IgD/FcδR is involved in T-cell acute lymphoblastic leukemia and regulated by IgD-Fc-Ig fusion protein.

T-cell acute lymphoblastic leukemia (T-ALL) has a poor prognosis as a result of severe immunosuppression and rapid tumor progression with resistance to conventional chemotherapy. Excessive IgD may play a role in T cell activation via IgD Fc receptor (FcδR). Here we aimed to investigate the effects of IgD in T-ALL and demonstrated the potential benefit by targeting IgD/FcδR in T-ALL patients with IgD-Fc-Ig fusion protein. In T-ALL patients' blood samples and cell lines, the level of IgD, the percentage of FcδR expressing cells and the binding affinity were determined by flow cytometry. T cell viability, proliferation and apoptosis were analyzed. A mouse xenograft model was used to evaluate the in vivo effect of IgD-Fc-Ig, an IgD-FcδR blocker. The levels of serum IgD and FcδR were abnormally increased in part of T-ALL patients and IgD could induce over-proliferation and inhibit apoptosis of T-ALL cells in vitro. FcδR was constitutively expressed on T-ALL cells. IgD-Fc-Ig showed similar binding affinity to FcδR and selectively blocked the stimulation effect of IgD on T-ALL cells in vitro. In vivo study exhibited that IgD-Fc-Ig may also have therapeutic benefit. IgD-Fc-Ig administration inhibited human T-ALL growth and extended survival in xenograft T-ALL mice. In conclusion, this work supports the idea of targeting IgD/FcδR in T-ALL patients with excessive IgD. IgD-Fc-Ig fusion protein might be a potential biological drug with high selectivity for T-ALL treatment.

An IgD-Fc-Ig fusion protein restrains the activation of T and B cells by inhibiting IgD-IgDR-Lck signaling in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by synovitis and the destruction of small joints. Emerging evidence shows that immunoglobulin D (IgD) stimulation induces T-cell activation, which may contribute to diseases pathogenesis in RA. In this study, we investigated the downstream signaling pathways by which IgD activated T cells as well as the possible role of IgD in the T-B interaction. Peripheral blood mononuclear cells were isolated from peripheral blood of healthy controls and RA patients. We demonstrated that IgD activated T cells through IgD receptor (IgDR)-lymphocyte-specific protein tyrosine kinase (Lck)-zeta-associated protein 70 (ZAP70)/phosphatidylinositol 3-kinase (PI3K)/nuclear factor kappa-B (NF-κB) signaling pathways; IgD-induced CD4+ T cells promoted the proliferation of CD19+ B cells in RA patients. A novel fusion protein IgD-Fc-Ig (composed of human IgD-Fc domain and IgG1 Fc domain, which specifically blocked the IgD-IgDR binding) inhibited the coexpression of IgDR and phosphorylated Lck (p-Lck) and the expression levels of p-Lck, p-ZAP70, p-PI3K on CD4+ T cells, and decreased NF-κB nuclear translocation in Jurkat cells. Meanwhile, IgD-Fc-Ig downregulated the expression levels of CD40L on CD4+ T cells as well as CD40, CD86 on CD19+ B cells in RA patients and healthy controls. It also decreased the expression levels of CD40L on CD4+ T cells and CD40 on CD19+ B cells from spleens of collagen-induced arthritis (CIA) mice and reduced IL-17A level in mouse serum. Moreover, administration of IgD-Fc-Ig (1.625-13 mg/kg, iv, twice a week for 4 weeks) in CIA mice dose-dependently decreased the protein expression levels of CD40, CD40L, and IgD in spleens. IgD-Fc-Ig restrains T-cell activation through inhibiting IgD-IgDR-Lck-ZAP70-PI3K-NF-κB signaling, thus inhibiting B-cell activation. Our data provide experimental evidences for application of IgD-Fc-Ig as a highly selective T cell-targeting treatment for RA.

Prediction of RNA-protein interactions by combining deep convolutional neural network with feature selection ensemble method.

RNA-protein interaction (RPI) plays an important role in the basic cellular processes of organisms. Unfortunately, due to time and cost constraints, it is difficult for biological experiments to determine the relationship between RNA and protein to a large extent. So there is an urgent need for reliable computational methods to quickly and accurately predict RNA-protein interaction. In this study, we propose a novel computational method RPIFSE (predicting RPI with Feature Selection Ensemble method) based on RNA and protein sequence information to predict RPI. Firstly, RPIFSE disturbs the features extracted by the convolution neural network (CNN) and generates multiple data sets according to the weight of the feature, and then use extreme learning machine (ELM) classifier to classify these data sets. Finally, the results of each classifier are combined, and the highest score is chosen as the final prediction result by weighting voting method. In 5-fold cross-validation experiments, RPIFSE achieved 91.87%, 89.74%, 97.76% and 98.98% accuracy on RPI369, RPI2241, RPI488 and RPI1807 data sets, respectively. To further evaluate the performance of RPIFSE, we compare it with the state-of-the-art support vector machine (SVM) classifier and other exiting methods on those data sets. Furthermore, we also predicted the RPI on the independent data set NPInter2.0 and drew the network graph based on the prediction results. These promising comparison results demonstrated the effectiveness of RPIFSE and indicated that RPIFSE could be a useful tool for predicting RPI.

Development of Indirect Competitive ELISA and Colloidal Gold Immunochromatographic Strip for Endosulfan Detection Based on a Monoclonal Antibody.

Endosulfan, as an effective broad-spectrum insecticide, has been banned in agricultural areas because of the potential harmful effects on human health. This study aimed to develop an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) and colloidal gold immunochromatographic (ICA) strip based on a prepared monoclonal antibody (mAb) for quantitative and qualitative detection of endosulfan. A new mAb with high sensitivity and affinity was designed and screened. The ic-ELISA showed a 50% inhibition concentration (IC50) value of 5.16 ng/mL for endosulfan. Under optimum conditions, the limit of detection (LOD) was determined to be 1.14 ng/mL. The average recoveries of endosulfan in spiked pear and apple samples ranged from 91.48-113.45% and 92.39-106.12% with an average coefficient of variation (CV) of less than 7%, respectively. The analysis of colloidal gold ICA strip could be completed within 15 min by naked eye and the visual limit of detection (vLOD) was both 40 ng/mL in pear and apple samples. In conclusion, both developed immunological methods were suitable and reliable for the on-site detection of endosulfan in real samples at trace levels.

Physical modification of high amylose starch using electron beam irradiation and heat moisture treatment: The effect on multi-scale structure and in vitro digestibility.

This study explores a new strategy for manipulating the digestibility of high-amylose maize starch (HAMS) through combinative modifications, namely depolymerization via electron beam irradiation (EBI) followed by reorganizing glucan chains via heat moisture treatment (HMT). The results show that semi-crystalline structure, morphological features and thermal properties of HAMS remained similar. However, EBI increased branching degree of the starch at high irradiation dosage (20 kGy), resulting in more readily leached amylose during heating. HMT increased the relative crystallinity (3.9-5.4% increase) and V-type fraction (0.6-1.9% increase), without significant changes (p > 0.05) in gelatinization onset temperature, peak temperature and enthalpy. Under simulated gastrointestinal conditions, the combination of EBI and HMT either had no effect or negative effect on starch enzymatic resistance, depending on the irradiation dosage. These results suggest that the depolymerization by EBI predominantly affects the changes in enzyme resistance, rather than the growth and perfection of crystallites induced by HMT.

Altered leaching composition of maize starch granules by irradiative depolymerization: The key role of degraded molecular structure.

The molecular composition of starch leachates from starch-based foods has been recently recognised as a crucial determinant of food properties. However, there is limited knowledge on the regulation of this composition through irradiative depolymerization of starch. This research investigates the leaching behaviour of maize starch depolymerized by electron beam irradiation, and the relationship between the composition of leached starch and structures of modified starch granules. The analysis using 1H NMR spectroscopy confirmed a decrease in the degree of branching (from 4.4 % to 2.8 %), while size-exclusion chromatography identified a newly-derived amylopectin fraction of a smaller hydrodynamic radius (approximately 60-80 nm). The structural properties of the starch granules were also analysed, revealing an increased BET-area of granules and reduced total crystallinity after depolymerization. In the leachates of swollen granules, the bimodal distribution of starch molecules evolves into unimodal with the increase of the irradiative dosage, while modified starch leached more starch molecules with Rh < 10 nm. The results of principal component analysis and Pearson correlation analysis indicate that the degree of branching of degraded starch molecules, as well as the newly-derived amylopectin fraction, significantly correlates (p < 0.01) with the molecular size of leached starch molecules (Rh < 10 nm). It is thus proposed that the cleavage of α-1,6 linkage may be a critical factor in controlling the leaching process of irradiated starch granules. This study highlights the potential of irradiative degradation to control the molecular composition and structure of starch leachates, thereby optimizing the properties of starch-based foods.

IgD enhances the release of neutrophil extracellular traps (NETs) via FcδR in rheumatoid arthritis patients.

Rheumatoid arthritis (RA) is a systemic autoimmune inflammatory disorder affecting primarily the joints. Neutrophils and the release of neutrophil extracellular traps (NETs) contribute to the pathogenesis of RA. However, IgD, which was abnormally higher in RA, has not been studied for its pathological role in neutrophil activation and NETs formation. To investigate the effects of IgD on neutrophil activation and NETs formation via IgD receptor (FcδR), we collect peripheral blood of RA patients and established adjuvant-induced arthritis (AA) rat model. We found that the expression of FcδR on neutrophils was significantly higher in RA patients compared with healthy controls. As a specific marker of NETs, the level of citrullinated histone H3 was positively correlated with sIgD and FcδR in RA patients. IgD enhances the release of NETs and promotes the proliferation of fibroblast-like synoviocytes (FLS) from RA patients by activating neutrophils. As a competitive FcδR blocker, IgD-Fc-Ig fusion protein could significantly reduce NETs formation and FcδR expression on neutrophils in vitro. In vivo, IgD-Fc-Ig could restrain IgD-induced neutrophil activation and NETs formation, thus inhibited FLS proliferation in AA rats. Data presented here demonstrate that neutrophils could be triggered by IgD to release NETs and take part in FLS proliferation in RA patients with excessive IgD. Blocking IgD-FcδR could inhibit neutrophil activation and NETs formation, and represent an additional attractive novel therapeutic strategy for the treatment of RA.

Childhood pheochromocytoma crisis complicated with brain stem infarction: A case report.

RATIONALE: Pheochromocytoma crises are very rarely seen in children. In this report, we present a case of the death related to occult pheochromocytoma crisis combined cerebral infarction. PATIENT CONCERNS: A 5-year-old boy has a 1-month history of polydipsia, polyuria, sweating, and weight loss of 2.5 kg. He was admitted to our hospital because of 1 week of anorexia, 2 days of vomiting, and 12 hours of convulsions and confusion. Magnetic resonance imaging of the brain and cervical spinal cord showed abnormal signals in the left parie-occipital lobe, medulla oblongata till C7 cervical vertebrae. DIAGNOSES: Based on patient's complaints and clinical appearance, provisional diagnosis of pheochromocytoma crisis complicated brainstem infarction was considered. INTERVENTIONS: Tracheal intubation, volume expansion, continuous infusion of dobutamine, and sedation reduce intracranial pressure. Chest compression was performed when the child suddenly developed sobbing respiration. OUTCOMES: The patient was dead. Congenital metabolic defects screening suggested mild ketonuria. Trio whole exon sequencing revealed a synonymous mutation of von Hippel-Lindau syndrome c.414 A > G in the decedent. Autopsy revealed pheochromocytoma, acute myocarditis, liquefaction necrosis of the medulla oblongata cerebral edema, and congestion. LESSONS: Early clinical symptoms of pheochromocytoma in children are not typical. It may induce serious complications and develop into a pheochromocytoma crisis and cause death without proper treatment.

Seek-and-Hide: Adversarial Steganography via Deep Reinforcement Learning.

The goal of image steganography is to hide a full-sized image, termed secret, into another, termed cover. Prior image steganography algorithms can conceal only one secret within one cover. In this paper, we propose an adaptive local image steganography (AdaSteg) system that allows for scale- and location-adaptive image steganography. By adaptively hiding the secret on a local scale, the proposed system makes the steganography more secured, and further enables multi-secret steganography within one single cover. Specifically, this is achieved via two stages, namely the adaptive patch selection stage and secret encryption stage. Given a pair of secret and cover, first, the optimal local patch for concealment is determined adaptively by exploiting deep reinforcement learning with the proposed steganography quality function and policy network. The secret image is then converted into a patch of encrypted noises, resembling the process of generating adversarial examples, which are further encoded to a local region of the cover to realize a more secured steganography. Furthermore, we propose a novel criterion for the assessment of local steganography, and also collect a challenging dataset that is specialized for the task of image steganography, thus contributing to a standardized benchmark for the area. Experimental results demonstrate that the proposed model yields results superior to the state of the art in both security and capacity.

Video Moment Retrieval With Noisy Labels.

Video moment retrieval (VMR) aims to localize the target moment in an untrimmed video according to the given nature language query. The existing algorithms typically rely on clean annotations to train their models. However, making annotations by human labors may introduce much noise. Thus, the video moment retrieval models will not be well trained in practice. In this article, we present a simple yet effective video moment retrieval framework via bottom-up schema, which is in end-to-end manners and robust to noisy label training. Specifically, we extract the multimodal features by syntactic graph convolutional networks and multihead attention layers, which are fused by the cross gates and the bilinear approach. Then, the feature pyramid networks are constructed to encode plentiful scene relationships and capture high semantics. Furthermore, to mitigate the effects of noisy annotations, we devise the multilevel losses characterized by two levels: a frame-level loss that improves noise tolerance and an instance-level loss that reduces adverse effects of negative instances. For the frame level, we adopt the Gaussian smoothing to regard noisy labels as soft labels through the partial fitting. For the instance level, we exploit a pair of structurally identical models to let them teach each other during iterations. This leads to our proposed robust video moment retrieval model, which experimentally and significantly outperforms the state-of-the-art approaches on standard public datasets ActivityCaption and textually annotated cooking scene (TACoS). We also evaluate the proposed approach on the different manual annotation noises to further demonstrate the effectiveness of our model.

Continuous hydrodynamic mixing weakens the dominance of Microcystis: evidences from microcosm and lab experiments.

Hydrodynamic mixing is one of the important environment factors in determining phytoplankton community compositions. Here the influences of continuous hydrodynamic mixing on abundance, morphology, and dominance of Microcystis were investigated in microcosm and lab experiments. Our research results showed that Cyanophyta contributed 57.16% to the total biomass in control, but Chlorophyta was the dominant group in continuous hydrodynamic mixing (CHM) group, contributing 76.54% to the total biomass in the microcosm experiment. The average number of Microcystis in control was 1.95 folds in CHM group. However, the mean abundance of Scenedesmus quadricauda and Pseudanabaena limnetica in CHM was 2.47 and 2.97 folds in control. In the lab experiment, the average number of Microcystis flos-aquae in control was 2.97 folds in CHM group. The mean size of M. flos-aquae colony in control (34.65 µm) group were significantly bigger than that in the CHM (26.78 µm) group. This research results demonstrated that continuous hydrodynamic mixing weakened the dominance of Microcystis, but was beneficial for the others algae (S. quadricauda and P. limnetica) and is helpful in understanding the effect of hydrodynamic mixing on Microcystis blooms in freshwater ecosystem.

The prospects for targeting FcR as a novel therapeutic strategy in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by synovial membrane hyperplasia, infiltration of inflammatory cells and bone tissue destruction. Although there have been many measures taken for RA therapy in recent years, they are not sufficiently safe or effective. Thus, it is very important to develop new drugs and slow down damage to other healthy organs in the case of RA. Lately, immunoglobulin Fc receptors (FcRs), such as the IgG Fc receptor (FcγR), IgA Fc receptor (FcαR), and IgD Fc receptor (FcδR), have been found to be involved in inducing or suppressing arthritis. FcRs interacting with immune complexes (ICs) are a key factor in the etiopathogenesis of RA. Therefore, an increasing number of methodsfor the targeted treatment of RA with FcRs are emerging, such as recombinant soluble FcγRs, recombinant multimeric Fc fragments and monoclonal antibodies, and have been demonstrated to significantly improve RA symptoms. Simultaneously, certain kinases involved in the downstream signaling of FcRs can also be a target for the treatment of RA, such as Syk and Btk inhibitors. An overview of these FcRs is provided in this review, including a description of FcR-related functions, signaling pathways, and potential FcR-targeting molecules for RA therapy. To date, the initial results of those developed FcR-targeting molecules have been promising. With this, FcRs might offer a better alternative to RA medication. Additionally, further pharmacological characterization and a better understanding of the unique mechanisms of FcR-targeting molecules are necessary.

Impact of light quality on freshwater phytoplankton community in outdoor mesocosms.

In shallow lakes, wind wave turbulence alters underwater spectral composition, but the influence of this phenomenon on phytoplankton community structure is poorly understood. We used 100L mesocosms to investigate the influence of light quality on a natural phytoplankton community collected from Taihu Lake in China. The communities in mesocosms were exposed to sunlight filtered for white, blue, green, and red light, while wave-making pumps simulated wind wave turbulence similar to Taihu Lake. Over the course of experiment, each filtered light reduced the total phytoplankton abundance compared to white light. The mean abundance of phytoplankton in controls was 1.72, 1.78, and 7.89 times of that in the red, blue, and green light treatments. Red, blue, and green light significantly promoted the growth of cyanobacteria, green algae, and diatoms, respectively, and induced successional change of the phytoplankton species under the tested conditions. The proportion of Microcystis to total phytoplankton abundance in controls and red light shifted from 87.09% at the beginning to 37.95% and 56.30% at the end of the experiment, respectively, and maintained its dominance, whereas Microcystis lost its dominance and was replaced by Scenedesmus (53.78%) and Synedra (53.18%) in the blue and green light, respectively. Given the process of how these phytoplankton compete in designated spectrum, exploring these influences could help provide new insights into the dominance formation of toxic cyanobacteria.

In situ monitoring of grape seed protein hydrolysis by Raman spectroscopy.

Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC50 of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval partial least squares (IPLS), and joint interval partial least squares (Si-PLS) models of DH, IC50 , and peptide content were established and the optimal pretreatment method was selected. In the optimal model, the corrected model r of the grape seed protein hydrolysis degree is 0.997, the Root Mean Square Error of Cross Validation (RMSECV) is 0.507%. The predicted model r value is 0.9932, the Root Mean Square Error of Prediction (RMSEP) is 1.15%. The corrected model r value of the IC50 is 0.9965, the RMSECV is 11.9%. The r value and RMSEP of predicted model are 0.9978 and 9.64%. The corrected model r value of the peptide content is 0.9955, the RMSECV is 12.7%, the predicted model r value is 0.9953, and the RMSEP is 15.4%. These results showed that in situ real-time monitoring of grape seed protein hydrolysis process can be achieved by Raman spectroscopy. PRACTICAL APPLICATIONS: This study uses Raman spectroscopy method to establish the quantification of proteolysis, IC50, and peptide content of the simulated digestive products during grape seed proteolysis. Analyze the model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. In situ real-time monitoring of grape seed proteolysis is of great significance to the entire grape seed active peptide industry.

Intermittent disturbance benefits colony size, biomass and dominance of Microcystis in Lake Taihu under field simulation condition.

Wind-driven wave disturbance is one of the environmental factors that shapes the formation of Microcystis blooms. Here we present data on the effect of different disturbance modes (continuous vs intermittent disturbances) on colony size, biomass and dominance of Microcystis in Lake Taihu under field conditions. Small submersible pumps were used to simulate different disturbance modes at turbulent dissipation rate (ε) of 2.98 × 10-6 m2 s-3. Our results show that the mean colony sizes of Microcystis in intermittent and continuous disturbance group were 1.94 and 1.23 times that of the control group, respectively. The mean densities of Microcystis in intermittent and continuous disturbance group were 4.23 and 2.91 times that of the control group, respectively. The mean proportion of Microcystis to total algae abundance in control group and continuous disturbance group changed from 78.3% at beginning of the experiment to 4.5% and 9.1% at the end of the experiment. However, the proportion of Microcystis to total algae cells in intermittent disturbance group was 65.7-94.3% during the whole experiment. The results demonstrated intermittent disturbances favored colony morphology, biomass and dominance of Microcystis. Our results suggested that intermittent disturbance benefited the formation of Microcystis bloom and was important in the development of predictive models for toxic cyanobacterial blooms under changing climates in shallow lakes.

Cu-Catalyzed atom transfer radical addition reactions of alkenes with α-bromoacetonitrile.

A practical, simple, and efficient copper-catalyzed atom transfer radical addition reaction of alkenes with α-bromoacetonitrile is realized. With this methodology, various γ-bromonitriles and ß,γ-unsaturated nitriles were efficiently constructed.