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Purpose: Current methods for patient‐specific voxel‐level dosimetry in radionuclide therapy suffer from a trade‐off between accuracy and computational efficiency. Monte Carlo (MC) radiation transport algorithms are considered the gold standard for voxel‐level dosimetry but can be computationally expensive, whereas faster dose voxel kernel (DVK) convolution can be suboptimal in the presence of tissue heterogeneities. Furthermore, the accuracies of both these methods are limited by the spatial resolution of the reconstructed emission image. To overcome these limitations, this paper considers a single deep convolutional neural network (CNN) with residual learning (named DblurDoseNet) that learns to produce dose‐rate maps while compensating for the limited resolution of SPECT images. Methods: We trained our CNN using MC‐generated dose‐rate maps that directly corresponded to the true activity maps in virtual patient phantoms. Residual learning was applied such that our CNN learned only the difference between the true dose‐rate map and DVK dose‐rate map with density scaling. Our CNN consists of a 3D depth feature extractor followed by a 2D U‐Net, where the input was 11 slices (3.3 cm) of a given Lu‐177 SPECT/CT image and density map, and the output was the dose‐rate map corresponding to the center slice. The CNN was trained with nine virtual patient phantoms and tested on five different phantoms plus 42 SPECT/CT scans of patients who underwent Lu‐177 DOTATATE therapy. Results: When testing on virtual patient phantoms, the lesion/organ mean dose‐rate error and the normalized root mean square error (NRMSE) relative to the ground truth of the CNN method was consistently lower than DVK and MC, when applied to SPECT images. Compared to DVK/MC, the average improvement for the CNN in mean dose‐rate error was 55%/53% and 66%/56%; and in NRMSE was 18%/17% and 10%/11% for lesion and kidney regions, respectively. Line profiles and dose–volume histograms demonstrated compensation for SPECT resolution effects in the CNN‐generated dose‐rate maps. The ensemble noise standard deviation, determined from multiple Poisson realizations, was improved by 21%/27% compared to DVK/MC. In patients, potential improvements from CNN dose‐rate maps compared to DVK/MC were illustrated qualitatively, due to the absence of ground truth. The trained residual CNN took about 30 s on a single GPU (Tesla V100) to generate a 512×$\; \times \;$512×$\; \times \;$130 dose‐rate map for a patient. Conclusion: The proposed residual CNN, trained using phantoms generated from patient images, has potential for real‐time patient‐specific dosimetry in clinical treatment planning due to its demonstrated improvement in accuracy, resolution, noise, and speed over the DVK/MC approaches. [ABSTRACT FROM AUTHOR]

Recently, a new type of Caenorhabditis elegans associative learning was reported, where nematodes learn to reach a target arm in an empty T‐maze, after they have successfully located reward (food) in the same side arm of a similar, baited, training maze. Here, we present a simplified mathematical model of C. elegans chemosensory and locomotive circuitry that replicates C. elegans navigation in a T‐maze and predicts the underlying mechanisms generating maze learning. Based on known neural circuitry, the model circuit responds to food‐released chemical cues by modulating motor neuron activity that drives simulated locomotion. We show that, through modulation of interneuron activity, such a circuit can mediate maze learning by acquiring a turning bias, even after a single training session. Simulated nematode maze navigation during training conditions in food‐baited mazes and during testing conditions in empty mazes is validated by comparing simulated behaviour with new experimental video data, extracted through the implementation of a custom‐made maze tracking algorithm. Our work provides a mathematical framework for investigating the neural mechanisms underlying this novel learning behaviour in C. elegans. Model results predict neuronal components involved in maze and spatial learning and identify target neurons and potential neural mechanisms for future experimental investigations into this learning behaviour. [ABSTRACT FROM AUTHOR]

S. aureus (SA) and P. aeruginosa (PA) contaminations in thermally hurt patients have controlled invasive illness producing humanity. Gold nanoparticles (AuNPs) engaged in behaviour have limits owed to their oxidative damage. Current examinations demonstrated the biosynthesis of highly biocompatible AuNPs from rich antioxidant of aqueous cutting of Aerva javanica (A. javanica). The cell viability of the biosynthesised AuNPs was examined by cancerous cell lines (MCF-7 and MDA-MB-231) and non-cancerous cell lines (HUVECs), which displayed the high biocompatibility in all the cell lines. We developed the encapsulation with chitosan hydrogels to the AuNPs for the burn wound infections created by the Sprague Dawley rats. Remarkable burn wound reduction in the chitosan hydrogels was found. The histological analysis also suggested the burn wound contracting without causing any damages. The outcomes indicated that AuNPs incorporate to the chitosan hydrogels are promising burn wound dressing resources for the treatment for wound healing. [ABSTRACT FROM AUTHOR]

FcγRIIB, the only inhibitory IgG Fc receptor, functions to suppress the hyper-activation of immune cells. Numerous studies have illustrated its inhibitory function through the ITIM motif in the cytoplasmic tail of FcγRIIB. However, later studies revealed that in addition to the ITIM, the transmembrane (TM) domain of FcγRIIB is also indispensable for its inhibitory function. Indeed, recent epidemiological studies revealed that a non-synonymous single nucleotide polymorphism (rs1050501) within the TM domain of FcγRIIB, responsible for the I232T substitution, is associated with the susceptibility to systemic lupus erythematosus (SLE). In this review, we will summarize these epidemiological and functional studies of FcγRIIB-I232T in the past few years, and will further discuss the mechanisms accounting for the functional loss of FcγRIIB-I232T. Our review will help the reader gain a deeper understanding of the importance of the TM domain in mediating the inhibitory function of FcγRIIB and may provide insights to a new therapeutic target for the associated diseases. [ABSTRACT FROM AUTHOR]

Embryonic develop-associated gene 1 (EDAG-1), a hematopoietic tissue-specific protein, is usually highly expressed in the placenta, fetal liver, bone marrow and leukemia cells, but the expression status in normal or solid tumor tissues is rarely reported. In this study, we found that EDAG-1 was up-regulated in thyroid carcinoma tissues and cells. Knockdown of EDAG-1 suppressed proliferation and enhanced cisplatin-induced apoptosis of thyroid carcinoma cells. We also demonstrated that knockdown of EDAG-1 inactivated the phosphatidylinositol-3 kinase (PI3K)/Akt signaling pathway in vitro and in vivo . Moreover, knockdown of EDAG-1 suppressed tumorigenesis of thyroid carcinoma in vivo . Taken together, these results suggest that EDAG-1 regulates the proliferation and apoptosis of thyroid carcinoma via the PI3K/Akt signaling pathway. [ABSTRACT FROM AUTHOR]

In the present study, we aimed to uncover the potential functions of circular RNA (circRNA) pleckstrin and Sec7 domain containing 3 (circ_PSD3) in papillary thyroid carcinoma (PTC) development. The abundance of circ_PSD3, PSD3 messenger RNA (mRNA), microRNA-637 (miR-637) and hemogen (HEMGN; EDAG-1) mRNA was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Flow cytometry was employed to measure cell cycle progression and cell apoptosis. Western blot assay was used to examine protein expression. The proliferation ability and motility of PTC cells were analyzed by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and transwell assays, respectively. The interaction between miR-637 and circ_PSD3 or HEMGN was tested by dual-luciferase reporter assay. Animal experiments were used to explore the role of circ_PSD3 in PTC progression in vivo. Circ_PSD3 was aberrantly up-regulated in PTC tumor tissues compared with adjacent normal tissues. Circ_PSD3 and HEMGN promoted the cell cycle progression, proliferation and metastasis and impeded the apoptosis of PTC cells. MiR-637 was a direct target of circ_PSD3, and miR-637 directly interacted with HEMGN mRNA in PTC cells. Circ_PSD3 silencing-induced effects in PTC cells were partly attenuated by the addition of anti-miR-637 or HEMGN overexpression plasmid. Circ_PSD3/miR-637/HEMGN regulated the activity of PI3K/Akt signal pathway in PTC cells. Circ_PSD3 silencing inhibited the tumor growth in vivo. Circ_PSD3 promoted the progression of PTC through regulating miR-637/HEMGN axis and activating PI3K/Akt signaling. Circ_PSD3/miR-637/HEMGN signaling axis might be a potential target for PTC therapy. [ABSTRACT FROM AUTHOR]