An AI-based novel system for predicting respiratory support in COVID-19 patients through CT imaging analysis.

The proposed AI-based diagnostic system aims to predict the respiratory support required for COVID-19 patients by analyzing the correlation between COVID-19 lesions and the level of respiratory support provided to the patients. Computed tomography (CT) imaging will be used to analyze the three levels of respiratory support received by the patient: Level 0 (minimum support), Level 1 (non-invasive support such as soft oxygen), and Level 2 (invasive support such as mechanical ventilation). The system will begin by segmenting the COVID-19 lesions from the CT images and creating an appearance model for each lesion using a 2D, rotation-invariant, Markov-Gibbs random field (MGRF) model. Three MGRF-based models will be created, one for each level of respiratory support. This suggests that the system will be able to differentiate between different levels of severity in COVID-19 patients. The system will decide for each patient using a neural network-based fusion system, which combines the estimates of the Gibbs energy from the three MGRF-based models. The proposed system were assessed using 307 COVID-19-infected patients, achieving an accuracy of [Formula: see text], a sensitivity of [Formula: see text], and a specificity of [Formula: see text], indicating a high level of prediction accuracy.

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review.

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists' proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists' capabilities and ameliorating patient outcomes in the realm of breast cancer management.

Oxygen Saturation in Hospitalized COVID-19 Patients and Its Relation to Colchicine Treatment: A Retrospective Cohort Study with an Updated Systematic Review.

Background: Colchicine has been proposed as a cytokine storm-blocking agent for COVID-19 due to its efficacy as an anti-inflammatory drug. The findings of the studies were contentious on the role of colchicine in preventing deterioration in COVID-19 patients. We aimed to evaluate the efficacy of colchicine in COVID-19-hospitalized patients. Design: A retrospective observational cohort study was carried out at three major isolation hospitals in Alexandria (Egypt), covering multiple centers. In addition, a systematic review was conducted by searching six different databases for published studies on the utilization of colchicine in patients with COVID-19 until March 2023. The primary outcome measure was to determine whether colchicine could decrease the number of days that the patient needed supplemental oxygen. The secondary outcomes were to evaluate whether colchicine could reduce the number of hospitalization days and mortality rate in these patients. Results: Out of 515 hospitalized COVID-19 patients, 411 were included in the survival analysis. After adjusting for the patients' characteristics, patients not receiving colchicine had a shorter length of stay (median: 7.0 vs. 6.0 days) and fewer days of supplemental oxygen treatment (median: 6.0 vs. 5.0 days), p < 0.05, but there was no significant difference in mortality rate. In a subgroup analysis based on oxygen equipment at admission, patients admitted on nasal cannula/face masks who did not receive colchicine had a shorter duration on oxygen supply than those who did [Hazard Ratio (HR) = 0.76 (CI 0.59-0.97)]. Using cox-regression analysis, clarithromycin compared to azithromycin in colchicine-treated patients was associated with a higher risk of longer duration on oxygen supply [HR = 1.77 (CI 1.04-2.99)]. Furthermore, we summarized 36 published colchicine studies, including 114,878 COVID-19 patients. Conclusions: COVID-19-hospitalized patients who were given colchicine had poorer outcomes in terms of the duration of supplemental oxygen use and the length of their hospital stay. Therefore, based on these findings, the use of colchicine is not recommended for COVID-19-hospitalized adults.

Impact of weight loss on sexual and psychological functions and quality of life in females with sexual dysfunction: A forgotten avenue.

Objectives: This study aimed to evaluate the impact of weight loss on sexual and psychological health as well as quality of life in females with sexual dysfunction. Materials and methods: The study was done at Delta University for Science and Technology in Gamasa, Egypt, on 40 obese married females having sexual dysfunction. Their age ranged from 20 to 40 years old, with a mean of 28.98 ± 4.96 years. They followed a weight loss program in the form of diet regimen and physical training for 6 months. Anthropometric measures, Arabic Female Sexual Function Index (FSFI), Arabic version of Hospital Anxiety and Depression Scale (HADS), and Arabic version of Short-Form 36 Health Survey (SF-36) were evaluated prior to starting the study, after 3 and 6 months of the study. Results: Statistical analysis revealed significant reductions in anthropometric measures, as well as significant improvements in HADS and SF-36 scores after both 3 and 6 months of weight loss intervention compared to the baseline measurements, while there were significant improvements in sexual arousal, lubrication, patient satisfaction as well as the total score of FSFI after 3 months and contrarily there were no statistically significant changes in any of the FSFI's domains or overall score after 6 months of the weight loss program compared to baseline. Conclusion: Weight loss improves females' anthropometric measures, psychological function and quality of life; however, it has no direct effect on female sexual dysfunction (FSD) after 6 months compared to baseline, so increased awareness of FSD is necessary as this issue suffers from inadequate identification and management.

Effect of Low-Level Laser Therapy on Knee Range of Motion and Functional Abilities After Total Knee Arthroplasty.

OBJECTIVE: The aim of this study was to determine the effectiveness of combined low-level laser therapy (LLL) and rehabilitation in patients following recent total knee replacement (TKR). METHODS: A double-blind randomized controlled study was conducted at the Orthopedic Department of Mansoura University Hospital. Forty-four patients were chosen from a total of 58 patients who met the inclusion criteria and were assigned randomly into control and experimental groups of equal size. Ultimately, 40 patients completed the study (20 from each group). Both groups participated in an intensive functional rehabilitation program, and the experimental group also received LLL therapy around the knee at the incisional line, the medial and lateral intra-articular space, above and below the patella, and at the popliteal fossa at low fluence (6 J/cm2, 650 nm continuous wave) and 60 s per point with a total dose of 48 J per session over 12 treatment sessions for six weeks. Knee range of motion (ROM) was measured with a digital goniometer, and functional abilities were assessed with the Arabic version of the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index. RESULTS: There were significant differences in all variables pre- and post-treatment within each group. Before treatment, there was no significant difference in any of the measured variables between the groups (P>0.05). After treatment, there were significant differences in knee flexion ROM and WOMAC index (P<0.05) but no significant difference in knee extension ROM between the groups (P>0.05). CONCLUSION: The addition of low-level laser therapy to a rehabilitation program post-TKR resulted in substantial enhancements in knee flexion range of motion and the WOMAC index.

Autonomic functions, tinnitus annoyance and loudness, and quality of life: Randomized-controlled responses to bee-humming (vibrational) respiratory training in tinnitus elderly.

BACKGROUND: In chronic subjective tinnitus (CST) studies, the effect of bee-humming respiratory training (BHRT), a type of pranayama breathing technique, on autonomic cardiovascular/respiratory physiological functions (systolic pressure, rates of breathing and pulse, and diastolic pressure), tinnitus annoyance (TA), tinnitus loudness (TL), and quality of life measures as tinnitus handicap inventory (THI) did not receive significant attention. OBJECTIVE: This study aimed to investigate the efficacy of BHRT on TL, THI, TA, and cardiovascular/respiratory autonomic functions in bilateral CST elderly (aged ≥65 years old). THE DESIGN, SETTING, PARTICIPANTS, AND INTERVENTION: The current study employs a prospective, single-blind design; it is a randomized-controlled for-tinnitus behavioral intervention. Forty-six CST elderly subjects were randomly assigned to one of two groups: the BHRT group (23 patients) or the control group (23 patients). The 4-week BHRT intervention was applied 30 min daily. OUTCOME MEASURES: TL, THI, TA, and cardiovascular/respiratory autonomic functions were evaluated. RESULTS: Significant BHRT-induced reductions of all measures were detected in the BHRT group, whereas no significant changes were observed in the controlled elderly group. CONCLUSION: The complementary choice for BHRT is considered an effective method to improve TL, TA, THI, and cardiovascular/respiratory autonomic functions in CST elderly.

The Role of 3D CT Imaging in the Accurate Diagnosis of Lung Function in Coronavirus Patients.

Early grading of coronavirus disease 2019 (COVID-19), as well as ventilator support machines, are prime ways to help the world fight this virus and reduce the mortality rate. To reduce the burden on physicians, we developed an automatic Computer-Aided Diagnostic (CAD) system to grade COVID-19 from Computed Tomography (CT) images. This system segments the lung region from chest CT scans using an unsupervised approach based on an appearance model, followed by 3D rotation invariant Markov-Gibbs Random Field (MGRF)-based morphological constraints. This system analyzes the segmented lung and generates precise, analytical imaging markers by estimating the MGRF-based analytical potentials. Three Gibbs energy markers were extracted from each CT scan by tuning the MGRF parameters on each lesion separately. The latter were healthy/mild, moderate, and severe lesions. To represent these markers more reliably, a Cumulative Distribution Function (CDF) was generated, then statistical markers were extracted from it, namely, 10th through 90th CDF percentiles with 10% increments. Subsequently, the three extracted markers were combined together and fed into a backpropagation neural network to make the diagnosis. The developed system was assessed on 76 COVID-19-infected patients using two metrics, namely, accuracy and Kappa. In this paper, the proposed system was trained and tested by three approaches. In the first approach, the MGRF model was trained and tested on the lungs. This approach achieved 95.83% accuracy and 93.39% kappa. In the second approach, we trained the MGRF model on the lesions and tested it on the lungs. This approach achieved 91.67% accuracy and 86.67% kappa. Finally, we trained and tested the MGRF model on lesions. It achieved 100% accuracy and 100% kappa. The results reported in this paper show the ability of the developed system to accurately grade COVID-19 lesions compared to other machine learning classifiers, such as k-Nearest Neighbor (KNN), decision tree, naïve Bayes, and random forest.

Dietary Pomegranate By-Product Alleviated the Oxidative Stress Induced by Dexamethasone in Laying Hens in the Pre-Peak Period.

This experiment was conducted to assess the inclusion of the by-products of pomegranate peels to ameliorate the harmful impacts of oxidative stress in the pre-peak period of laying hens. For this, 120 local Egyptian strain hens (Inshas hens) aged 24 weeks old were used in four treatments. Pomegranate peel powder was included at 2% and 4% in the diets of laying hens subjected to oxidative injuries induced by dexamethasone compared with negative and positive control groups for 12 weeks. The addition of pomegranate peel powder (PPP) reduced the adverse effects of oxidative stress induced by dexamethasone on body weight (p = 0.006) and egg production (p = 0.010) comparing to the positive control. Additionally, pomegranate peel powder had a significant positive lowering effect on plasma cholesterol (p < 0.001) and triglyceride contents (p = 0.005) compared to control groups. The lipid peroxidation indicators (MDA) were reduced, but the antioxidative enzymes (SOD, CAT, and GPx) and total antioxidant blood capacity were improved with PPP. Based on the obtained data, the present research recommends using dietary PPP up to 4% to mitigate adverse oxidative stress effects in the pre-peak laying period and as a sustainable and economical approach for agricultural development.