Quantitative annotations of T-Cell repertoire specificity.

The specificity of a T-cell receptor (TCR) repertoire determines personalized immune capacity. Existing methods have modeled the qualitative aspects of TCR specificity, while the quantitative aspects remained unaddressed. We developed a package, TCRanno, to quantify the specificity of TCR repertoires. We created deep-learning-based, epitope-aware vector embeddings to infer individual TCR specificity. Then we aggregated clonotype frequencies of TCRs to obtain a quantitative profile of repertoire specificity at epitope, antigen and organism levels. Applying TCRanno to 4195 TCR repertoires revealed quantitative changes in repertoire specificity upon infections, autoimmunity and cancers. Specifically, TCRanno found cytomegalovirus-specific TCRs in seronegative healthy individuals, supporting the possibility of abortive infections. TCRanno discovered age-accumulated fraction of severe acute respiratory syndrome coronavirus 2 specific TCRs in pre-pandemic samples, which may explain the aggressive symptoms and age-related severity of coronavirus disease 2019. TCRanno also identified the encounter of Hepatitis B antigens as a potential trigger of systemic lupus erythematosus. TCRanno annotations showed capability in distinguishing TCR repertoires of healthy and cancers including melanoma, lung and breast cancers. TCRanno also demonstrated usefulness to single-cell TCRseq+gene expression data analyses by isolating T-cells with the specificity of interest.

Leveraging conformal prediction to annotate enzyme function space with limited false positives.

Machine learning (ML) is increasingly being used to guide biological discovery in biomedicine such as prioritizing promising small molecules in drug discovery. In those applications, ML models are used to predict the properties of biological systems, and researchers use these predictions to prioritize candidates as new biological hypotheses for downstream experimental validations. However, when applied to unseen situations, these models can be overconfident and produce a large number of false positives. One solution to address this issue is to quantify the model's prediction uncertainty and provide a set of hypotheses with a controlled false discovery rate (FDR) pre-specified by researchers. We propose CPEC, an ML framework for FDR-controlled biological discovery. We demonstrate its effectiveness using enzyme function annotation as a case study, simulating the discovery process of identifying the functions of less-characterized enzymes. CPEC integrates a deep learning model with a statistical tool known as conformal prediction, providing accurate and FDR-controlled function predictions for a given protein enzyme. Conformal prediction provides rigorous statistical guarantees to the predictive model and ensures that the expected FDR will not exceed a user-specified level with high probability. Evaluation experiments show that CPEC achieves reliable FDR control, better or comparable prediction performance at a lower FDR than existing methods, and accurate predictions for enzymes under-represented in the training data. We expect CPEC to be a useful tool for biological discovery applications where a high yield rate in validation experiments is desired but the experimental budget is limited.

Virus-Inspired Glucose and Polydopamine (GPDA)-Coating as an Effective Strategy for the Construction of Brain Delivery Platforms.

The ability of drugs to cross the blood-brain barrier (BBB) is crucial for treating central nervous system (CNS) disorders. Inspired by natural viruses, here we report a glucose and polydopamine (GPDA) coating method for the construction of delivery platforms for efficient BBB crossing. Such platforms are composed of nanoparticles (NPs) as the inner core and surface functionalized with glucose-poly(ethylene glycol) (Glu-PEG) and polydopamine (PDA) coating. Glu-PEG provides selective targeting of the NPs to brain capillary endothelial cells (BCECs), while PDA enhances the transcytosis of the NPs. This strategy is applicable to gold NPs (AuNPs), silica, and polymeric NPs, which achieves as high as 1.87% of the injected dose/g of brain in healthy brain tissues. In addition, the GPDA coating manages to deliver NPs into the tumor tissue in the orthotopic glioblastoma model. Our study may provide a universal strategy for the construction of delivery platforms for efficient BBB crossing and brain drug delivery.

Experimental Observation of the Fully Ferroelectric-Fully Ferroelastic Effect in Multiferroic Hybrid Perovskites.

Since the concept of "multiferroic" was first proposed in 1968, the coupling effect between different ferroic orders has attracted great interest in energy, information, and biomedical fields. However, the fully ferroelectric-fully ferroelastic effect has never been experimentally observed in hybrid perovskites, even though this effect was predicted to exist half a century ago. Realizing such cross-linking effects of polarization vectors and strain tensors has always been a huge challenge because of the complex difference in these two ferroic origins. Here, we report a multiferroic with full ferroelectricity and full ferroelasticity in two-dimensional (2D) hybrid perovskites based on ferroelectrochemistry. The dynamic molecular reorientations endow (cyclohexanemethylaminium)2PbCl4 with a desired symmetry change of 4̅2mFmm2 at a Curie temperature of 411.8 K. More strikingly, the switchable evolution of ferroelastic domains was directly observed under the control of either electric or mechanical fields, which is the first experimental observation of a fully ferroelectric-fully ferroelastic effect in hybrid perovskites. This work would provide new insights into understanding the intrinsic cross-linking mechanism between ferroelectricity and ferroelasticity toward the development of multichannel interactive microelectronic devices.

Metal-Free Perovskite Ferroelectrics with the Most Equivalent Polarization Axes.

Ferroelectricity in metal-free perovskites (MFPs) has emerged as an academic hotspot for their lightweight, eco-friendly processability, flexibility, and degradability, with considerable progress including large spontaneous polarization, high Curie temperature, large piezoelectric response, and tailoring coercive field. However, their equivalent polarization axes as a key indicator are far from enough, although multiaxial ferroelectrics are highly preferred for performance output and application flexibility that profit from as many equivalent polarization directions as possible with easier reorientation. Here, by implementing the synergistic overlap of regulating anionic geometries (from spherical I- to octahedral [PF6]- and to tetrahedral [ClO4]- or [BF4]-) and cationic asymmetric modification, we successfully designed multiaxial MFP ferroelectrics CMDABCO-NH4-X3 (CMDABCO = N-chloromethyl-N'-diazabicyclo[2.2.2]octonium; X = [ClO4]- or [BF4]-) with the lowest P1 symmetry. More impressively, systemic characterizations indicate that they possess 24 equivalent polarization axes (Aizu notations of 432F1 and m3̅mF1, respectively)─the maximum number achievable for ferroelectrics. Benefiting from the multiaxial feature, CMDABCO-NH4-[ClO4]3 has been demonstrated to have excellent piezoelectric sensing performance in its polycrystalline sample and prepared composite device. Our study provides a feasible strategy for designing multiaxial MFP ferroelectrics and highlights their great promise for use in microelectromechanical, sensing, and body-compatible devices.

Organic-Inorganic Rare-Earth Double Perovskite Ferroelectric with Large Piezoelectric Response and Ferroelasticity for Flexible Composite Energy Harvesters.

Hybrid organic-inorganic perovskite (HOIP) ferroelectric materials have great potential for developing self-powered electronic transducers owing to their impressive piezoelectric performance, structural tunability and low processing temperatures. Nevertheless, their inherent brittle and low elastic moduli limit their application in electromechanical conversion. Integration of HOIP ferroelectrics and soft polymers is a promising solution. In this work, a hybrid organic-inorganic rare-earth double perovskite ferroelectric, [RM3HQ]2RbPr(NO3)6 (RM3HQ = (R)-N-methyl-3-hydroxylquinuclidinium) is presented, which possesses multiaxial nature, ferroelasticity and satisfactory piezoelectric properties, including piezoelectric charge coefficient (d33) of 102.3 pC N-1 and piezoelectric voltage coefficient (g33) of 680 × 10-3 V m N-1. The piezoelectric generators (PEG) based on composite films of [RM3HQ]2RbPr(NO3)6@polyurethane (PU) can generate an open-circuit voltage (Voc) of 30 V and short-circuit current (Isc) of 18 µA, representing one of the state-of-the-art PEGs to date. This work has promoted the exploration of new HOIP ferroelectrics and their development of applications in electromechanical conversion devices.

White Matter Hyperintensity is Associated with Malignant Cerebral Edema in Ischemic Stroke Treated with Thrombectomy.

BACKGROUND: White matter hyperintensity (WMH) burden may lead to poor clinical outcomes after endovascular thrombectomy (EVT). But the relationship between WMH burden and cerebral edema (CED) is unclear. PURPOSE: To examine the association between WMH burden and CED and functional outcome in patients treated with EVT. STUDY TYPE: Retrospective. SUBJECT: 344 patients with acute anterior circulation large-vessel occlusion stroke who received EVT at two comprehensive stroke centers. Mean age was 62.6 ± 11.6 years and 100 patients (29.1%) were female. FIELD STRENGTH/SEQUENCE: 3T, including diffusion-weighted imaging and fluid-attenuated inversion recovery (FLAIR) images. ASSESSMENT: The severity of WMH was evaluated using the Fazekas scale on a FLAIR sequence before EVT. The severity of CED was assessed using CED score (three for malignant cerebral edema [MCE]) and net water uptake (NWU)/time on post-EVT cranial CT. The impact of WMH burden on MCE, NWU/time, and 3-month poor outcome (modified Rankin scale >2) after EVT were assessed. STATISTICAL TESTS: Pearson's chi-squared test, Fisher exact test, 2-tailed t test, Mann-Whitney U test, multivariable logistic regression, multivariate regression analysis, Sobel test. A P value <0.05 was considered statistically significant. RESULTS: WMH burden was not significantly associated with MCE and parenchymal hemorrhage (PH) in the whole population (P = 0.072; P = 0.714). WMH burden was significantly associated with an increased risk of MCE (OR, 1.550; 95% CI, 1.128-2.129), higher NWU/time (Coefficient, 0.132; 95% CI, 0.012-0.240), and increased risk of 3-month poor outcome (OR, 1.434; 95% CI, 1.110-1.853) in the subset of patients without PH. Moreover, the connection between WMH burden and poor outcome was partly mediated by CED in patients without PH (regression coefficient changed by 29.8%). DATA CONCLUSION: WMH burden is associated with CED, especially MCE, and poor outcome in acute ischemic stroke patients treated with EVT. The association between WMH burden and poor outcome may partly be attributed to postoperative CED. TECHNICAL EFFICACY: Stage 5.

Comparative study of optical coherence tomograph and histological images of eustachian tube nasopharyngeal region and adjacent structures in vivo and ex-vivo miniature pigs.

OBJECTIVES: Optical Coherence Tomograph (OCT) imaging technology can be used to examine, in vivo, the human ET. At present, it is impossible to achieve the OCT scanning vivo and ex vivo in the same individual human body, or study the consistency between OCT images and histological images of the eustachian tube nasopharyngeal region and adjacent structures. The aim of this study was to determine the consistency between OCT images and histological sections in vivo and ex vivo in miniature pigs. METHODS: OCT imaging was performed on five adult miniature pigs in vivo and ex vivo. The images of the eustachian tube OCT (ET-OCT), nasopharynx OCT (NP-OCT) and histological cross sections were further studied. RESULTS: All five miniature pigs achieved the OCT scan successfully, acquiring ET-OCT and NP-OCT images in vivo and ex vivo on both sides. The acquired ET OCT images closely matched the histological images, revealing details of the cartilage, submucosa, glands, and mucosa. The lower segment of the ET wall mucosa had an abundance of glands and submucosal tissues, with more low-signal areas appearing in the ex vivo images. The NP-OCT images of the nasopharynx matched the details of the mucosa and submucosal tissues. The ex-vivo OCT images showed thicker mucosa and more scattered slightly lower signal areas compared to the vivo OCT images. CONCLUSIONS: ET-OCT images and NP-OCT images matched the histological structure of eustachian tube nasopharyngeal region structures in miniature pigs both in vivo and ex vivo. OCT images may be sensitive to changes in edema and ischemia status. There is a great potential for morphological assessment of inflammation, edema, injure, mucus gland status.

Y-Net: Identification of Typical Diseases of Corn Leaves Using a 3D-2D Hybrid CNN Model Combined with a Hyperspectral Image Band Selection Module.

Corn diseases are one of the significant constraints to high-quality corn production, and accurate identification of corn diseases is of great importance for precise disease control. Corn anthracnose and brown spot are typical diseases of corn, and the early symptoms of the two diseases are similar, which can be easily misidentified by the naked eye. In this paper, to address the above problems, a three-dimensional-two-dimensional (3D-2D) hybrid convolutional neural network (CNN) model combining a band selection module is proposed based on hyperspectral image data, which combines band selection, attention mechanism, spatial-spectral feature extraction, and classification into a unified optimization process. The model first inputs hyperspectral images to both the band selection module and the attention mechanism module and then sums the outputs of the two modules as inputs to a 3D-2D hybrid CNN, resulting in a Y-shaped architecture named Y-Net. The results show that the spectral bands selected by the band selection module of Y-Net achieve more reliable classification performance than traditional feature selection methods. Y-Net obtained the best classification accuracy compared to support vector machines, one-dimensional (1D) CNNs, and two-dimensional (2D) CNNs. After the network pruned the trained Y-Net, the model size was reduced to one-third of the original size, and the accuracy rate reached 98.34%. The study results can provide new ideas and references for disease identification of corn and other crops.

[Qirong Tablets inhibits apoptosis of ovarian granulosa cells via PI3K/Akt/ HIF-1 signaling pathway].

This study aims to observe the effect and explore the mechanism of Qirong Tablets in the treatment of premature ovarian insufficiency(POI) in mice via the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/hypoxia inducible factor 1(HIF-1) signaling pathway. Sixty SPF female BALB/c mice were randomly divided into normal group, model group, positive control group, Qirong Tablets low-, medium-and high-dose group. The normal group was intraperitoneally injected with the same amount of normal saline, and the other groups were intraperitoneally injected with cyclophosphamide 120 mg·kg~(-1)·d~(-1) once to establish a POI animal model. After the model was successfully established, the low-, medium-and high-dose groups of Qirong Tablets were administered orally with 0.6, 1.2, 2.4 mg·kg~(-1)·d~(-1) respectively. The positive control group was given 0.22 mg·kg~(-1)·d~(-1) Clementine Tablets by intragastric administration, and the normal group and model group were given intragastric administration with the same amount of normal saline, and the treatment was 28 d as a course of treatment. After drug intervention, enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of estradiol(E_2), follicle-stimulating hormone(FSH), luteinizing hormone(LH), and anti-mullerian hormone(AMH) in peripheral blood, and hematoxylin-eosin(HE) staining to observe the ovarian tissue. Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling(TUNEL) assay was used to detect the apoptosis of granulosa cells, and Western blot to determine the expression levels of B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), caspase-3, PI3K, Akt, and HIF-1. Compared with the normal group, the modeling of POI caused loose or destroyed ovarian tissue with vacuolar structures, edema and fibrosis in the ovarian interstitium, disordered or loose arrangement of granulosa cells, and reduced normal follicles. Compared with the model group, drug interventions restored the ovarian tissue and follicles at all the development stages and reduced atretic follicles. Compared with the normal group, the modeling of POI lowered the serum level of E_2 and AMH(P<0.01), and elevated the level of FSH and LH(P<0.01). Compared with the model group, high-dose Qirong Tablets elevated the levels of E_2 and AMH(P<0.05), and lowered the levels of FSH and LH(P<0.05). Compared with the normal group, the modeling of POI up-regulated the protein levels of PI3K, Akt, HIF-1, Bax, and caspase-3 and down-regulated the protein level of Bcl-2 in the ovarian tissue(P<0.01). Compared with the model group, low-, medium-, and high-dose Qirong Tablets down-regulated the protein levels of PI3K, Akt, HIF-1, Bax, and caspase-3 proteins and up-regulated the protein level of Bcl-2 in the ovarian tissue(P<0.05). In conclusion, Qirong Tablets can up-regulate the expression Bcl-2, down-regulate the expression of Bax and caspase-3 in POI mice. Qirong Tablets may inhibit the apoptosis of follicular granulosa cells in mice, thereby delaying ovarian aging, improving reproductive axis function, and strengthening ovarian reserve capacity, which may be associated with the inhibition of PI3K/Akt/HIF-1 pathway.

Role of Ezrin in Asthma-Related Airway Inflammation and Remodeling.

Ezrin is an actin binding protein connecting the cell membrane and the cytoskeleton, which is crucial to maintaining cell morphology, intercellular adhesion, and cytoskeleton remodeling. Asthma involves dysfunction of inflammatory cells, cytokines, and airway structural cells. Recent studies have shown that ezrin, whose function is affected by extensive phosphorylation and protein interactions, is closely associated with asthma, may be a therapeutic target for asthma treatment. In this review, we summarize studies on ezrin and discuss its role in asthma-related airway inflammation and remodeling.

Low trifloxystrobin-tebuconazole concentrations induce cardiac and developmental toxicity in zebrafish by regulating notch mediated-oxidative stress generation.

Trifloxystrobin-tebuconazole (TFS-TBZ) is a novel, broad-spectrum fungicide that has been frequently detected in both the environment and agricultural products. However, its adverse effects on aquatic organisms remain unknown. In this study, the adverse effects of ecologically relevant TFS-TBZ concentrations (i.e., 75.0, 112.5, and 150.0 µg/L) on the heart and development of zebrafish were investigated. TFS-TBZ was found to substantially hinder development, inhibit growth, and cause significant abnormity at higher concentrations. Moreover, TFS-TBZ caused severe pericardial edema, heart loop failure, cardiac linearization, and ultra-slow heartbeat, implying that TFS-TBZ might induce congenital heart disease. TFS-TBZ inhibited Notch signaling and increased the intracellular generation of reactive oxygen species, resulting in decreased myocardial cell proliferation and increased apoptosis. The use of sodium valproate and Gadofullerene illustrated the relevance of the Notch signaling system and oxidative stress. Finally, TFS-TBZ exposure conveys severe developmental toxicity to the zebrafish heart. The underlying mechanism is regulation notch mediated-oxidative stress generation, implying that TFS-TBZ may be potentially hazardous to aquatic organisms in the environment.

What is optimal timing of warming for transferring vitrified cleavage stage of day 3 slow-growing embryos? A cohort retrospective study.

PURPOSE: To evaluate optimal warming time, the early warming or the routine warming time, for transferring vitrified-warmed and cultured overnight cleavage stage of the slow-growing embryos on day 3 in frozen embryo transfer (FET) cycle. METHODS: This was a retrospective cohort study from January 2017 to July 2018. A total of 705 FET patients aged < 40 years were included and 1486 embryos were formed, of which 1366 embryos were eventually transferred. RESULTS: For slow-growing embryos, the clinical pregnancy rate of early warming group [152/468 (32.5%)] was significantly higher than that of routine warming group (55/235 (23.4%)) [OR 1.39 (CI 1.06-1.81), p = 0.01], while there was no statistically significant difference in pregnancy loss in early warming group [39/170 (22.9%)] versus in routine warming group [16/62 (25.8%)] [OR 0.89 (CI 0.53-1.47), p = 0.65]. CONCLUSION: For slow-growing embryos, higher pregnancy outcomes were shown in early warming strategy as compared to the routine warming, which suggested that the improvement of endometrium-embryo synchronism may correct the time difference brought by the slow-growing embryos.

Laser-assisted hatching zona thinning does not improve the pregnancy outcomes of poor-quality blastocysts in frozen-thawed embryo transfer cycle: a retrospective cohort study.

It had been suggested, after facilitating the hatching process, improved pregnancy outcomes could be attained in embryos with thick and hard zona. This study aimed to determine the effect of zona thinning on pregnancy outcomes in poor-quality frozen-thawed blastocysts. This retrospective study included 230 women (≤ 40 years) who underwent frozen embryo transfer of poor-quality blastocysts (scored < 3BB). In total, 105 patients were in the assisted hatching group in which the zona was thinned by laser before transfer and 125 patients were in the control group in which the blastocysts were non-manipulated. Patients' demographics, cycle characteristics, and pregnancy outcomes were compared between the assisted hatching group and the control group. Further, regression analysis was applied to test the correlation between assisted hatching and live birth. All parameters in the patients' demographic characteristics and the cycle's characteristics were not significantly different between two groups. As for pregnancy outcomes, the second trimester pregnancy loss was significantly higher in the assisted hatching group (P = 0.035). Other pregnancy outcomes, including implantation rate, clinical pregnancy rate, biochemical miscarriage rate, the first trimester pregnancy loss, ongoing pregnancy rate, and live birth rate were comparable between two groups. The logistic regression analysis demonstrated no association between live birth and assisted hatching (univariate, OR = 0.787, P > 0.05; multivariate, OR = 0.652, P > 0.05), and the area under the receiver operating characteristic curve of the regression model was almost 0.7. It suggested that zona thinning may not be supposed to perform on poor-quality, frozen-thawed blastocysts. The indications of assisted hatching were still needed to further investigate.

A comprehensive review of microorganism-derived cyclic peptides: Bioactive functions and food safety applications.

Cyclic peptides possess advanced structural characteristics of stability and play a vital role in medical treatment and agriculture. However, the biological functions of microorganism-derived cyclic peptides (MDCPs) and their applications in food industry were relatively absent. MDCPs are derived from extensive fermented food or soil. In this review, the synthesis approaches and structural characteristics are overviewed, while the interrelationship between bioactivities and functions is emphasized. This review summarizes the bioactivities of MDCPs from in vitro to in vivo, including antimicrobial activities, immune regulation, and antiviral cell activation. Their multiple functions as well as applications during food product processing, packaging, and storage are also comprehensively reviewed. Remarkably, some potential risks and cytotoxicity of MDCPs are also critically discussed. Moreover, future applications of MDCPs in the development of novel food additives and bioengineering materials are organized. Based on this review of native MDCPs, it is noteworthy that expected improvements of synthetic cyclic peptides in bioactive properties present potential valuable applications in future food, including artificial meat.

A Tumor-Penetrating Nanomedicine Improves the Chemoimmunotherapy of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with a low survival rate. The therapeutic effect of chemotherapy and immunotherapy for PDAC is disappointing due to the presence of dense tumor stroma and immunosuppressive cells in the tumor microenvironment (TME). Herein, a tumor-penetrating nanoparticle is reported to modulate the deep microenvironment of PDAC for improved chemoimmunotherapy. The tumor pH-sensitive polymer is synthesized by conjugating N,N-dipentylethyl moieties and monomethoxylpoly(ethylene glycol) onto PAMAM dendrimer, into whose cavity a hydrophobic gemcitabine (Gem) prodrug is accommodated. They self-assemble into nanoparticles (denoted as SPN@Pro-Gem) with the size around 120 nm at neutral pH, but switch into small particles (≈8 nm) at tumor site to facilitate deep delivery of Gem into the tumor parenchyma. In addition to killing cancer cells that resided deeply in the tumor tissue, SPN@Pro-Gem could modulate the TME by reducing the abundance of tumor-associated macrophages and myeloid-derived suppressor cells as well as upregulating the expression level of PD-L1 of tumor cells. This collectively facilitates the infiltration of cytotoxic T cells into the tumors and renders checkpoint inhibitors more effective in previously unresponsive PDAC models. This study reveals a promising strategy for improving the chemoimmunotherapy of pancreatic cancer.

A molecular insight into the dissociable regulation of associative learning and motivation by the synaptic protein neuroligin-1.

BACKGROUND: In a changing environment, a challenge for the brain is to flexibly guide adaptive behavior towards survival. Complex behavior and the underlying neural computations emerge from the structural components of the brain across many levels: circuits, cells, and ultimately the signaling complex of proteins at synapses. In line with this logic, dynamic modification of synaptic strength or synaptic plasticity is widely considered the cellular level implementation for adaptive behavior such as learning and memory. Predominantly expressed at excitatory synapses, the postsynaptic cell-adhesion molecule neuroligin-1 (Nlgn1) forms trans-synaptic complexes with presynaptic neurexins. Extensive evidence supports that Nlgn1 is essential for NMDA receptor transmission and long-term potentiation (LTP), both of which are putative synaptic mechanisms underlying learning and memory. Here, employing a comprehensive battery of touchscreen-based cognitive assays, we asked whether impaired NMDA receptor transmission and LTP in mice lacking Nlgn1 does in fact disrupt decision-making. To this end, we addressed two key decision problems: (i) the ability to learn and exploit the associative structure of the environment and (ii) balancing the trade-off between potential rewards and costs, or positive and negative utilities of available actions. RESULTS: We found that the capacity to acquire complex associative structures and adjust learned associations was intact. However, loss of Nlgn1 alters motivation leading to a reduced willingness to overcome effort cost for reward and an increased willingness to exert effort to escape an aversive situation. We suggest Nlgn1 may be important for balancing the weighting on positive and negative utilities in reward-cost trade-off. CONCLUSIONS: Our findings update canonical views of this key synaptic molecule in behavior and suggest Nlgn1 may be essential for regulating distinct cognitive processes underlying action selection. Our data demonstrate that learning and motivational computations can be dissociated within the same animal model, from a detailed behavioral dissection. Further, these results highlight the complexities in mapping synaptic mechanisms to their behavioral consequences, and the future challenge to elucidate how complex behavior emerges through different levels of neural hardware.

Application Progress of Deinococcus radiodurans in Biological Treatment of Radioactive Uranium-Containing Wastewater.

Radioactive uranium wastewater contains a large amount of radionuclide uranium and other heavy metal ions. The radioactive uranium wastewater discharged into the environment will not only pollute the natural environment, but also threat human health. Therefore, the treatment of radioactive uranium wastewater is a current research focus for many researchers. The treatment in radioactive uranium wastewater mainly includes physical, chemical and biological methods. At present, the using of biological treatment to treat uranium in radioactive uranium wastewater has been gradually shown its superiority and advantages. Deinococcus radiodurans is a famous microorganism with the most radiation resistant to ionizing radiation in the world, and can also resist various other extreme pressures. D. radiodurans can be directly used for the adsorption of uranium in radioactive waste water, and it can also transform other functional genes into D. radiodurans to construct genetically engineered bacteria, and then applied to the treatment of radioactive uranium containing wastewater. Radionuclides uranium in radioactive uranium-containing wastewater treated by D. radiodurans involves a lot of mechanisms. This article reviews currently the application of D. radiodurans that directly or construct genetically engineered bacteria in the treatment of radioactive uranium wastewater and discusses the mechanism of D. radiodurans in bioremediation of uranium. The application of constructing an engineered bacteria of D. radiodurans with powerful functions in uranium-containing wastewater is prospected.

Nanoparticle-Enabled Dual Modulation of Phagocytic Signals to Improve Macrophage-Mediated Cancer Immunotherapy.

Activation of the phagocytosis of macrophages to tumor cells is an attractive strategy for cancer immunotherapy, but the effectiveness is limited by the fact that many tumor cells express an increased level of anti-phagocytic signals (e.g., CD47 molecules) on their surface. To promote phagocytosis of macrophages, a pro-phagocytic nanoparticle (SNPACALR&aCD47 ) that concurrently carries CD47 antibody (aCD47) and a pro-phagocytic molecule calreticulin (CALR) is constructed to simultaneously modulate the phagocytic signals of macrophages. SNPACALR&aCD47 can achieve targeted delivery to tumor cells by specifically binding to the cell-surface CD47 and block the CD47-SIRPα pathway to inhibit the "don't eat me" signal. Tumor cell-targeted delivery increases the exposure of recombinant CALR on the cell surface and stimulates an "eat me" signal. Simultaneous modulation of the two signals enhances the phagocytosis of 4T1 tumor cells by macrophages, which leads to significantly improved anti-tumor efficacy in vivo. The findings demonstrate that the concurrent blockade of anti-phagocytic signals and activation of pro-phagocytic signals can be effective in macrophage-mediated cancer immunotherapy.

Assessing concordance among human, in silico predictions and functional assays on genetic variant classification.

MOTIVATION: A variety of in silico tools have been developed and frequently used to aid high-throughput rapid variant classification, but their performances vary, and their ability to classify variants of uncertain significance were not systemically assessed previously due to lack of validation data. This has been changed recently by advances of functional assays, where functional impact of genetic changes can be measured in single-nucleotide resolution using saturation genome editing (SGE) assay. RESULTS: We demonstrated the neural network model AIVAR (Artificial Intelligent VARiant classifier) was highly comparable to human experts on multiple verified datasets. Although highly accurate on known variants, AIVAR together with CADD and PhyloP showed non-significant concordance with SGE function scores. Moreover, our results indicated that neural network model trained from functional assay data may not produce accurate prediction on known variants. AVAILABILITY AND IMPLEMENTATION: All source code of AIVAR is deposited and freely available at https://github.com/TopGene/AIvar. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.