Transcriptomic Analysis of Age-Associated Periventricular Lesions Reveals Dysregulation of the Immune Response.

White matter lesions (WML) are a common feature of the ageing brain associated with cognitive impairment. The gene expression profiles of periventricular lesions (PVL, n = 7) and radiologically-normal-appearing (control) periventricular white matter cases (n = 11) obtained from the Cognitive Function and Ageing Study (CFAS) neuropathology cohort were interrogated using microarray analysis and NanoString to identify novel mechanisms potentially underlying their formation. Histological characterisation of control white matter cases identified a subgroup (n = 4) which contained high levels of MHC-II immunoreactive microglia, and were classified as "pre-lesional." Microarray analysis identified 2256 significantly differentially-expressed genes (p ≤ 0.05, FC ≥ 1.2) in PVL compared to non-lesional control white matter (1378 upregulated and 878 downregulated); 2649 significantly differentially-expressed genes in "pre-lesional" cases compared to PVL (1390 upregulated and 1259 downregulated); and 2398 significantly differentially-expressed genes in "pre-lesional" versus non-lesional control cases (1527 upregulated and 871 downregulated). Whilst histological evaluation of a single marker (MHC-II) implicates immune-activated microglia in lesion pathology, transcriptomic analysis indicates significant downregulation of a number of activated microglial markers and suggests established PVL are part of a continuous spectrum of white matter injury. The gene expression profile of "pre-lesional" periventricular white matter suggests upregulation of several signalling pathways may be a neuroprotective response to prevent the pathogenesis of PVL

Study the beneficial role of laser irradiation combination with indirect swim-up sperm preparation technique against oxidative DNA damage in infertile men

Background: In order to offer successful assisted reproductive procedures, a variety of in vitro sperm preparation techniques were created to separate normal and motile spermatozoa from other constituents of the sample. Much research on the laser as a sperm motility stimulant has been undertaken, and the results have indicated that the Laser has a good effect on sperm activation in vitro and improves progressive forward movement.  Objective: This study is aimed to identify the differences in sperm activation by ISU with or without laser methods and compare them. And detection of oxidative damage to the DNA before and after laser by assessment of the 8-Hydroxydeoxyguanosine (8-OHDG) as a biomarker. Patients and Methods: The current study was conducted on 30 semen samples, divided into two groups (Asthenozoospermia and Normozoospermia individuals), during the period of attendance at the infertility clinic at the High Institute for Infertility Diagnosis and Assisted Reproductive Technologies, Al-Nahrain University. From November 2021 until March 2022. Each sperm sample was separated into three portions

CFD analysis on optimizing the annular fin parameters toward an improved storage response in a triple-tube containment system

Due to the low thermal conductivity of the phase change material and low thermal diffusion inside the phase change material, this study seeks to improve the melting response of a triple-tube latent heat storage system via employing annular fins by optimizing their structural parameters, including the fin number, location, and dimensions. Natural convection effects are numerically evaluated considering different numbers and the locations of the fins, including fin numbers of 4, 10, 16, 20, and 30 in a vertical system orientation. The fins are attached to the inner and outer sides of the annulus, accommodating the phase change material between the inner and center tubes. The fins' number and location are identical on both sides of the annulus, and the volume of the fins is the same across all scenarios evaluated. The results show that the higher the number of fins used, the greater the heat communication between the fins and the phase change material layers in charge, resulting in faster melting and a higher rate of heat storage. Due to the limited natural convection effect and lower heat diffusion at the heat exchanger's bottom, an additional fin is added, and its thickness is assessed. The results show that the case with equal fin thickness, that is, both original fins and the new fin, performs the best performance compared with that for the cases with an added fin with thicknesses of 0.5, 1, and 2 mm. Eliminating an extra fin from the base of the system for the case with 30 fins increases the charging time by 53.3%, and reduces the heat storage rate by 44%. The overall melting time for the case with an added fin to the bottom is 1549 s for the case with 30 fins which is 85.8%, 34.2%, 18%, and 8.8% faster than the cases with 4, 10, 16, and 20 fins, respectively. This study reveals that further attention should be given to the position and number of annular fins to optimize the melting mechanism in phase-changing materials-based heat storage systems

Robust Automatic Modulation Classification Using Convolutional Deep Neural Network Based on Scalogram Information

This study proposed a two-stage method, which combines a convolutional neural network (CNN) with the continuous wavelet transform (CWT) for multiclass modulation classification. The modulation signals’ time-frequency information was first extracted using CWT as a data source. The convolutional neural network was fed input from 2D pictures. The second step included feeding the proposed algorithm the 2D time-frequency information it had obtained in order to classify the different kinds of modulations. Six different types of modulations, including amplitude-shift keying (ASK), phase-shift keying (PSK), frequency-shift keying (FSK), quadrature amplitude-shift keying (QASK), quadrature phase-shift keying (QPSK), and quadrature frequency-shift keying (QFSK), are automatically recognized using a new digital modulation classification model between 0 and 25 dB SNRs. Modulation types are used in satellite communication, underwater communication, and military communication. In comparison with earlier research, the recommended convolutional neural network learning model performs better in the presence of varying noise levels

Robust Automatic Modulation Classification Using Convolutional Deep Neural Network Based on Scalogram Information

This study proposed a two-stage method, which combines a convolutional neural network (CNN) with the continuous wavelet transform (CWT) for multiclass modulation classification. The modulation signals’ time-frequency information was first extracted using CWT as a data source. The convolutional neural network was fed input from 2D pictures. The second step included feeding the proposed algorithm the 2D time-frequency information it had obtained in order to classify the different kinds of modulations. Six different types of modulations, including amplitude-shift keying (ASK), phase-shift keying (PSK), frequency-shift keying (FSK), quadrature amplitude-shift keying (QASK), quadrature phase-shift keying (QPSK), and quadrature frequency-shift keying (QFSK), are automatically recognized using a new digital modulation classification model between 0 and 25 dB SNRs. Modulation types are used in satellite communication, underwater communication, and military communication. In comparison with earlier research, the recommended convolutional neural network learning model performs better in the presence of varying noise levels

Induction of apoptosis and autophagy via regulation of AKT and JNK mitogen-activated protein kinase pathways in breast cancer cell lines exposed to gold nanoparticles loaded with TNF-α and combined with doxorubicin

Gold nanoparticles (GNPs) tagged with peptides are pioneers in bioengineered cancer therapy. The aim of the current work was to elucidate the potential anticancer interactions between doxorubicin and GNPs loaded with tumor necrosis factor-alpha (TNF-α). To investigate whether GNPs loaded with TNF and doxorubicin could stimulate autophagy and apoptosis in breast cancer cells. Two human breast cancer cell lines, MCF-7 and AMJ-13, as well as different apoptotic and autophagy markers, were used. In both cell types, treatment with TNF-loaded GNPs in conjunction with doxorubicin increased the production of apoptotic proteins including Bad, caspase-3, caspase-7, and p53 with upregulation of the LC3-II and Beclin1 proteins. In addition, the findings showed that the mitogen-activated protein kinase signaling pathway was dramatically affected by the GNPs loaded with TNF-α and combined with doxorubicin. This had the effect of decreasing p-AKT while simultaneously increasing p-JNK1/2. The findings demonstrated that GNPs loaded with TNF-α and combined with doxorubicin can induce both autophagy and apoptosis in breast cancer cells. These results suggest that TNF- and doxorubicin-loaded GNPs provide a therapeutic option as a nanomedicine to inhibit the proliferation of breast cancer

Graphene oxide-induced, reactive oxygen species-mediated mitochondrial dysfunctions and apoptosis: high-dose toxicity in normal cells - supplementary figures

Aim: The cytotoxic effects of graphene oxide nanoparticles (GONPs) using MTT assays, observance of apoptotic markers, and oxidative stress were outlined. Materials & methods: Rat embryonic fibroblasts (REFs) and human epithelial breast cells (HBLs) were used at 250, 500 and 750 μg/ml concentrations. Results: Significant cytotoxic and apoptotic effects were observed. Analyses of CYP2E1 and malondialdehyde concentrations in REF and HBL-100 cell lines after exposing to GONPs confirmed the nanomaterials toxicity. However, the glutathione levels in REF and HBL-100 cell lines showed a substantial reduction compared with the control. The cytochrome CYP2E1, glutathione, malondialdehyde and caspase-3 alterations provided a plausible interlinked relationship. Conclusion: The study confirmed the GONPs cytotoxic effects on REF and HBL-100 cell lines. The outcome suggested caution in wide-spread applications of GONPs, which could have implications for occupational health also.</p