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During 2020-2021, countries in Latin America and the Caribbean reported clinical emergence of carbapenemase-producing Enterobacterales that had not been previously characterized locally, increased prevalence of carbapenemases that had previously been detected, and co-production of multiple carbapenemases in some isolates. These increases were likely fueled by changes related to the COVID-19 pandemic, including empirical antibiotic use for potential COVID-19-related bacterial infections and healthcare limitations resulting from the rapid rise in COVID-19 cases. Strengthening antimicrobial resistance surveillance, epidemiologic research, and infection prevention and control programs and antimicrobial stewardship in clinical settings can help prevent emergence and transmission of carbapenemase-producing Enterobacterales.

The global rise of carbapenem-resistant Acinetobacter baumannii (CRAB) strains poses a critical challenge to healthcare systems due to limited therapeutic options and high mortality rates, especially in intensive care settings. This review explores the epidemiological landscape and molecular mechanisms driving carbapenem resistance, including the production of diverse beta-lactamases (particularly OXA-type enzymes), porin loss, efflux pump overexpression, and mutations in antibiotic targets. Emerging treatment strategies are discussed, such as the use of new beta-lactam–beta-lactamase inhibitor combinations (e.g., sulbactam–durlobactam), siderophore cephalosporins, next-generation polymyxins, as well as novel agents like zosurabalpin and rifabutin (BV100). Alternative approaches—including phage therapy, antimicrobial peptides, CRISPR-based gene editing, and nanoparticle-based delivery systems—are also evaluated for their potential to bypass traditional resistance mechanisms. Furthermore, advances in artificial intelligence and multi-omics integration are highlighted as tools for identifying novel drug targets and predicting resistance profiles. Together, these innovations represent a multifaceted strategy to overcome CRAB infections, yet their successful implementation requires further clinical validation and coordinated surveillance efforts. This analysis highlights the urgent need for continued investment in innovative treatments and effective resistance monitoring to limit the spread of CRAB and protect the effectiveness of last-line antibiotics.

Although many clinically significant strains belonging to the family Enterobacteriaceae fall into a restricted number of genera and species, there is still a substantial number of isolates that elude this classification and for which proper identification remains challenging. With the current improvements in the field of genomics, it is not only possible to generate high-quality data to accurately identify individual nosocomial isolates at the species level and understand their pathogenic potential but also to analyse retrospectively the genome sequence databases to identify past recurrences of a specific organism, particularly those originally published under an incorrect or outdated taxonomy. We propose a general use of this approach to classify further clinically relevant taxa, i.e., Phytobacter spp., that have so far gone unrecognised due to unsatisfactory identification procedures in clinical diagnostics. Here, we present a genomics and literature-based approach to establish the importance of the genus Phytobacter as a clinically relevant member of the Enterobacteriaceae family.

Table 01b) [7]. [...]Blue-Poli (BP), designed by Becker and Pillonetto (BP), combines the disk elution test with the sharpness of the bromothymol blue turn and can be prepared quickly, showing 100% sensitivity, specificity, and accuracy for Enterobacterales isolates. [...]it can be easily implemented as a screening test for Enterobacterales polymyxin susceptibility in the routine of small and medium laboratories in lower-middle-income countries, providing fast and reliable results. Liu, Y-Y; Wang, Y; Walsh, TR; Yi, L-X; Zhang, R; Spencer, J; Doi, Y; Tian, G; Dong, B; Huang, X; Yu, L-F; Gu, D; Ren, H; Chen, X; Lv, L; He, D; Zhou, H; Liang, Z; Liu, J-H; Shen, J. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Two-site evaluation of the colistin broth disk elution test to determine colistin in vitro activity against gram-negative bacilli.

Background Between November 2013 and June 2014, 56 cases of bacteremia (15 deaths) associated with the use of Total Parenteral Nutrition (TPN) and/or calcium gluconate (CG) were reported in four Brazilian states. Methods We analyzed 73 bacterial isolates from four states: 45 from blood, 25 from TPN and three from CG, originally identified as Acinetobacter baumannii, Rhizobium radiobacter, Pantoea sp. or Enterobacteriaceae using molecular methods. Results The first two bacterial species were confirmed while the third group of species could not be identified using standard identification protocols. These isolates were subsequently identified by Multi-Locus Sequence Analysis as Phytobacter diazotrophicus , a species related to strains from similar outbreaks in the United States in the 1970’s. Within each species, TPN and blood isolates proved to be clonal, whereas the R. radiobacter isolates retrieved from CG were found to be unrelated . Conclusion This is the first report of a three-species outbreak caused by TPN contaminated with A. baumannii , R. radiobacter and P. diazotrophicus . The concomitant presence of clonal A. baumannii and P. diazotrophicus isolates in several TPN and blood samples, as well as the case of one patient, where all three different species were isolated simultaneously, suggest that the outbreak may be ascribed to a discrete contamination of TPN. In addition, this study highlights the clinical relevance of P. diazotrophicus , which has been involved in outbreaks in the past, but was often misidentified as P. agglomerans .

BackgroundThe gold standard for microbial detection in prosthetic joint infections is the multiple culture of the peri-prosthetic tissue. The fluid cultures after sonication can improve the recovery of the microorganisms.ObjectiveThe aim of this study was to evaluate the sonication technique with a plastic bag and the effect of refrigeration on microorganism detection with conventional culturing, MALDI-TOF MS and qPCR assay on an orthopedic screw model.MethodsWe produced biofilms of Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans on orthopedic screws, which were stored under different conditions and temperatures before sonication. After sonication, the mass spectrometry by MALDI-TOF, qPCR and culture protocols was performed using the sonicated fluid, for detecting the microorganisms involved in the biofilm.ResultsThe bacterial bioburden decreased by approximately one log after the refrigeration period, in the screws containing P. aeruginosa and S. aureus biofilms. All the microorganisms involved in the screw biofilms were detected with MALDI-TOF and qPCR. Significant reductions in CFU counts occurred only in groups stored in the plastic bag, indicating that changes in temperature and humidity may favor cell death. However, this variation is not important for this model as it did not affect the detection owing to the high counts obtained.ConclusionMicrobial identification by MALDI-TOF in sonicated fluid is feasible. With qPCR, there were no differences between the detection in the screws processed immediately or after refrigeration. It is necessary to consider whether or not the refrigeration period would affect microbial recovery in an explanted prosthesis.

Background The escalating threat of AMR demands a paradigm shift in antimicrobial prescribing practices. The application programming interface (API) is conceived as an advanced system, integrating artificial intelligence and machine learning, to optimize clinical decision-making in the context of antimicrobial therapy. This study outlines the development and evaluation of the software, emphasizing its potential impact on antimicrobial stewardship. Methods The API was meticulously constructed in two phases. In the initial phase, an algorithm leveraging decision flow, developed by a collaboration of information technology experts, infectious disease and microbiology specialists, was designed. This algorithm accounts for a comprehensive array of variables influencing antimicrobial treatment outcomes. Subsequently, a Machine Learning model was employed to assess the probability of success for each available antimicrobial drug. The second phase involved a rigorous evaluation through ten hypothetically described clinical cases, assessed independently by five infectious disease specialists (IDP team) in a double-blinded study. Results generated were then compared with the antimicrobial prescriptions made by the IDP team. Results Utilizing the World Health Organization's AWaRe classification system as a benchmark, the API demonstrated a 50% prescription at both the Access and Watch categories, with a 0% allocation in the Reserve category. In comparison, the IDP team exhibited an 11.9% prescription in the Access, 73.9% at Watch, and 14.5% at Reserve category. Conclusion Despite potential disparities between expert opinions and the software, the proposed system, characterized by its conservative nature, holds promise in refining and validating clinical decisions. Moreover, the implementation of the API has the potential to mitigate selective pressure that contributes to antimicrobial resistance, thus fortifying antimicrobial stewardship practices.

The acoustic sensitivity of Autism Spectrum Disorder (ASD) individuals highly impacts their intelligibility in noisy urban environments. In this Letter, the disturbance sensing level is examined with perceptual listening tests that demonstrate the impact of their append High Internal Noise (HIN) profile on intelligibility. This particular sensing level is then proposed as additional aid to ASD diagnosis. In this Letter, a novel intelligibility enhancement scheme is also introduced for ASD particular circumstances. For this proposal, harmonic features estimated from speech signal frames are considered as center frequencies of auditory filterbanks. A gain factor is further applied to the output of the filtered samples. The experimental results demonstrate that the proposal improved the acoustic intelligibility of ASD and Neurotypicals (NT) people considering four acoustic noises at different signal-to-noise ratios.

Phytobacter diazotrophicus is an emerging opportunistic pathogen associated with hospital outbreaks and a reservoir of antimicrobial resistance genes; however, its clonal epidemiology remains poorly understood. Accurate identification and rapid clonal typing are crucial for infection control. Core genome MLST (cgMLST) is the genomic gold standard; however, it is both costly and time-consuming. Fourier-transform infrared (FT-IR) spectroscopy using the IR Biotyper® emerges as a rapid and accessible typing alternative. This study evaluated the performance of the IR Biotyper® in discriminating P. diazotrophicus outbreak isolates, compared to cgMLST. Eight epidemiologically relevant isolates, including two from a total parenteral nutrition (TPN) outbreak and four from a hemodialysis clinic, along with two outliers, were analyzed. Its identification was confirmed by API20E, MALDI-TOF MS, nifL gene qPCR, and WGS. Both cgMLST, based on 7,755 conserved genes, and the Fourier Transform Infrared (FT-IR) Spectroscopy by IR Biotyper® were used for clonal typing, with the spectral cutoff empirically determined based on known clonal isolates. Both methodologies demonstrated remarkable agreement in detecting clonal clusters. The two TPN outbreak isolates showed 23 allele differences (ADs) by cgMLST and consistently clustered according to the IR Biotyper. Similarly, the four isolates from the outbreak at hemodialysis clinic formed homogeneous clusters by both methods (5-27 ADs by cgMLST). The outlier isolates were consistently discriminated. FT-IR spectroscopy (IR Biotyper®) proved promising and complementary to cgMLST for typing P. diazotrophicus in outbreak scenarios, offering a rapid and cost-effective alternative for detecting clonal events. Its applicability in routine epidemiological surveillance is significant. Phytobacter diazotrophicus is an emerging opportunistic pathogen of increasing concern in clinical environments, associated with hospital outbreaks and carrying antimicrobial resistance genes. Rapid detection and precise clonal characterization are essential for infection control and epidemiological surveillance. However, these are challenging for less-understood species. Genomic methods, such as cgMLST, are the gold standard, but their cost and time limitations hinder routine application in outbreak response. This study evaluated the IR Biotyper system, a rapid and accessible phenotypic tool that uses Fourier Transform Infrared Spectroscopy, compared to cgMLST for clonal typing of P. diazotrophicus. Our findings demonstrate a remarkable agreement between the two methods in identifying clonal clusters. This validation suggests the potential of the IR Biotyper as an effective tool for real-time screening and active surveillance of P. diazotrophicus in clinical settings. This enables a more agile response to outbreaks and aids in managing antimicrobial resistance, reserving high-resolution genomic analyses for more in-depth investigations.