Search

The accreting millisecond X-ray pulsar IGR J17498−2921 went into X-ray outburst on 2023 April 13–15, for the first time since its discovery on 2011 August 11. Here, we report on the first follow-up NuSTAR observation of the source, performed on 2023 April 23, around 10 d after the peak of the outburst. The NuSTAR spectrum of the persistent emission (3–60 keV band) is well described by an absorbed blackbody with a temperature of |$kT_{\mathrm{ bb}}=1.61\pm 0.04$|  keV, most likely arising from the NS surface and a Comptonization component with power-law index |$\Gamma =1.79\pm 0.02$|⁠ , arising from a hot corona at |$kT_{e}=16\pm 2$| keV. The X-ray spectrum of the source shows robust reflection features which have not been observed before. We use a couple of self-consistent reflection models, relxill and relxillCp , to fit the reflection features. We find an upper limit to the inner disc radius of |$6\: R_{\mathrm{ ISCO}}$| and |$9\: R_{\mathrm{ ISCO}}$| from relxill and relxillCp model, respectively. The inclination of the system is estimated to be |$\simeq 40^{\circ }$| from both reflection models. Assuming magnetic truncation of the accretion disc, the upper limit of magnetic field strength at the pole of the NS is found to be |$B\lesssim 1.8\times 10^{8}$| G. Furthermore, the NuSTAR observation revealed two type-I X-ray bursts and the burst spectroscopy confirms the thermonuclear nature of the burst. The blackbody temperature reaches nearly 2.2 keV at the peak of the burst. [ABSTRACT FROM AUTHOR]

Background: Volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) remains computationally expensive and sensitive to input dose objectives creating challenges for manual and automatic planning. Reinforcement learning (RL) involves machine learning through extensive trial‐and‐error, demonstrating performance exceeding humans, and existing algorithms in several domains. Purpose: To develop and evaluate an RL approach for VMAT MPO for localized prostate cancer to rapidly and automatically generate deliverable VMAT plans for a clinical linear accelerator (linac) and compare resultant dosimetry to clinical plans. Methods: We extended our previous RL approach to enable VMAT MPO of a 3D beam model for a clinical linac through a policy network. It accepts an input state describing the current control point and predicts continuous machine parameters for the next control point, which are used to update the input state, repeating until plan termination. RL training was conducted to minimize a dose‐based cost function for prescription of 60 Gy in 20 fractions using CT scans and contours from 136 retrospective localized prostate cancer patients, 20 of which had existing plans used to initialize training. Data augmentation was employed to mitigate over‐fitting, and parameter exploration was achieved using Gaussian perturbations. Following training, RL VMAT was applied to an independent cohort of 15 patients, and the resultant dosimetry was compared to clinical plans. We also combined the RL approach with our clinical treatment planning system (TPS) to automate final plan refinement, and creating the potential for manual review and edits as required for clinical use. Results: RL training was conducted for 5000 iterations, producing 40 000 plans during exploration. Mean ± SD execution time to produce deliverable VMAT plans in the test cohort was 3.3 ± 0.5 s which were automatically refined in the TPS taking an additional 77.4 ± 5.8 s. When normalized to provide equivalent target coverage, the RL+TPS plans provided a similar mean ± SD overall maximum dose of 63.2 ± 0.6 Gy and a lower mean rectum dose of 17.4 ± 7.4 compared to 63.9 ± 1.5 Gy (p = 0.061) and 21.0 ± 6.0 (p = 0.024) for the clinical plans. Conclusions: An approach for VMAT MPO using RL for a clinical linac model was developed and applied to automatically generate deliverable plans for localized prostate cancer patients, and when combined with the clinical TPS shows potential to rapidly generate high‐quality plans. The RL VMAT approach shows promise to discover advanced linac control policies through trial‐and‐error, and algorithm limitations and future directions are identified and discussed. [ABSTRACT FROM AUTHOR]

The inference of neuronal connectome from large-scale neuronal activity recordings, such as two-photon Calcium imaging, represents an active area of research in computational neuroscience. In this work, we developed FARCI (Fast and Robust Connectome Inference), a MATLAB package for neuronal connectome inference from high-dimensional two-photon Calcium fluorescence data. We employed partial correlations as a measure of the functional association strength between pairs of neurons to reconstruct a neuronal connectome. We demonstrated using in silico datasets from the Neural Connectomics Challenge (NCC) and those generated using the state-of-the-art simulator of Neural Anatomy and Optimal Microscopy (NAOMi) that FARCI provides an accurate connectome and its performance is robust to network sizes, missing neurons, and noise levels. Moreover, FARCI is computationally efficient and highly scalable to large networks. In comparison with the best performing connectome inference algorithm in the NCC, Generalized Transfer Entropy (GTE), and Fluorescence Single Neuron and Network Analysis Package (FluoroSNNAP), FARCI produces more accurate networks over different network sizes, while providing significantly better computational speed and scaling. [ABSTRACT FROM AUTHOR]

Analyzes the expression of genes for tyrosinase, tyrosinase-related protein 1, tyrosinase-related protein 2 and melanocortin-1 receptor using reverse transcription polymerase chain reaction. Result of the incubation of melanocyte-stimulating hormone/isobutylmethylxanthine; Correlation of the abundance and gel mobility pattern with changes in activity in hybrids and parental melanoma cells.

Transcranial near-infrared stimulation (tNIRS) has been proposed as a tool to modulate cortical excitability. However, the underlying mechanisms are not clear where the heating effects on the brain tissue needs investigation due to increased near-infrared (NIR) absorption by water and fat. Moreover, the risk of localized heating of tissues (including the skin) during optical stimulation of the brain tissue is a concern. The challenge in estimating localized tissue heating is due to the light interaction with the tissues' constituents, which is dependent on the combination ratio of the scattering and absorption properties of the constituent. Here, apart from tissue heating that can modulate the cortical excitability ("photothermal effects"); the other mechanism reported in the literature is the stimulation of the mitochondria in the cells which are active in the adenosine triphosphate (ATP) synthesis. In the mitochondrial respiratory chain, Complex IV, also known as the cytochrome c oxidase (CCO), is the unit four with three copper atoms. The absorption peaks of CCO are in the visible (420–450 nm and 600–700 nm) and the near-infrared (760–980 nm) spectral regions, which have been shown to be promising for low-level light therapy (LLLT), also known as "photobiomodulation". While much higher CCO absorption peaks in the visible spectrum can be used for the photobiomodulation of the skin, 810 nm has been proposed for the non-invasive brain stimulation (using tNIRS) due to the optical window in the NIR spectral region. In this article, we applied a computational approach to delineate the "photothermal effects" from the "photobiomodulation", i.e., to estimate the amount of light absorbed individually by each chromophore in the brain tissue (with constant scattering) and the related tissue heating. Photon migration simulations were performed for motor cortex tNIRS based on a prior work that used a 500 mW cm − 2 light source placed on the scalp. We simulated photon migration at 630 nm and 700 nm (red spectral region) and 810 nm (near-infrared spectral region). We found a temperature increase in the scalp below 0.25 °C and a minimal temperature increase in the gray matter less than 0.04 °C at 810 nm. Similar heating was found for 630 nm and 700 nm used for LLLT, so photothermal effects are postulated to be unlikely in the brain tissue. [ABSTRACT FROM AUTHOR]

Abstract: β1,6-acetylgulcosaminyltransferase V (GnT-V) forms β1,6 branching on the trimannosyl terminus of N-glycans, allowing for the production of β1,6Glc-NAc-bearing oligosaccharides. These are used by healthy myeloid cells and cancer cells alike for systemic migration. GnT-V has multiple glycoprotein substrates and thereby exerts global effects on cancer progression, characteristic of a master regulator of metastasis. Yet little is known of the regulation of GnT-V expression by tumor cells. It was previously reported that fusion of macrophages with Cloudman S91 mouse melanoma cells produced macrophage–melanoma hybrids with up-regulated GnT-V expression regarding mRNA and enzymatic activity. Majority of these hybrids showed increased chemotactic motility in vitro and elevated metastatic potential in vivo. Here we attempted to understand this at the molecular genetic level focusing on DNA hypermethylation as a potentially key step. Treatment of cells with 5-Aza-dC, an inhibitor of DNA methylation, resulted in decreased expression of GnT-V mRNA and β1,6-branched oligosaccharides along with reduced glycosylation of LAMP-1, a major substrate for GnT-V. This was accompanied by reduced chemotactic motility of the cells. The results suggested that DNA hypermethylation in some fashion stimulated GnT-V expression. We thus investigated the promoter region of the GnT-V gene for hypermethylation of CpG islands, comparing macrophage-melanoma hybrids of low and high metastatic potential with the parental melanoma cell line. Genomic DNA after bisulfite modification amplified from this region showed identical sequences between the cell lines. The findings indicated that differential methylation of the promoter region of GnT-V gene was not responsible for its transcriptional control, rather, appeared to be controlled through a negative regulator, nm23, whose own expression was regulated by hypermethylation. Although our studies involved a highly experimental system, the results further suggest that by whatever mechanism, reduction of GnT-V activity through 5-Aza-dC treatment might provide a new approach towards prevention of metastatic progression. [Copyright &y& Elsevier]