Publications by authors named "Muhammad Hamza Saeed"

Introduction: Hematopoietic stem cell transplantation (HSCT) is a widely used transplant method for different cancerous and non-cancerous conditions, particularly when conventional treatments fail. Again, Epstein-Barr Virus (EBV), one of the major contributors to gastric carcinoma can cause post-transplantation lymphoproliferative disease (PTLD) after transplantations. However, the global prevalence of EBV-associated PTLD in HSCT recipients is yet to be determined.

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Background This retrospective cross-sectional analysis assessed the regulatory role of microRNA-375 (miR-375) in the insulin signaling pathway and its clinical relevance for the treatment of type 2 diabetes mellitus (T2DM) in a Pakistani cohort. Methodology The study analyzed data from 300 adult patients with clinically confirmed T2DM to identify associations between miR-375 expression levels, insulin signaling pathway-specific biomarkers, glycemic indices, and treatment response. Results The mean miR-375 levels were found to be inversely correlated with HbA1c (r = -0.

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This retrospective observational cohort study aimed to evaluate the comparative effectiveness of dual antiplatelet therapy (DAPT) versus single antiplatelet therapy (SAPT) in patients presenting with acute stroke at a tertiary care center in Muzaffarabad. A total of 250 patients aged 40-89 years (mean age=63.89; n=136; 54.

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This retrospective observational study assessed the comparative effectiveness of high-flow nasal cannula (HFNC) therapy versus noninvasive positive pressure ventilation (NIPPV) in a cohort of 300 patients diagnosed with acute hypoxemic respiratory failure (AHRF). The mean age of the participants was 53.92 years (SD = 22.

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 (​​​​​​) infection (CDI) poses a tremendous clinical challenge, especially in patients with recurrent disease and antibiotic resistance. Fecal microbiota transplantation (FMT) has become a new therapeutic strategy for restoring gut microbiota and decreasing CDI recurrence. The study aims to assess the clinical effectiveness of FMT in adult subjects with recurrent or refractory CDI, determine its effect on gut microbiome diversity, and track safety outcomes and rates of recurrence post-treatment.

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Typically, load forecasting models are trained in an offline setting and then used to generate predictions in an online setting. However, this approach, known as batch learning, is limited in its ability to integrate new load information that becomes available in real-time. On the other hand, online learning methods enable load forecasting models to adapt efficiently to new incoming data.

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