Explore the vast range of titles available.

Artificial intelligence (AI) is increasingly being used in medicine to enhance the speed and accuracy of disease diagnosis and treatment. AI-based image analysis is expected to play a crucial role in future healthcare facilities and laboratories, offering improved precision and cost-effectiveness. As technology advances, the requirement for specialized software knowledge to utilize AI applications is diminishing. Our study will examine the advantages and challenges of employing AI-based image analysis in the field of immunology and will investigate whether physicians without software expertise can use MS Azure Portal for ANA IIF test classification and image analysis. This is the first study to perform Hep-2 image analysis using MS Azure Portal. We will also assess the potential for AI applications to aid physicians in interpreting ANA IIF results in immunology laboratories. The study was designed in four stages by two specialists. Stage 1: creation of an image library, Stage 2: finding an artificial intelligence application, Stage 3: uploading images and training artificial intelligence, Stage 4: performance analysis of the artificial intelligence application. In the first training, the average pattern identification accuracy for 72 testing images was 81.94%. After the second training, this accuracy increased to 87.5%. Patterns Precision improved from 71.42 to 79.96% after the second training. As a result, the number of correctly identified patterns and their accuracy increased with the second training process. Artificial intelligence-based image analysis shows promising potential. This technology is expected to become essential in healthcare facility laboratories, offering higher accuracy rates and lower costs.

Lower respiratory tract (LRT) infections require rapid and accurate diagnosis. While bacterial culture remains the gold standard, multiplex PCR (mPCR) enables faster and more sensitive detection of multiple pathogens. This study evaluates the Bio-Speedy mPCR panel for 18 bacteria in comparison to conventional culture. A total of 100 LRT samples were analyzed. Complete concordance between the methods was observed in 85% of samples, with mPCR detecting pathogens slightly more frequently (62% vs. 53%). Discrepancies were primarily due to prior antibiotic therapy, low bacterial loads, colonization, or pathogens not included in the PCR panel. The sensitivity and specificity of mPCR were 79.3% and 96.8%, respectively, with negative agreement at 98.9% and positive agreement at 57.0%. Considering culture-negative but clinically relevant PCR-positive results, the sensitivity improved to 98.1% and the positive agreement to 86.7%. mPCR offers early pathogen detection, enabling timely therapy and potentially improving outcomes, particularly in intensive care settings. While culture remains indispensable for viable pathogen identification, combining mPCR with conventional methods provides complementary information, particularly when prior antibiotic use or the presence of fastidious pathogens may compromise culture results. Careful consideration of cost, patient population, and clinical context is recommended for optimal implementation of mPCR panels.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is routinely used in clinical microbiology for rapid species identification; however, its potential to support early antimicrobial decision-making remains under active investigation. Rapid discrimination of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-susceptible Staphylococcus aureus (MSSA) at the time of identification could facilitate earlier optimization of antimicrobial therapy and infection control measures. In this study, MALDI-TOF MS spectral data were analyzed to evaluate supervised machine learning–based differentiation of MRSA and MSSA. A total of 91 S. aureus isolates (37 MRSA and 54 MSSA) were included, with methicillin susceptibility determined by the cefoxitin disk diffusion test according to EUCAST guidelines and used as the reference standard. MALDI-TOF MS spectra were acquired following standard on-plate extraction, subjected to quality control, and preprocessed prior to analysis. Principal component analysis demonstrated partial but consistent separation between MRSA and MSSA isolates. A Random Forest classifier was trained and validated using stratified 10-fold cross-validation, achieving an overall classification accuracy of 81.3% and a receiver operating characteristic area under the curve of 0.916. Class-specific analysis revealed high precision for MRSA (95.5%) and excellent recall for MSSA (98.1%). These findings indicate that MALDI-TOF MS combined with machine learning can provide clinically relevant information for rapid MRSA/MSSA differentiation and may serve as a cost-free decision-support approach in routine clinical microbiology workflows, complementing standard phenotypic susceptibility testing.

Background/Objectives: Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections present a significant clinical challenge due to limited therapeutic options and high transmission potential. This study aimed to identify the resistance genes associated with carbapenemase production in CRKP isolates and evaluate the in vitro activity of ceftazidime/avibactam (CZA) and meropenem/vaborbactam (MEV), among other β-lactam/β-lactamase inhibitor combinations. Methods: Between October 2021 and June 2022, a total of 504 CRKP isolates were grown from patient samples in intensive care units. When duplicate patient samples were removed, the remaining 89 isolates were included in the study. Bacterial identification and antimicrobial susceptibility testing were per-formed using MALDI-TOF, Phoenix M50, and disk diffusion methods, following EUCAST guidelines. PCR analyses identified carbapenemase genes such as OXA-48, NDM, and KPC. Results: The most prevalent carbapenemase gene was OXA-48 (79.8%), followed by NDM (21.4%) and KPC (17.9%). The susceptibility rate to CZA was 82.0%, significantly higher than MEV (10.1%). All isolates were resistant to piperacillin/tazobactam and ceftolozane/tazobactam. Among MEV-resistant isolates, most carried the OXA-48 gene, while NDM was common in CZA-resistant isolates. Conclusions: CZA demonstrates high efficacy against OXA-48-producing CRKP, making it a viable treatment option in settings where OXA-48 predominates. The limited activity of MEV in this study underscores the need for molecular surveillance of resistance mechanisms to guide empirical therapy.

Candida auris has emerged as a significant fungal threat due to its rapid worldwide spread since its first appearance, along with its potential for antimicrobial resistance and virulence properties. This study was designed to examine virulence characteristics, the efficacy of ceragenins, and biofilm-derived drug resistance in seven C. auris strains isolated from Turkish intensive care patients. It was observed that none of the tested strains exhibited proteinase or hemolysis activity; however, they demonstrated weak phospholipase and esterase activity. In addition, all strains were identified as having moderate to strong biofilm formation characteristics. Upon determining the minimum inhibitory concentrations (MIC) of ceragenins, it was discovered that CSA-138 exhibited the highest effectiveness with a MIC range of 1–0.5 µg/mL, followed by CSA-131 with a MIC of 1 µg/mL. Also, antimicrobial agents destroyed mature biofilms at high concentrations (40–1280 µg/mL). The investigation revealed that the strains isolated from Türkiye displayed weak exoenzyme activities. Notably, the ceragenins exhibited effectiveness against these strains, suggesting their potential as a viable treatment option.

Introduction Candida auris has emerged as a significant global health threat due to its resistance to multiple antifungal agents and its prominent role in healthcare-associated infections. This study aims to compare the clinical characteristics, risk factors, antifungal resistance profiles, and mortality rates of candidemia caused by C. auris and non-auris Candida spp. (NACS). Materials and methods This retrospective cohort study was conducted at a tertiary care hospital from 2021 to 2024. Patients aged 18 years and older with positive blood cultures for Candida spp. were included. Demographic data, comorbidities, risk factors, mortality rates, and treatment protocols were analyzed. Results A total of 1,088 candidemia cases were included in the study ( C. auris : 126 cases, NACS: 962 cases). The length of hospital stay was significantly longer in the C. auris group compared to the NACS group (50.98 ± 38.79 vs. 33.05 ± 25.57 days, p  < 0.001). Independent risk factors for C. auris candidemia included longer hospitalization before candidemia (OR 1.01, 95% CI 1.01–1.02, p  < 0.001), chronic obstructive pulmonary disease (OR 1.89, 95% CI 1.07–3.31, p  = 0.026), prior antifungal use within 30 days (OR 1.92, 95% CI 1.22–3.03, p  = 0.005), and ICU admission (OR 2.08, 95% CI 1.10–3.92, p  = 0.023). Antifungal resistance rates among C. auris isolates were 96.49% for fluconazole, 72.81% for amphotericin B, and 25.89% for caspofungin. The 30-day mortality rate was lower in the C. auris group (48.4%) compared to the NACS group (60.2%) ( p  = 0.012). Conclusion Although crude 30-day mortality was lower in the C. auris group, adjusted analysis showed comparable 30-day mortality between the C. auris and NACS groups. These findings highlight the increasing clinical burden of C. auris and support accurate species identification, local antifungal susceptibility surveillance, and rigorous infection-control measures. Clinical trial number Not applicable.

Background: Typing methods are essential in understanding of the transmission dynamics of Neisseria gonorrhoeae. Several typing methods were described including opa-typing. Goals: The goal of this study was to type all of the strains we isolated in the recent past by using auxo-, sero-, and opa-typing, and to compare the discriminatory power of these methods. Study: Auxotyping, serotyping, and opa-typing were performed for 56 N. gonorrhoeae strains isolated from male patients with urethritis. Results: A total of 9 auxotypes and 33 serovars were detected. Combining the 2 systems, a total of 45 distinct auxotype/serovar (A/S) classes were identified. The most common A/S class was NR/Bsty (5 strains). Fifty-five distinct patterns were detected by opa-typing. Two strains that have been isolated 16 months apart gave identical patterns with opa-typing and their A/S class was also identical (NR/Bsty). Simpson's index of diversity was found as 0.664, 0.961, 0.987, and 0.999 for auxotyping, serotyping, A/S class, and opa-typing, respectively. Conclusions: Opa-typing is a potential useful method for typing N. gonorrhoeae as a result of its high discriminatory power, rapidity, ease and relatively lower cost.

Candida auris has emerged as a significant fungal threat due to its rapid worldwide spread since its first appearance, along with its potential for antimicrobial resistance and virulence properties. This study was designed to examine virulence characteristics, the efficacy of ceragenins, and biofilm-derived drug resistance in seven C. auris strains isolated from Turkish intensive care patients. It was observed that none of the tested strains exhibited proteinase or hemolysis activity; however, they demonstrated weak phospholipase and esterase activity. In addition, all strains were identified as having moderate to strong biofilm formation characteristics. Upon determining the minimum inhibitory concentrations (MIC) of ceragenins, it was discovered that CSA-138 exhibited the highest effectiveness with a MIC range of 1–0.5 µg/mL, followed by CSA-131 with a MIC of 1 µg/mL. Also, antimicrobial agents destroyed mature biofilms at high concentrations (40–1280 µg/mL). The investigation revealed that the strains isolated from Türkiye displayed weak exoenzyme activities. Notably, the ceragenins exhibited effectiveness against these strains, suggesting their potential as a viable treatment option.