selection in S. purpurea. Using heterologous expression in the Saccharomyces cerevisiae mutant H1246, site-directed mutagenesis studies demonstrated that a positive selection site results in changes to the wax esters profile. This difference may play an important role in S. purpurea in response to drought conditions, indicating that S. purpurea has evolved specific strategies involving its wax biosynthetic pathway as part of its long-term adaptation to the Qinghai-Tibet Plateau.

An Exception Handling Approach for Privacy-Preserving Service Recommendation Failure in a Cloud Environment.

Service recommendation has become an effective way to quickly extract insightful information from massive data. However, in the cloud environment, the quality of service (QoS) data used to make recommendation decisions are often monitored by distributed sensors and stored in different cloud platforms. In this situation, integrating these distributed data (monitored by remote sensors) across different platforms while guaranteeing user privacy is an important but challenging task, for the successful service recommendation in the cloud environment. Locality-Sensitive Hashing (LSH) is a promising way to achieve the abovementioned data integration and privacy-preservation goals, while current LSH-based recommendation studies seldom consider the possible recommendation failures and hence reduce the robustness of recommender systems significantly. In view of this challenge, we develop a new LSH variant, named converse LSH, and then suggest an exception handling approach for recommendation failures based on the converse LSH technique. Finally, we conduct several simulated experiments based on the well-known dataset, i.e., Movielens to prove the effectiveness and efficiency of our approach.

A mathematical optimization model for efficient assignment of inpatients in an oncology center in China.

This paper addresses a problem for assignment of chemo-receiving inpatients in an oncology care center, which has not been addressed in the literature. Chemotherapy is regarded as one of the most effective treatments for cancer. In recent years, as cancer incidence increased, the number of patients admitted to a cancer treatment center has also been rising. How to balance the workload of medical service resources by planning admission of patients has become an essential problem that must be given consideration by policy- makers. The allocation of chemotherapy patients, different from that of the routine inpatients, is restrained by treatment agreements of patients and presents periodic features. Therefore, the allocation of chemotherapy patients is much more difficult than that of routine patients. A mixed integer programming (MIP) model was first formulated for this problem in order to maximize the usage of beds. Specific features of chemotherapy, such as chemotherapy protocols, were integrated into this model. The inpatient assignment problem was proved to be non-deterministic polynomial- complete and we propose an exact method to solve it. Numerical experiments on suitable use-case scenarios and a practical Chinese oncology center were performed to test and evaluate this model. The obtained results demonstrated the effectiveness of our method. Some useful managerial implication are provided for policy-makers through the analysis of obtained results. The models and methods suggested here can be effectively applied in similar departments of other countries and regions.

Effects of nano bamboo charcoal on PAHs-degrading strain Sphingomonas sp. GY2B.

Nano bamboo charcoal (NBC) has been commonly used in the production of textiles, plastics, paint, etc. However, little is known regarding their effects towards the microorganisms. The effects of NBC on phenanthrene degrading strain Sphingomonas sp. GY2B were investigated in the present study. Results showed that the addition of NBC could improve the phenanthrene removal by Sphingomonas sp. GY2B, with removal efficiencies increased by 10.29-18.56% in comparison to the control at 24h, and phenanthrene was almost completely removed at 48h. With the presence of low dose of NBC (20 and 50mgL(-1)), strain GY2B displayed a better growth at 6h, suggesting that NBC was beneficial to the growth of GY2B and thus resulting in the quick removal of phenanthrene from water. However, the growth of strain GY2B in high dose of NBC (200mgL(-1)) was inhibited at 6h, and the inhibition could be attenuated and eliminated after 12h. NBC-effected phenanthrene solubility experiment suggested that NBC makes a negligible contribution to the solubilization of phenanthrene in water. Results of electronic microscopy analysis (SEM and TEM) indicated NBC may interact with the cell membrane, causing the enhanced membrane permeability and then NBC adsorbed on the membrane would enter into the cells. The findings of this work would provide important information for the future usage and long-term environmental risk assessment of NBC.

Rothia endophytica sp. nov., an actinobacterium isolated from Dysophylla stellata (Lour.) Benth.

A novel endophytic actinobacterium, designated strain YIM 67072(T), was isolated from healthy roots of Dysophylla stellata (Lour.) Benth. Cells of this aerobic, cream-yellow-coloured strain occurred singly, in pairs or in tetrads, were Gram-stain-positive and ovoid- to spherical-shaped. Strain YIM 67072(T) grew at 4-45 °C, pH 5.0-10.0 and in the presence of 0-7 % (w/v) NaCl. Phylogenetic analysis based on 16S rRNA gene sequences showed that strain YIM 67072(T) belonged to the genus Rothia. The isolate contained MK-7 as the major component of the quinone system. The peptidoglycan type was A3α. The polar lipid profile consisted predominantly of diphosphatidylglycerol and glycolipids. The major fatty acids were anteiso-C15 : 0, iso-C15 : 0, anteiso-C17 : 0 and iso-C16 : 0. The DNA G+C content was 53.2 mol%. However, strain YIM 67072(T) differed from its closest relatives Rothia nasimurium CCUG 35957(T) (98.5 % 16S rRNA gene sequence similarity), Rothia amarae JCM 11375(T) (97.6 %) and Rothia terrae L-143(T) (97.3 %) in many phenotypic characteristics. Moreover, the levels of DNA-DNA relatedness between the novel isolate and the three above-mentioned type strains were 28.7±1.3 %, 36.5±1.2 %, 46.8±1.5 %, respectively. Based on comparative analysis of physiological and chemotaxonomic data, strain YIM 67072(T) represents a novel species of the genus Rothia, for which the name Rothia endophytica sp. nov. is proposed. The type strain is YIM 67072(T) ( = DSM 26247(T) = JCM 18541(T)).

Sequential Order-Aware Coding-Based Robust Subspace Clustering for Human Action Recognition in Untrimmed Videos.

Human action recognition (HAR) is one of most important tasks in video analysis. Since video clips distributed on networks are usually untrimmed, it is required to accurately segment a given untrimmed video into a set of action segments for HAR. As an unsupervised temporal segmentation technology, subspace clustering learns the codes from each video to construct an affinity graph, and then cuts the affinity graph to cluster the video into a set of action segments. However, most of the existing subspace clustering schemes not only ignore the sequential information of frames in code learning, but also the negative effects of noises when cutting the affinity graph, which lead to inferior performance. To address these issues, we propose a sequential order-aware coding-based robust subspace clustering (SOAC-RSC) scheme for HAR. By feeding the motion features of video frames into multi-layer neural networks, two expressive code matrices are learned in a sequential order-aware manner from unconstrained and constrained videos, respectively, to construct the corresponding affinity graphs. Then, with the consideration of the existence of noise effects, a simple yet robust cutting algorithm is proposed to cut the constructed affinity graphs to accurately obtain the action segments for HAR. The extensive experiments demonstrate the proposed SOAC-RSC scheme achieves the state-of-the-art performance on the datasets of Keck Gesture and Weizmann, and provides competitive performance on the other 6 public datasets such as UCF101 and URADL for HAR task, compared to the recent related approaches.

Differences in pseudogene evolution contributed to the contrasting flavors of turnip and Chiifu, two Brassica rapa subspecies.

Pseudogenes are important resources for investigation of genome evolution and genomic diversity because they are nonfunctional but have regulatory effects that influence plant adaptation and diversification. However, few systematic comparative analyses of pseudogenes in closely related species have been conducted. Here, we present a turnip (Brassica rapa ssp. rapa) genome sequence and characterize pseudogenes among diploid Brassica species/subspecies. The results revealed that the number of pseudogenes was greatest in Brassica oleracea (CC genome), followed by B. rapa (AA genome) and then Brassica nigra (BB genome), implying that pseudogene differences emerged after species differentiation. In Brassica AA genomes, pseudogenes were distributed asymmetrically on chromosomes because of numerous chromosomal insertions/rearrangements, which contributed to the diversity among subspecies. Pseudogene differences among subspecies were reflected in the flavor-related glucosinolate (GSL) pathway. Specifically, turnip had the highest content of pungent substances, probably because of expansion of the methylthioalkylmalate synthase-encoding gene family in turnips; these genes were converted into pseudogenes in B. rapa ssp. pekinensis (Chiifu). RNA interference-based silencing of the gene encoding 2-oxoglutarate-dependent dioxygenase 2, which is also associated with flavor and anticancer substances in the GSL pathway, resulted in increased abundance of anticancer compounds and decreased pungency of turnip and Chiifu. These findings revealed that pseudogene differences between turnip and Chiifu influenced the evolution of flavor-associated GSL metabolism-related genes, ultimately resulting in the different flavors of turnip and Chiifu.

Philanthropic sales in live-streaming shopping: The impact of online interaction on consumer impulse buying.

As philanthropic sales via live-streaming shopping have played an important role in alleviating the huge backlog of agricultural products during the outbreak of the COVID-19 pandemic, this paper aims to study how online interaction in philanthropic marketing exerts influence on consumer impulse buying behaviors. We empirically explore four major dimensions of online interactions in philanthropic live-streaming sales, i.e., the live streamers' image, the herd effect of consumers, the responsiveness of sellers, and the mutual trust between consumers. The results reveal that the herd effect of consumers and the responsiveness of sellers could promote consumers' empathy ability toward the growers of the products sold lively, whereas the live streamers' image and the mutual trust between consumers have little effect on empathy promotions. Meanwhile, both the consumers' empathy ability and the live streamers' image positively affect consumers' impulse buying behavior, which suggests a partial moderating role of consumers' empathy ability. Lastly, by taking both social and business perspectives, we provide managerial implications for improving the effectiveness and efficiency of philanthropic live-streaming sales to alleviate social and economic pressure in emergencies.

Multiple lines of evidence supports the two varieties of Halenia elliptica (Gentianaceae) as two species.

Delimiting species requires multiple sources of evidence. Here, we delimited two varieties of Halenia elliptica (Gentianaceae) using several lines of evidence, including morphological traits and mating system in a sympatric population, phylogenetic relationships based on nrITS and cpDNA (rpl16) data, and complete chloroplast genome sequences. Comparative analysis of 21 morphological traits clearly separates the two varieties of H. elliptica. Examination of the flowering process and pollination treatments indicate that H. elliptica var. grandiflora produces seeds via outcrossing, whereas H. elliptica var. elliptica produces seeds via mixed mating. Furthermore, hand-pollinated hybridization of the two varieties produced no seeds. Observations of pollinators showed that when bees began a pollination bout on H. elliptica var. grandiflora they preferred to continue pollinating this variety; however, when they began a pollination bout on H. elliptica var. elliptica, they showed no preference for either variety. Phylogenetic analysis confirmed the monophyly of H. elliptica, which was further divided into two monophyletic clades corresponding to the two varieties. A large number of variants from the chloroplast genomes reflected remarkable genetic dissimilarities between the two varieties of H. elliptica. We recommend that the two varieties of H. elliptica should be revised as two species (H. elliptica and H. grandiflora). Our findings indicate that H. elliptica varieties may have split into two separate species due to a shift in mating system, changes in flowering phenology and/or post-pollination reproductive isolation.

The release of hydrogen reaction of graphene modified NaAlH4.

In this experiment, we prepared a better performance graphene, by using butyrolactone and flavanone, promoting the graphite into high quality graphene strip. The obtained graphene were used to catalyze the hydrogen released by NaAlH4. The result proved that 5 wt% doped butyrolactone treated graphite and 2 wt% doped flavanone-treated graphite are good catalyst in NaAlH4's decomposition process.

A statistical approach to secure health care services from DDoS attacks during COVID-19 pandemic.

Over the course of this year, more than a billion people have been afflicted by the COVID-19 outbreak. As long as individuals maintain their social distance, they should all be secure at this period. Because of this, there has been a rise in the usage of different online technologies, but at the same time, there has also been a rise in the likelihood of different cyber-attacks. A DDoS assault, the most prevalent and deadly of them all, impairs an online resource for its users. Thus, in this paper, we have proposed a filtering approach that can work efficiently in the COVID-19 scenario and detect the DDoS attack. We base our proposed approach on statistical methods like packet score and entropy variation for the identification of DDoS attack traffic. We have implemented our proposed approach on Omnet++ and for testing its efficiency we have checked it with different test cases. Our proposed approach detects the DDoS attack traffic with 96% accuracy and can also clearly have differentiated the DDoS attack traffic from the flash crowd.

Development of Microsatellite Markers for a Dioecious Herpetospermum pedunculosum (Cucurbitaceae).

Understanding the evolution of flower diversity is a central topic in plant evolutionary ecology, and natural selection on floral traits via male fitness could be estimated quantitatively using microsatellites. Here, based on RNA sequencing, we developed simple sequence repeat primers and verified polymorphisms in 2 wild populations of Herpetospermum pedunculosum (Cucurbitaceae), a dioecious annual plants native to the Himalaya Mountains. A total of 131 paired primers were designed; 15 paired primers were found to be polymorphic, with the expected heterozygosity varying between 0.280 and 0.767. We also identified 58 genotypes in 20 plants from the 2 populations. Conclusively, these primers could be effective in examining male fitness and population genetic structure of H pedunculosum in future studies.

A machine learning model to classify aortic dissection patients in the early diagnosis phase.

Aortic dissection is one of the most clinical-challenging and life-threatening cardiovascular diseases associated with high morbidity and mortality. Aortic dissection requires fast diagnosis and timely therapy. Any delay or misdiagnosis can cause severe consequence to aortic dissection patients with even higher mortality. To better help physicians identify the potential dissection within the scope of all misdiagnosed patients, this paper describes a method which is developed with data mining methods for aortic dissection patient classification and prediction in the phase of early diagnosis. Various machine learning algorithms were used to build the models which were all trained and tested on the patient dataset with cross validation. Among them, Bayesian Network model achieved the best performance by predicting at a precision rate of 84.55% with Area Under the Curve (AUC) value of 0.857. On this basis, the Bayesian Network model can help physicians better with early diagnosis of aortic dissection in clinical practice. Beyond this study, more data from diverse regions and the internal pathology can be crucial to further build a universal model with broader predictive power.