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Motivation Identifying the target genes of transcription factors (TFs) is of great significance for biomedical researches. However, using biological experiments to identify TF–target gene interactions is still time consuming, expensive and limited to small scale. Existing computational methods for predicting underlying genes for TF to target is mainly proposed for their binding sites rather than the direct interaction. To bridge this gap, we in this work proposed a deep learning prediction model, named HGETGI, to identify the new TF–target gene interaction. Specifically, the proposed HGETGI model learns the patterns of the known interaction between TF and target gene complemented with their involvement in different human disease mechanisms. It performs prediction based on random walk for meta-path sampling and node embedding in a skip-gram manner. Results We evaluated the prediction performance of the proposed method on a real dataset and the experimental results show that it can achieve the average area under the curve of 0.8519 ± 0.0731 in fivefold cross validation. Besides, we conducted case studies on the prediction of two important kinds of TF, NFKB1 and TP53. As a result, 33 and 32 in the top-40 ranking lists of NFKB1 and TP53 were successfully confirmed by looking up another public database (hTftarget). It is envisioned that the proposed HGETGI method is feasible and effective for predicting TF–target gene interactions on a large scale. Availability and implementation The source code and dataset are available at https://github.com/PGTSING/HGETGI. Supplementary information Supplementary data are available at Bioinformatics online.

Existing API approaches usually independently leverage detection or classification models to distinguish allergic pollens from Whole Slide Images (WSIs). However, palynologists tend to identify pollen grains in a progressive learning manner instead of the above one-stage straightforward way. They generally focus on two pivotal problems during pollen identification. (1) Localization: where are the pollen grains located? (2) Classification: which categories do these pollen grains belong to? To perfectly mimic the manual observation process of the palynologists, we propose a progressive method integrating pollen localization and classification to achieve allergic pollen identification from WSIs. Specifically, data preprocessing is first used to cut WSIs into specific patches and filter out blank background patches. Subsequently, we present the multi-scale detection model to locate coarse-grained pollen regions (targeting at “pollen localization problem”) and the multi-classifiers combination to determine the fine-grained category of allergic pollens (targeting at “pollen classification problem”). Extensive experimental results have demonstrated the feasibility and effectiveness of our proposed method.

Oil and its pollutants, which enter environment through natural oil seepage and many human activities, have considerable impacts on birds. We summarized the research advances in how oil pollutants influence birds and the cleaning technology of polluted birds and their habitats. The toxicity and destruction to feather structure are the major impacts of oil pollution on birds. Oil pollution can lead to birds' death, and also produce many chronic harms, including causing hemolytic anemia, reducing their immunity, disrupting thermal insulation and waterproo-fing performance of feather. It is an important way to reduce the impacts of oil pollution on birds by timely cleaning up the oil in bird habitats as well as carrying out the clean and repair work to the polluted birds. As a big oil-consuming country, China has been left behind by foreign countries in the studies of the effects of oil pollution on birds. More attention should be paid on the short-term and long-term impacts of oil pollution on birds and the cleaning and remediation technologies of the polluted birds and their habitats.石油污染物通过自然泄漏和各种人类活动进入生态环境,对鸟类的生存产生影响。本文综述了国内外有关石油污染物对鸟类所产生的影响、受污染鸟类及其栖息地的清洁修复技术的研究现状以及发展趋势。现有研究发现,石油的毒性和石油对羽毛结构与功能的破坏是石油污染影响鸟类的主要原因。石油污染不仅对鸟类有直接的致死作用,而且能产生许多慢性危害,包括引起鸟类溶血性贫血、使其免疫能力下降、降低羽毛的保温和防水能力等。对鸟类栖息地中的石油污染进行及时清理并开展对受污染鸟类的清洁修复工作,是减轻石油污染对鸟类影响的重要手段。我国作为石油消费大国,关于石油污染对鸟类影响的研究与国外相比滞后,亟需在石油污染对鸟类的短期和长期影响、受污染鸟类及其栖息地的清洁修复技术等方面开展更多的研究。.

BACKGROUND Chimeric antigen receptor T cell (CART) therapy has benefited many refractory lymphoma patients, but some patients experience poor effects. Previous studies have shown that programmed cell death protein-1 (PD-1) inhibitors can improve and prolong the therapeutic effect of CAR-T cell treatment. CASE SUMMARY A 61-year-old male presented with 15-d history of diarrhea and lower-limb edema. A large mass was detected in the pelvis, and pathology indicated non-Hodgkin diffuse large B-cell lymphoma. After three cycles of the R-CHOP chemotherapeutic regimen, the patient showed three subcutaneous nodules under the left armpit and both sides of the cervical spine. Pathological examination of the nodules indicated DLBCL again. The patient was diagnosed with relapsed and refractory diffuse large B-cell lymphoma. We recommended CAR-T cell treatment. Before treatment, the patient’s T cell function and expression of immune detection points were tested. Expression of PD-1 was obviously increased (52.7%) on cluster of differentiation (CD)3+ T cells. The PD-1 inhibitor (3 mg/kg) was infused prior to lymphodepleting chemotherapy with fludarabine and cyclophosphamide. CAR-CD19 T cells of 3 × 106/kg and CAR-CD22 T cells 1 × 106/kg were infused, respectively. The therapeutic effect was significant, and the deoxyribonucleic acid copy numbers of CAR-CD19 T cells and CAR-CD22 T cells were stable. Presently, the patient has been disease-free for more than 12 mo. CONCLUSION This case suggests that the combination of PD-1 inhibitors and CAR-T cells improved therapeutic efficacy in B-cell lymphoma.

Shoot multiplication induced by exogenous cytokinins (CKs) has been commonly used in Phalaenopsis micropropagation for commercial production. Despite this, mechanisms of CKs action on shoot multiplication remain unclear in Phalaenopsis. In this study, we first identified key CKs metabolic genes, including six isopentenyltransferase (PaIPTs), six cytokinin riboside 5′ monophosphate phosphoribohydrolase (PaLOGs), and six cytokinin dehydrogenase (PaCKXs), from the Phalaenopsis genome. Then, we investigated expression profiles of these CKs metabolic genes and endogenous CKs dynamics in shoot proliferation by thidiazuron (TDZ) treatments (an artificial plant growth regulator with strong cytokinin-like activity). Our data showed that these CKs metabolic genes have organ-specific expression patterns. The shoot proliferation in vitro was effectively promoted with increased TDZ concentrations. Following TDZ treatments, the highly expressed CKs metabolic genes in micropropagated shoots were PaIPT1, PaLOG2, and PaCKX4. By 30 days of culture, TDZ treatments significantly induced CK-ribosides levels in micropropagated shoots, such as tZR and iPR (2000-fold and 200-fold, respectively) as compared to the controls, whereas cZR showed only a 10-fold increase. Overexpression of PaIPT1 and PaLOG2 by agroinfiltration assays resulted in increased CK-ribosides levels in tobacco leaves, while overexpression of PaCKX4 resulted in decreased CK-ribosides levels. These findings suggest de novo biosynthesis of CKs induced by TDZ, primarily in elevation of tZR and iPR levels. Our results provide a better understanding of CKs metabolism in Phalaenopsis micropropagation.

Owing to early diagnosis and rapid development of treatments for cancers, the five-year survival rate of all cancer types has markedly improved worldwide. Over time, however, there has been an increase in the number of cancer patients who develop coronary artery disease (CAD) due to different causes. First, many risk factors are shared between cancer and CAD. Second, inflammation and oxidative stress are common underlying pathogeneses in both disorders. Lastly, cancer therapy can result in endothelial injury, coronary artery spasm, and coagulation, thereby increasing the risk of CAD. As more cancer patients are being diagnosed with CAD, specialized cardiac care should be established to minimize the cardiovascular mortality of cancer survivors. Keywords: Cancer, Coronary artery disease, Cardio-oncology

MotivationInteraction between transcription factor (TF) and its target genes establishes the knowledge foundation for biological researches in transcriptional regulation, the number of which is, however, still limited by biological techniques. Existing computational methods relevant to the prediction of TF-target interactions are mostly proposed for predicting binding sites, rather than directly predicting the interactions. To this end, we propose here a graph attention-based autoencoder model to predict TF-target gene interactions using the information of the known TF-target gene interaction network combined with two sequential and chemical gene characters, considering that the unobserved interactions between transcription factors and target genes can be predicted by learning the pattern of the known ones. To the best of our knowledge, the proposed model is the first attempt to solve this problem by learning patterns from the known TF-target gene interaction network.ResultsIn this paper, we formulate the prediction task of TF-target gene interactions as a link prediction problem on a complex knowledge graph and propose a deep learning model called GraphTGI, which is composed of a graph attention-based encoder and a bilinear decoder. We evaluated the prediction performance of the proposed method on a real dataset, and the experimental results show that the proposed model yields outstanding performance with an average AUC value of 0.8864 +/- 0.0057 in the 5-fold cross-validation. It is anticipated that the GraphTGI model can effectively and efficiently predict TF-target gene interactions on a large scale.AvailabilityPython code and the datasets used in our studies are made available at https://github.com/YanghanWu/GraphTGI

Background Recent evidences have suggested that human microorganisms participate in important biological activities in the human body. The dysfunction of host-microbiota interactions could lead to complex human disorders. The knowledge on host-microbiota interactions can provide valuable insights into understanding the pathological mechanism of diseases. However, it is time-consuming and costly to identify the disorder-specific microbes from the biological “haystack” merely by routine wet-lab experiments. With the developments in next-generation sequencing and omics-based trials, it is imperative to develop computational prediction models for predicting microbe-disease associations on a large scale. Results Based on the known microbe-disease associations derived from the Human Microbe-Disease Association Database (HMDAD), the proposed model shows reliable performance with high values of the area under ROC curve (AUC) of 0.9456 and 0.8866 in leave-one-out cross validations and five-fold cross validations, respectively. In case studies of colorectal carcinoma, 80% out of the top-20 predicted microbes have been experimentally confirmed via published literatures. Conclusion Based on the assumption that functionally similar microbes tend to share the similar interaction patterns with human diseases, we here propose a group based computational model of Bayesian disease-oriented ranking to prioritize the most potential microbes associating with various human diseases. Based on the sequence information of genes, two computational approaches (BLAST+ and MEGA 7) are leveraged to measure the microbe-microbe similarity from different perspectives. The disease-disease similarity is calculated by capturing the hierarchy information from the Medical Subject Headings (MeSH) data. The experimental results illustrate the accuracy and effectiveness of the proposed model. This work is expected to facilitate the characterization and identification of promising microbial biomarkers.

Shoot multiplication induced by exogenous cytokinins (CKs) has been commonly used in

Objective: This study aims to explore the role of aniline-actin binding protein (ANLN) in the prognosis of lung adenocarcinoma (LUAD) and its role in immune infiltration, and to provide new ideas for clinical diagnosis and treatment.Methods: In this study, we applied bioinformatics methods to analyze the expression pattern and prognostic value of ANLN in LUAD ,and confirmed its independent prognostic value through Cox analysis. TIMER was used to evaluate the correlation between ANLN and tumor infiltrating immunity. LinkedOmics was used to study the co-expressed genes and functional networks related to ANLN.The TIMER database was used to analyze the correlation between ANLN co-expressed genes and tumor infiltrating immune cells. Results: ANLN is highly expressed in most cancers. In the TCGA-LUAD cohort, ANLN was highly expressed in LUAD. ANLN was significantly related to the grade , T stage and N stage of patients with LUAD. It was verified in multiple independent queues. The high expression and highly mutation of ANLN predicts poor survival .Multivariate COX analysis showed that ANLN was an independent risk factor for survival . GSEA analysis shows that ANLN regulates cell cycle, and other pathways. The expression of ANLN was significantly correlated with the level of B cell infiltration.Conclusions: ANLN is closely related to the prognosis of patients with LUAD and tumor immune cell infiltration suggesting that ANLN is a key factor regulating the recruitment of immune cells to LUAD and may play an important role in immune.

Developing noble-metal-based catalysts with ultralow loading to achieve excellent performance for selective hydrogenation of alkynes under mild reaction conditions is highly desirable but still faces huge challenges. To this end, a SO3H-anchored covalent organic framework (COF-SO3H) as the support was deliberately designed, and then ultralow-content Pd (0.38 wt %) was loaded by a wet-chemistry immersion dispersion method. The resulting Pd0.38/COF-SO3H composite exhibits outstanding performance for the selective hydrogenation of phenylacetylene with 97.06% conversion and 93.15% selectivity to styrene under mild reaction conditions (1 bar of H2, 25 °C). Noticeably, the turnover frequency value reaches as high as 3888 h-1, which outperforms most of reported catalysts for such use. Moreover, such a catalyst also exhibits excellent activity for a series of other alkynes and high stability without obvious loss of catalytic performance after five consecutive cycles.

Background l-2-aminobutyric acid (l-ABA) is an unnatural amino acid that is a key intermediate for the synthesis of several important pharmaceuticals. To make the biosynthesis of l-ABA environmental friendly and more suitable for the industrial-scale production. We expand the nature metabolic network of Escherichia coli using metabolic engineering approach for the production of l-ABA. Results In this study, Escherichia coli THR strain with a modified pathway for threonine-hyperproduction was engineered via deletion of the rhtA gene from the chromosome. To redirect carbon flux from 2-ketobutyrate (2-KB) to l-ABA, the ilvIH gene was deleted to block the l-isoleucine pathway. Furthermore, the ilvA gene from Escherichia coli W3110 and the leuDH gene from Thermoactinomyces intermedius were amplified and co-overexpressed. The promoter was altered to regulate the expression strength of ilvA* and leuDH. The final engineered strain E. coli THR ΔrhtAΔilvIH/Gap-ilvA*-Pbs-leuDH was able to produce 9.33 g/L of l-ABA with a yield of 0.19 g/L/h by fed-batch fermentation in a 5 L bioreactor. Conclusions This novel metabolically tailored strain offers a promising approach to fulfill industrial requirements for production of l-ABA. Electronic supplementary material The online version of this article (10.1186/s12934-019-1095-z) contains supplementary material, which is available to authorized users.

Uranium is the most radioactive element using in the nuclear industry and nuclear technology application. However, it is harmful for environment and human health due to its high toxicity and mobility. Thus designing effective material for uranium removal is highly desirable. In this paper, a novel adsorbent of nZVI@Zn-MOF-74 prepared by anchoring nZVI on Zn-MOF-74 was investigated for the removal of uranium from aqueous solutions. Impressively, nZVI was synthesized for the first time by a spraying approach in a simple and convenient manner. The experimental results indicated that nZVI@Zn-MOF-74 can significantly enhance the removal of U(VI) than both Zn-MOF-74 material and nZVI, leading to high adsorption capacity up to 348 mg/g at pH = 3 and 298 K. The origin, as unveiled by XPS, is due to both U(VI) adsorption from Zn-MOF-74 and U(VI)-to-U(IV) reduction by nZVI.

In this work, we found that the open-metal site in a metal-organic framework (MOF) can be used to enhance such selectivity. Hydrogenation of phenylacetylene over such a catalyst enables ultrahigh styrene selectivity of 92% at full conversion with a turnover frequency of 98.1 h-1. The origin of ultrahigh selectivity, as unveiled by density functional theory calculation, is due to a coordination interaction between the open Zn(II) site and the C≡C bond of phenylacetylene.

Herein we report a novel azo metal-organic framework (MOF), namely Zn2(DMF)(ADC)2(L)0.5 (ECUT-100, H2ADC=azobenzene-4,4'-dicarboxylic acid, L=N, N'-di(pyridin-4-yl)naphthalene-1,4-dicarboxamide), showing a polycatenated 3D array of interlaced 2D bilayers. Without any pre-treatment the as-synthesized ECUT-100 samples effectively adsorb U(VI), leading to the ultrahigh adsorption capacity up to 381 mg/g. This value is greatly higher than that observed in most established porous adsorbents. The origin is primarily due to the free standing azo and amide groups from ADC2- and L ligands that may provide special interactions with U(VI) ions.

In this work, we designed a hybrid catalyst composed of a metal–organic framework (MOF), Pt nanoparticles (NPs), and ferric oxide, namely, Co-MOF-74@(Pt@Fe2O3), which enables not only high turnover frequencies of up to 245.7 h–1 but also ultrahigh 100% selectivity toward cinnamyl alcohol in the hydrogenation of cinnamaldehyde under mild conditions. This excellent performance is attributed to the fact that such a hybrid catalyst enables not only strong steric constraint to provide the favored C═O adsorption of cinnamaldehyde but also strong metal–support interaction to lower the electron density of Pt NPs.

Uranium is not only a radioactive element but also an important nuclear-energy source. Thus the design of material for effective uranium adsorption is highly desirable from both environmental and energy considerations. In this work, a new azo-MOF was explored such use. It shows excellent U(VI) removal performance with the adsorption capacity up to 200 mg/g. The adsorption, as disclosed by the adsorption kinetics, is dominated by chemical adsorption, mainly due to coordination interaction between azo/amide and U(VI) ions. The results suggest that design of material with free-standing azo or amide groups benefits to U(VI) removal.

We present here the first use of a photoassisted multicomponent postsynthetic modification method to anchor a ZIF-90 scaffold with a pyrimidinethione fragment. The resultant materials, namely, ZIF-90-THP and ZIF-90-THF, show ultrahigh Hg(II) adsorption capacity values of up to 596 and 403 mg/g, respectively, relative to the pristine ZIF-90, which just affords a corresponding value of 47 mg/g, suggesting a 12.7- and 8.6-fold enhancement in the Hg(II) adsorption capacity.

In this study, we present the first case of applying the MOF+ technique for in situ preparation of a hybrid material, namely, Zn-MOF-74@ (Pd@Fe2O3). This as-synthesized material can well maintain both the integrity of the framework and porosity. Notably, Zn-MOF-74@(Pd@Fe2O3) exhibits outstanding catalytic performance in the hydrogenation reaction of alkene and semihydrogenation reaction of phenylacetylene, thus providing a new guideline for the design of MOF-based hybrid materials for catalytic purpose.

Significant synergic effect from metal-organic framework (MOF) and Fe2SO4, so-called MOF+ technique, is for the first time exploited to remove toxic chromate from aqueous solution. The results show that relative to the pristine MOF samples without detectable chromate removal, MOF+ method enables super-performance, giving a 796 Cr mg/g adsorption capacity. The value is almost eight-fold bigger than the best value established in MOF adsorbents, and presents the highest one among all repored porous adsorbents for such use until now. The adsorption mechanism, unlike an anion-exchange process that dominates the chromate removal in all reported MOF adsorbents, as unveiled by X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM), is due to the surface enrichment of abundant Fe0.75Cr0.25(OH)3 nanospheres on MOF samples. This study outlines a new guideline for designing MOFs with ultrahigh removal capacity toward chromate.

Activation of the extremely inert U O bond of uranyl group is presents not only a high scientific challenge, but also a powerful tool to modify the physical and chemical properties of materials with unique electronic and magnetic features. Distinct from all homogeneous methods of U O activation reported in the literature, this work presents, for the first time, a solid-liquid reaction through post-modification approach on uranyl-organic framework to generate stable U–O activated metal-organic framework. Two different molecules such as B-chlorocatecholborane (Cl-BCat) and diborane pinacolate ((Bpin)2, pin ​= ​pinacolate) were used to carry out this task, giving activating efficiency of 37% for Cl-BCat and 50% for (Bpin)2, respectively. Impressively, this U O activation directly leads to significant change in the physical and chemical properties, for example, a diamagnetic-to-paramagnetic transformation and significant reduction in photocatalytic oxidation efficiency, as compared to the properties of pristine MOF.

Directly extracting uranium from alkaline solution and seawater through an effective and economical method is still a challenging task. In this work, we for the first time propose a method of anionic exchange, based on a cationic MOF (metal-organic framework) adsorbent, namely Co-SLUG-35, to directly extract U(VI) from alkaline solution and seawater (South China Sea). The U(VI) adsorption experiments indicates that the EDS2− anions in Co-SLUG-35 can be completely replaced by U(VI) ions in an anionic manner, leading to an adsorption capability of 118 mg/g from alkaline U(VI) solution and excellent extraction efficiency of 1.05 mg/g from 1 L actual seawater in the concentration of 5.35 ppb. Most importantly, unlike other MOFs where degassing is primarily needed, however the use of present MOF need not any pretreatment. Moreover, ultrahigh selectivity towards U(VI) ions even over CrO42− and Cl− ions is also observed in Co-SLUG-35, suggesting its superior potential in extraction of uranium from seawater.

Mercury (Hg2+) ions have very high toxicity and widely spread as environmental pollutants. At present, many efforts have been taken to remove the hazardous materials of mercury(II) by adsorption, and it is highly desirable to develop a novel adsorbent with high adsorptive capacities. However it is still a big challenge to remove the ultra-low-concentration mercury ions from water. In this paper, MOF-74-Zn is explored for such function, showing high removal rate of Hg(II) from water without any pretreatment, especially for the ultra-trace Hg(II) ions in the ppb magnitude with the removal rate reaching to 54.48%, 69.71%, 72.26% when the initial concentration of Hg(II) is 20ppb, 40ppb, 50ppb, respectively.

A series of O-substituted trifluoroatrolactamide derivatives has been synthesized and fully characterized by 1H NMR, 13C NMR, 19F NMR, HRMS and X-ray diffraction analyses. The fungicidal activity of these compounds was evaluated and the results showed that some of them exhibited potent in vitro fungicidal activity against Erysiphe graminis and Pyricularia oryzae. Their structure-property relationships were investigated using density functional theory calculations. The X-ray crystal structure of one of these compounds adopted a monoclinic space group with the following unit cell parameters: a = 24.285 (13) A, b = 9.006 (5) A, c = 9.794 (5) A, β = 92.110 (9)o, V = 2140.6 (19) A3 and Z = 4. A comparison of these experimental results with the theoretical values revealed that there was good agreement between the two sets of data. The subsequent biological evaluation of these compounds showed that some of them exhibited potent in vitro fungicidal activity against Erysiphe graminis and Pyricularia oryzae.

To explore the nest survival rate of Reeves's pheasant(Syrmaticus reevesii) and the nest-site factors that affect it, we conducted artificial nest experiments with reference to natural nests at Dongzhai National Nature Reserve(DNNR), Henan Province and Pingjingguan, Hubei Province from April to June 2014 simulating the situation in its early and later breeding season. We also determined distance characteristics of the nest sites using ArcGIS 10.0. Nest survival models were constructed in Program MARK for data analysis. Results indicated that in the early breeding season, the apparent survival rate(ASR) in DNNR(52.4%) was significantly greater than that in Pingjingguan(13.5%), and the ASR in the later breeding season in DNNR(26.7%) was not indistinctively correlated with Pingjingguan(3.2%). The daily survival rate(DSR) in the later breeding season was 93.8% in DNNR and 92.0% in Pingjingguan, respectively. The DSRs were both negatively correlated with nest distance to forest edges and settlements. The DSR in Pingjingguan was positively correlated with nest distance to paths and negatively correlated with nest distance to water sources. However, the DSR in DNNR was negatively correlated with nest distance to paths but positively correlated with nest distance to water sources.

MOF materials, as new catalysts, show high catalytic activity and size-, regio-, and stereo-selectivity. However, artificially controlling their catalytic process by convenient external stimulus such as light is still unexploited. Such photocontrol over an organic reaction may enable switchable catalytic activities and/or selectivities, consequently producing desired products from a pool of building blocks according to the order and type of stimuli applied. In this study, we present a novel MOF catalyst, which not only offers ultrahigh photocontrol with the on/off ratio as high as 407, but also displays disparate photomodulation in reaction kinetics towards various aldehyde substrates in light of their sizes, thus creating the first example of MOFs showing photoswitchable catalysis. The origin, as unveiled by photoswitching adsorption experiments and density functional theory calculations, is due to photoswitching storage of guest molecules in the metal–organic framework (MOF).

Clinical trials of chimeric antigen receptors (CARs) targeting CD19 have produced impressive results in hematological malignancies, including diffuse large B-cell lymphoma (DLBCL). However, a notable number of patients with DLBCL fail to achieve remission after CD19 CAR T-cell therapy and may therefore require a dual targeted CAR T-cell therapy. A 31-year-old man with refractory DLBCL was assessed in the present case report. The patient was treated with sequential infusion of single CD19 CAR T cells followed by dual CD19/CD22-targeted CAR T cells. The outcome was that the patient achieved partial remission after the first single CD19 CAR T-cell infusion and complete remission after the dual CD19/CD22-targeted CAR T-cell infusion. Grade 1 cytokine release syndrome (CRS) was observed after the single CD19 CAR T-cell infusion, while grade 3 CRS and hemophagocytic syndrome were observed after the dual targeted CAR T-cell infusion, but these adverse effects alleviated after the treatments. To the best of our knowledge, the present case report is the first to describe the successful application of dual CD19/CD22-targeted CAR T-cell therapy for the treatment of refractory DLBCL. The report suggests that dual CD19/CD22-targeted CAR T-cell therapy may represent a promising option for the treatment of refractory DLBCL; however, caution should be taken due to potential CRS development.

A series of novel substituted 3,3,3-trifluoro-2-methoxy-N-methyl-N,2-diphenylpropanamides were synthesized from α-hydroxyacetamide using CH3I as the methylating agent. Their chemical structures were characterized by 1H NMR, 13C NMR, 19F NMR, and HRMS X-ray analysis. The dimethylated trifluoroatrolactamide exhibited moderate antifungal activity.

Brooding is a major breeding investment of parental birds during the early nestling stage, and has important effects on the development and survival of nestlings. Investigating brooding behavior can help to understand avian breeding investment strategies. From January to June in 2013 and 2014, we studied the brooding behaviors of long-tailed tits (Aegithalos caudatus glaucogularis) in Dongzhai National Nature Reserve, Henan Province, China. We analyzed the relationships between parental diurnal brooding duration and nestling age, brood size, temperature, relative breeding season, time of day and nestling frequencies during brooding duration. Results showed that female and male long-tailed tit parents had different breeding investment strategies during the early nestling stage. Female parents bore most of the brooding investment, while male parents performed most of the nestling feedings. In addition, helpers were not found to brood nestlings at the two cooperative breeding nests. Parental brooding duration was significantly associated with the food delivered to nestlings (F=86.10, df=1, 193.94, P

This work presents an in situ method, similar to the ‘crystalline sponge’ method, to accurately identify and absolutely separate small volatile organic molecules (such as methanol, ethanol, propanol and DMF).

The cell walls of oomycetes are composed of cellulose, making cellulose synthase enzymes good targets for carboxylic acid amide fungicides. Valinamide carbamates are amino acid fungicides that represent excellent alternatives to conventional synthetic pesticides in terms of their ability to reduce the negative impacts of these compounds on human health and the environment. In a continuation of our research towards the development of new cellulose synthase inhibitors, we have developed a series of “stretched” analogues of iprovalicarb by the introduction of an additional OCH2 linker. The bioassay results indicated that compounds containing a small group at the para-position of phenyl gave excellent fungicidal activities with EC50 values ranging from 0.59 to 2.06 μmol L−1. Most notably, the introduction of a propargyloxy group led to a pronounced increase in the fungicidal activity. Furthermore, compound 7o bearing a propargyloxy group was identified as the most promising candidate because of its excellent fungicidal potency against oomycete diseases and good fungicidal activity against non-oomycete diseases.

Herein, we report an elaborate method, size-selective crystallization of Ln-MOFs, to isolate lanthanide (Ln) ions. Herein, 13 lanthanide ions, except for the radioactive Pm(iii) ion, were separated by four types of Ln-MOFs: type I (La-Pr), type II (Nd-Eu), type III (Gd-Ho), and type IV (Er-Lu). Further systemic investigation also suggested the highly selective separation of lanthanide ions by this method.

The great efforts have been devoted to fabricate excellent hydrogenation catalysts owing to the broad applications in industrial fields. However, the preparation processes of traditional hydrogenation catalysts are often complicated. Herein, mono-valence PtI@COF was synthesized as a catalyst for semi-hydrogenation of phenylacetylene for the first time. The easily prepared SO3H-linked COF possesses a two-dimensional eclipsed layered-sheet structure, making its incorporation with metal ions feasible. The as-prepared PtI@COF composite exhibits excellent performance for semi-hydrogenation phenylacetylene with 93.5% conversion and 90.2% selectivity to styrene under mild reaction conditions (1 ​bar H2, 25 ​°C) within 20 ​min. It’s worth noting that the turnover frequency (TOF) value reaches at 3965 h-1, which outperforms most of recently reported excellent Pt-based catalysts for this reaction.

In this study, we present the first case of applying the MOF+ technique for in situ preparation of a hybrid material, namely, Zn-MOF-74@ (Pd@Fe2O3). This as-synthesized material can well maintain both the integrity of the framework and porosity. Notably, Zn-MOF-74@(Pd@Fe2O3) exhibits outstanding catalytic performance in the hydrogenation reaction of alkene and semihydrogenation reaction of phenylacetylene, thus providing a new guideline for the design of MOF-based hybrid materials for catalytic purpose.

MicroRNAs (miRNAs) have been proved to be targeted by the small molecules recently, which made using small molecules to target miRNAs become a possible therapy for human diseases. Therefore, it is very meaningful to investigate the relationships between small molecules and miRNAs, which is still yet in the newly-developing stage. In this paper, we presented a prediction model of Graphlet Interaction based inference for Small Molecule-MiRNA Association prediction (GISMMA) by combining small molecule similarity network, miRNA similarity network and known small molecule-miRNA association network. This model described the complex relationship between two small molecules or between two miRNAs using graphlet interaction which consists of 28 isomers. The association score between a small molecule and a miRNA was calculated based on counting the numbers of graphlet interaction throughout the small molecule similarity network and the miRNA similarity network, respectively. Global and two types of local leave-one-out cross validation (LOOCV) as well as five-fold cross validation were implemented in two datasets to evaluate GISMMA. For Dataset 1, the AUCs are 0.9291 for global LOOCV, 0.9505, and 0.7702 for two local LOOCVs, 0.9263 ± 0.0026 for five-fold cross validation; for Dataset 2, the AUCs are 0.8203, 0.8640, 0.6591, and 0.8554 ± 0.0063, in turn. In case study for small molecules, 5-Fluorouracil, 17β-Estradiol and 5-Aza-2'-deoxycytidine, the numbers of top 50 miRNAs predicted by GISMMA and validated to be related to these three small molecules by experimental literatures are in turn 30, 29, and 25. Based on the results from cross validations and case studies, it is easy to realize the excellent performance of GISMMA.

This study explored the friction and wear behavior of a Ni-based exhaust valve at high temperatures. Nickel-based superalloy was used with two types of processing states: the original forged sample and the sample under the standard T1 heat treatment. At room temperature and a loading force of 10[Formula: see text]N, the average friction coefficient of the T1 heat-treated specimen is 0.61, which was lower than that of the forged sample (0.78). The wear rate of this specimen was also lower than that of the forged sample at the same temperature and loading force. Thus, T1 heat treatment can significantly improve the wear resistance of the alloy because of [Formula: see text] phase and carbides. The wear rate was the minimum at 550∘C and increased again at 750∘C dominated by the formation and flake-off of the oxide film.

In this paper the density matrices derived from combinatorial Laplacian matrix of graphs is considered. More specifically, the paper places emphasis on the star-relevant graph, which means adding certain edges on peripheral vertices of star graph. Initially, we provide the spectrum of the density matrices corresponding to star-like graph (i.e., adding an edge on star graph) and present that the Von Neumann entropy increases under the graph operation (adding an edge on star graph) and the graph operation cannot be simulated by local operation and classical communication (LOCC). Subsequently, we illustrate the spectrum of density matrices corresponding to star-alike graph (i.e., adding one edge on star-like graph) and exhibit that the Von Neumann entropy increases under the graph operation (adding an edge on star-like graph) and the graph operation cannot be simulated by LOCC. Finally, the spectrum of density matrices corresponding to star-mlike graph (i.e., adding m nonadjacent edges on the peripheral vertices of star graph) is demonstrated and the relation between the graph operation and Von Neumann entropy, LOCC is revealed in this paper.

Extraction of uranium from seawater is very important to overcome the growing crisis in the sustainable development of energy, and consequently has attracted an enormous amount of attention. Herein, we report the application of MOF materials in the extraction of uranium from seawater. Without any pre-treatment and within one minute, this MOF material shows a one-off extraction efficiency of 0.53 mg g−1 from 1 L artificial seawater in the concentration of 6 ppb, suggesting its significant potential for the extraction of uranium from seawater. This significant ability is mainly dependent on free standing carboxyl groups in the MOF channel that coordinate to UO2+ ions via the U–O coordination bond.

Mercury (Hg2+), even an ultra-low-concentration amount in water, presents a serious environmental concern. Thus, the removal, especially Hg(II) content at the ultratrace levels (ppb), from water is still challenging. In this work, without any pretreatment, anovel MOF material can act as a high-capacity and collectable adsorbent for the removal of Hg(II) from water, especially for ultratrace Hg2+ ions in the ppb magnitude, mainly due to a combined effect from the pore walls functionalized by free-standing, accessible acylamide and hydroxyl units.