Increasing antimicrobial resistance of nosocomial pathogens is becoming a serious threat to public health. To control the spread of this resistance, it is necessary to detect β-lactamase-producing organisms in the clinical setting. The aims of the study were to design a PCR assay for rapid detection of clinically encountered β-lactamase genes described in Enterobacteriaceae and Gram-negative non-fermenting bacteria. The functionality of proposed primers was verified using eight reference strains and 17 strains from our collection, which contained 29 different β-lactamase genes. PCR products of the test strains were confirmed by Sanger sequencing. Sequence analysis was performed using bioinformatics software Geneious. Overall, 67 pairs of primers for detecting 12 members of the class C β-lactamase family, 15 members of class A β-lactamases, six gene families of subclass B1, one member each of subclasses B2, B3 and class D β-lactamases were designed, of which 43 pairs were experimentally tested in vitro. All 29 β-lactamase genes, including 10 oxacillinase subgroups, were correctly identified by PCR. The proposed set of primers should be able to specifically detect 99.7% of analyzed β-lactamase subtypes and more than 79.8% of all described β-lactamase genes.
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http://dx.doi.org/10.1093/femsle/fnab068 | DOI Listing |
Cancer Rep (Hoboken)
January 2025
Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Background: Bioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.
Aim: In this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs).
Methods And Results: Common DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes.
Kaohsiung J Med Sci
January 2025
Department of Pathology, Duke University Medical Center, Durham, North Carolina, USA.
SET domain bifurcated histone lysine methyltransferase 1 (SETDB1/ESET), a pivotal H3K9 methyltransferase, has been extensively studied since its discovery over two decades ago. SETDB1 plays critical roles in immune regulation, including B cell maturation, T-cell activity modulation, and endogenous retrovirus (ERV) silencing. While essential for normal immune cell function, SETDB1 overexpression in cancer cells disrupts immune responses by suppressing tumor immunogenicity and facilitating immune evasion.
View Article and Find Full Text PDFJ Antimicrob Chemother
January 2025
Research Laboratory, Botswana Harvard Health Partnership, Gaborone, Botswana.
Objectives: We assessed HIV-1 drug resistance profiles among people living with HIV (PLWH) with detectable viral load (VL) and on dolutegravir-based antiretroviral therapy (ART) in Botswana.
Methods: The study utilised available 100 residual HIV-1 VL samples from unique PLWH in Francistown who had viraemia at-least 6 months after initiating ART in Botswana's national ART program from November 2023 to January 2024. Viraemia was categorized as low-level viraemia (LLV) (VL: 200-999 copies/mL) or virologic failure (VF) (VL ≥1000 copies/mL).
Mol Genet Genomic Med
January 2025
The State Key Laboratory for Complex Severe and Rare Diseases, the State Key Sci-Tech Infrastructure for Translational Medicine, Peking Union Medical College Hospital, Beijing, China.
Background: Primary ciliary dyskinesia (PCD) is a rare autosomal recessive disorder characterized by dysfunction of motile cilia. While approximately 50 genes have been identified, around 25% of PCD patients remain genetically unexplained; elucidating the pathogenicity of specific variants remains a challenge.
Methods: Whole exome sequencing (WES) and Sanger sequencing were conducted to identify potential pathogenic variants of PCD.
Per Med
January 2025
Department of Clinical Pharmacy, Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet.
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