Background: Clostridioides difficile ( C. difficile ) infection (CDI) has become a global health issue with increasing prevalence, severity, and mortality rates. While studies and strategies have been implemented to control the incidence, frequent outbreaks have been reported in Europe, North America, and Asia due to the emergence of hypervirulent strains and increased antibiotic use. Objective: This review aims to determine the prevalence, drug resistance, and prevalent strains of CDI. Design: Systematic review and meta-analysis conducted in accordance with PRISMA 2020 guidelines. Data sources and methods: A search was conducted in three major databases. Data were categorized into three topics: detection of toxigenic C. difficile in stool; C. difficile typing using multi-locus sequence typing (MLST) or ribotyping (RT); and antimicrobial susceptibility testing. Results: The pooled proportion of toxigenic C. difficile was 15.00% (95% confidence interval (CI): [12.55; 17.92]) among patients presenting with diarrhea who were tested for CDI across predominantly hospital-based settings, with Africa reporting the highest (29.34%), followed by North America (19.39%) and Asia (13.36%). Ribotypes RT591, RT027 and RT014/020 were the most prevalent strains; hypervirulent strains, such as ST1 (RT027) and ST11 (RT078), were also prevalent. Resistance to vancomycin and fidaxomicin was 6.60% (95% CI: [3.19; 10.98]) and 0.72% (95% CI: [0.00; 3.06]), respectively. Conclusion: There is a high prevalence of toxigenic C. difficile causing diarrhea globally, especially in Africa, the Americas, Asia, and Europe. The low in vitro resistance rates observed for vancomycin and fidaxomicin suggest their effectiveness in treating CDI. The rise of RT591, RT014/020, ST1, ST3, and others suggests the rapid evolution of C. difficile . Incorporating both ribotyping and multi-locus sequencing into surveillance and epidemiological studies will be crucial for understanding its molecular epidemiology. Trial registration : The review has been registered with the International Prospective Register of Systematic Reviews, registration number: CRD420261277259.
The rapid rise of artificial intelligence (AI) in both scientific research and everyday life over the last decade has renewed interest in how AI-driven methods can support fungal research, diagnostics, and clinical microbiology. At the same time, advances in imaging technologies and increasing access to large collections of microscopy and medical imaging data have created new opportunities for automated image analysis. In this review, we examine the recent development of AI-based image analysis methods for microscopy in general, with a particular focus on fungal imaging applications. We discuss how deep learning approaches, especially Convolutional Neural Networks (CNNs) and U-nets, have transformed image classification and object detection tasks by enabling automated recognition of fungal cells, spores, hyphae, and infection-related structures with high accuracy. Finally, we explore emerging developments in the field, particularly the introduction of vision transformers and hybrid transformer-based architectures.
Tuberculosis (TB) remains a major global health challenge despite the availability of effective antimicrobial therapy and standardized multidrug treatment regimens. Although current treatment approaches achieve favorable outcomes in many patients, considerable variability in treatment response, bacterial clearance, relapse, and treatment failure persists. Such variability cannot be explained solely by drug efficacy and instead reflects the complex biological environment in which anti-tuberculosis therapy operates. Treatment outcomes are influenced by multiple interconnected determinants, including host-related factors, pharmacological variability, lesion heterogeneity, and pathogen-specific characteristics. Host factors such as immune status, diabetes, HIV infection, and malnutrition can significantly alter disease progression and therapeutic response. Pharmacokinetic variability may result in substantial differences in systemic and tissue drug exposure among patients receiving similar guideline-based treatment regimens. At the site of infection, heterogeneous lesion microenvironments influence drug penetration and bacterial survival, while pathogen-related factors, including bacterial burden, persistence, drug tolerance, and antimicrobial resistance, further contribute to variability in treatment outcomes. Understanding the interplay among host, pathogen, lesion, and pharmacological factors provides important opportunities for improving treatment precision and therapeutic effectiveness. This review examines the major determinants influencing tuberculosis treatment outcomes and discusses emerging precision-therapy strategies, including therapeutic drug monitoring, patient stratification, lesion-informed treatment approaches, and host-directed interventions. Recognizing and addressing biological variability may represent an important step toward more individualized and effective tuberculosis management.
Background Aminoglycosides are widely used in dual antipseudomonal therapy for acute pulmonary exacerbations in cystic fibrosis (CF). Due to altered pharmacokinetics in CF, achieving recommended pharmacokinetic/pharmacodynamic (PK/PD) targets is challenging and the impact of target attainment on clinical outcomes remains unclear. Objectives To evaluate whether currently recommended aminoglycoside dosing regimens in CF achieve PK/PD targets in clinical practice, and whether target attainment correlates with clinical improvements in CF patients. Design/methods A two-year, single-center cohort study was conducted in adult CF patients receiving aminoglycoside during acute exacerbation. Aminoglycoside levels were obtained to estimate PK parameters. Clinical symptoms and pulmonary function were assessed at admission (baseline) and discharge. Results Fourteen treatment courses were analyzed among nine patients. Amikacin (n=10, mean dose 30.9 ± 2 mg/kg), or gentamicin (n=4, mean dose 10.5 ± 0.7 mg/kg) were administered. The target C max :MIC ratio of 8-10 was achieved in 50% of amikacin courses and none of the gentamicin courses. Most patients improved clinically, evident by symptoms’ resolution and increased ppFEV 1 . Target attainment was associated with a numerically greater ppFEV 1 improvement, though not statistically significant (P=0.29). Conclusions The pre-defined PK/PD target was attained in less than half of the cases treated, underscoring the need for optimized dosing strategies. Nonetheless, clinical improvement occurred regardless of target attainment. This highlights the need of larger randomized controlled studies to define the relationship between aminoglycoside PK/PD target achievement and clinical outcomes among CF patients.
Enterococcal bacteremia and endovascular infections remain difficult to treat because of intrinsic antimicrobial tolerance, increasing resistance, and frequent involvement of high-inoculum or deep-seated infection. While β-lactams generally demonstrate limited bacterial killing activity against enterococci when used alone, accumulating experimental and clinical data suggest that selected β-lactams may enhance the activity of companion agents, particularly daptomycin. This narrative review summarizes the mechanistic rationale, preclinical evidence, and available clinical data supporting adjunctive β-lactams for enterococcal bacteremia and endovascular infections. The strongest clinical evidence supports ampicillin plus ceftriaxone for Enterococcus faecalis infective endocarditis, whereas emerging data suggest that selected β-lactams may potentiate high-dose daptomycin against vancomycin-resistant Enterococcus faecium . Proposed mechanisms include complementary penicillin-binding protein inhibition, alterations in cell envelope physiology, increased antimicrobial binding, and suppression of resistance emergence. However, available clinical data are derived largely from retrospective studies and remain heterogenous with respect to patient populations, infectious syndromes, β-lactam selection, dosing strategies, and treatment duration. Current evidence favors a phenotype-directed approach rather than routine combination therapy for all enterococcal bloodstream infections. Adjunctive β-lactams appear most justifiable in patients with persistent bacteremia, endovascular infection, high-inoculum disease, elevated daptomycin minimum inhibitory concentrations, prosthetic material, or other features associated with microbiologic failure or relapse, whereas uncomplicated bacteremia may derive limited benefit. Important questions remain regarding optimal patient selection, β-lactam choice, and duration of therapy. Given the practical and financial barriers to conducting randomized trials in this population, mechanistic, translational, and observational studies will likely remain the foundation of real-world clinical decision-making.
