Search

Antimicrobial resistance (AMR) presents a significant threat to global healthcare. Proteus mirabilis causes catheter-associated urinary tract infections (CAUTIs) and exhibits increased antibiotic resistance. Traditional diagnostics still rely on culture-based approaches, which remain time-consuming. Here, we study the use of machine learning (ML) to classify bacterial resistance profiles using straightforward microscopic imaging of P. mirabilis for resistance classification integrated with radiomics feature analysis and ML models. From 150 P. mirabilis strains isolated from catheters of patients diagnosed with a CAUTI, 30 % displayed multidrug resistance using the standardized disk diffusion method, and 60 % showed strong biofilm activity in microtiter plate assays. As a more rapid alternative, we introduce wavelet-based and regular microscopy imaging with feature extraction/selection, following image preprocessing steps (image denoising, normalization, and mask creation). These features enable training and testing different ML models with 5-fold cross-validation for P. mirabilis resistance classification. From these models, the Random Forest (RF) algorithm exhibited the highest performance with ACC = 0.95, specificity = 0.97, sensitivity = 0.88, and AUC = 0.98 among the other ML algorithms considered in this study for P. mirabilis resistance classification. This successful application of wavelet-based feature Radiomics analysis with RF model represents a crucial step towards a precise, rapid, and cost-effective method to distinguish antibiotic resistant P. mirabilis strains., Competing Interests: Declaration of competing interest The authors of this manuscript have no conflicts of interest to declare, and all the listed authors have actively contributed to the research and preparation of this manuscript. We have included the names and affiliations of all authors in the manuscript file., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Introduction: (67)Ga citrate has been extensively used to detect infection and inflammation since 1971. However, its clinical utility is compromised due to several limitations. The present project explored whether (68)Ga-apo-transferrin ((68)Ga-TF), when prepared in vitro, is a useful agent for positron emission tomography (PET) imaging of bacterial infection., Methods: An infection was induced in male Wistar rats by injecting 5 × 10(5) CFU units of Staphyococcus aureus in the right thigh muscle. (68)Ga-TF was synthesized by mixing (68)GaCl(3) with apo-transferrin (TF, 2 mg) in sodium carbonate (0.1 M, pH 7.0) and incubating at 40 °C for 1 h. Animals were injected with 10-15 MBq of (68)Ga-TF containing approximately 0.2 mg TF and imaged at different time intervals using Siemens Biograph PET-CT., Results: When (68)Ga-TF were injected in the infected rats, the infection lesion was detectable within 20 min post injection. The biodistribution showed the uptake at the lesion increased with time as shown by significantly increased standard uptake values for up to 4 h post injection. There was a considerable decrease in the background activity during the same period of study, giving higher target-to-muscle ratios. Blood pool activity at 3 h post injection was insignificant. (68)GaCl(3) (when not conjugated to TF) did not localize at the infection lesion up to 120 min post injection., Conclusion: The preliminary results suggest that (68)Ga-TF is capable of detecting S. aureus infection in the rat model, within an hour after intravenous injection., (Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.)

We report a case of staghorn nephrolithiasis that evolved into xanthogranulomatous pyelonephritis with perinephric abscess, nephrobronchial fistula, and lung abscess. The patient was an intravenous drug abuser who tested positive for human immunodeficiency virus, without evidence of acquired immunodeficiency syndrome. He presented with a 2-month history of untreated repeated episodes of left flank pain and hyperpyrexia. Treatment involved left nephrectomy, debridement of abscess, tube drainage, and intravenous antibiotics. The patient illustrates the need to consider untreated nephrolitiasis as a predisposing factor for pulmonary complications.