Neuroprotective and cognitive enhancing effects of herbecetin against thioacetamide induced hepatic encephalopathy in rats via upregulation of AMPK and SIRT1 signaling pathways.

Acute liver injury, there is a risky neurological condition known as hepatic encephalopathy (HE). Herbacetin is a glycosylated flavonoid with many pharmacological characteristics. The purpose of this study was to assess the ability of herbacetin to protect against the cognitive deficits associated with thioacetamide (TAA) rat model and delineate the underlying behavioral and pharmacological mechanisms. Rats were pretreated with herbacetin (20 and 40 mg/kg) for 30days. On 30th day, the rats were injected with TAA (i.p. 350 mg/kg) in a single dose. In addition to a histpathological studies, ultra-structural architecture of the brain, liver functions, oxidative stress biomarkers, and behavioral tests were evaluated. Compared to the TAA-intoxicated group, herbacetin improved the locomotor and cognitive deficits, serum hepatotoxicity indices and ammonia levels. Herbacetin reduced brain levels of malodialdeyde, glutamine synthetase (GS), tumor necrosis factor- alpha (TNF-α), interleukin 1 B (IL-1ß), annexin v, and increased brain GSH, Sirtuin 1 (SIRT1), and AMP-activated kinase (AMPK) expression levels. Also, herbacetin improve the histopathological changes and ultra- structure of brain tissue via attenuating the number of inflammatory and apoptotic cells. Herbacetin treatment significantly reduced the toxicity caused by TAA. These findings suggest that herbacetin might be taken into account as a possible neuroprotective and cognitive enhancing agent due to its ability to reduce oxidative stress, inflammation and apoptosis associated with TAA.

Novel drugs affecting diabetic peripheral neuropathy.

Diabetic peripheral neuropathy (DPN) poses a significant threat, affecting half of the global diabetic population and leading to severe complications, including pain, impaired mobility, and potential amputation. The delayed manifestation of diabetic neuropathy (DN) makes early diagnosis challenging, contributing to its debilitating impact on individuals with diabetes mellitus (DM). This review examines the multifaceted nature of DPN, focusing on the intricate interplay between oxidative stress, metabolic pathways, and the resulting neuronal damage. It delves into the challenges of diagnosing DN, emphasizing the critical role played by hyperglycemia in triggering these cascading effects. Furthermore, the study explores the limitations of current neuropathic pain drugs, prompting an investigation into a myriad of pharmaceutical agents tested in both human and animal trials over the past decade. The methodology scrutinizes these agents for their potential to provide symptomatic relief for DPN. The investigation reveals promising results from various pharmaceutical agents tested for DPN relief, showcasing their efficacy in ameliorating symptoms. However, a notable gap persists in addressing the underlying problem of DPN. The results underscore the complexity of DPN and the challenges in developing therapies that go beyond symptomatic relief. Despite advancements in treating DPN symptoms, there remains a scarcity of options addressing the underlying problem. This review consolidates the state-of-the-art drugs designed to combat DPN, highlighting their efficacy in alleviating symptoms. Additionally, it emphasizes the need for a deeper understanding of the diverse processes and pathways involved in DPN pathogenesis.

Lauric acid attenuates hepato-metabolic complications and molecular alterations in high-fat diet-induced nonalcoholic fatty liver disease in rats.

Nonalcoholic fatty liver disease (NAFLD) has emerged as a major chronic liver illness characterized by increase of lipid content in the liver. This study investigated the role of lauric acid to treat NAFLD in male adult Sprague Dawley rats. In this study, to induce NAFLD in the rats, a high-fat diet (HFD) was administered for eight consecutive weeks. Lauric acid groups received lauric acid (250 and 500 mg/kg; orally), concurrently with HFD for eight consecutive weeks. Lauric acid could ameliorate the serum levels of TG, TC, ALT, AST, blood glucose, and insulin. Moreover, lauric acid significantly elevated the levels of SOD, GSH, catalase, and IL-10. Additionally, it lowered the hepatic levels of MDA, ROS, MPO, 4-HNE, interleukin (IL)-1ß, and tumor necrosis factor (TNF-α). Furthermore, lauric acid significantly up-regulated the hepatic expression of IRS1, AMPK, PI3K, and SIRT1 genes. In parallel, lauric acid could improve the histopathological picture of the liver and reduce the liver apoptosis via decreasing the expression of annexin V (Anx V). Finally, our data proposed that lauric acid could be an effective candidate for the NAFLD treatment.

Mitigating effect of ferulic acid on di-(2-ethylhexyl) phthalate-induced neurocognitive dysfunction in male rats with a comprehensive in silico survey.

Di-(2-ethylhexyl) phthalate (DEHP) is the most abundant phthalate threatening public health-induced neurotoxicity. This neurotoxicity is associated with behavioral and biochemical deficits in male rats. Our study investigated the neuroprotective effect of ferulic acid (FA) on male rats exposed to DEHP. Thirty-two male Wistar rats were assigned to four groups. Group I control rats received corn oil, group II intoxicated rats received 300 mg/kg of DEHP, group III received 300 mg/kg of DEHP + 50 mg/kg of FA, and group IV received 50 mg/kg of FA, all agents administrated daily per os for 30 days. Anxiety-like behavior, spatial working memory, and recognition memory were assessed. Also, brain oxidative stress biomarkers, including brain malondialdehyde (MDA), reduced glutathione (GSH), nitric oxide (NO), superoxide dismutase (SOD), brain-derived neurotrophic factor (BDNF) as well as heme oxygenase-1 (HO-1) were measured. Moreover, brain histopathology examinations associated with immunohistochemistry determination of brain caspase-3 were also evaluated. Furthermore, docking simulation was adapted to understand the inhibitory role of FA on caspase-3 and NO synthase. Compared to DEHP-intoxicated rats, FA-treated rats displayed improved cognitive memory associated with a reduced anxious state. Also, the redox state was maintained with increased BNDF levels. These changes were confirmed by restoring the normal architecture of brain tissue and a decrement in the immunohistochemistry caspase-3. In conclusion, FA has potent antioxidant and antiapoptotic properties that confirm the neuroprotective activity of FA, with a possible prospect for its therapeutic capabilities and nutritional supplement value.

Immunoregulatory role of hesperidin against ovalbumin (OVA)-induced bronchial asthma and depression in rats.

Links between bronchial asthma and depression have recently become a great subject of interest. The present study was carried out to assess the protective role of hesperidin against ovalbumin (OVA)-induced bronchial asthma that is associated with depression in rats, for this purpose, four groups. Rats were sensitized with intraperitoneal administration of 200 µg OVA/10 mg aluminum hydroxide (Al (OH) 3 for 3 consecutive days then at day 11 followed by intranasal challenge with OVA (1.5 mg/kg) at days 19, 20, and 21. Rats were pretreated with hesperidin (100 & 200 mg/kg) 1h before OVA challenge. At the end of the study, behavioral tests, biochemical indices, and histopathological architectures of lung and brain tissues were evaluated. Our findings showed that hesperidin significantly ameliorated the reduction in motor activity, motor coordination, forced swimming, CD4, CD25 and foxp3, interleukin-10 (IL-10), dopamine, serotonin, and neurotrophin-3 (NT3) as well as alleviated the elevation in transforming growth factor-beta (TGF-ß), tumor necrosis factor-alpha (TNF-α), iL-5, and immunoglobulin E (IgE). In addition, hesperidin reduced cellular infiltration, alveolar sacs damage, the bronchioles wall disruption, and nuclei pyknosis in neuron cells. Finally, hesperidin may provide protection against OVA-induced asthma and depression. This impact could be mediated in part by its anti-inflammatory and immunoregulatory properties.

Chitosan tamarind-based nanoparticles as a promising approach for topical application of curcumin intended for burn healing: in vitro and in vivo study.

One of the most prevalent worldwide problems that affect all ages and genders is skin burn. The goal of our study was to assess the ability of curcumin nanoparticles to cure a rat burn model. Three formulations were selected after several tests were performed including investigation of encapsulation efficiency, particle size and zeta potential measurements. In vitro release was achieved on the three selected formulations. The effectiveness of the chosen formulation for healing was evaluated. The induced burn wound was smeared, starting just after excision, once daily with curcumin nanoparticles for 18 days. Our findings revealed that curcumin nanoparticles improved the burn healing potential by augmenting the skin regeneration indices as evidenced by enhancing the new production of hyaluronic acid and collagen type I. Additionally, curcumin nanoparticles could increase levels of vascular endothelial growth factor and alpha smooth muscle activity while drastically reducing the skin's tumour necrosis factor content, revealing a significant potential for burn healing process that is also reflected in the histopathological and immunohistochemical studies. Finally, our results demonstrated that curcumin nanoparticles revealed a significant potential for burn healing than curcumin alone due to its potent antimicrobial, antioxidant and anti-inflammatory properties.

An Ultra-Wide Band MIMO Antenna System with Enhanced Isolation for Microwave Imaging Applications.

This paper introduces a novel two-port ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna system with enhanced isolation characteristics. The antenna, designed on a thin 0.787 mm RO5880 substrate, achieves a compact form factor of 52 × 26 mm2 and offers a wide bandwidth of 9.2 GHz (2.3 GHz to 11.5 GHz) while meeting the VSWR 2:1 criterion. Notably, the proposed antenna demonstrates an impressive increase in isolation, up to 16 dB, through the integration of a shared radiator with small rectangular slots, effectively reducing interference and improving overall performance. Furthermore, a comprehensive analysis of additional MIMO performance parameters, including the envelope correlation coefficient (ECC) and diversity gain, confirms their satisfactory limits, validating the potential of the proposed UWB-MIMO antenna for various UWB applications. The time domain analysis of the UWB antenna is also analyzed, and results are found to be within satisfactory limits. Simulation and measurement results further support the practicality and effectiveness of the antenna design, highlighting its compact size, wide bandwidth, and enhanced isolation characteristics, positioning it as a promising solution for advanced UWB microwave imaging systems.

Synergistic effect of arginine and Lactobacillus plantarum against potassium dichromate induced-acute liver and kidney injury in rats: Role of iNOS and TLR4/NF-κB signaling pathways.

Objectives: Our study was conducted to evaluate the synergistic effect of arginine (ARG) and Lactobacillus plantarum against potassium dichromate (K2Cr2O7) induced-acute hepatic and kidney injury. Materials and Methods: Fifty male Wistar rats were divided into five groups. The control group received distilled water. The potassium dichromate group (PDC) received a single dose of PDC (20 mg/kg; SC). The arginine group (ARG) and Lactobacillus plantarum group received either daily doses of ARG (100 mg/kg, PO) or L. plantarum (109 CFU/ml, PO) for 14 days. The combination group (ARG+L. plantarum) received daily doses of ARG (100 mg/kg) with L. plantarum (109 CFU/ml), orally for 14 days, before induction of acute liver and kidney injury. Forty eight hours after the last dose of PDC, serum biochemical indices, oxidative stress biomarkers, pro-inflammatory cytokines, histopathological and immunohistochemical analysis were evaluated. Results: Combining ARG with L. plantarum restored the levels of serum hepatic & kidney enzymes, hepatic & renal oxidative stress biomarkers, and TLR 4/ NF-κB signaling pathway. Furthermore, they succeeded in decreasing the expression of iNOS and ameliorate the hepatic and renal markers of apoptosis: Caspase-3, Bax, and Bcl2. Conclusion: This study depicts that combining ARG with L. plantarum exerted a new bacteriotherapy against hepatic and renal injury caused by PDC.

Cold plasma approach fortifies the topical application of thymoquinone intended for wound healing via up-regulating the levels of TGF-ß, VEGF, and α-SMA in rats.

Wound healing is a series of coordinated events that involve tissue repair and regeneration. Cold atmospheric plasma approach sheds the light on the mechanism that initiates the inflammatory responses throughout the healing cascade. The present study was planned to assess the effect of thymoquinone treated with cold plasma (TQcp) on the rat wound model compared to thymoquinone (TQ). To assess the wound healing potential of TQcp, a full-thickness wound model was used. The induced wound was smeared, starting just after excision, twice daily with TQcp and TQ for 7 days. Our findings revealed that TQcp improved the skin healing potential by augmenting the skin regeneration indices as evidenced by enhancing the new production of hyaluronic acid and collagen type I. TQcp significantly reduced the skin content of tumor necrosis factor- α and inhibited the hypertrophic scarring by up-regulating the skin content of transforming growth factor-beta. Furthermore, TQcp enhanced the levels of interleukin-10, alpha smooth muscle actin and vascular endothelial growth factor, demonstrating a great potential for wound healing that also reflected in the histopathological and ultra-structural picture of the skin. Finally, our results demonstrated that TQcp revealed a significant potential for wound healing than TQ alone.

Neuromodulatory role of L-arginine: nitric oxide precursor against thioacetamide-induced-hepatic encephalopathy in rats via downregulation of NF-κB-mediated apoptosis.

The aim of the present study was to investigate the impact of arginine (ARG), a nitric oxide (NO) precursor, on thioacetamide (TAA)-induced hepatic encephalopathy (HE) in rats by injection of TAA (100 mg/kg, i.p) three times per week for six consecutive weeks. TAA-injected rats were administered ARG (100 mg/kg; p.o.) concurrently with TAA for the six consecutive weeks. Blood samples were withdrawn, and rats were sacrificed; liver and brain tissues were isolated. Results of the present study demonstrated that ARG administration to TAA-injected rats revealed a restoration in the serum and brain ammonia levels as well as serum aspartate transaminase, alanine transaminase, and alkaline phosphatase and total bilirubin levels as well as behavioral alterations evidenced by restoration in locomotor activity, motor skill performance, and memory impairment. ARG showed also improvement in the hepatic and neuro-biochemical values, pro-inflammatory cytokines, and oxidative stress biomarkers. All these results were confirmed by histopathological evaluation as well as ultrastructural imaging of the cerebellum using a transmission electron microscope. Furthermore, treatment with ARG could ameliorate the immunological reactivity of nuclear factor erythroid-2-related factor 2 (Nrf2) and cleaved caspase-3 proteins in the cerebellum and hepatic tissues. From all the previous results, it can be fulfilled that ARG showed a beneficial role in modulating the adverse complications associated with TAA-induced HE in rats via reducing hyperammonemia and downregulating nuclear factor kappa B (NF-κB)-mediated apoptosis.

Febuxostat attenuates aluminum chloride-induced hepatorenal injury in rats with the impact of Nrf2, Crat, Car3, and MNK-mediated apoptosis.

Aluminum (Al) is a ubiquitous xenobiotic with known toxicity for both humans and animals. Our study was conducted to investigate the protective role of febuxostat (Feb) against aluminum chloride (AlCl3)-induced hepatorenal injury in rats. Hepatorenal injury was induced by oral administration of AlCl3 (40 mg/kg b.w.), for 2 months. Twenty-four male Sprague-Dawley rats were randomly allocated into four groups (six rats/group). The first group received the vehicle thought the experiment. The second group was considered as a control positive group. The third and fourth groups received oral treatment of Feb (10 mg/kg.b.w.) and (15 mg/kg.b.w.), respectively with AlCl3, concurrently for 2 months. Twenty-four hours, after the last treatment, serum biochemical, molecular, histopathology, and immunohistochemical studies were evaluated. Our findings showed that rats intoxicated with Alcl3 had disturbed biochemical picture. In addition, intoxication with AlCl3 increased oxidative stress and apoptosis, as demonstrated by an increase in malodialdeyde (MDA), carnitine o-acetyltransferase (Crat), and carbonic anhydrase (Car3) with a decrease in glutathione (GSH), MAP kinase-interacting serine/threonine kinase (MNK) and nuclear factor-erythroid 2-related factor 2 (Nrf2) mRNA expression. Furthermore, the levels of tumor necrosis factor-alpha (TNF-α) and the levels of caspase-3 were elevated with sever hepatic and renal pathological changes. Conversely, Feb (15 mg/kg.b.w.) could improve the serum biochemical indices and repressed MDA, Crat, and Car3 levels, whereas it increased GSH, MNK, and Nrf2 levels. Feb inhibited the apoptotic effect of AlCl3 in the liver and kidney by decreasing caspase-3 and TNF-α expression. The protective effect of Feb against AlCl3 toxicity was confirmed by histopathological findings. Moreover, molecular docking studies supported the anti-inflammatory effect of Feb due to its significant binding interactions with cyclooxygenase-1 (COX-1), NF-kappa-B-inducing kinase (NIK), and mitogen-activated protein kinases-p38 (MAPK-p38). The findings suggest that Feb system Feb can avert Alcl3-induced hepatotoxicity and nephrotoxicity by enhancing the antioxidant defense system, and inhibiting the inflammatory cascade and apoptosis.

SFBC Recognition over Orthogonal Frequency Division Multiplexing Schemes in the Presence of Inphase and Quadrature Phase Discrepancies for Cognitive Radio Applications.

A radio is adaptive if it can autonomously analyze the communications environment and instantly modify its settings to achieve the best possible efficiency. In orthogonal frequency division multiplexing (OFDM) transmissions, identifying the space frequency block coding (SFBC) category utilized is one of the most important tasks of an adaptive receiver. Previous approaches to this problem did not take into consideration the fact that real systems typically suffer from transmission defects. This study offers a novel maximum likelihood recognizer capable of distinguishing between SFBC OFDM waveforms in the context of inphase and quadrature phase differences (IQDs). The theoretical findings show that IQDs arising from the transmitter and recipient can be combined with channel paths to generate so-called effective channel paths. The conceptual examination demonstrates that the outlined maximum likelihood strategy of the SFBC recognition and effective channel estimation processes is implemented by an expectation maximization tool utilizing the error control decoders' soft outputs. The simulations results reveal that the suggested strategy delivers a much greater recognition accuracy than the typical approaches outlined in the comparable literature. At a signal-to-noise ratio (SNR) of 14 dB, for example, the proposed approach achieves a bit error rate (BER) of 0.00002, which is very close to the case of perfect estimation and compensation for IQDs, outperforming the previous reported works which achieved BERs of 0.01 and 0.02.

An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models.

Emergency medicine (EM) is one of the attractive research fields in which researchers investigate their efforts to diagnose and treat unforeseen illnesses or injuries. There are many tests and observations are involved in EM. Detection of the level of consciousness is one of these observations, which can be detected using several methods. Among these methods, the automatic estimation of the Glasgow coma scale (GCS) is studied in this paper. The GCS is a medical score used to describe a patient's level of consciousness. This type of scoring system requires medical examination that may not be available with the shortage of the medical expert. Therefore, the automatic medical calculation for a patient's level of consciousness is highly needed. Artificial intelligence has been deployed in several applications and appears to have a high performance regarding providing automatic solutions. The main objective of this work is to introduce the edge/cloud system to improve the efficiency of the consciousness measurement through efficient local data processing. Moreover, an efficient machine learning (ML) model to predict the level of consciousness of a certain patient based on the patient's demographic, vital signs, and laboratory tests is proposed, as well as maintaining the explainability issue using Shapley additive explanations (SHAP) that provides natural language explanation in a form that helps the medical expert to understand the final prediction. The developed ML model is validated using vital signs and laboratory tests extracted from the MIMIC III dataset, and it achieves superior performance (mean absolute error (MAE) = 0.269, mean square error (MSE) = 0.625, R 2 score = 0.964). The resulting model is accurate, medically intuitive, and trustworthy.

Dose-dependent toxic effects of di-(2-ethylhexyl) phthalate in male rats: Focus on behavioral alterations and inducing TLR4/NF-κB signaling pathway.

Di -(2-ethylhexyl) phthalate (DEHP) is a widely used phthalate that possesses a public health concern. Different concentrations of DEHP, including 50, 300, and 750 mg/kg were administrated orally for 28 days in male rats. Body weight and vital organs weight were measured as well as anxiety-like behavior, short and long-term memory were investigated. Brain inflammatory cytokines, including IL-1ß, TLR4, NF-κB, TNF-α, and IL1-6 were assessed. Brain caspase-3, neuropeptide-Y (NPY), and brain histopathology were also evaluated. DEHP triggers the release of pro-inflammatory cytokines via inducing the nuclear translocation of the signaling pathway; TLR 4/ NF-κB leads to cognitive impairment and neurodegeneration, which is confirmed by the impaired brain architecture. Also, DEHP upgrades the expression levels of brain caspase-3 and NPY. In conclusion, exposure to high doses of DEHP persuades great toxicity visualized by behavioral, biochemical, and histological impairments when compared to the low doses.

Neuroprotective effect of tangeretin against chromium-induced acute brain injury in rats: targeting Nrf2 signaling pathway, inflammatory mediators, and apoptosis.

Potassium dichromate (PD) is an environmental xenobiotic commonly recognized as teratogenic, carcinogenic, and mutagenic in animals and humans. The present study was conducted to investigate the role of tangeretin (TNG) as a neuro-protective drug against PD-induced brain injury in rats. Thirty-two male adult Wistar rats were blindly divided into four groups (8 rats/group). The first group received saline intranasally (i.n.). The second group received a single dose of PD (2 mg/kg, i.n.). The third group received TNG (50 mg/kg; orally), for 14 days followed by i.n. of PD on the last day of the experiment. The fourth group received TNG (100 mg/kg; orally) for 14 days followed by i.n. of PD on the last day of the experiment. Behavioral indices were evaluated 18 h after PD administration. Neuro-biochemical indices and histopathological studies were evaluated 24 h after PD administration. Results of the present study revealed that rats intoxicated with PD induced- oxidative stress and inflammation via an increase in malondialdehyde (MDA) and a decrease in nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway and glutathione(GSH) levels with an increase in brain contents of tumor necrosis factor-alpha (TNF-α) and interleukin (IL-6). Pre-treatment with TNG (100 mg/kg; orally) ameliorated behavior, cholinergic activities, and oxidative stress and decreased the elevated levels of pro-inflammatory mediators; TNF-α and IL-6 with a decrease in brain content of chromium residues detected by Plasma-Optical Emission Spectrometer. Also, the histopathological picture of the brain was improved significantly in rats that received TNG (100 mg/kg). Additionally, TNG decreased caspase-3 expression in the brain of PD rats. In conclusion, TNG possesses a significant neuroprotective role against PD-induced acute brain injury via modulating the Nrf2 signaling pathway and quenching the release of inflammatory mediators and apoptosis in rats.

Levonorgestrel-releasing intrauterine system versus systemic progestins in management of endometrial hyperplasia: A systemic review and meta-analysis.

INTRODUCTION: Endometrial hyperplasia is associated with varying risk of endometrial cancer. The aim of this review is to assess effectiveness of levonorgestrel-releasing intrauterine system (LNG-IUS), compared to systemic progestins, in management of endometrial hyperplasia MATERIALS AND METHODS: A search on studies comparing LNG-IUS to systemic progestins was conducted on Scopus, Web of science, Cochrane, PubMed and Embase databases, from the date of inception to September 20th, 2020. Studies were excluded if they were non-comparative, animal studies, review articles, case reports, case series, and conference papers. Primary outcomes include resolution/regression rate, failure rate, and hysterectomy rate. Analysis was pooled using random effect model and was expressed as pooled odds ratios (OR) and 95% confidence interval (CI). Quality assessment was performed using Cochrane Risk of Bias Tool and the Newcastle-Ottawa Scale (NOS) assessment tool. MOGGE Meta-analysis Matrix was used to illustrate multiple subgroup analyses. RESULTS: Out of 341 studies retrieved from literature search, 12 were eligible. LNG-IUS yielded significantly higher resolution/regression rate (91.3% vs 68.6%, OR 3.42, 95% CI 1.86-6.30). Failure and hysterectomy rates were significantly lower in LNG-IUS group compared to systemic progestins' group (19.2% vs. 32.3%, OR 0.34, 95% CI 0.20-0.57 and 9.3% vs. 24.1%, OR 0.41, 95% CI 0.29-0.57, respectively). Subgroup analysis of studies including complex hyperplasia only did not show significant difference in resolution/regression rate was not statistically significant. CONCLUSION: LNG-IUS is associated with high success rate in management of women with endometrial hyperplasia. However, specific effectiveness of LNG-IUS on more advanced histologic subtypes is less studied.

Efficient multimodal deep-learning-based COVID-19 diagnostic system for noisy and corrupted images.

INTRODUCTION: In humanity's ongoing fight against its common enemy of COVID-19, researchers have been relentless in finding efficient technologies to support mitigation, diagnosis, management, contact tracing, and ultimately vaccination. OBJECTIVES: Engineers and computer scientists have deployed the potent properties of deep learning models (DLMs) in COVID-19 detection and diagnosis. However, publicly available datasets are often adulterated during collation, transmission, or storage. Meanwhile, inadequate, and corrupted data are known to impact the learnability and efficiency of DLMs. METHODS: This study focuses on enhancing previous efforts via two multimodal diagnostic systems to extract required features for COVID-19 detection using adulterated chest X-ray images. Our proposed DLM consists of a hierarchy of convolutional and pooling layers that are combined to support efficient COVID-19 detection using chest X-ray images. Additionally, a batch normalization layer is used to curtail overfitting that usually arises from the convolution and pooling (CP) layers. RESULTS: In addition to matching the performance of standard techniques reported in the literature, our proposed diagnostic systems attain an average accuracy of 98% in the detection of normal, COVID-19, and viral pneumonia cases using corrupted and noisy images. CONCLUSIONS: Such robustness is crucial for real-world applications where data is usually unavailable, corrupted, or adulterated.

Deploying Machine Learning Techniques for Human Emotion Detection.

Emotion recognition is one of the trending research fields. It is involved in several applications. Its most interesting applications include robotic vision and interactive robotic communication. Human emotions can be detected using both speech and visual modalities. Facial expressions can be considered as ideal means for detecting the persons' emotions. This paper presents a real-time approach for implementing emotion detection and deploying it in the robotic vision applications. The proposed approach consists of four phases: preprocessing, key point generation, key point selection and angular encoding, and classification. The main idea is to generate key points using MediaPipe face mesh algorithm, which is based on real-time deep learning. In addition, the generated key points are encoded using a sequence of carefully designed mesh generator and angular encoding modules. Furthermore, feature decomposition is performed using Principal Component Analysis (PCA). This phase is deployed to enhance the accuracy of emotion detection. Finally, the decomposed features are enrolled into a Machine Learning (ML) technique that depends on a Support Vector Machine (SVM), k-Nearest Neighbor (KNN), Naïve Bayes (NB), Logistic Regression (LR), or Random Forest (RF) classifier. Moreover, we deploy a Multilayer Perceptron (MLP) as an efficient deep neural network technique. The presented techniques are evaluated on different datasets with different evaluation metrics. The simulation results reveal that they achieve a superior performance with a human emotion detection accuracy of 97%, which ensures superiority among the efforts in this field.

Middle-East OBGYN graduate education (MOGGE) foundation practice guidelines: use of labor charts in management of labor. Practice guideline no. 04-O-21.

Since the 50 s of the last century, labor charts have been proposed and appraised as a tool to diagnose labor abnormalities and guide decision-making. The partogram, the most widely adopted form of labor charts, has been endorsed by the world health organization (WHO) since 1994. Nevertheless, recent studies and systematic reviews did not support clinical significance of application of the WHO partogram. These results have led to further studies that investigate modifications to the structure of the partogram, or more recently, to reconstruct new labor charts to improve their clinical efficacy. This guideline appraises current evidence on use of labor charts in management of labor specially in low-resource settings.

Efficient deep learning approach for augmented detection of Coronavirus disease.

The new Coronavirus disease 2019 (COVID-19) is rapidly affecting the world population with statistics quickly falling out of date. Due to the limited availability of annotated Coronavirus X-ray and CT images, the detection of COVID-19 remains the biggest challenge in diagnosing this disease. This paper provides a promising solution by proposing a COVID-19 detection system based on deep learning. The proposed deep learning modalities are based on convolutional neural network (CNN) and convolutional long short-term memory (ConvLSTM). Two different datasets are adopted for the simulation of the proposed modalities. The first dataset includes a set of CT images, while the second dataset includes a set of X-ray images. Both of these datasets consist of two categories: COVID-19 and normal. In addition, COVID-19 and pneumonia image categories are classified in order to validate the proposed modalities. The proposed deep learning modalities are tested on both X-ray and CT images as well as a combined dataset that includes both types of images. They achieved an accuracy of 100% and an F1 score of 100% in some cases. The simulation results reveal that the proposed deep learning modalities can be considered and adopted for quick COVID-19 screening.