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Alzheimer's disease is the extremely popular cause of dementia that causes memory loss. People who have Alzheimer's disease suffer from a disorder in neurodegenerative which leads to loss in many brain functions. Nowadays researchers prove that early diagnosis of the disease is the most crucial aspect to enhance the care of patients' lives and enhance treatment. Traditional approaches for diagnosis of Alzheimer's disease (AD) suffers from long time with lack both efficiency and the time it takes for learning and training. Lately, deep-learning-based approaches have been considered for the classification of neuroimaging data correlated to AD. In this paper, we study the use of the Convolutional Neural Networks (CNN) in AD early detection, VGG-16 trained on our datasets is used to make feature extractions for the classification process. Experimental work explains the effectiveness of the proposed approach.

Introduction: Bleomycin is a widely used chemotherapy which is used in the treatment of many tumors. Lung injury especially pulmonary fibrosis is considered as one of the most common side effects of it.Aim of the work: We aimed to evaluate the possible effect of Green tea versus Metformin on Bleomycin induced pulmonary injury in adult male albino rats.Materials and Methods: 48 adult male albino rats were used in this study. The rats were divided into six groups of eight rats each. Control group, Bleomycin group, Bleomycin with Green tea group, Bleomycin with Metformin group, green tea group and Metformin group. Bleomycin was administered intra-tracheally to ensure induction of fibrosis. All animals were sacrificed after 14 days of starting the experiment. The lung sections were prepared and stained with H&E stain, Mallory′s trichrome stain and immunohistochemical staining for alpha smooth muscle actin (α –SMA). Morphometric measurements and statistical analysis were performed.Results: There was marked multifocal distortion of the lung architecture with significant increase of area % of collagen deposition and α –SMA staining in Bleomycin group compared to control group. There was noticeable partial preservation of normal lung structure in combined Bleomycin with either Metformin or Green tea groups compared to Bleomycin group. The effect of Green tea was more obvious than Metformin which still showed more areas of congestion and hemorrahge in the lung. In addition to significant decrease in area % of collagen deposition and α-SMA in both combined Bleomycin with either Green tea or Metformin groups compared to Bleomycin group. While both Metformin and Green tea groups appeared as the control.Conclusion: We can conclude that administration of either Green tea or Metformin can attenuate Bleomycin induced lung injury. Green tea produced more protective effect than Metformin.

Background Elderly patients often need post-acute care after hospital discharge. Involvement of social workers can positively affect the discharge planning process. Aim To investigate the effect of screening patients at risk for post-acute care needs by social workers on time with respect to social workers’ notification, length of stay and delays in discharge compared to usual care. Methods Cluster randomized stepped wedge trial design for five clusters (wards) and two steps (control to intervention) was used. A total of 400 patients (200 per period) with high risk of post-acute care needs (defined as Post-Acute Care Discharge score, PACD ≥ 7) were included. Social workers performed a screening to decide about self-referral to their services (intervention period), which was compared to a highly structured standard SW notification by physicians and nurses (control period). A Generalized Estimating Equations model adjusted the clustering and baseline differences. Results A total of 139 patients were referred to social services (intervention: n = 76; control: n = 63). Time to social workers’ notification was significantly shorter in the intervention period when adjusted for all the differences in baseline (Mdn 1.2 vs 1.7, Beta = -0.73, 95%-CI 1.39 to -0.09). Both the length of stay and the delayed discharge time in nights showed no significant differences (Mdn 10.0 vs 9.1, Beta = -0.12, 95%-CI 0.46 to .22 nights 95%-CI, resp. Mdn 0.0 vs 0.0, Beta = .11, 95%-CI -0.64 to 0.86). Conclusion Screening speeded up social workers’ notification but did not accelerate the discharge processes. The screening by social workers might show process improvement in settings with less structured discharge planning.