Notes

Ketogenic diet plans and the nervous system: any scoping review of neurological results through dietary ketosis throughout canine scientific studies.
ted inflammatory pathway and the Nrf2-mediated anti-oxidation pathway which are the major pathways of WTD for alleviating the symptoms of RA.
Primary effusion lymphoma (PEL) is an aggressive B cell non-Hodgkin lymphoma that develops especially in AIDS patients and immunocompromised patients infected with human herpes virus-8 (HHV-8)/Kaposi's sarcoma-associated herpesvirus (KSHV). PEL has a poor prognosis in patients despite conventional chemotherapeutic treatment, and a safe and efficient therapy is required.

To examine the effects on PEL of cucurbitacin B (CuB), a triterpene found in plants of the Cucurbitaceae family that has several anti-cancer activities.

We evaluated the anti-cancer activities of CuB in vitro and in vivo.

Cell proliferation of PEL cell lines was measured by MTT assay. Cleaved caspases and signaling transduction associated proteins were analyzed by western blotting. Wright and Giemsa staining and immunofluorescence staining were carried out to observe cell morphology. Cell cycles were analyzed by flow cytometry. RT-PCR was performed to detect viral gene expressions. A xenograft mouse model was employed to evaluate the anti-cancer activity of CuB in vivo.

CuB inhibited cell proliferation of PEL cell lines (BCBL-1, BC-1, GTO and TY-1) in a dose-dependent manner (0-50 nM) and induced apoptosis of BCBL-1 cells via caspase activation in a dose- and time-dependent manner. In addition, CuB caused cell-shape disruption by inducing actin aggregation and suppressing the p-cofilin level, resulting in BCBL-1 cell arrest at the G2/M phase. In contrast, CuB showed almost no suppression of p-STAT3 and p-Akt activation, which were constitutively activated by KSHV-derived proteins. Furthermore, CuB (0.5 mg/kg) via intraperitoneal injection significantly (p < 0.05) suppressed solid tumor growth in the xenograft mouse model.

This study suggests that CuB is a promising agent for PEL treatment.
This study suggests that CuB is a promising agent for PEL treatment.
Hyperglycemia-induced cardiovascular dysfunction has been linked to oxidative stress and accelerated apoptosis in the diabetic myocardium. While there is currently no treatment for diabetic cardiomyopathy (DCM), studies suggest that the combinational use of anti-hyperglycemic agents and triterpenes could be effective in alleviating DCM.

To investigate the therapeutic effect of methyl-3β-hydroxylanosta-9,24-dien-21-oate (RA3), in the absence or presence of the anti-diabetic drug, metformin (MET), against hyperglycemia-induced cardiac injury using an in vitro H9c2 cell model.

To mimic a hyperglycemic state, H9c2 cells were exposed to high glucose (HG, 33mM) for 24h. Thereafter, the cells were treated with RA3 (1μM), MET (1μM) and the combination of MET (1μM) plus RA3 (1μM) for 24h, to assess the treatments therapeutic effect.

Biochemical analysis revealed that RA3, with or without MET, improves glucose uptake via insulin-dependent (IRS-1/PI3K/Akt signaling) and independent (AMPK) pathways whilst ameliorating the activity of antioxidant enzymes in the H9c2 cells. Mechanistically, RA3 was able to alleviate HG-stimulated oxidative stress through the inhibition of reactive oxygen species (ROS) and lipid peroxidation as well as the reduced expression of the PKC/NF-кB cascade through decreased intracellular lipid content. Subsequently, RA3 was able to mitigate HG-induced apoptosis by decreasing the activity of caspase 3/7 and DNA fragmentation in the cardiomyoblasts.

RA3, in the absence or presence of MET, demonstrated potent therapeutic properties against hyperglycemia-mediated cardiac damage and could be a suitable candidate in the prevention of DCM.
RA3, in the absence or presence of MET, demonstrated potent therapeutic properties against hyperglycemia-mediated cardiac damage and could be a suitable candidate in the prevention of DCM.Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the healthcare system. Chest X-ray (CXR) imaging has several advantages over other imaging and detection techniques. Numerous works have been reported on COVID-19 detection from a smaller set of original X-ray images. However, the effect of image enhancement and lung segmentation of a large dataset in COVID-19 detection was not reported in the literature. We have compiled a large X-ray dataset (COVQU) consisting of 18,479 CXR images with 8851 normal, 6012 non-COVID lung infections, and 3616 COVID-19 CXR images and their corresponding ground truth lung masks. To the best of our knowledge, this is the largest public COVID positive database and the lung masks. Five different image enhancement techniques histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE), image complement, gamma correctin technique. The accuracy, precision, sensitivity, F1-score, and specificity were 95.11%, 94.55%, 94.56%, 94.53%, and 95.59% respectively for the segmented lung images. The proposed approach with very reliable and comparable performance will boost the fast and robust COVID-19 detection using chest X-ray images.The new coronavirus disease known as COVID-19 is currently a pandemic that is spread out the whole world. Several methods have been presented to detect COVID-19 disease. Computer vision methods have been widely utilized to detect COVID-19 by using chest X-ray and computed tomography (CT) images. This work introduces a model for the automatic detection of COVID-19 using CT images. A novel handcrafted feature generation technique and a hybrid feature selector are used together to achieve better performance. The primary goal of the proposed framework is to achieve a higher classification accuracy than convolutional neural networks (CNN) using handcrafted features of the CT images. In the proposed framework, there are four fundamental phases, which are preprocessing, fused dynamic sized exemplars based pyramid feature generation, ReliefF, and iterative neighborhood component analysis based feature selection and deep neural network classifier. In the preprocessing phase, CT images are converted into 2D matrices and resized to 256 × 256 sized images. The proposed feature generation network uses dynamic-sized exemplars and pyramid structures together. Two basic feature generation functions are used to extract statistical and textural features. The selected most informative features are forwarded to artificial neural networks (ANN) and deep neural network (DNN) for classification. ANN and DNN models achieved 94.10% and 95.84% classification accuracies respectively. The proposed fused feature generator and iterative hybrid feature selector achieved the best success rate, according to the results obtained by using CT images.
Electroencephalography (EEG) measures the electrical brain activity in real-time by using sensors placed on the scalp. Artifacts due to eye movements and blinking, muscular/cardiac activity and generic electrical disturbances, have to be recognized and eliminated to allow a correct interpretation of the Useful Brain Signals (UBS). Independent Component Analysis (ICA) is effective to split the signal into Independent Components (IC) whose re-projection on 2D topographies of the scalp (images also called Topoplots) allows to recognize/separate artifacts and UBS. Topoplot analysis, a gold standard for EEG, is usually carried out offline either visually by human experts or through automated strategies, both unenforceable when a fast response is required as in online Brain-Computer Interfaces (BCI). We present a fully automatic, effective, fast, scalable framework for artifacts recognition from EEG signals represented in IC Topoplots to be used in online BCI.

The proposed architecture, optimized to contain thrline BCI. In addition, its scalable architecture and ease of training are necessary conditions to apply it in BCI, where difficult operating conditions caused by uncontrolled muscle spasms, eye rotations or head movements, produce specific artifacts that need to be recognized and dealt with.The present study examines a temporal relation of walking behavior during locomotion transition (walking to stair ascent) to electrooculography (EOG) signals recorded from eye movement. Further, electroencephalography (EEG) signals from the occipital region of the brain are processed to understand the relative occurrence in EOG and EEG signals during the transition. The dipole sources in the occipital region with reference to EOG detection were estimated from independent components and then clustered using the k means algorithm. The dynamics of the dipoles in the occipital cluster in different frequency bands revealed significant desynchronization in the β and low γ bands, followed by resynchronization. This transitional behavior coincided with transient features suggesting possible saccadic movement of the eyes in the EOG signal. selleck chemical With the data from six able-bodied participants, the desynchronization in EEG from the occipital region was detected by nearly 2.2 ± 0.5s before the transition. Using preprocessing techniques on the EOG signal followed by detecting saccades from the derivative of the EOG signal, the eye movements were detected by nearly 2.5 ± 0.5s before the transition. The EOG decoded intention of transition appeared as early as 3.0 ± 1.63s before desynchronization in the EEG. A paired t-test analysis showed that the EOG-based intent decoding of transition reflects significantly earlier than occipital EEG (p less then 0.00001). This study could lead to a multi-modal neural-machine interface that may produce results superior to previous attempts involving only EEG and EMG signals.The motion performed by some protozoa is a crucial visual stimulus in microscopy analysis, especially when they have almost imperceptible morphological characteristics. Microorganisms can be distinguished through the interactions of their locomotion with neighboring elements, as observed in some parasitological analysis of Trypanosoma cruzi. In dye-free blood microscopy, the low contrast of this parasite makes it difficult to detect them. Thus, the parasite's interaction with the neighborhood, such as collisions with blood cells and shocks during the escape of confinements in cell clumps, generates collateral motions that assist its detection. Assuming that the collateral motion of the parasite can be sufficiently noticeable to overcome the dynamic contexts of inspection, we propose a novel computational approach that is based on motion saliency. We estimate motion in microscopy videos using dense optical flow and we investigate vestiges in saliency maps that could characterize the collateral motion of parasites. Our biological-inspired method shows that the parasite's collateral motion is a relevant feature for T. cruzi detection. Therefore, our computational model is a promising aid in the research and medical diagnosis of Chagas disease.In patients with swollen optic nerve head and normal visual function, optic disc drusen (ODD) is the most common diagnosis. The best tests for detecting ODD are funds autofluorescence and enhanced-depth imaging ocular coherence tomography (EDIOCT). After ODD has been ruled out, asymmetric papilledema should be assumed to be the cause and MRI of the brain and orbits with contrast and venography should be performed in all patients. It allows one to look for indirect signs of increased inctracranial pressure (ICP), optic perineuritis, and other inflammatory or compressive processes affecting optic nerve or its sheath such as optic nerve sheath meningioma. If imaging signs of raised ICP are present, lumbar puncture should be performed with measurement of opening pressure and analysis of cerebrospinal fluid (CSF) contents in all patients with fever, meningismus or neurologic deficits as well as patients who are not in the typical demographic group for idiopathic intracranial hypertension (IIH). Optic nerve sheath enhancement on MRI should prompt work-up for causes of optic perineuritis.
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