Buurhenry6648

Research Highlight Norton, A. M., Remnant, E. J., Tom, J., Buchmann, G., Blacquiere, T., & Beekman, M. (2021). Adaptation to vector-based transmission in a honeybee virus. Journal of Animal Ecology, 90, https//besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2656.13493. In their paper on the adaptation to vector-based transmission via the mite Varroa destructor in a honeybee virus, Norton et al. study how high versus low levels of a viral vector affect viral load and potential competition between two strains of Deformed Wing Virus, an important highly virulent bee virus with the potential to spill-over into other pollinators and bee-associated insect species. This paper addresses two very timely issues, on the one hand on viral evolutionary ecology in response to vector-borne transmission, and on the other hand providing much needed information on an important honey bee pathogen. Using a complex natural system, this study shows that vector-borne transmission, and the control of the vector, can select for complex host-pathogen-vector interactions and that adaptations to changing transmission landscapes in fast evolving pathogens can create conditions for emerging pathogens to transition to endemic diseases.Th2 and Th17 immune response contribute to allergic rhinitis (AR) development. ML351 mw Targeting Th2 and Th17 response has been shown to ameliorate AR. Ibrutinib is an inhibitor for IL2-inducible T-cell kinase, which can promote Th2 and Th17 immune response. We sought to investigate the effect of ibrutinib on AR and the underlying mechanisms. We established house dust mite-induced AR mouse model and treated AR mice with ibrutinib. The symptoms of AR, serum level of immunoglobulin E, percentage of Th1, Th2, Th17, and Treg in nasal lymphoid tissues were monitored. We also established in vitro T cell differentiation cell culture model. The T cells were treated with ibrutinib and the expression of specific transcriptional factors and cytokines was measured. The activation of PLC-γ1/calcium/NFAT2 signaling pathway was detected. Ibrutinib treatment had no effects on the development of lymphocytes and myeloid cells, but alleviated AR symptoms and decreased Th2 cell population in nasal lymphoid tissue. Meanwhile, iburitnib suppressed Th2 and Th17 differentiation in vitro. link2 Moreover, iburitnib prevented phosphorylation of PLC-γ1and nuclear translocation of NFAT2 in Th2 cells. link3 Our results suggested that ibrutinib could ameliorate AR symptoms through suppression of Th2 differentiation in AR mouse model.

To develop and test an optimized radiomics model based on multi-planar automated breast volume scan (ABVS) images to identify malignant and benign breast lesions.

Patients (n=200) with breast lesions who underwent ABVS examinations were included. For each patient, 208 radiomics features were extracted from the ABVS images, including axial plane and coronal plane. Recursive feature elimination, random forest, and chi-square test were used to select features. A support vector machine, logistic regression, and extreme gradient boosting were utilized as classifiers to differentiate malignant and benign breast lesions. The area under the curve, sensitivity, specificity, accuracy, and precision was used to evaluate the performance of the radiomics models. Generalization of the radiomics models was verified through 5-fold cross-validation.

For a single plane or a combination of planes, a combination of recursive feature elimination, and support vector machine yielded the best performance when identifying breast lesions. The machine learning models based on a combination of planes performed better than those based on a single plane. Regarding the axial plane and coronal plane, the machine learning model using a combination of recursive feature elimination and support vector machine yielded the optimal identification performance average area under the curve (0.857 ± 0.058, 95% confidence interval, 0.763-0.957); the average values of sensitivity, specificity, accuracy, and precision were 87.9, 68.2, 80.7, and 82.9%, respectively.

The optimized radiomics model based on ABVS images can provide valuable information for identifying benign and malignant breast lesions preoperatively and guide the accurate clinical treatment. Further external validation is required.

The optimized radiomics model based on ABVS images can provide valuable information for identifying benign and malignant breast lesions preoperatively and guide the accurate clinical treatment. Further external validation is required.

Proton pencil beam energy spectrum is an essential parameter for calculations of dose and linear energy transfer. We extract the energy spectrum from measured integral depth dose (IDD).

A measured IDD (measIDD) in water is decomposed into many IDDs of mono-energetic pencil beams (monoIDDs) in water. A simultaneous iterative technique is used to do the decomposition that extracts the energy spectrum of protons from the measIDD. The monoIDDs are generated by our analytic random walk model-based proton dose calculation algorithm. The linear independence of the monoIDDs is considered and high spatial resolution monoIDDs are used to improve their linear independence. To validate the extraction, first we use synthesized IDDs (synIDD) with Gaussian energy spectrum and compare the extracted energy spectrum with the Gaussian; second, for the energy spectrum extracted from measIDDs, the accuracy of the extraction is validated by comparing the calculated IDD from the energy spectrum with the measIDD. The measIDDs arese three examples, and the relative differences of the resultant calculated IDDs from the measIDDs were within 4.7%, 7.4%, and 4.5%, respectively.

Our algorithm accurately extracted the energy spectrum from the synIDDs and measIDDs. High-resolution monoIDDs are necessary to extract low-energy spectrum. Energy spectrum extraction from measIDD reveals important information for beam modeling.

Our algorithm accurately extracted the energy spectrum from the synIDDs and measIDDs. High-resolution monoIDDs are necessary to extract low-energy spectrum. Energy spectrum extraction from measIDD reveals important information for beam modeling.Pyrazole derivatives correspond to a family of heterocycle molecules with important pharmacological and physiological applications. At present, we perform a density functional theory (DFT) calculations and a quantitative structure-activity relationship (QSAR) evaluation on a series of 1-(4,5-dihydro-1H-pyrazol-1-yl) ethan-1-one and 4,5-dihydro-1H-pyrazole-1-carbothioamide derivatives as an epidermal growth factor receptor (EGFR) inhibitory activity. We thus propose a virtual screening protocol based on a machine-learning study. This theoretical model relates the studied compounds' biological activity to their calculated physicochemical descriptors. Moreover, the linear regression function is used to validate the model via the evaluation of Q2 ext and Q2 cv parameters for external and internal validations, respectively. Our QSAR model shows a good correlation between observed activities IC50 and predicted ones. Our model allows us to mitigate time-consuming problems and waste chemical and biological products in the preclinical phases.The plant hormone ethylene plays vital roles in plant development, including pollen tube (PT) growth. Many studies have used the ethylene precursor, 1-aminocyclopropane-1-carboxylic acid (ACC), as a tool to trigger ethylene signaling. Several studies have suggested that ACC can act as a signal molecule independently of ethylene, inducing responses that are distinct from those induced by ethylene. In this study, we confirmed that ethylene receptor function is essential for promoting PT growth in tomato, but interestingly, we discovered that ACC itself can act as a signal that also promotes PT growth. Exogenous ACC stimulated PT growth even when ethylene perception was inhibited either chemically by treating with 1-methylcyclopropene (1-MCP) or genetically by using the ethylene-insensitive Never Ripe (NR) mutant. Treatment with aminoethoxyvinylglycine, which reduces endogenous ACC levels, led to a reduction of PT growth, even in the NR mutants. Furthermore, GUS activity driven by an EIN3 Binding Site promoter (EBSGUS transgene) was triggered by ACC in the presence of 1-MCP. Taken together, these results suggest that ACC signaling can bypass the ethylene receptor step to stimulate PT growth and EBS driven gene expression.

The delineation of organs at risk (OARs) is fundamental to cone-beam CT (CBCT)-based adaptive radiotherapy treatment planning, but is time consuming, labor intensive, and subject to interoperator variability. We investigated a deep learning-based rapid multiorgan delineation method for use in CBCT-guided adaptive pancreatic radiotherapy.

To improve the accuracy of OAR delineation, two innovative solutions have been proposed in this study. First, instead of directly segmenting organs on CBCT images, a pretrained cycle-consistent generative adversarial network (cycleGAN) was applied to generating synthetic CT images given CBCT images. Second, an advanced deep learning model called mask-scoring regional convolutional neural network (MS R-CNN) was applied on those synthetic CT to detect the positions and shapes of multiple organs simultaneously for final segmentation. The OAR contours delineated by the proposed method were validated and compared with expert-drawn contours for geometric agreement using the Dica synthetic CT-aided deep learning framework for automated delineation of multiple OARs on CBCT. The proposed method could be implemented in the setting of pancreatic adaptive radiotherapy to rapidly contour OARs with high accuracy.

To derive the isodose line R relative to the prescription dose below which irradiated normal tissue (NT) regions benefit from a hypofractionated schedule with an isoeffective dose to the tumor. To apply the formalism to clinical case examples.

From the standard biologically effective dose (BED) equation based on the linear-quadratic (LQ) model, the BED of an NT that receives a relative proportion r of the prescribed dose per fraction for a given α/β-ratio of the tumor, (α/β)

, and NT, (α/β)

, is derived for different treatment schedules while keeping the BED to the tumor constant. Based on this, the "break-even" isodose line R is then derived. The BED of NT regions that receive doses below R decreases for more hypofractionated treatment schedules, and hence a lower risk for NT injury is predicted in these regions. To assess the impact of a linear behavior of BED for high doses per fraction (>6Gy), we evaluated BED also using the LQ-linear (LQ-L) model.

The formalism provides the equations to derirent relative dose levels compared to a reference schedule in a compact manner.

The formalism may be used to estimate below which relative isodose line R there will be a differential sparing of NT when increasing hypofractionation. More generally, it allows to assess changes of the therapeutic index for sets of isoeffective treatment schedules at different relative dose levels compared to a reference schedule in a compact manner.Five novel permanent cell lines have been established from gill, heart, kidney, eye and fin of snubnose pompano, Trachinotus blochii. They were designated as snubnose pompano gill (SPG), snubnose pompano heart (SPH), snubnose pompano kidney (SPK), snubnose pompano eye (SPE) and snubnose pompano fin (SPF), respectively. All these cell lines were characterized and cryopreserved successfully at different passage levels. Cell lines were passaged every alternate day; SPG, SPH, SPK, SPE and SPF cell lines attained passage levels of 68, 74, 82, 79 and 106, respectively, since the initiation of their development in 2019. The cell lines grew well in Leibovitz's 15 medium containing 15% foetal bovine serum at 28°C. Immunophenotyping of the cell lines revealed the presence of fibronectin and pancytokeratin. No mycoplasma contamination was found. The transfection study revealed the gene expression efficiency of these cell lines by expressing the green fluorescent protein (GFP). The authentication on origin of cell lines from T.