Cat-transmitted sporotrichosis is caused by the emerging fungal pathogen Sporothrix brasiliensis and constitutes a significant public health issue that affects people living in resource-poor urban centers in Brazil. The lack of knowledge about transmission dynamics makes it difficult to propose public health policies to contain the advance of sporotrichosis. We describe the recent emergence of 1,176 cases of sporotrichosis in cats (2016 to 2021) in the metropolitan region of Recife, Brazil, leading to significant zoonotic transmission and an overwhelming occurrence of S. brasiliensis as the etiological agent. Most cases were from cats in the cities of Olinda (408/1,176; 34.70%), Jaboatão dos Guararapes (332/1,176; 28.23%), and Recife (237/1,176; 20.15%). Molecular typing using amplified fragment length polymorphism (EcoRI-GA/MseI-AG) revealed low polymorphic information content (PIC = 0.2499) and heterozygosity (H = 0.2928), typical of an outbreak scenario. Dendrogram and multivariate cluster analysis revealed that isolates from Pernambuco are closely related to Rio de Janeiro isolates. We report a substantial occurrence of MAT1-2 idiomorphs in the metropolitan region of Recife (0:60 ratio; χ2 = 60.000, P < 0.0001). The limited population differentiation and genetic diversity of the isolates from Pernambuco suggest a recent introduction, possibly via a founder effect, from the parental population in Rio de Janeiro. Our findings emphasize the critical importance of molecular surveillance of S. brasiliensis for outbreak response. A comprehensive one-health strategy is mandatory to control the spread of cat-transmitted sporotrichosis driven by S. brasiliensis, encompassing sanitary barriers, quick diagnosis, and treatment.

Yersinia enterocolitica (Y. enterocolitica) is the most frequent etiological agent of yersiniosis and has been responsible for several national outbreaks in Norway and elsewhere. A standardized high-resolution method, such as core genome Multilocus Sequence Typing (cgMLST), is needed for pathogen traceability at the national and international levels. In this study, we developed and implemented a cgMLST scheme for Y. enterocolitica. We designed a cgMLST scheme in SeqSphere + using high-quality genomes from different Y. enterocolitica biotype sublineages. The scheme was validated if more than 95% of targets were found across all tested Y. enterocolitica: 563 Norwegian genomes collected between 2012 and 2022 and 327 genomes from public data sets. We applied the scheme to known outbreaks to establish a threshold for identifying major complex types (CTs) based on the number of allelic differences. The final cgMLST scheme included 2,582 genes with a median of 97.9% (interquartile range 97.6%-98.8%) targets found across all tested genomes. Analysis of outbreaks identified all outbreak strains using single linkage clustering at four allelic differences. This threshold identified 311 unique CTs in Norway, of which CT18, CT12, and CT5 were identified as the most frequently associated with outbreaks. The cgMLST scheme showed a very good performance in typing Y. enterocolitica using diverse data sources and was able to identify outbreak clusters. We recommend the implementation of this scheme nationally and internationally to facilitate Y. enterocolitica surveillance and improve outbreak response in national and cross-border outbreaks.

BACKGROUND: The aim of this study is to assess the efficacy of a multiparametric ultrasound imaging omics model in predicting the risk of postoperative recurrence and molecular typing of breast cancer.
METHODS: A retrospective analysis was conducted on 534 female patients diagnosed with breast cancer through preoperative ultrasonography and pathology, from January 2018 to June 2023 at the Affiliated Cancer Hospital of Xinjiang Medical University. Univariate analysis and multifactorial logistic regression modeling were used to identify independent risk factors associated with clinical characteristics. The PyRadiomics package was used to delineate the region of interest in selected ultrasound images and extract radiomic features. Subsequently, radiomic scores were established through Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM) methods. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated. Evaluation of diagnostic efficacy and clinical practicability was conducted through calibration curves and decision curves.
RESULTS: In the training set, the AUC values for the postoperative recurrence risk prediction model were 0.9489, and for the validation set, they were 0.8491. Regarding the molecular typing prediction model, the AUC values in the training set and validation set were 0.93 and 0.92 for the HER-2 overexpression phenotype, 0.94 and 0.74 for the TNBC phenotype, 1.00 and 0.97 for the luminal A phenotype, and 1.00 and 0.89 for the luminal B phenotype, respectively. Based on a comprehensive analysis of calibration and decision curves, it was established that the model exhibits strong predictive performance and clinical practicability.
CONCLUSIONS: The use of multiparametric ultrasound imaging omics proves to be of significant value in predicting both the risk of postoperative recurrence and molecular typing in breast cancer. This non-invasive approach offers crucial guidance for the diagnosis and treatment of the condition.

OBJECTIVE: To investigate the genetic profile and characterize antimicrobial resistance, including the main β-lactam antibiotic resistance genes, in Acinetobacterbaumannii isolates from a tertiary hospital in Recife-PE, Brazil, in the post-COVID-19 pandemic period.
RESULTS: Acinetobacter baumannii isolates were collected between 2023 and 2024 from diverse clinical samples. Antimicrobial resistance testing followed standardized protocols, with β-lactamase-encoding genes detected via PCR and sequencing. Investigation into ISAba1 upstream of blaOXA-carbapenemase and blaADC genes was also conducted. Genetic diversity was assessed through ERIC-PCR. Among the 78 A. baumannii, widespread resistance to multiple antimicrobials was evident. Various acquired β-lactamase-encoding genes (blaOXA-23,-24,-58,-143, blaVIM, and blaNDM) were detected. Furthermore, this is the first report of blaVIM-2 in A. baumannii isolates harboring either the blaOXA-23-like or the blaOXA-143 gene in Brazil. Molecular typing revealed a high genetic heterogeneity among the isolates, and multi-clonal dissemination.
CONCLUSIONS: The accumulation of genetic resistance determinants underscores the necessity for stringent infection control measures and robust antimicrobial stewardship programs to curb multidrug-resistant strains.

Angiogenesis has been discovered to be a critical factor in developing tumors and ischemic diseases. However, the role of angiogenesis-related genes (ARGs) in acute myocardial infarction (AMI) remains unclear.
The GSE66360 dataset was used as the training cohort, and the GSE48060 dataset was used as the external validation cohort. The random forest (RF) algorithm was used to identify the signature genes. Consensus clustering analysis was used to identify robust molecular clusters associated with angiogenesis. The ssGSEA was used to analyze the correlation between ARGs and immune cell infiltration. In addition, we constructed miRNA-gene, transcription factor network, and targeted drug network of signature genes. RT-qPCR was used to verify the expression levels of signature genes.
Seven signature ARGs were identified based on the RF algorithm. Receiver operating characteristic curves confirmed the classification accuracy of the risk predictive model based on signature ARGs (area under the curve [AUC] = 0.9596 in the training cohort and AUC = 0.7773 in the external validation cohort). Subsequently, the ARG clusters were identified by consensus clustering. Cluster B had a more generalized high expression of ARGs and was significantly associated with immune infiltration. The miRNA and transcription factor network provided new ideas for finding potential upstream targets and biomarkers. Finally, the results of RT-qPCR were consistent with the bioinformatics analysis, further validating our results.
Angiogenesis is closely related to AMI, and characterizing the angiogenic features of patients with AMI can help to risk-stratify patients and provide personalized treatment.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly prevalent and deadly cancer, with limited treatment options for advanced-stage patients. Disulfidptosis is a recently identified mechanism of programmed cell death that occurs in SLC7A11 high-expressing cells due to glucose starvation-induced disintegration of the cellular disulfide skeleton. We aimed to explore the potential of disulfidptosis, as a prognostic and therapeutic marker in HCC.
METHODS: We classified HCC patients into two disulfidptosis subtypes (C1 and C2) based on the transcriptional profiles of 31 disulfrgs using a non-negative matrix factorization (NMF) algorithm. Further, five genes (NEIL3, MMP1, STC2, ADH4 and CFHR3) were screened by Cox regression analysis and machine learning algorithm to construct a disulfidptosis scoring system (disulfS). Cell proliferation assay, F-actin staining and PBMC co-culture model were used to validate that disulfidptosis occurs in HCC and correlates with immunotherapy response.
RESULTS: Our results suggests that the low disulfidptosis subtype (C2) demonstrated better overall survival (OS) and progression-free survival (PFS) prognosis, along with lower levels of immunosuppressive cell infiltration and activation of the glycine/serine/threonine metabolic pathway. Additionally, the low disulfidptosis group showed better responses to immunotherapy and potential antagonism with sorafenib treatment. As a total survival risk factor, disulfS demonstrated high predictive efficacy in multiple validation cohorts. We demonstrated the presence of disulfidptosis in HCC cells and its possible relevance to immunotherapeutic sensitization.
CONCLUSIONS: The present study indicates that novel biomarkers related to disulfidptosis may serve as useful clinical diagnostic indicators for liver cancer, enabling the prediction of prognosis and identification of potential treatment targets.

BACKGROUND: Serratia marcescens is known to cause outbreaks in neonatal intensive care units (NICUs). Traditionally epidemiological data, antimicrobial resistance patterns and epidemiological typing have been used to guide infection prevention methods. Whole-genome sequencing (WGS) applications such as core-genome multi-locus sequence typing (cgMLST) applied during an outbreak would potentially yield more information.
OBJECTIVE: To use cgMLST to acquire detailed information on the source and spread of bacteria, enabling more efficient control measures during an S. marcescens outbreak at a NICU.
METHODS: Neonates admitted to the NICU of the Leiden University Medical Center (LUMC) during an outbreak between September 2023 and January 2024, with S. marcescens being cultured, were included. Environmental samples were taken to search for a common source, antibiotic susceptibility testing was performed, and antimicrobial resistance genes were analysed.
RESULTS: S. marcescens strains from 17 of the 20 positive patients were available for molecular typing. The cgMLST scheme revealed five different complex types consisting of four separate clusters. Multiple clusters made an unidentified persistent environmental source as cause of the outbreak less likely, leading to a quick downscaling of infection prevention measures. Differences were shown in aminoglycoside resistance patterns of isolates within the same complex types and patients.
CONCLUSIONS: The use of ad-hoc cgMLST provided timely data for rational decision-making during an S. marcescens outbreak at the NICU. Antibiotic phenotyping alone was found not to be suitable for studying clonal spread during this outbreak with S. marcescens.

BACKGROUND: In Taiwan, sequence type (ST) 239 and ST59 were two major clones among meticillin-resistant Staphylococcus aureus (MRSA) clinical isolates in the past two decades. USA300 (ST8) prevailed in the Americas but not in outside areas. Recently USA300 (ST8) emerged and was increasingly identified in Taiwan; we thus conducted an island-wide study to explore the role of USA300 among MRSA isolates.
METHODS: One hundred MRSA bloodstream isolates identified in 2020 from each of the six participating hospitals in Taiwan were collected and characterized. The first 10 ST8 isolates from each hospital were further analysed by whole-genome sequencing.
RESULTS: Of the 590 confirmed MRSA isolates, a total of 22 pulsotypes and 21 STs were identified. The strain of pulsotype AI/ST8 was the most common lineage identified, accounting for 187 isolates (31.7%) and dominating in five of six hospitals, followed by pulsotype A/ST239 (14.7%), pulsotype C/ST59 (13.9%) and pulsotype D/ST59 (9.2%). Of the 187 pulsotype AI/ST8 isolates, 184 isolates were characterized as USA300 and clustered in three major sub-pulsotypes, accounting for 78%. Ninety per cent of the 60 ST8 isolates for whole-genome sequencing were clustered in three major clades.
CONCLUSIONS: In 2020, USA300 became the most common clone of MRSA in Taiwan, accounting for >30% of MRSA bloodstream isolates island wide. Most of USA300 isolates circulating in Taiwan might have been imported on multiple occasions and evolved into at least three successful local clades. MRSA USA300 has successfully established its role in Taiwan, an area outside of the Americas.

OBJECTIVE: Staphylococcus aureus (S. aureus) spreads worldwide and occurrence of mastitis caused by it holds significant implications for public health. We aim to reveal the molecular typing, antibiotic resistance and virulence gene profile of S. aureus causing mastitis through investigation.
METHODS: A total of 200 isolates of S. aureus were collected from outpatients infected with mastitis in a hospital in Beijing from 2020.7 to 2021.7. The molecular characteristics were analyzed by MLST and spa typing, virulence genes were screened by PCR, antibiotic susceptible test was performed by VITEK® 2 Compact system and phylogenetic analysis was performed by MEGA11 and iTOL.
RESULTS: Nineteen sequence types (STs) belonging to 9 clone complexes (CCs) were identified. ST22 was the most dominant clone (77.0%, 154/200). MRSA accounted for 19.0% (38/200) and 89.5% (34/38) of MRSA isolates belonged to CC22 and CC59. The isolates had relatively low levels of antibiotic resistance, with the exception of β-lactams and macrolides with resistance rates above 50.0%. The carrying rate of pvl in the ST22-MRSA strains were 84.2% and the detection rates of seb and pvl in the MRSA isolates were significantly higher than those in the MSSA isolates, while the hlg, fnbA and sdrD showed opposite results. Whole genome sequenced specimens of MRSA strains X4 and B5 show the same evolutionary origin as ST22 EMRSA-15 (HE681097), which is popular in Europe.
CONCLUSIONS: The method based on molecular epidemiology is an important tool for tracking the spread of S. aureus infections. We need to be alert to the major MRSA clones CC22 and CC59 in the region and be vigilant to the possible pandemic and spread of ST22 EMRSA-15.

UNASSIGNED: In this study, we investigated the value of molecular typing combined with integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) semi-quantitative indices in endometrial cancer risk stratification.
UNASSIGNED: A retrospective study was conducted on 86 patients who were pathologically diagnosed with endometrial cancer and underwent surgical treatment after curettage at the Department of Obstetrics and Gynecology, Xuanwu Hospital, Capital Medical University between January 2017 and March 2023. Prior to surgery, each patient underwent integrated PET/MRI examination. The postoperative samples were subjected to pathological diagnosis, immunohistochemistry, and POLE gene sequencing. The differences in clinicopathological features between the four molecular subtypes and the differences in integrated PET/MRI semi-quantitative indexes (SUV max, ADC min) between the four molecular subtypes were analyzed. The cutoff value of molecular typing combined with integrated PET/MRI semi-quantitative indices for endometrial cancer risk stratification was determined.
UNASSIGNED: There were statistically significant differences in pathological types and tumor grades among the four molecular subtypes of endometrial cancer. The values of the four integrated PET/MRI semi-quantitative indices (SUV max and ADC min) of the molecular subtypes were statistically different. The SUV max was greater in the p53abn mutation group than in the POLE mutation group (P < 0.05). The ADC minimum of the POLE mutation group and the MMR-d group was lower than the NSMP group (P < 0.05). Molecular typing combined with the integrated PET/MRI semi-quantitative SUV max index can predict the low/medium risk group of endometrial cancer and the medium-high/high risk group, and the cut-off value of SUV max for predicting the risk of early endometrial cancer was 14.72 (sensitivity 66.7%, specificity 68.7%).
UNASSIGNED: Molecular typing combined with integrated PET/MRI semi-quantitative indicators is useful to achieve risk stratification in patients diagnosed with endometrial cancer and guide individualized treatment.