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Recent advances in multi-kernel-based methods for outlier detection have positioned them as an attractive way to detect instances that are markedly different from the remaining data in a dataset. Currently, most outlier detection approaches based on multi-kernel learning are simply a convex combination of various kernels with handcrafted weights, meaning that these weights may not be suitable. Meanwhile, this combination of weights does not sufficiently consider the intrinsic correlations of instances when fusing different kernels. Thus, a key challenge is how to adaptively learn an appropriate combination of weights for capturing a new feature space in which outliers can be better detected than the original space. Simultaneously, it is still a burning issue to get the optimal combination of weights due to considerable computational cost and memory usage when the feature or instance size is large. In this paper, we propose a novel method for efficient adaptive multi-kernel for outlier detection (EAMOD), which automatically learns the optimal weight for each training instance under different kernels using a non-negative function. In addition, we design a safe screening rule (SSR) for EAMOD to improve its training efficiency without any loss of accuracy. To the best of our knowledge, it is the first attempt to develop SSR for multi-kernel-based outlier detection methods. Extensive experiments show that EAMOD is effective and efficient.

Outlier detection methods based on distance measure have been used in numerous applications due to their effectiveness and interpretability. However, distances among instances heavily depend on the feature space in which they reside. For an outlier, distances from it to the normal instances may be extremely close in one feature space, failing to separate them from each other, while this situation is reversed in another space. Meanwhile, the distance measure is sensitive to a few “marginal instances” (i.e., normal instances located very close to outliers in the feature space) during the estimation of whether a test instance is an outlier or not. In this article, we propose a robust multi-kernel nearest neighborhood (RMKN) method for outlier detection. Specifically, in the training phase, we only consider normal instances and transform them into a Polynomial kernel function weighted digraph to capture their geometric relationships in the original feature space. Then, we develop an objective function based on the weighted digraph to find a latent feature space via multi-kernel learning such that distances among normal instances in this latent feature space are as close as possible while preserving their original distributions. In the detecting phase, we design an outlying score based on the two-stage multi-kernel $k$k-nearest nearest neighbors to detect outliers. Extensive experiments with ten datasets show that RMKN is effective and robust.

Rank support vector machine (RSVM) is widely used in multilabel classification problems. However, as the number of labels and instances soars, the training efficiency of the model will be greatly reduced. Unfortunately, few effective methods can solve this problem. In this article, we propose a safe screening rule (SSR) for RSVM to improve its training speed. This is the first attempt to construct SSR for multilabel learning problems. SSR for RSVM can screen and delete most of the instances based on their relevant–irrelevant label pairs, which is the biggest difference in the existing SSR. After this process, the scale of RSVM can be substantially reduced before solving it. The sequential version of SSR for RSVM is further introduced to accelerate the whole parameter tuning process. One important advantage of SSR is that it is safe, which means we can obtain the same optimal solution as the original problem by utilizing it. Extensive experiments with five benchmark datasets, three large-scale datasets, and one type 2 diabetes dataset show that our approach is efficient and safe.

Water washing can remove chlorides from municipal solid waste incineration fly ash but with high consumptions of energy and reagents for the following wastewater treatment. In this study, a novel method named delayed bubbling washing (water washing first and then CO2bubbling washing) was proposed to promote the chlorine dissolution. The mechanisms were considered as the less shell formed outside ash particles and the reaction between CaClOH and H2CO3during washing. However, for single-stage washing, the incomplete dehydration of washed ash greatly weakened the chloride removal effect. Three-stage countercurrent washing addressed this issue well with the best bubbling position in the first stage. Through the combination of delayed bubbling washing and three-stage countercurrent washing, the chlorine content in the product was lowered to 0.85% at a liquid–solid ratio of 2.5 mL/g, the cost of wastewater treatment was reduced by 23%, the byproduct of NaCl was reduced by 14.5%, and the CO2emission was reduced by 23 kg/ton of ash.

FtmOx1 is a nonheme iron (NHFe) endoperoxidase, catalyzing three disparate reactions, endoperoxidation, alcohol dehydrogenation, and dealkylation, under in vitro conditions; the diversity complicates its mechanistic studies. In this study, we use two substrate analogues to simplify the FtmOx1-catalyzed reaction to either a dealkylation or an alcohol dehydrogenation reaction for structure–function relationship analysis to address two key FtmOx1 mechanistic questions: (1) Y224 flipping in the proposed COX-like model vs α-ketoglutarate (αKG) rotation proposed in the CarC-like mechanistic model and (2) the involvement of a Y224 radical (COX-like model) or a Y68 radical (CarC-like model) in FtmOx1-catalysis. When 13-oxo-fumitremorgin B (7) is used as the substrate, FtmOx1-catalysis changes from the endoperoxidation to a hydroxylation reaction and leads to dealkylation. In addition, consistent with the dealkylation side-reaction in the COX-like model prediction, the X-ray structure of the FtmOx1•CoII•αKG•7ternary complex reveals a flip of Y224 to an alternative conformation relative to the FtmOx1•FeII•αKG binary complex. Verruculogen (2) was used as a second substrate analogue to study the alcohol dehydrogenation reaction to examine the involvement of the Y224 radical or Y68 radical in FtmOx1-catalysis, and again, the results from the verruculogen reaction are more consistent with the COX-like model.

Background: Changes in precipitation patterns crucially impact soil microbial communities, and the ecosystem in Qinghai-Tibet Plateau (QTP) is highly vulnerable to climate change. However, we do not fully understand how soil microbial communities in the source wetlands of QTP respond to changes in precipitation. In this study, we employed advanced techniques such as high-throughput sequencing and metabolomics to investigate how soil microbial communities in a source wetland of Qinghai Lake respond to changes in precipitation after quadrennial precipitation treatment. Results: Our findings showed that the predominant microbiota in the source wetland was Proteobacteria. Interestingly, alterations in precipitation levels, whether increased or reduced, did not significantly impact the diversity or functional groups of the microbial community. However, the structure of the microbial community did respond notably to changes in precipitation, leading to shifts in the relative abundance of Spirochaetes and Treponema. A notable finding was that reduced precipitation levels (– 25% and − 50%) and mild increases in precipitation (25%) within the region contributed to increased soil carbon content. However, this effect ceased to manifest when precipitation increased by 50%. Additionally, the reduction in precipitation prompted the release of soil metabolites like syringic acid and aldosterone, while enhanced precipitation resulted in a decrease in aldosterone content. Conclusions: Precipitation changes altered the relative abundance of soil microbial communities and metabolites, which was conducive to increasing carbon storage in this alpine wetland.

Hydroxyapatite (HAP) is widely used as a loaded catalyst support due to its excellent ion exchange properties. In this study, a series of Ni-based hydroxyapatite catalysts were prepared by a novel method, one-pot co-precipitation (denoted as Ni/HAP-OP), for dry reforming of methane (DRM) testing. The textural, structure, and physicochemical properties of the catalysts were studied by inductively coupled plasma spectroscopy (ICP), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), the Brunauer–Emmett–Teller (BET) method, scanning transmission electron microscopy (STEM), and hydrogen temperature-programmed reduction (H2-TPR), and the spent catalysts were analyzed by thermogravimetric analysis (TGA), Raman, and transmission electron microscopy (TEM). The Ni/HAP-OP catalysts exhibit a typical hydroxyapatite structure. The Ni0.5/HAP-OP catalyst has the highest dispersion of Ni among the prepared catalysts, and most of the added Ni is in the form of Ni2+[I] and Ni2+[II] in the lattice of hydroxyapatite. When Ni is post-impregnated (Ni0.5/HAP), almost half of the Ni is present in the form of NiO. The different coordination configurations of Ni are confirmed to play an important role in the DRM reaction. Naturally, the Ni0.5/HAP-OP catalyst shows excellent catalytic activity and catalytic stability in the 200 h stability test compared with Ni0.5/HAP, with stable CH4(about 94%) and CO2(95%) conversion. The deactivation is only 0.014 and 0.017% h–1, respectively, and the H2/CO ratio in the syngas is always maintained close to 1.0. Analyses of the spent catalysts reveal that amorphous carbon deposits are observed around the metallic Ni on the Ni0.5/HAP catalyst, and Raman analysis indicates the presence of both amorphous and graphitic carbon deposits. In contrast, only trace amounts of graphitic carbon are present in the Ni0.5/HAP-OP catalyst after 200 h of the DRM reaction. The Ni-based hydroxyapatite catalysts prepared by the one-pot co-precipitation method exhibit high activity and stability for the DRM reaction thanks to the confinement of Ni particles and the inhibition of carbon deposition.

We identified CLASP2, dynein, and JIP3 as possible new doublecortin (DCX) targets that are involved in DCX regulation of the dendritic distribution of somatic Golgi apparatus in mouse neurons.

Krüppel-like factor 5 (KLF5) is an oncogenic factor that is highly expressed in basal-like breast cancer (BLBC) and promotes cell proliferation, survival, migration, stemness, and tumor growth; however, its posttranslational modifications are poorly defined. Protein arginine methyltransferase 5 (PRMT5) is also an oncogene implicated in various carcinomas, including breast cancer. In this study, we found that PRMT5 interacts with KLF5 and catalyzes the di-methylation of KLF5 at Arginine 57 (R57) in a methyltransferase activity-dependent manner in BLBC cells. Depletion or pharmaceutical inhibition (using PJ-68) of PRMT5 decreased the expression of KLF5 and its downstream target genes in vitro and in vivo. PRMT5-induced KLF5R57me2 antagonizes GSK3β-mediated KLF5 phosphorylation and subsequently Fbw7-mediated KLF5 ubiquitination and coupled degradation. Functionally, PRMT5 promotes breast cancer stem cell maintenance and proliferation, at least partially, by stabilizing KLF5. PRMT5 and KLF5 protein levels were positively correlated in clinical BLBCs. Taken together, PRMT5 methylates KLF5 to prevent its phosphorylation, ubiquitination, and degradation, and thus promotes breast cancer stem cell maintenance and proliferation. These findings suggest that PRMT5 is a potential therapeutic target for BLBC.

With dramatically increasing emission of heavy metals and chlorinated compounds from thermal treatments of fuels and wastes, kaolin, one of the widely used materials in the industry, was researched to control these pollutants in recent years. To investigate the retention of lead chloride (PbCl2) by kaolin and metakaolin obtained from thermal activation of kaolin, the PbCl2adsorption experiment in a two-stage furnace was conducted from 600 to 900 °C under N2, H2O, and O2. Furthermore, the toxicity leaching procedure was also utilized to evaluate the leachability of Pb from used sorbents. The results showed that the capture efficiency of PbCl2by the sorbents and leachability of Pb from the used sorbents were closely related to the increase of the experimental temperature. The retention of Pb by raw kaolin was superior to that by metakaolin; however, the leachability of Pb from the used metakaolin was totally lower. Adding H2O in the adsorption experiment can obviously increase the retention of Pb by the sorbents and decrease the leachability of Pb from the used sorbents. Besides, the effects of adding O2on promoting the retention of Pb by kaolin and reducing the leachability of Pb from used kaolin were also noticeable due to the influence of adding O2on enhancing chemical adsorption and melting behavior of kaolin. The maximum capture efficiency of Pb by kaolin and the minimum ratio of leachability from the used kaolin can reach 74.01% and 1.60%, respectively, with the addtion of O2in the adsorption experiment at 900 °C.

In China, coal, often with a high level of sulfur, is always mixed with municipal solid waste (MSW) in waste incineration plants due to the low heating value and high moisture content of MSW. The influence of sulfur compounds on the volatilization of heavy metals in MSW is of great concern for China’s waste incineration plants. In this study, the continuous dynamic volatilization process of Pb and Cd is investigated by adding different forms of sulfur compounds, elemental sulfur (S), and sodium sulfate (Na2SO4), to the simulated MSW in a laboratory incinerator, at both 1 and 3 wt %, respectively. The experimental results show that the added S begins to affect the volatilization of Pb and Cd at about 700 °C; adding S can lead up to 49.6% reduction in the volatilization of Pb, as the produced sulfur dioxide is promoting the formation of a condensed sulfate phase, and part of Pb is fixed in the form of PbS in the bottom ash. But for Cd, adding S causes up to 15.9% increase in its volatilization as S seizes part of O2in the air, which is conducive to forming the reducing atmosphere. In the reducing atmosphere, CdO can be easily reduced to Cd, which volatilizes more easily than CdO at high temperatures. In fact, in the reducing atmosphere, the volatilization of Cd far outweighs the volatilization of Pb at 700–800 °C. On the other hand, adding Na2SO4almost has no influence on the volatilization of lead and cadmium below 900 °C.

Antimicrobial peptides (AMPs) offer an opportunity to overcome multidrug resistance. Here, novel peptides were designed based on AMP fragments derived from sea cucumber hemolytic lectin to enhance anti-methicillin-resistant Staphylococcus aureus(MRSA) activity with less side effects. Two designed peptides, CGS19 (LARVARRVIRFIRRAW-NH2) and CGS20 (RRRLARRLIFFIRRAW-NH2), exhibited strong antibacterial activities against clinically isolated MRSA with MICs of 3–6 μM, but no obvious cytotoxicity was observed. Consistently, CGS19 and CGS20 exerted rapid bactericidal activity and effectively induced 5.9 and 5.8 log reduction of MRSA counts in mouse subeschar, respectively. Further, CGS19 and CGS20 kill bacteria not only through disturbing membrane integrity but also by binding formate-tetrahydrofolate ligase, a key enzyme in the folate metabolism pathway, thereby inhibiting the folate pathway of MRSA. CGS19 and CGS20 are promising lead candidates for drug development against MRSA infection. The dual mechanisms on the identical peptide sequence or scaffold might be an underappreciated manner of treating life-threatening pathogens.

A binary classification problem in the high-dimensional settings is studied via the ensemble learning with each base classifier constructed from the linear discriminant analysis (LDA), and these base classifiers are integrated by the weighted voting. The precision matrix in the LDA rule is estimated by the modified Cholesky decomposition (MCD), which is able to provide us with a set of precision estimates by considering multiple variable orderings, and hence yield a group of different LDA classifiers. Such available LDA classifiers are then integrated to improve the classification performance. The simulation and the application studies are conducted to demonstrate the merits of the proposed method. [ABSTRACT FROM AUTHOR]

Pullulanases are well-known debranching enzymes that hydrolyze α-1,6-glycosidic linkages in starch and oligosaccharides. However, most of the pullulanases exhibit limited activity for practical applications. Here, two sites (787 and 621) lining the catalytic pocket of Bacillus naganoensispullulanase were identified as being critical for enzymatic activity by triple-code saturation mutagenesis. Subsequently, both sites were subjected to NNK-based saturation mutagenesis to obtain positive variants. Among the variants showing enhanced activity, the enzymatic activity and specific activity of D787C were 1.5-fold higher than those of the wild-type (WT). D787C also showed a 1.8-fold increase in kcatand a 1.7-fold increase in kcat/Km. In addition, D787C maintained higher activity compared with that of WT at temperatures over 60 °C. All the positive variants showed higher acid resistance, with D787C maintaining 90% residual activity at pH 4.0. Thus, enzymes with improved properties were obtained by saturation mutagenesis at the active site.

Lithium–sulfur (Li–S) battery has been attracting increasing attention because of its high energy density and the presence of abundance of sulfur. However, its commercialization is still restricted owing to the low conductivity of sulfur, large volume expansion, and a severe polysulfide–shuttle effect. To address these problems, here, we have reported for the first time a simple template-free solvothermal method combined with a subsequent calcination method to prepare cobalt-doped vanadium nitride (VN) yolk–shell nanospheres, encapsulated in a thin layer of a nitrogen-doped carbon (Co-VN@C) composite as an ideal sulfur host. Benefiting from the unique structural advantages and the synergistic effect of conductive VN, cobalt, and nitrogen-doped carbon (NC), the obtained composite could not only facilitate the kinetics of polysulfide conversion as a functional catalyst but also physically confine and chemically absorb the polysulfides effectively. With these advantages, the batteries present a high initial discharge capacity of 1379.2 mAh g–1at 0.1 C (1 C is defined as 1675 mA g–1), good rate performance, and excellent cycling performances (∼715 mAh g–1at 0.5 C after 200 cycles and ∼600 mAh g–1at 1 C after 300 cycles, respectively), even with a high areal sulfur loading of 4.07 mg cm–2(∼830 mAh g–1at 0.2 C after 100 cycles). These results demonstrate that the rationally designed multifunctional sulfur host material Co-VN@C has great potential for application in Li–S batteries.

The transcriptional factor MED12 is part of the essential mediator transcriptional complex that acts as a transcriptional coactivator in all eukaryotes. Missense gain-of-function mutations in human MED12are associated with uterine leiomyomas, yet the role of MED12deficiency in tumorigenesis and reproductive biology has not been fully explored. We generated a Med12reproductive conditional knockout mouse model to evaluate its role in uterine mesenchyme, granulosa cells, and oocytes. Mice heterozygous for Med12deficiency in granulosa cells and uterus (Med12fl/+Amhr2-Cre)were subfertile, while mice homozygous for Med12deficiency in granulosa cells and uterus (Med12fl/flAmhr2-Cre) were infertile. Morphological and histological analysis of the Med12fl/flAmhr2-Crereproductive tract revealed atrophic uteri and hyperchromatic granulosa cells with disrupted expression of Lhcgr, Esr1, and Esr2. Med12fl/flAmhr2-Cremice estrous cycle was disrupted, and serum analysis showed blunted rise in estradiol in response to pregnant mare serum gonadotropin. Uterine atrophy was partially rescued by exogenous steroid supplementation with dysregulation of Notch1and Smoexpression in steroid supplemented Med12fl/flAmhr2-Creuteri, indicating intrinsic uterine defects. Oocyte-specific ablation of Med12caused infertility without disrupting normal folliculogenesis and ovulation, consistent with maternal effects of Med12in early embryo development. These results show the critical importance of Med12in reproductive tract development and that Med12loss of function does not cause tumorigenesis in reproductive tissues.Med12 conditional deficiency causes uterine, ovarian and post-fertilization dysfunction and infertility.

ABSTRACTAflatoxins are among the most powerful carcinogens in nature. The major aflatoxin-producing fungi are Aspergillus flavusand A. parasiticus. Numerous crops, including peanut, are susceptible to aflatoxin contamination by these fungi. There has been an increased use of RNA interference (RNAi) technology to control phytopathogenic fungi in recent years. In order to develop molecular tools targeting specific genes of these fungi for the control of aflatoxins, it is necessary to obtain their genome sequences. Although high-throughput sequencing is readily available, it is still impractical to sequence the genome of every isolate. Thus, in this work, the authors proposed a workflow that allowed prescreening of 238 Aspergillussection Flaviisolates from peanut seeds from Georgia, USA. The aflatoxin biosynthesis cluster (ABC) of the isolates was fingerprinted at 25 InDel (insertion/deletion) loci using capillary electrophoresis. All isolates were tested for aflatoxins using ultra-high-performance liquid chromatography. The neighbor-joining, three-dimension (3D) principal coordinate, and Structure analyses revealed that the Aspergillusisolates sampled consisted of three main groups determined by their capability to produce aflatoxins. Group I comprised 10 non-aflatoxigenic A. flavus; Group II included A. parasiticus; and Group III included mostly aflatoxigenic A. flavusand the three non-aflatoxigenic A. caelatus. Whole genomes of 10 representative isolates from different groups were sequenced. Although InDels in Aspergillushave been used by other research groups, this is the first time that the cluster analysis resulting from fingerprinting was followed by whole-genome sequencing of representative isolates. In our study, cluster analysis of ABC sequences validated the results obtained with fingerprinting. This shows that InDels used here can predict similarities at the genome level. Our results also revealed a relationship between groups and their capability to produce aflatoxins. The database generated of Aspergillusspp. can be used to select target genes and assess the effectiveness of RNAi technology to reduce aflatoxin contamination in peanut.

Four waste materials, paper, wood, textile and kitchen garbage, in municipal solid waste were gasified separately with oxygen in a fixed bed reactor. The yields of products char, tar and gas, the composition of gas components H2, CO, CO2and CH4, and the lower heating value (LHV) were examined at temperatures between 700 and 900°C and equivalence ratio (ER) between 0.14 and 0.32. Characteristics of gas evolution during gasification were investigated. Results show that a higher temperature improves the formation of H2and CO while lowers the yield of CO2and CH4. The LHV of syngas increases with temperature and varies in the range of 6–10MJ·m−3, reaching the maximum at 800°C or above. As ER increases, both combustible gas component and LHV of syngas decrease while the yield of CO2rises linearly. The appropriate ER for obtaining high quality gas is in the range of 0.18–0.23. Temperature and ER have significant effects on the product distribution. Higher temperature and ER are favorable for higher gas yield and lower yield of char and tar in the gasification of textile and kitchen garbage. At 800°C, the gas evolution may be divided into two regions. In the first region, the flow rate of gas increases and then decreases rapidly, while in the second region the flow rate decreases monotonically to lower level.

With the rapid development of economy and accelerated pace of urbanization in China, the trip share of private cars has been increasing continually. This study investigates the optimal mode-split for a developing megacity and optimizes the weighted generalized travel cost per capita for one trip on an urban transport network. The main urban area of Beijing is taken as the study area of this research and the revealed preference survey method is utilized to get the trip survey data. Based on a nest-logit model, an optimization model is developed for the minimal weighted generalized travel cost per capita for one trip. The phase estimation method with the Newton-Raphson algorithm and the genetic algorithm are used to solve the optimization model. In addition, different cases are studied to assess the effect of different transport policies for the improvement of urban transport in Beijing. These policies are concerned with parking fee, taxi average fare, bus priority and rail transfer time. It is found that the bus priority policy for reducing the in-vehicle time of a bus trip has the greatest weighted generalized travel cost per capita for one trip in Beijing. Moreover, successful rail transfer time reduction is more beneficial to travellers in comparison to the effect of increasing parking fees of private cars or increasing the average fare of taxi utilization. In the future research, more comprehensive policy packages are worthy of studies in a further.

A reasonable prediction of the possibility of traffic congestion is able to help traffic managers to make efficient decisions to reduce the negative effect of traffic congestion. Previous research has made valuable analyses in this field. However, they rarely consider the dependency and uncertainty of traffic jams. In consideration of the characteristics of traffic congestion from different perspectives, this research proposes a Bayesian Network (BN) analysis approach to predict the possibility of urban traffic congestion. The built-up area of Beijing is taken as the study area of this research. A comprehensive set of variables are utilized to reflect the characteristics of traffic congestion from various viewpoints. The BN method is used to analyze the uncertainty and probability of traffic congestion, and is proved to be fully capable of representing the stochastic nature of traffic congestion. Furthermore, the difference of the congestion probabilities because of applying different urban transport development policies is analyzed in comparison. The study results show that the both road construction and bus system development at the same time can obviously mitigate traffic congestion for the built-up area of Beijing. In the future research, the impact of the comprehensive development of various travel modes on urban traffic congestion needs further studies.

Tar is one of the biggest bottlenecks hindering the development of biomass gasification. Herein, Ni−Fe/olivine catalysts prepared by thermal fusion (TF‐olivine) and wetness impregnation (WI‐olivine) are selected as the tar in situ cracking catalyst, and four oily materials (waste cooking oil [WCO], waste cooking oil‐based biodiesel [WCB], palm oil [PO], palm oil‐based biodiesel [PB]) are selected as subsequent tar absorbents. The results show that the tar efficiency increases with the increase in oil absorbent temperature. The absorption efficiency of PO and PB is higher than that of WCO and WCB. The absorption efficiency of tar can reach up to 92.96%. After adding TF‐olivine as the in situ catalyst, the removal efficiency of tar in the biomass catalytic decomposition oil absorbent purification system is further improved. In the fixed‐bed experimental device with a biomass feed rate of 30 g h−1, the tar removal rate reaches 99.96%. In the biomass‐circulating fluidized bed gasification device with a feed rate of 3.9 kg h−1, the tar content is reduced to 8.6 mg Nm−3, and the tar removal rate is up to 99.89%. The in situ catalytic oil absorption purification system provides a promising approach for efficient removal of biomass tar. In a biomass‐circulating fluidized bed gasification device with a feed rate of 3.9 kg h−1using an in situ catalytic oil absorption purification system, the tar content is 8.6 mg Nm−3and the tar removal rate is as high as 99.89%. The in situ catalytic oil absorption and purification system provides a promising method for efficient removal of biomass tar.

Pathogen infections impose severe challenges in clinical practice, especially for patients infected with antibiotic-resistant microbes. The thioredoxin (Trx) system in Gram-positive bacteria serves as an ideal antimicrobial target for novel medicine design due to the structural differences from corresponding system in mammals. However, a backup thiol-dependent antioxidant glutathione (GSH) system limits the effectiveness of drugs in many Gram-negative bacteria. Herein, we synthesize a thiol-targeting nanoinhibitor based on an enzyme-responsive covalent organic framework (COF) coloaded with silver nanoparticles (AgNPs) and ebselen (EBS) (Ag-TA-CON@EBS@PEG) to exert synergistic antibacterial effects. Since azoreductase can dissociate the enzyme-responsive COF, we adopt this strategy to achieve the accurate release of EBS and Ag+at infection sites. Our research identifies that the functionalized nanoinhibitor shows excellent bactericidal performance for Gram-positive and Gram-negative bacteria in vitroand exhibits low toxicity to normal cells. Besides, the nanoinhibitor presents favorable biocompatibility, anti-inflammatory property, and effective wound healing ability in mice. This paper provides a promising clinical strategy for synergistic antibacterial therapy and enhanced wound healing properties viaan optimized combination of the targeted nanomedicines with an intelligent drug conveying platform.

Genome-based discovery of two previously unreported fungal bifunctional terpene synthases (BFTSs) from phytopathogenic fungi are reported: FoFS catalyzing the formation of fusoxypenes A–C (1–3) and (−)-astellatene (4) and AtAS capable of synthesizing preaspterpenacid I (6). Interestingly, FoFS and AtAS catalyzed the formation of enantiomeric sesterterpenes with a 5–6–7–3–5 ring system. C22-oxidative modification of preaspterpenacid I by AtP450 was characterized as well. Plausible cyclization pathways of the fusoxypenes were illustrated by DFT calculations.

Kruppel-like factor 2 (KLF2) is associated with acute and chronic inflammation. However, the role of KLF2 in rheumatoid arthritis (RA) remains unknown. Here, we investigated the expression of KLF2 in mice with collagen-induced arthritis (CIA) to determine whether KLF2 levels correlate with inducible nitric oxide synthase (iNOS) production in vitro. Hematoxylin and eosin staining was used to assess the synovitis and bone destruction in mice. The concentration of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and nitric oxide (NO) in synovial fluid was determined by enzyme-linked immunosorbent assay, while western blot (WB) analysis was employed to detect the expression of KLF2 and iNOS in the synovium, heart, and kidneys. The expression of iNOS in MH7A cells was analyzed by quantitative polymerase chain reaction (PCR) and WB. The expression of KLF2 and iNOS was significantly elevated in the synovium, heart, and kidneys of CIA mice. This was correlated to an increase in the severity of arthritis and the concentration of inflammatory mediators including TNF-α, IL-6, and NO in joint fluid. KLF2 and iNOS expression in vitro was induced by TNF-α and KLF2 knockdown significantly reduced the TNF-α-induced iNOS expression. These findings indicate that KLF2 influences synovial inflammation in CIA mice by regulating iNOS production in synoviocytes.

Software traceability recovery has become more and more important to the software life cycle recent days with the increasing complexity of software system. However, it is a tedious and error-prone task by manual. Many researchers have devoted themselves in building and predicting traceability links. In this paper, we approach a novel method to calculate text similarity and improve our results by a learning to rank method. And a couple of experiments are conducted to verify our method.