Publications by authors named "M A Akhmedov"

Patients undergoing hematopoietic cell transplantation (HCT) have an increased risk of developing severe infections. In recent years, bloodstream infections caused by Gram-negative bacteria have been increasingly reported among HCT recipients, and many of these infections are caused by bacterial strains of the Enterobacterales order. Among these pathogens, particularly concerning are the multidrug-resistant Enterobacterales (MDRE), such as Extended Spectrum β-lactamase-producing Enterobacterales and Carbapenem-resistant Enterobacterales, since infections caused by these pathogens are difficult to treat due to the limited antimicrobial options and are associated with worse transplant outcomes.

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Infections are major cause of morbidity and mortality in patients with multiple myeloma. Current treatment landscape of newly-diagnosed multiple myeloma includes different classes of drugs, such as proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies, all of which are characterized by specific risk and pattern of infectious complications. Additionally, autologous and allogeneic hematopoietic cell transplantation, widely used in the treatment of multiple myeloma, are complex procedures, carrying a significant risk of complications, and mainly infections.

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Fluoroquinolones (FQ) has been used after allogeneic hematopoietic stem cell transplantation (allo-HCT) for decades. This study on 284 allo-HCT recipients aimed to analyze the impact of FQ on pre-engraftment BSI. A total of 154 patients were colonized with resistant gram-negative bacteria, and 130 patients were not.

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Background: Bloodstream infections (BSIs) are major cause of morbidity and mortality after allogeneic hematopoietic cell transplantation (allo-HCT). This study aimed to analyze the incidence, etiology, risk factors and outcomes of post-engraftment BSI in allo-HCT recipients.

Materials And Methods: The retrospective study included 261 patients with documented engraftment after first allo-HCT performed from January 2018 till September 2021.

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Summary: Accessing the collection of perturbed gene expression profiles, such as the LINCS L1000 connectivity map, is usually performed at the individual dataset level, followed by a summary performed by counting individual hits for each perturbagen. With the metaLINCS R package, we present an alternative approach that combines rank correlation and gene set enrichment analysis to identify meta-level enrichment at the perturbagen level and, in the case of drugs, at the mechanism of action level. This significantly simplifies the interpretation and highlights overarching themes in the data.

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