Search Results (1,331)

Legionella pneumophila (L. pneumophila) infection is characterized by a wide spectrum of manifestations, from influenza-like illness to life-threatening atypical pneumonia with multiorgan failure. The aim of our study was the assessment of in vitro and ex vivo neutrophil activation in L. pneumophila infections, as well as the role of neutrophils’ peptides such as LL-37 in infection. The ability of neutrophils to form ex vivo extracellular traps (NETs) in response to bacterial infection was examined by immunofluorescence. In parallel, patients’ sera, as well as opsonized standard L. pneumophila strains, were used for in vitro activation of neutrophils from healthy individuals. The serum levels of interleukins were assessed using the LEGENDplexTM Multi-Analyte Flow Assay Kit. Furthermore, citrullinated cf-DNA as a marker of neutrophil extracellular traps (NETs) was detected in the serum of patients with acute infection. It was demonstrated that neutrophils released NETs in vitro and ex vivo upon L. pneumophila (interaction in an autophagy-independent manner. Notably, IL-1b was detected on NETs, but an antimicrobial peptide LL-37 was absent. The lack of antimicrobial activity failed to inhibit bacterial proliferation. In addition, in vitro and ex vivo NETs formation was observed during the Clarithromycin treatment. Those NETs were decorated with bioactive antimicrobial peptide LL-37, which inhibits bacterial proliferation. The findings provide evidence that neutrophils release NETs in vitro and ex vivo by expressing the IL1β protein in them. The lack of expression of the antimicrobial peptide LL-37 on the NETs demonstrates the inability of the cells to inhibit proliferation, and consequently the elimination of L. pneumophila. Clarithromycin plays a dual role in the elimination. Full article

Background: Carbapenem-resistant Klebsiella pneumoniae (CRKp) is a critical global health threat due to its multidrug resistance, primarily driven by carbapenemase production. Rapid and accurate detection of carbapenemases is essential for effective treatment and infection control. This study evaluates the validity of the NG-Test CARBA 5, a rapid immunochromatographic assay, for detecting five major carbapenemases (KPC, NDM, VIM, IMP, OXA-48-like) in clinical CRKp isolates. Methods: Clinical isolates of CRKp were collected from various clinical specimens at the Military Medical Academy in Belgrade, Serbia, between January 2023 and October 2024. Detection of carbapenemases was performed using NG-Test CARBA 5, while PCR served as the reference method. Diagnostic performance was assessed by calculating sensitivity, specificity, and Cohen’s kappa coefficient. Results: Among 312 isolates, OXA-48-like was the most prevalent carbapenemase. NG-Test CARBA 5 showed high sensitivity (98.7%) and specificity (100%) overall, with excellent agreement for NDM (κ = 0.947), OXA-48-like (κ = 0.957), and KPC (κ = 0.978). However, it failed to detect VIM in five PCR-positive isolates, suggesting potential limitations. Conclusions: NG-Test CARBA 5 is a rapid and reliable tool for detecting major carbapenemases in CRKp, though its performance for VIM detection requires further investigation. This assay has the potential to improve clinical diagnostics and strengthen infection control in settings with high antimicrobial resistance. Full article

Respiratory syncytial virus (RSV) remains a leading cause of pneumonia in young children in Mexico and worldwide. To investigate RSV dynamics in Mexico, we conducted a multicenter study from August 2021 to July 2023 in six hospitals across five States, analyzing respiratory samples from children under five years with pneumonia. Multiplex RT-PCR identified 203 RSV-positive cases, of which 123 were RSV-B and 80 RSV-A. Interestingly, 77% of the collected samples showed evidence of coinfection with other respiratory pathogens, with rhinovirus, Haemophilus influenzae, and Streptococcus pneumoniae being the most common. Also, RSV-B dominated in 2021–2022, whereas RSV-A prevailed in 2022–2023, mirroring trends observed in the United States. Sequences of the genes encoding G and F proteins showed that RSV-A lineages were more diverse, with A.D.1, A.D.1.8, and A.D.5.2 being frequently detected. In contrast, nearly all RSV-B sequences belonged to lineage B.D.E.1. Finally, ancestral state inference suggests repeated introductions from the USA and other North American countries, with limited evidence of sustained local circulation. These findings show different trends in RSV circulation between two consecutive seasons and the importance of genomic surveillance to monitor RSV diversity, evaluate vaccine impact, and inform public health strategies in Mexico’s evolving post-pandemic respiratory virus landscape. Full article

Hypervirulent Klebsiella pneumoniae (hvKp) has emerged as a significant public health concern, yet rare sublineages remain poorly characterized. Here, we described a K30-ST198 hvKp sublineage identified in four isolates from two patients, including three sequential strains (K30B1, K30B2, K30B3) recovered over eight months from recurrent liver abscesses and one strain (K30-HUMV1) from a urinary tract infection. All isolates exhibited a yYpermucoviscous phenotype and resistance restricted to ampicillin and amoxicillin. Screening with the eazyplex hvKp assay detected ybt and rmpA in all strains, yielding a virulence score of 1. Biofilm production was strong in K30B1, K30B2, moderate in K30-HUMV1, but weak in K30B3. In the Galleria mellonella infection model, K30B1 showed higher virulence than the other isolates. Whole-genome sequencing identified the ICEKp1 carrying hypervirulence-associated genes (ybt, pagO, rmpAC, iroBCDN) together with additional virulence factors (fim, mrkD, uge, ureA, wabG, wcaJ, mliC), while antibiotic resistance genes were limited to fosA and bla_SHV-77. Protein structures and their functional domains were predicted using AlphaFold v3.0.1 and ColabFold v1.5.5, based on pLDDT scores, providing further insights into gene functionality. This work represents one of the first detailed characterizations of K30-ST198 hvKp, underscoring the need for integrated genomic, phenotypic, and structural approaches in hvKp surveillance. Full article

Background: Antimicrobial resistance (AMR) is a major global health threat, particularly in surgical site infections (SSIs), where multidrug-resistant (MDR) pathogens complicate treatment. Objective: This study aimed to identify antimicrobial resistance genes and assess their prevalence in bacterial species causing SSIs in Lebanon. Materials and Methods: The present research is a multicenter and prospective study that included patients who developed SSIs after surgery in seven hospitals, within the period of January 2024–September 2024. Bacterial isolates from wound swabs or tissue samples were identified using standard microbiological methods. Antimicrobial susceptibility was tested by disk diffusion, and resistance genes were detected by PCR. Data were analyzed using Statistical Package for the Social Sciences (SPSS). Results: Among 6933 surgical patients, 63 developed SSIs (0.91%; 95% CI [0.70–1.15]). Gram-negative bacteria predominated (73%), mainly Escherichia coli and Pseudomonas aeruginosa, while Gram-positive isolates accounted for 27%, mostly Staphylococcus aureus. MDR was observed in 71% of Gram-positive and 61% of Gram-negative isolates. The most frequent genes were mecA in S. aureus (100%) and coagulase-negative staphylococci (83.3%); bla_CTX-M in E. coli, Klebsiella pneumoniae, and Enterobacter cloacae (100%); and bla_NDM in E. cloacae (100%) and Acinetobacter baumannii (60%). bla_KPC was less common, and no isolates carried Imipenemase (IMP), Verona integron-encoded metallo-β-lactamase (VIM), and Oxacillinase-48-like β-lactamase (OXA-48). Conclusions: This study highlights the high prevalence of antibiotic resistance in agents causing SSIs in Lebanese hospitals. Resistance genes, particularly mecA, bla_CTX-M, and blaNDM, were highly prevalent in SSI pathogens, underscoring the urgent need for surveillance and judicious antibiotic use in Lebanese hospitals. Full article

Background: Urinary tract infections (UTIs) are among the most common hospital- and community-acquired infections, creating a substantial healthcare burden due to recurrence, complications, and rising antimicrobial resistance. Accurate diagnosis and timely antimicrobial therapy are essential. This study aimed to identify trends in the etiology, treatment, and resistance patterns of UTIs through a retrospective analysis of urine isolates processed at the Laboratory of Microbiology at University Hospital St. George in Plovdiv, the largest tertiary care and reference microbiology center in Bulgaria, between 2017 and 2022. Materials and Methods: A retrospective single-center study was performed at the hospital’s Microbiology Laboratory. During the study period, 74,417 urine samples from 25,087 hospitalized patients were screened with the HB&L UROQUATTRO system. Positive specimens were cultured on blood agar, Eosin-Methylene Blue, and chromogenic media. Identification was performed using biochemical assays, MALDI-TOF MS, and the Vitek 2 Compact system. Antimicrobial susceptibility testing included disk diffusion, MIC determination, broth microdilution (for colistin), and Vitek 2 Compact, interpreted according to EUCAST standards. Descriptive analysis and temporal resistance trends were evaluated with regression models, and interrupted time-series analysis was applied to assess COVID-19-related effects. Results: Out of 10,177 isolates, Gram-negative bacteria predominated (73%), with Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis as the leading pathogens. Among Gram-positives, Enterococcus faecalis was the most frequent. In the post-COVID-19 period, ESBL production increased in E. coli (34–38%), K. pneumoniae (66–77%), and P. mirabilis (13.5–24%). Carbapenem resistance rose in K. pneumoniae (to 40.6%) and P. aeruginosa (to 24%), while none was detected in E. coli. Colistin resistance increased in K. pneumoniae but remained absent in E. coli and P. aeruginosa. High-level aminoglycoside resistance in E. faecalis was stable (~70%), and vancomycin resistance in E. faecium rose from 4.6% to 8.9%. Conclusions: Both community- and hospital-acquired UTIs in Southeastern Bulgaria are increasingly linked to multidrug-resistant pathogens, particularly ESBL-producing and carbapenem-resistant Enterobacterales. Findings from the region’s largest referral center highlight the urgent need for continuous surveillance, rational antibiotic use, and novel therapeutic approaches. Full article

This study aimed to evaluate short-term clinical outcomes in COVID-19 pneumonia patients using parameters derived from a commercial deep learning-based automatic detection algorithm (DLAD) applied to serial chest radiographs (CXRs). We analyzed 391 patients with COVID-19 who underwent serial CXRs during isolation at a residential treatment center (median interval: 3.57 days; range: 1.73–5.56 days). Patients were categorized into two groups: the improved group (n = 309), who completed the standard 7-day quarantine, and the deteriorated group (n = 82), who showed worsening symptoms, vital signs, or CXR findings. Using DLAD’s consolidation probability scores and gradient-weighted class activation mapping (Grad-CAM)-based localization maps, we quantified the consolidation area through heatmap segmentation. The weighted area was calculated as the sum of the consolidation regions’ areas, with each area weighted by its corresponding probability score. Change rates (Δ) were defined as per-day differences between consecutive measurements. Prediction models were developed using Cox proportional hazards regression and evaluated daily from day 1 to day 7 after the subsequent CXR acquisition. Among the imaging factors, baseline probability and ΔProbability, ΔArea, and ΔWeighted area were identified as prognostic indicators. The multivariate Cox model incorporating baseline probability and ΔWeighted area demonstrated optimal performance (C-index: 0.75, 95% Confidence Interval: 0.68–0.81; integrated calibration index: 0.03), with time-dependent AUROC (Area Under Receiver Operating Curve) values ranging from 0.74 to 0.78 across daily predictions. These findings suggest that the Δparameters of DLAD can aid in predicting short-term clinical outcomes in patients with COVID-19. Full article

In neonatal care, donor human milk (DHM) is used when maternal milk is unavailable or insufficient. In several countries, including Germany, raw (i.e., unpasteurised) DHM is occasionally administered under specific clinical conditions. However, the lack of standardised, evidence-based microbiological testing protocols raises concerns about the reliability of safety assessments for this high-risk patient group. The objective of this study was to assess the performance of four culture-based microbiological methods for detecting Enterobacterales in donor human milk, using both spiked samples and raw milk. We compared the detection limits of four culture-based microbiological methods, with and without enrichment, using spiked DHM samples and 93 raw DHM samples from a single donor (limited generalisation). Artificially inoculated samples contained defined concentrations of E. coli, K. pneumoniae, and S. ureilytica. Detection limits varied by several orders of magnitude (2.86 × 10² CFU/mL to 4.90 × 10⁰ CFU/mL). In real samples, enrichment-based methods detected Gram-negative pathogens in four out of ninety-three samples (three S. ureilytica, one P. juntendi); direct plating detected none. Increasing the sample volume and applying enrichment improved detection sensitivity. Whole-genome sequencing confirmed species identity and showed that the S. ureilytica isolates from a single donor were clonally related, indicating a recurring detection pattern and underscoring the need for longitudinal microbiological monitoring. In view of the new EU SoHO Regulation classifying DHM as a Substance of Human Origin, these findings highlight the urgent need for standardised, sensitive protocols to ensure neonatal safety. Full article

Background: Chronic and acute wounds are often colonized by polymicrobial biofilms, delaying healing and complicating treatment. Rapid, non-invasive detection of pathogenic bacteria is therefore crucial for timely and targeted therapy. This study investigated porphyrin-producing bacterial species using the handheld cureVision imaging system. Methods: In this study, 20 clinically relevant, porphyrin-producing bacterial species were cultured on δ-aminolevulinic acid (ALA)-supplemented agar and analyzed using the handheld cureVision imaging system under 405 nm excitation. Both Red-Green-Blue (RGB) and fluorescence images were acquired under ambient daylight conditions, and fluorescence signals were quantified by grayscale intensity analysis. Results: All tested species exhibited measurable red porphyrin-associated fluorescence, with the highest intensities observed in Klebsiella pneumoniae, Klebsiella oxytoca, Veillonella parvula, and Alcaligenes faecalis. A standardized detectability threshold of 0.25, derived from negative controls, enabled semi-quantitative comparison across species. Statistical analysis confirmed that the fluorescence intensities of all bacterial samples were significantly elevated compared to the control (Wilcoxon signed-rank test and sign test, both p < 0.001; median intensity = 0.835, IQR: 0.63–0.975). Conclusions: These results demonstrate that the cureVision system enables robust and reliable detection of porphyrin-producing wound bacteria, supporting its potential as a rapid, non-invasive diagnostic method for assessing wound colonization and guiding targeted clinical interventions. Full article

The expanded newborn screening (NBS) program in the Russian Federation, launched in 2023, includes the detection of severe forms of T- and B-cell immunodeficiencies via TREC/KREC quantification. We report a rare case of a male infant having multiple congenital anomalies and lymphopenia identified through this program. Genetic testing revealed a 25.8 Mb terminal deletion spanning 13q31.2–qter, consistent with 13q deletion syndrome. Initial NBS revealed reduced TREC levels, prompting further evaluation. The patient exhibited a complex phenotype, including central nervous system malformation (alobar holoprosencephaly), severe congenital heart disease, renal hypoplasia, limb and genitourinary anomalies, and facial dysmorphism. Postnatal complications included pneumonia, pleuritis, and chylothorax. Flow cytometry demonstrated mild T- and B-cell lymphopenia. The genomic defect was characterized using long-read third-generation sequencing, enabling precise breakpoint identification and accurate mapping of deleted genes. The deletion was confirmed via subtelomeric FISH analysis. The patient died at 7 months of age due to the progression of underlying congenital anomalies and associated complications. Our findings broaden the clinical characterization of distal 13q deletion syndrome and demonstrate the value of long-read sequencing in structural chromosomal analysis. They further highlight the difficulties of caring for neonates having complex malformations and immune dysfunction. Given the potential for both primary and secondary immune disturbances, comprehensive immunological evaluation should be considered in patients having 13q deletion syndrome to improve diagnostic accuracy and inform appropriate clinical management. Full article

Early and accurate detection of pneumonia from chest X-ray images is essential for improving treatment and clinical outcomes. Medical imaging datasets often exhibit class imbalance and uncertainty in feature extraction, which complicates conventional classification methods and motivates the use of advanced approaches combining deep learning and fuzzy logic. This study proposes a hybrid approach that combines deep learning architectures (VGG16, EfficientNetV2, MobileNetV2, ResNet50) for feature extraction with fuzzy logic-based classifiers, including Fuzzy C-Means, Fuzzy Decision Tree, Fuzzy KNN, Fuzzy SVM, and ANFIS (Adaptive Neuro-Fuzzy Inference System). Feature selection techniques were also applied to enhance the discriminative power of the extracted features. The best-performing model, ANFIS with MobileNetV2 features and Gaussian membership functions, achieved an overall accuracy of 98.52%, with Normal class precision of 97.07%, recall of 97.48%, and F1-score of 97.27%, and Pneumonia class precision of 99.06%, recall of 98.91%, and F1-score of 98.99%. Among the fuzzy classifiers, Fuzzy SVM and Fuzzy KNN also showed strong performance with accuracy above 96%, while Fuzzy Decision Tree and Fuzzy C-Means achieved moderate results. These findings demonstrate that integrating deep feature extraction with neuro-fuzzy reasoning significantly improves diagnostic accuracy and robustness, providing a reliable tool for clinical decision support. Future research will focus on optimizing model efficiency, interpretability, and real-time applicability. Full article

Addressing the critical challenge in the differential diagnosis of severe inflammatory lung diseases, we propose a novel methodology for the analysis of macrophage surface receptors, CD68 and CD206, using specific non-antibody ligands. We developed a non-antibody alternative for the fluorometric detection of CD68+ cells, focusing on macrophages as key functional markers in inflammatory processes. Our marker based on dioleylphosphatidylserine (DOPS), a specific ligand to CD68, was incorporated into a liposomal delivery system. The specificity of this DOPS-based ligand can be precisely modulated by the liposome’s composition and the polyvalent presentation of the ligand. We synthesized a series of fluorescently-labeled DOPS-based ligands and developed a liposome-based sandwich fluorometric assay. This assay enables the isolation and quantification of CD68 receptor presence from bronchoalveolar lavage fluid (BALF). The results confirmed the specific binding of DOPS/lecithin liposomes to CD68+ cells compared to control lecithin systems. Furthermore, the incorporation of PEGylated ‘stealth’ liposomes significantly enhanced binding specificity and facilitated the generation of distinct binding profiles, which proved valuable in differentiating various inflammatory conditions. This approach yielded unique binding profiles of PS-based ligands to CD68+ cells, which varied significantly among a broad range of respiratory conditions, including primary ciliary dyskinesia, bronchial asthma, bronchitis, bacterial infection, pneumonia, and bronchiectasis. Confocal Laser Scanning Microscopy demonstrated selective binding and intracellular localization of the DOPS-based marker within CD68+ macrophages from BALF samples of patients with bronchitis or asthma. The binding parameters of this multivalent composite ligand with the CD68 receptor are comparable to those of antibodies. The inherent binding specificity of phosphatidylserine may offer a sufficient and viable alternative to conventional antibodies. Our results demonstrate the remarkable potential of this novel DOPS-based assay as a complementary tool for the developing non-antibody-based systems for the differential diagnosis of the respiratory diseases, warranting further investigation in larger clinical studies. Full article

Background/Objectives: Carbapenem-resistant Gram-negative bacilli (CR-GNB) pose a growing challenge to public health worldwide due to limited treatment options. This cross-sectional study investigated the characteristics of CR-GNB isolated from clinical specimens in Lagos, Nigeria. Methods: Gram-negative bacilli (GNB) and clinical data were obtained from three multi-specialist private hospitals between March and June 2023. The GNB were identified using the Analytical Profile Index (API) and investigated for CR-GNB by disk diffusion. Antimicrobial resistance patterns and carbapenemase gene data for presumptive carbapenemase-producing Gram-negative bacilli (CP-GNB) were analyzed using Vitek-2 and polymerase chain reaction (PCR). Results: Of 317 GNB, 29.0% (n = 92) were CR-GNB. Significantly higher numbers of CR-GNB were reported from the intensive care unit and oncology department (p = 0.009). Of all CR-GNB, 17 isolates (18.5%) were classified as presumptive CP-GNB. In this subgroup, resistance rates of ampicillin/sulbactam (100.0%) and trimethoprim/sulfamethoxazole (100.0%) were highest. Ten (10) CP-GNB were confirmed, representing 3.15% of all GNB tested. Seven isolates of New Delhi Metallo-β-lactamase (bla_NDM) were found among P. aeruginosa, K. pneumoniae, E. coli, and A. baumannii. The bla_NDM was identified in strains classified as extensively drug-resistant (XDR) and pandrug-resistant. Conversely, the bla_KPC was detected solely in multidrug-resistant and XDR strains. Conclusions: Emerging CR-GNB, specifically CP-GNB, in Nigeria emphasize the need for specific therapeutic management of infected patients. Antimicrobial stewardship and long-term surveillance efforts must be implemented in healthcare settings, as well as improved, accelerated microorganism identification techniques. Full article

Background: Class B carbapenemases confer high-level resistance to carbapenems in Klebsiella pneumoniae. In Brazil, data on the national burden and geographic distribution of these genes among clinical K. pneumoniae isolates are sporadic. We performed a systematic review and meta-analysis to estimate the prevalence of MβL genes in Brazilian clinical K. pneumoniae. Methods: We searched SciELO, PubMed, ScienceDirect and LILACS for original studies published between 2006 and 2024 reporting molecular detection of MβL in clinical K. pneumoniae isolates from Brazil. Articles were independently screened, along with the extracted data and appraised study quality using Joanna Briggs Institute checklists. A random-effects meta-analysis estimated the pooled prevalence of MβL producers and assessed heterogeneity and publication bias. Results: Fifteen studies including 3.533 clinical K. pneumoniae isolates met inclusion criteria. Overall, 402 isolates (11.4%) harbored MβL genes, yielding a pooled prevalence of 44.6%. Subgroup analysis demonstrated highest prevalence in the Southeast. bla_NDM was the dominant variant (present in 14/15 studies), with bla_VIM and bla_IMP rarely detected. Meta-regression revealed an inverse association between sample size and reported prevalence, and no significant publication bias was observed. Conclusions: MβLs, particularly NDM, are widespread in Brazilian clinical K. pneumoniae but show marked regional heterogeneity driven by differences in study design, laboratory capacity, and outbreak dynamics. Urgent expansion of standardized and multicenter molecular surveillance, including allele-specific detection, and strengthened laboratory infrastructure are needed and may inform targeted infection-control and antimicrobial-stewardship interventions. Full article

Background: Inborn errors of immunity (IEIs) are a heterogeneous group of rare disorders caused by genetic defects in one or more components of the immune system. The Jeffrey Modell Foundation’s (JMF) Ten Warning Signs are widely used for early detection; however, their diagnostic sensitivity is limited. Machine learning (ML) approaches may improve prediction accuracy by integrating additional clinical variables into decision-making frameworks. Methods: This retrospective study included 298 participants (98 IEI, 200 non-IEI) evaluated at a university-affiliated clinical immunology clinic between January and December 2020. IEI diagnoses were confirmed using European Society for Immunodeficiencies (ESID) criteria. Two datasets were constructed: one containing only JMF criteria and another combining JMF criteria with additional clinical variables. Four ML algorithms—random forest (RF), k-nearest neighbors (k-NN), support vector machine (SVM), and naive Bayes (NB)—were trained and optimized using nested 5-fold stratified cross-validation repeated three times. Performance metrics included accuracy, sensitivity, specificity, F1 score, Youden Index, and the area under the receiver operating characteristic curve (AUROC). SHapley Additive exPlanations (SHAP) were applied to evaluate feature importance. Results: Using only JMF criteria, the best-performing model was SVM (accuracy: 0.90 ± 0.04, sensitivity: 0.93 ± 0.05, AUROC: 0.91 ± 0.02). With the addition of clinical variables, the SVM achieved superior performance (accuracy: 0.94 ± 0.03, sensitivity: 0.97 ± 0.03, AUROC: 0.99 ± 0.00), outperforming both the classical JMF criteria (accuracy: 0.91, sensitivity: 0.87, AUROC: 0.90) and the JMF-only SVM model. SHAP analysis identified family history of early death, pneumonia history, and ICU admission as the most influential predictors. Conclusions: ML models, particularly SVM integrating JMF criteria with additional clinical variables, substantially improve IEI prediction compared with classical JMF criteria. Implementation of such models in clinical settings may facilitate earlier diagnosis and timely intervention, potentially reducing morbidity and healthcare burden in IEI patients. Full article