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Although MALDI-TOF mass spectrometry (MS) is considered as the gold standard for rapid and cost-effective identification of microorganisms in routine laboratory practices, its capability for antimicrobial resistance (AMR) detection has received limited focus. Nevertheless, recent studies explored the predictive performance of MALDI-TOF MS for detecting AMR in clinical pathogens when machine learning techniques are applied. This chapter describes a routine MALDI-TOF MS workflow for the rapid screening of AMR in foodborne pathogens, with Campylobacter spp. as a study model.

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This research focused on distinguishing distinct matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) spectral signatures of three Enterococcus species. We evaluated and compared the predictive performance of four supervised machine learning algorithms, K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), to accurately classify Enterococcus species. This study involved a comprehensive dataset of 410 strains, generating 1640 individual spectra through on-plate and off-plate protein extraction methods. Although the commercial database correctly identified 76.9% of the strains, machine learning classifiers demonstrated superior performance (accuracy 0.991). In the RF model, top informative peaks played a significant role in the classification. Whole-genome sequencing showed that the most informative peaks are biomarkers connected to proteins, which are essential for understanding bacterial classification and evolution. The integration of MALDI-TOF MS and machine learning provides a rapid and accurate method for identifying Enterococcus species, improving healthcare and food safety.

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Objective: MALDI-TOF-MS facilitates the identification of microorganisms from positive cultures in a timely and accurate manner. It eliminates the necessity for the application of biochemicals and operates on the principle of proteomics. It decreases the time required to report culture results. Prompt detection and notification of the pathogen, prior to the disclosure of antimicrobial susceptibilities, could potentially shorten the duration until the initial antibiotic adjustment is necessary, thereby influencing patients' clinical prognoses. Methodology: Fifty patients in the conventional arm and one hundred patients in the interventional arm were compared in a pre and post quasi-experimental study conducted at a tertiary care centre in North India. Patients with positive cultures from medical wards and intensive care units were included. Comparing the time to first antibiotic modification after culture positivity, MALDI-TOF-MS-based identification, and clinical outcomes in both arms was the primary objective. Antibiotic modifications, escalation, and de-escalation were all recorded. Results: The intervention arm exhibited a substantially shorter median time to first antibiotic modification (2010 mins vs 2905 mins, p=0.002) than the conventional arm. In the interventional group, a total of 44 out of 100 antibiotic modifications were implemented. Of these, 19 (43.3%) were determined solely by the MALDI report, without the anticipation of susceptibility assessments. De-escalation of antibiotics constituted the pre-dominant form of modification (47.4%). The difference between the 27% and 32% mortality rates in the intervention arm and the conventional arm was not statistically significant (p=0.52). Conclusion: MALDI-TOF-MS facilitates the modification of antibiotics early on. The primary benefit lies in the reduction of superfluous antibiotic usage. Early organism identification and reporting prior to the availability of susceptibility results did not result in any mortality benefit. This strategy, when combined with a strong antimicrobial stewardship programme, can aid in the reduction of antibiotic use.

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The venom of the Odontobuthus doriae scorpion, prevalent in East Asia and Iran, has not been fully characterized. This study provides the first proteomic profile of O. doriae venom to explore its potential as a medical. 2D-PAGE analysis revealed 96 protein spots with isoelectric points from 3 to 9 and molecular weights between 6.6 to 205 kDa. Fourteen toxin fractions were isolated via HPLC, and SDS-PAGE showed seven protein bands ranging from 3.8 to 182 kDa. MALDI-TOF MS identified Peptide 1 and Peptide 2, resembling Hemoglobin beta-2 chain and Chaperonin HSP60 and suggest potential therapeutic applications for P1 and P2.

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Staphylococcus species are widespread in poultry environments and can cause various infections, often when the host's defences are compromised. This manuscript reports on a co-infection of chickens with Staphylococcus lentus and Staphylococcus aureus associated with an outbreak of arthritis, synovitis, and osteomyelitis in an organic broiler breeder flock in Austria. Clinically, the affected flock showed weakness, lethargy, lameness, and increased mortality. Post-mortem examinations identified purulent arthritis and femoral head necrosis. Bacteriological analysis using MALDI-TOF MS identified both S. aureus and S. lentus in the affected joints. Antibiotic resistance testing revealed significant resistance, particularly in S. lentus. Histological analysis showed severe inflammation and bacterial colonies in the joints. While S. aureus is a common pathogen in poultry, S. lentus is less frequently reported. This study emphasises the need for detailed bacterial characterisation in outbreaks to better understand the role of less common pathogens like S. lentus. Further research is necessary to elucidate the impact of S. lentus on poultry health and its role in causing arthritis and synovitis, highlighting the importance of comprehensive investigation in such outbreaks.

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This study provides an emended description of Acinetobacter faecalis, a species previously described based on a single isolate (YIM 103518T) from elephant feces in China. Our emended description is based on 15 novel isolates conspecific with the A. faecalis type strain, obtained from eight cattle farms in the Czech Republic. The A. faecalis strains have relatively small genomes (≈2.5-2.7 Mbp), with a GC content of 36.3-36.7 mol%. Core genome-based phylogenetic analysis showed that the 15 strains, together with the type strain of A. faecalis, form a distinct and internally coherent phylogroup within the genus. Pairwise genomic ANIb values for the 16 A. faecalis strains were 97.32-99.04 %, while ANIb values between the genomes of the 16 strains and those of the other Acinetobacter spp. were ≤ 86.2 %. Analysis of whole-cell MALDI-TOF mass spectra supported the distinctness and cohesiveness of the taxon. The A. faecalis strains could be differentiated from the other validly named Acinetobacter spp. by the absence of hemolytic activity along with their ability to grow at 37 °C and on L-aspartate, ethanol, and L-glutamate but not at 41 °C or on adipate or 2,3-butanediol. Reduced susceptibility to sulfamethoxazole, trimethoprim and/or streptomycin was shown in eight strains, along with the presence of corresponding antibiotic resistance genes. In conclusion, this study provides a comprehensive description of A. faecalis and demonstrates its occurrence in cattle feces. Though the ecological role of A. faecalis remains unknown, our results show its ability to acquire antibiotic resistance genes, likely as an adaptation to antibiotic selection pressure in livestock farms.

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BACKGROUND: Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning for the rapid detection of ceftazidime-avibactam (CZA) resistance in KP to improve clinical decision-making processes. METHODS: Out of 107,721 bacterial samples, 675 specimens of KP with suspected multi-drug resistance were selected. These specimens were collected from a tertiary hospital and four secondary hospitals between 2022 and 2023 to evaluate CZA resistance. We used MALDI-TOF MS and machine learning to develop an AI-CDSS with enhanced speed of resistance detection. RESULTS: Machine learning models, especially light gradient boosting machines (LGBM), exhibited an area under the curve (AUC) of 0.95, indicating high accuracy. The predictive models formed the core of our newly developed AI-CDSS, enabling clinical decisions quicker than traditional methods using culture and antibiotic susceptibility testing by a day. CONCLUSIONS: The study confirms that MALDI-TOF MS, integrated with machine learning, can swiftly detect CZA resistance. Incorporating this insight into an AI-CDSS could transform clinical workflows, giving healthcare professionals immediate, crucial insights for shaping treatment plans. This approach promises to be a template for future anti-resistance strategies, emphasizing the vital importance of advanced diagnostics in enhancing public health outcomes.

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Burkholderia pseudomallei is the causative agent of melioidosis, a disease highly endemic to Southeast Asia and northern Australia, though the area of endemicity is expanding. Cases may occur in returning travelers or, rarely, from imported contaminated products. Identification of B. pseudomallei is challenging for laboratories that do not see this organism frequently, and misidentifications by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and automated biochemical testing have been reported. The in vitro diagnostic database for use with the Vitek MS has recently been updated to include B. pseudomallei and we aimed to validate the performance for identification in comparison to automated biochemical testing with the Vitek 2 GN card, quantitative real-time polymerase chain reaction (qPCR) targeting the type III secretion system, and capsular polysaccharide antigen detection using a lateral flow immunoassay (LFA). We tested a "derivation" cohort including geographically diverse B. pseudomallei and a range of closely related Burkholderia species, and a prospective "validation" cohort of B. pseudomallei and B. cepacia complex clinical isolates. MALDI-TOF MS had a sensitivity of 1.0 and specificity of 1.0 for the identification and differentiation of B. pseudomallei from related Burkholderia species when a certainty cutoff of 99.9% was used. In contrast, automated biochemical testing for B. pseudomallei identification had a sensitivity of 0.83 and specificity of 0.88. Both qPCR and LFA correctly identified all B. pseudomallei isolates with no false positives. Due to the high level of accuracy, we have now incorporated MALDI-TOF MS into our laboratory's B. pseudomallei identification workflow.IMPORTANCEBurkholderia pseudomallei causes melioidosis, a disease associated with high morbidity and mortality that disproportionately affects rural areas in Southeast Asia and northern Australia. The known area of endemicity is expanding and now includes the continental United States. Laboratory identification can be challenging which may result in missed or delayed diagnoses and poor patient outcomes. In this study, we compared mass spectrometry using an updated spectral database with multiple other methods for B. pseudomallei identification and found mass spectrometry highly accurate. We have therefore incorporated this fast and cost-effective method into our laboratory's workflow for B. pseudomallei identification.

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BACKGROUND: The use of matrix-assisted laser desorption/ionization-time-of-flight mass spectra (MALDI-TOF MS) with machine learning (ML) has been explored for predicting antimicrobial resistance. This study evaluates the effectiveness of MALDI-TOF MS paired with various ML classifiers and establishes optimal models for predicting antimicrobial resistance and mecA gene existence among Staphylococcus aureus. MATERIALS AND METHODS: The antimicrobial resistance against tier 1 antibiotics and MALDI-TOF MS of S. aureus were analyzed using data from the Database of Resistance against Antimicrobials with MALDI-TOF Mass Spectrometry (DRIAMS) and one medical center (CS database). Five ML classifiers were used to analyze performance metrics. The Shapley value quantified the predictive contribution of individual feature. RESULTS: The LightGBM demonstrated superior performance in predicting antimicrobial resistance for most tier 1 antibiotics among oxacillin-resistant S. aureus (ORSA) than all and oxacillin-susceptible S. aureus (OSSA) in both databases. In DRIAMS, MLP encompassed excellent predictive performance, expressed as accuracy/AUROC/AUPR, for clindamycin (0.74/0.81/0.90), tetracycline (0.86/0.87/0.94), and trimethoprim-sulfamethoxazole (0.95/0.72/0.97). In CS database, Ada and LightGBM retained excellent performance for erythromycin (0.97/0.92/0.86) and tetracycline (0.68/0.79/0.86), respectively. Mass-to-charge ratio (m/z) features of 2,411-2,414 and 2,429-2,432 correlated with clindamycin resistance, while 5,033-5,036 was linked to erythromycin resistance in DRIAMS. In CS database, overlapping features of 2,423-2,426, 4,496-4,499, and 3,764-3,767 simultaneously predicted mecA existence and oxacillin resistance. CONCLUSION: The predictive performance of antimicrobial resistance against S. aureus using MALDI-TOF MS depends on database characteristics and ML algorithm selected. Specific and overlapping MS features are excellent predictive markers for mecA and specific antimicrobial resistance.

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The global antimicrobial resistance crisis has been the driver of several international strategies on antimicrobial stewardship. For their implementation on field level, the veterinary sector encounters several specific challenges and in particular: (i) a shortage of experts in key disciplines related to antimicrobial stewardship, (ii) a lack of evidence-based antimicrobial treatment guidelines, and (iii) inferior diagnostic tests available compared to human medicine. The present white paper describes how the COST Action ENOVAT (the European Network for Optimization of Veterinary Antimicrobial Treatment, CA18217), comprising 332 persons from 51 countries, worked towards solutions to these challenges. Initially, surveys were conducted to explore the present state in Europe in terms of existing antimicrobial use guidelines and microbiology practices performed. Concurrently, various research activities were launched to optimize diagnostics, including development of epidemiological cut-offs, clinical breakpoints and matrix-assisted laser desorption ionization time of flight mass spectrometry interpretive criteria. Also, guidelines drafting groups working towards evidence-based antimicrobial treatment guidelines for six conditions in food-producing and companion animals were established. The processes and outcomes, also in terms of capacity building, are summarized in this white paper where emphasis is placed on sustainability of the activities. Although several ENOVAT initiatives and spin-off projects will continue beyond the Action, we recommend that a new European veterinary research agenda is launched focusing on research and funding leading to long-term impacts on veterinary antimicrobial use.

Antimicrobial resistance is an urgent global public health threat that is amplified by over- and misuse of antimicrobials. As a result of antimicrobial resistance, antibiotics and other antimicrobial medicines become ineffective and infections become difficult or impossible to treat. This goes for human infections, but also for infections in animals. In a recently finished European project called ENOVAT we tried to tackle the problem of antimicrobial resistance in animals. We focused on two topics. First we optimized and harmonized diagnostics of bacterial infections in the laboratory, and second we developed evidence-based treatment guidelines to support veterinary practitioners on how and when to use antibiotics in the best way. Improved diagnostics and new treatment guidelines can help veterinary practitioners to a more sensible antibiotic choice and with that less over- and misuse of antimicrobials. This article summarizes the process and progress of the work done in the ENOVAT project. Emphasis is also put on how the project benefitted from a unique consortium encompassing 332 professionals with diverse backgrounds, from 51 countries.

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This case report describes the case of a female infant hospitalized for severe pneumonia. During the treatment process, various antibiotics are used to treat and prevent further infection. The child had a weak physical condition, combined with neuroblastoma, paraneoplastic syndrome, and low immune function, leading to Tsukamurella tyrosinosolvens infection. The treatment was eventually abandoned owing to poor prognosis. This study aims to through the medium, dyeing, electron microscope observation, 16s rRNA and high-throughput sequencing investigated the morphological characteristics, staining properties, electron microscope morphology, antibiotic resistance, and genomic characteristics of Tsukamurella tyrosinosolvens. The aim of the study is to provide data reference for clinical laboratory staff in bacteria identification research, and to provide relevant help for clinicians in diagnosis and treatment.

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Flavonifractor plautii is an obligate anaerobic rod bacterium that is part of the human gut microbiota. We describe a case of bacteremia caused by F. plautii in a mildly immunocompromised patient with acute generalized peritonitis. The patient is an 83-year-old male, with a history of stage III hepatocellular carcinoma 11 months prior, stage I gastric cancer, and cerebral infarction three months prior. He visited the emergency room of our hospital with a chief complaint of right-sided abdominal pain. A partial resection of the colon was performed due to stenosis of the transverse colon. Due to increasing abdominal pain, the patient underwent surgery for acute generalized peritonitis on the 11th postoperative day. F. plautii was detected in blood cultures collected prior to surgery, and the patient was treated with piperacillin/tazobactam 2.25 g four times a day for 11 days. The patient resumed eating and was discharged with no recurrence. This species may also stain gram-negative, and caution should be exercised in reporting results due to the potential impact on initial antimicrobial therapy. Gram staining showed variation in the length of the bacterium, which is considered a characteristic of this species. Appropriate antimicrobial therapy for F. plautii has yet to be established, and further accumulation of cases is needed to understand the resistance mechanism and confirm the effectiveness of different antimicrobials.

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The large-scale isolation of bovine lactoferrin (bLF) typically involves using large amounts of concentrated eluents, which might introduce impurities to the final product. Sometimes, protein pre-concentration is required for the greater accuracy of experimental results. In this research, the supplied bLF sample was subjected to additional ultrafiltration (UF) to eliminate possible small impurities, such as salts and peptides of bLF. Beforehand, the basic characterization of native bLF, including surface-charge properties and the structural sensitivity to the various pH conditions, was performed. The study aimed to evaluate the difference in molecular mass, primary structure, surface morphology, and elemental composition of the protein before and after UF. The research was provided by application of spectroscopic, spectrometric, electrophoretic, and microscopic techniques. The evident changes in the surface morphology of bLF were observed after UF, while the molecular masses of both proteins were comparable. According to MALDI-TOF/MS results, UF had a positive impact on the bLF sample representation, improving the identification parameters, such as sequence coverage and intensity coverage.

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OBJECTIVES: This study aimed to evaluate an expanded matrix-assisted laser desorption-ionization-time of flight mass spectrometry (MALDI-TOF MS) database for the identification of Haemophilus species other than H. influenzae (Hi). METHODS: A total of 144 Haemophilus species, cultured from respiratory samples from people (living) with cystic fibrosis, were identified with MALDI-TOF MS and 16S rRNA sequencing. Of these, 99 Haemophilus strains showed >99% similarity with the best matching strain in the National Center for Biotechnology Information (NCBI) database and were assigned to a single Haemophilus subspecies using both MALDI-TOF MS and 16S rRNA sequencing. The MS profiles of a subset of strains (n = 58/99) were added to the Bruker MALDI-TOF MS database. Subsequently, 270 different strains that were analyzed previously in a routine setting were re-analyzed. RESULTS: 16S rRNA sequencing reliably identified 99/144 Haemophilus strains (>99% similarity). H. haemolyticus 16S rRNA identification was suboptimal since only 3/21 H. haemolyticus strains attained a similarity of >99% with H. haemolyticus 16S rRNA sequence in the NCBI database. Expansion of the MALDI-TOF MS database improved the number of reliable identifications only moderately for H. haemolyticus, H. influenzae and H. paraphrohaemolyticus (<10%). By contrast, improved identification was more outspoken for H. parahaemolyticus, H. parainfluenzae, H. sputorum and H. pittmaniae (>85%). CONCLUSION: 16S rRNA sequencing is a valuable method for the identification of Haemophilus sp. other than Hi. Expansion of the MALDI-TOF MS database, based on 16S rRNA sequencing results, increased the proportion of reliable identifications and in this study resulted in an increase of 10% of Haemophilus sp. other than Hi strain identifications.

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Complete identification methods are critical for evaluating nontuberculous mycobacteria (NTM). Here, we describe a novel diagnostic method for identification of eight NTM, Mycobacterium tuberculosis complex, and three drug resistance markers using PCR/matrix-assisted, laser-desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) from cultured organisms. With this technology, a multiplex end-point PCR is performed for targets of interest. Detection probes that are extended in the presence of a target are added. The extended probes have greater molecular weight and can be detected by MALDI-TOF MS. An AFB Primary Panel was designed to differentiate Mycobacterium avium; Mycobacterium intracellulare subsp. chimaera; Mycobacterium avium complex (other); Mycobacterium abscessus subsp. abscessus, bolletii, and massiliense; Mycobacterium kansasii, and M. tuberculosis complex. This design should cover 90% (3,483/3,691) of mycobacteria seen onsite. A development set of unblinded isolates (n = 217) was used to develop PCR primers, detection probes, and probe barcodes. It demonstrated 99.1% (215/217) agreement with reference methods. An evaluation set using blinded isolates (n = 320) showed an overall sensitivity of 94.3% (range by target: 90.0-100%). Overall specificity from negative media, non-target mycobacteria, and bacteria was 99.1% (108/109; range by target: 94.4-100%). Three drug resistance markers erm (41), rrl, and rrs demonstrated 100%, 91%, and 100% sensitivity, respectively, and >99% specificity. Limit of detection per target ranged from 2.2 × 103 to 9.9 × 106 CFU/mL. The AFB Primary Panel allows for mycobacterial speciation, subspeciation, and resistance mutation detection, which is essential for diagnosis, appropriate therapy, identifying outbreaks, and managing treatment-refractory disease. It can perform with high-throughput and high specificity and sensitivity from isolates.IMPORTANCEEven closely related mycobacteria can have unique treatment patterns, but differentiating these organisms is a challenge. Here, we tested an innovative platform that combines two commonly used technologies and creates something new: matrix-assisted, laser-desorption ionization time-of flight mass spectrometry was performed on PCR amplicons instead of on proteins. This created a robust system with the advantages of PCR (high discriminatory power, high throughput, detection of resistance) with the advantages of mass spectrometry (more targets, lower operational cost) in order to identify closely related mycobacterial organisms.

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In this study, 80 carbapenem-resistant Klebsiella pneumoniae (CR-KP) and 160 carbapenem-susceptible Klebsiella pneumoniae (CS-KP) strains detected in the clinic were selected and their matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) peaks were collected. K-means clustering was performed on the MS peak data to obtain the best "feature peaks", and four different machine learning models were built to compare the area under the ROC curve, specificity, sensitivity, test set score, and ten-fold cross-validation score of the models. By adjusting the model parameters, the test efficacy of the model is increased on the basis of reducing model overfitting. The area under the ROC curve of the Random Forest, Support Vector Machine, Logistic Regression, and Xgboost models used in this study are 0.99, 0.97, 0.96, and 0.97, respectively; the model scores on the test set are 0.94, 0.91, 0.90, and 0.93, respectively; and the results of the ten-fold cross-validation are 0.84, 0.81, 0.81, and 0.85, respectively. Based on the machine learning algorithms and MALDI-TOF MS assay data can realize rapid detection of CR-KP, shorten the in-laboratory reporting time, and provide fast and reliable identification results of CR-KP and CS-KP.

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The purpose of this study was to conduct a comparative analysis of the composition of the dominant groups of vaginal microorganisms in healthy pregnant women and pregnant women infected with HPV using a microbiological culture-based method. The MALDI TOF MS method and 16S rRNA gene fragment sequencing were used to identify microorganisms isolated from healthy pregnant women (n=32) and pregnant women infected with HPV (n=24). It was found that vaginal secretion samples from both groups contained bacteria of 4 phyla: Bacillota, Actinomycetota, Pseudomonadota, Bacteroidota, and Ascomycota fungi. The most common microbial community in healthy pregnant women being CST I (p=0.0007), and CST V in pregnant women infected with HPV (p=0.0001). At the genus level, a total of 25 taxa were found in all samples, with Lactobacillus being the dominant genus overall. Escherichia (p<0.0001) and Prevotella (p=0.0001) concentrations were higher in HPV infected patients. When calculating the Pearson correlation coefficient for the phyla, it was found that Bacillota correlated negatively with HPV genotypes 16 and 51 (p≤0.05), but positively with HPV genotype 59 (p≤0.05), just like Actinomycetota (p≤0.05). Bacteroidota correlated positively with HPV genotype 56 (0.001

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BACKGROUND: The increased resistance rate of Salmonella to third-generation cephalosporins represented by ceftriaxone (CRO) may result in the failure of the empirical use of third-generation cephalosporins for the treatment of Salmonella infection in children. The present study was conducted to evaluate a novel method for the rapid detection of CRO-resistant Salmonella (CRS). METHODS: We introduced the concept of the ratio of optical density (ROD) with and without CRO and combined it with matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) to establish a new protocol for the rapid detection of CRS. RESULTS: The optimal incubation time and CRO concentration determined by the model strain test were 2 h and 8 µg/ml, respectively. We then conducted confirmatory tests on 120 clinical strains. According to the receiver operating characteristic curve analysis, the ROD cutoff value for distinguishing CRS and non-CRS strains was 0.818 [area under the curve: 1.000; 95% confidence interval: 0.970-1.000; sensitivity: 100.00%; specificity: 100%; P < 10- 3]. CONCLUSIONS: In conclusion, the protocol for the combined ROD and MALDI-TOF MS represents a rapid, accurate, and economical method for the detection of CRS.

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Non-diphtheroid Corynebacterium sepsis is rare and has affected only immunocompromised or particularly predisposed patients so far. We present the first case of urosepsis caused by Corynebacterium aurimucosum in a 67-year-old woman, without any known immunodeficiencies and in absence of any immunosuppressive therapy, admitted to the hospital for fever and acute dyspnea. This work suggests a new approach in evaluating the isolation of Corynebacteria, especially if isolated from blood. In particular, it highlights the potential infectious role of C. aurimucosum (often considered a contaminant and only rarely identified as an etiological agent of infections) and its clinical consequences, detailing also interesting aspects about its microbiological diagnosis and relative therapy and clarifying contrasting data of literature.

[Box: see text].

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Timely and accurate identification of yeasts is essential for adequate treatment, considering the increase in antifungal resistance of some species, particularly for C. auris. Current matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) manufacturer's protocol for identification of yeasts requires 24- to 72-h cultivation on Sabouraud dextrose media (SAB), but not some of the mainstay primary culture media used in mycology such as inhibitory mold agar (IMA), Mycosel, CHROMagar Candida Plus, and CHROMagar Candida. As culture media can influence MALDI-TOF MS identification results, this study evaluated the accuracy and performance of identification of clinically relevant yeasts on these first-line media using the VITEK-MS MALDI-TOF MS system.IMPORTANCEIn this study, a panel of 140 strains (21 species) was used to assess the performance of the selected media. Although not in the manufacturer's list of accepted media, IMA and chromogenic media are suitable for the identification of yeasts on the VITEK-MS systems. CHROMagar Candida Plus allowed the identification of 135/140 isolates tested after 24-h incubation similar to SAB reference media (137/140). Yeast isolates that grew on Mycosel selective media were also reliably identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. VITEK-MS system with IVD database V3.2 correctly identified C. auris strains to the species level on CHROMagar Candida Plus alleviating the need for subcultivation and reduced turnaround time (24-72 h) to identification for patient screening.