Antimicrobial resistance is a growing global public health concern, and carbapenem-resistant Enterobacterales (CRE) represent one of the most urgent threats due to limited treatment options. While CRE are primarily associated with healthcare settings, increasing evidence suggests that food systems may serve as additional reservoirs and transmission interfaces for clinically significant antibiotic-resistant bacteria. This study aimed to characterize CRE from vegetables, with a focus on isolates carrying carbapenem resistance genes on mobile genetic elements and evaluating their transferability to a recipient bacterium. Commercial vegetable samples were collected from retail grocery stores or farmers' markets and screened for CRE using selective enrichment and CHROMagar™ mSuperCARBA™. Antimicrobial susceptibility testing was performed according to Clinical and Laboratory Standards Institute (CLSI) guidelines. Whole-genome sequencing using Illumina short-read and Oxford Nanopore long-read platforms was conducted to characterize resistance genes and the plasmid sequence. Conjugation assays were performed to assess plasmid transferability to Escherichia coli DH5α. The results indicated that a carbapenem-resistant Kluyvera sichuanensis isolate (CA-CRE-C23) was recovered from a spinach sample. Genomic analysis identified a 51,477-bp hybrid ColKP3-IncX3 plasmid carrying the carbapenemase gene blaOXA-181 and quinolone resistance gene qnrS1. Conjugation experiments, disk diffusion, and sequencing confirmed successful plasmid transfer from K. sichuanensis isolate (CA-CRE-C23) to E. coli DH5α. The plasmid structure closely resembled globally disseminated IncX3 hybrid plasmids carrying blaOXA-181, which have been predominantly reported in clinical isolates. In conclusion, the detection of a transferable hybrid plasmid harboring blaOXA-181 in a fresh produce-associated K. sichuanensis isolate expands the known host range of this resistance gene and underscores the importance of food-chain surveillance in understanding the environmental dissemination of high-risk antimicrobial resistance genes.

Prolonged cold storage (CS) of donor kidneys results in poor outcomes after transplantation. We reported earlier that cold storage (CS) of rat kidneys for 18 h followed by transplantation (CS + Tx) reduces proteasome function, disrupts protein homeostasis, and compromises graft function. The goal of the present study was to define the contribution of specific heat shock proteins (Hsp) to CS-induced disruption of renal graft function and determine the benefit conferred by their pharmacological inhibition. We subjected kidneys isolated from donor Lewis rats to 18-h CS with or without pharmacological inhibition of heat shock protein 72 (Hsp72), a stress-inducible member of the Hsp70 family. Subsequently, the donor kidneys were transplanted into Lewis rats (CS + Tx). Hsp72 was upregulated in kidney grafts after CS + Tx, and this finding was coupled to a reciprocal loss of cognate Hsc70 and profound tubular injury. Knockdown of Hsc70 in renal cells increased Hsp72, compromised proteasome function, and increased mitochondrial oxidative stress. The addition of HS-72, a Hsp72-specific inhibitor, to the CS solution restored proteasome function and improved renal injury/function after transplantation. Our study shows that CS + Tx dysregulates heat shock proteins in the kidney, and targeting a single disrupted protein, Hsp72, can improve graft function.NEW & NOTEWORTHY Our study using a rat renal transplant model shows that cold storage (CS)-induced injury involves dysregulation of heat shock proteins in the kidney and provides proof of concept that targeting a single disrupted protein, heat shock protein 72 (Hsp72), can improve graft function.

Abstract Ischemia–reperfusion injury (IRI) is a major driver of acute kidney injury and development of chronic kidney disease. Although complement activation worsens IRI, the roles of upstream (C3) versus downstream (C5) components remain unclear. Renal IRI was surgically induced in C3 knockout (C3 − / − ) and C5 knockout (C5 − / − ) Lewis rats, and the renal function as well as histopathology were systematically assessed. Further, quantitative proteomics coupled with pathway enrichment analysis was performed to define complement‐dependent mechanisms. C3 and C5 deficiency conferred strong protection against renal IRI with improved renal function, reduced tubular necrosis, and lower expression of injury markers (KIM‐1, NGAL). Post‐IRI, C3 −/− enhanced mitochondrial, metabolic, and purine pathways while suppressing immune and extra‐cellular matrix programs. C5 −/− affected extracellular matrix remodeling and structural pathways with modest immune suppression. We demonstrate for the first time that upstream C3 −/− impacts a diverse range of renal injury and repair mechanisms compared to C5 −/− alone, although both interventions successfully reduced IRI‐mediated injury. Together, these findings highlight strategies for future complement‐based therapies targeting the upstream or downstream cascade.

Carbapenem-resistant and extended-spectrum beta-lactamase (ESBL)-producing bacteria, once largely confined to healthcare settings, are increasingly detected in community environments. Food and the environment may act as important reservoirs for clinically relevant antibiotic-resistant bacteria. A large-scale surveillance study was conducted from 2022 to 2023 to assess antibiotic resistance in retail fresh vegetables across three U.S. regions: the Midsouth, Midwest, and West Coast. A total of 1218 samples representing five vegetable categories (carrots, lettuce, spinach, sprouts/microgreens, and salads) were analyzed for carbapenem-resistant bacteria and ESBL-producing Enterobacterales. Culture-based methods included selective isolation on CHROMagar, antibiotic susceptibility testing, phenotypic evaluation of ESBL and carbapenem resistance, and carbapenemase detection and typing. Whole-genome sequencing of phenotypically resistant isolates was used to identify beta-lactamase genes. Overall, 62 carbapenem-resistant isolates (5.09%) and 70 ESBL-producing Enterobacterales isolates (5.74%) were recovered. Carbapenemase-producing Enterobacterales included 30 Enterobacter strains and one Kluyvera strain, with carbapenem-resistant Enterobacter most frequently isolated from sprouts and microgreens. ESBL-producing strains included 39 Serratia, 20 Enterobacter, 6 Klebsiella, 3 Raoultella, and 2 Rahnella isolates. Comparative genomic analyses showed close similarity between vegetable isolates and human clinical strains. Notably, the carbapenemase gene blaIMI-6 identified in Enterobacter asburiae from microgreens was transferable to Escherichia coli by conjugation. Shotgun metagenomics of 40 samples further confirmed diverse resistance genes. These findings highlight vegetables as potential reservoirs of clinically important antibiotic resistance and emphasize the need for ongoing surveillance in both vegetable products and their production environments.

AIMS:To achieve optimal application of antimicrobials to poultry processing requires an understanding of the potential for resistance by foodborne pathogens such as Salmonella. The objective of this study was to use transposon sequencing (Tn-seq) to identify genetic factors required for Salmonella Typhimurium's tolerance to PAA. METHODS AND RESULTS:A genome-saturated Tn5 mutant library (input pool) was inoculated in two replicates into either 6% chicken meat extract (CME) or 11% diluted Luria-Bertani (LB) broth, both supplemented with 15 ppm PAA. Cultures were incubated for 90 minutes at 37°C. Viable Tn5 mutant cells recovered on LB agar plates were combined to form four output pools (two CME and two LB). Genomic DNA extracted from these pools were deep sequenced (Tn5-junction reads). Conditionally essential genes required for fitness in 6% CME and 11% LB were identified and subjected to pathway enrichment analysis (ShinyGO graphical gene-set enrichment tool). We identified two overlapping sets of conditionally essential genes (276 common genes) required for survival in the presence of PAA. In CME, 362 conditionally essential genes were identified, while LB media revealed 536 genes. Pathway enrichment analysis showed that these genes were significantly enriched in pathways such as pyruvate metabolism, the tricarboxylic acid cycle, fumarate reductase/succinate dehydrogenase (transmembrane subunit and 2Fe-2S iron-sulfur cluster binding domain), stress response, and oxidoreductase activity. Notably, genes previously shown to increase sensitivity to PAA upon inactivation (sdhC, zwf, pta, and icdA) were identified as conditionally essential in this study, further validating the Tn-seq data.

Background Doxorubicin (DOX)-based chemotherapy has improved survival outcomes in breast cancer patients but is often limited by doxorubicin-induced cardiotoxicity (DIC). Currently, no validated biomarkers can predict early DIC. Identifying novel biomarkers is essential for detecting patients at higher risk and enable timely interventions before irreversible cardiac injury occurs. Methods Twenty-seven breast cancer patients treated with DOX-containing chemotherapy were stratified by change in left ventricular ejection fraction (LVEF): 19 patients who maintained normal cardiac function (normal, decline < 10%) and 8 who developed cardiotoxicity (abnormal, decline > 10%). Plasma samples were collected at baseline and after chemotherapy for untargeted metabolomic profiling. Both baseline and pre-post designs were employed to capture static and dynamic metabolic alterations associated with DIC. Stepwise logistic regression was used to filter non-informative metabolites, and predictive performance was further validated using Random Forest modeling. Results A well-marked separation of plasma metabolomic profiles was observed between normal and abnormal cardiotoxicity groups at baseline (T0). Statistical analysis identified 100 significant metabolites at baseline (T0) and 78 metabolites after the first cycle of chemotherapy (T0-T1), with 10 metabolites common to both time-points: 3-phosphoglycerate, 2-hydroxyphenylacetate, inosine, taurine, suberate (C8-DC), sebacate (C10-DC), sphingadienine, oxindolylalanine. Machine learning models identified key metabolites (e.g., sebacate [C10-DC], 2-hydroxyhippurate, orotate, picolinate, and suberate [C8-DC]) as candidate predictors of cardiotoxicity, achieving moderate discriminatory performance in cross-validation, with higher specificity than sensitivity, indicating limited detection of abnormal cases. Conclusions Metabolomic profiling shows potential for early detection of DIC in breast cancer patients, supporting personalized interventions to prevent irreversible cardiac damage.

Once viewed primarily as an energy store, adipose tissue (AT) is now recognized as an active endocrine organ that communicates with both the heart and liver to coordinate systemic metabolism. Under conditions of nutrient overload, maladaptive AT signaling can propagate dysfunction across these organs, yet the extent to which these pathways diverge between males and females is still poorly characterized. As obesity rates continue to rise worldwide, uncovering the earliest transcriptional and physiological disturbances initiated by AT is essential for understanding the onset of cardiometabolic disease. We hypothesized that acute dietary fat overload elicits sexually divergent AT transcriptional responses that subsequently shape tissue-specific remodeling in the heart and liver. Using a pre-clinical model of diet-induced obesity (DIO), age-matched male and female mice were fed sucrose-matched high-fat or low-fat diets for one week. Despite comparable caloric intake, males exhibited increased adiposity and rapid expansion of white adipose tissue (WAT), whereas females maintained superior glucose tolerance. Early induction of extracellular matrix remodeling genes in both sexes indicated that fibrotic cues arise within days of nutrient excess. Integrative transcriptomic profiling across AT, heart, and liver revealed coordinated yet sex-divergent metabolic reprogramming. In WAT, both sexes showed suppression of fatty acid biosynthesis and pyruvate metabolism, but females uniquely upregulated cell cycle pathways and downregulated PPAR signaling, suggesting increased adipocyte turnover and reduced inflammatory activation. Cross-tissue correlation analysis demonstrated that these early AT programs paralleled organ-specific signatures in the heart and liver. Heart RNA-seq revealed that female mice were protected from the strong induction of stress–remodeling genes and inflammatory mediators observed in males, while liver transcriptomics showed robust male-biased upregulation of lipogenic, inflammatory, and hepatokine pathways, consistent with their greater adiposity and lipolytic drive. Gene-level concordance highlighted distinct clusters of sex-specific heart–liver crosstalk, including male-biased induction of acute-phase response factors and female-biased preservation of metabolic resilience. To translate these findings, human iPSC-derived cardiac cells were exposed to conditioned medium from fatty acid–loaded adipocytes generated from male and female human mesenchymal stem cells. Female adipocytes displayed reduced lipid accumulation and recapitulated the adaptive transcriptomic signatures identified in murine AT. Cardiac cells exposed to female adipocyte conditioned medium showed diminished lipid loading and attenuated expression of remodeling and stress-response genes, reinforcing a cardioprotective effect of the female AT secretome. Together, these murine and human data identify a sexually dimorphic, multi-organ transcriptional network that emerges within days of dietary fat exposure. Females mount a more adaptive AT response that confers downstream protection against hepatic steatosis and cardiac metabolic remodeling. This study provides, to our knowledge, the first integrated transcriptomic analysis of the AT–heart–liver triad during the acute onset of diet-induced cardiometabolic disease, highlighting the essential role of sex as a biological variable. Targeting early inter-organ communication may offer new therapeutic avenues to mitigate metabolic dysfunction in obesity. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Most studies on the effects of galactic cosmic rays (GCR) have relied on terrestrial irradiation using spatially homogeneous dose distributions of mono-energetic beams comprised of one ion species. Here, we exposed mice to novel beams that more closely mimic GCR, namely, comprising poly-energetic ions of multiple species. Six-month-old male and female C57BL/6J mice were exposed to 0 Gy, 0.5 Gy, or 1.5 Gy simplified simulated 5 ion GCR (GCRsim). Exposure to microgravity was simulated using hindlimb unloading (HLU). At nine months post exposure, the mice were terminated to assess for the presence of exposure-induced epigenetic alterations. DNA hypermethylation in the 5’-untranslated regions of Lx_III, MdFanc_I, and MdMus_II families of the Long Interspersed Nucleotide Element 1 (LINE-1) was observed in the lungs of male mice. These effects were accompanied by increases in the expression of DNA methyltransferases Dnmt1 and Dnmt3a, and methyl-binding protein, MecP2. Trends towards DNA hypomethylation, although insignificant, were observed in the lungs of female mice in the HLU + 1.5 Gy GCRsim group. Altogether, our findings suggest persistent and sex-specific epigenetic reprogramming in the mouse lung and suggests that the DNA methylation status of LINE-1 can serve as a robust and reliable biomarker of previous radiation exposure.

Background. Prolonged cold storage (CS) of kidneys results in poor long-term outcomes after transplantation (Tx). We reported previously that CS of rat kidneys for 18 h before transplant impaired proteasome function, disrupted protein homeostasis, and reduced graft function. The goal of the present study was to identify the renal proteins, including phosphoproteins, that are dysregulated by this CS injury. Methods. Isolated donor Lewis rat kidneys were subject to 18 h CS and transplanted into recipient Lewis rats (CS + Tx). Autotransplantation (transplant with 0 h CS) or Sham (right nephrectomy) surgeries served as controls. The proteome of kidney homogenates was analyzed with tandem mass-tag mass spectrometry to identify CS-induced abnormalities in kidney grafts. Results. CS injury disrupted the renal proteome/phosphoproteome landscape in kidney grafts and dysregulated numerous signaling pathways. We identified 3217 phosphopeptides (with 1398 novel phosphosites) that were significantly dysregulated in a CS-specific manner. In particular, proteins and pathways such as complement system and mitogen-activated protein kinases, including p38MAPK, were upregulated, whereas antioxidant/metabolic pathways, such as glutathione, were suppressed in CS + Tx groups compared with autotransplantation and sham controls. Conclusions. This study provides deeper insight into the disruption of the renal proteome/phosphoproteome caused by CS injury and provides a novel set of pathways and molecules, including p38MAPK, that can be investigated to delineate their specific role in renal transplant outcomes, ultimately improving outcomes for patients with end-stage kidney disease.

Background: Breast cancer is a complex and heterogeneous disease characterized by distinct molecular subtypes with varying prognoses and treatment responses. Multiple factors influence breast cancer outcomes including tumor biology, patient characteristics, and treatment modalities. Demographic factors such as age, race/ethnicity, menopausal status, and body mass index have been correlated with variations in incidence, mortality, and survival rates. Over the past decade, comprehensive genomic profiling has been widely used to identify molecular biomarkers and signatures to develop novel therapeutic strategies for patients. For instance, the FLEX registry (NCT03053193) enrolled stage I–III breast cancer patients across 90 institutions in the United States and stratified risk groups based on a 70-gene signature (MammaPrint®-MP) and molecular subtype based on an 80-gene signature (BluePrint®-BP). This study aimed to identify the gene expression patterns and biomarkers associated with breast cancer risk and progression by integrating transcriptomic and clinical data. Methods: Targeted 111 unique gene expression and clinical data points from 978 breast cancer samples, representing each BP subtype (26% Luminal A, 26% Luminal B, 25% Basal, 23% HER2), obtained from Agendia Inc. These genes were selected based on their involvement in the mercapturic acid pathway, white and brown adipose tissue markers, inflammation markers, tumor-associated genes, apoptosis, autophagy, and ER stress markers. All statistical analyses, including principal component analysis (PCA), were performed using R version [4.4.0]. Prognostic values and genetic alterations were investigated using various web-based programs as described in the Methods section. Results: PCA of gene expression data revealed distinct clustering patterns associated with risk categories and molecular subtypes, particularly with principal component 4 (PC4). Genes related to oxidative stress, autophagy, apoptosis, and histone modification showed altered expression across risk categories and molecular subtypes. Key differentially expressed genes included SOD2, KLK5, KLK7, IL8, GSTM1/2, GLI1, CBS, and IGF1. Pathway analysis highlighted the enrichment of processes related to autophagy, cellular stress response, apoptosis, glutathione metabolism, deacetylation, and oxidative stress in high-risk and basal-like tumors compared with Ultralow and Luminal A tumors, respectively. Conclusions: This study identified gene expression signatures associated with breast cancer risk and molecular subtypes. These findings provide insights into the biological processes that may drive breast cancer progression and could inform the development of prognostic biomarkers and personalized therapeutic strategies.

While anthracyclines, commonly used in cancer treatment, are well known to cause cardiotoxicity, no validated biomarkers currently exist that can predict the early development of doxorubicin-induced cardiotoxicity (DIC). Therefore, identifying early biomarkers of DIC is urgently needed. Metabolomics approaches have been used to elucidate this relationship and identified related metabolite markers. However, differences in pre-clinical model systems make it challenging to draw definitive conclusions from the discoveries and translate findings into clinical applications. A systematic literature search on metabolomics studies of DIC was conducted with the goal to identify and compare study results reported using in vitro models, animal models, and studies from clinical patients. Metabolites identified across all studies were pooled to uncover biologically meaningful patterns that are significantly enriched in the data. Finally, pooled metabolites perturbed by DIC were mapped to metabolic pathways to explore potential pathological implications. We reviewed 28 studies published between 2000 and 2024 that utilized metabolomics approaches to investigate DIC. The included studies used a variety of analytical techniques, including LC–MS, GC–MS, and NMR. The analysis revealed that metabolites such as inosine, phenylalanine, arginine, and tryptophan were commonly perturbed across all study models, with carnitine metabolism and purine and pyrimidine metabolism being the most affected pathways. Metabolite Set Enrichment Analysis (MSEA) using MetaboAnalyst identified the arginine biosynthesis, citrate cycle, and alanine, aspartate, and glutamate metabolism pathways as significantly enriched. These findings underscore the potential of metabolomics in identifying early biomarkers for DIC, providing a foundation for future studies aimed at preventing cardiotoxicity and improving treatment strategies for cancer patients receiving DOX-containing therapies. Altogether, metabolomics studies suggest metabolic alterations in DIC, albeit little overlap between studies especially with animal and human studies. Attempts at intercepting these pathways have shown that intervention in DIC may be possible. Future research should focus on developing precise cardiotoxicity models that incorporate cancer metabolism, as these will be crucial in bridging the gap between laboratories (in vitro and animal models) and clinical studies to identify subclinical biomarkers in the early stage of DIC that can effectively identify new targets for interventions to reduce lethal cardiovascular disease risk.

Significant racial disparities exist in prostate cancer (PCa), particularly among African American (AA) men, who consume fewer green vegetables and face prolonged environmental exposure such as arsenic. However, the role of DNA methylation in folate and arsenic metabolism in PCa formation and progression remains unclear, especially among AA men. Blood DNA methylation was analyzed in 117 PCa cases from the North Carolina-Louisiana Prostate Cancer Project (PCaP), including AAs and European Americans (EAs). PCa aggressiveness was classified using clinical stage, Gleason score, and PSA level. Plasma folate and folic acid were quantified and categorized into quartiles. Univariate and multivariate analyses assessed the effect of plasma folate and PCa aggressiveness on DNA methylation profiles, adjusting for age, race, smoking, urinary heavy metal concentrations, and cell compositions. Significant separation of DNA methylation profiles by race was observed at baseline. Variations in dietary folate, heavy metal exposure, cell compositions, and smoking histories significantly affected DNA methylation profiles. When examining the methylation changes associated with metal exposure and PCa aggressiveness, arsenic and cadmium showed significant interactions with aggressive PCa. Plasma folic acid had the most influence on DNA methylation profiles compared to unmetabolized folic acid and synthetic folates. Conclusions: Plasma folic acid levels interact with PCa aggressiveness, suggesting nutritional status is important to prevent aggressive outcomes in PCa. Additionally, arsenic exposure significantly contributes to the methylation profiles, highlighting the need to reduce arsenic exposure among high-risk populations. Ping-Ching Hsu, Se-Ran Jun, L. Joseph. Su. Modulation of DNA methylation by plasma folate and heavy metals in relation to prostate cancer aggressiveness [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr C089.

We report the emergence of cefiderocol resistance in a blaOXA-72 carbapenem-resistant Acinetobacter baumannii isolate from a sacral decubitus ulcer. Cefiderocol was initially used; however, a newly approved sulbactam-durlobactam therapy with source control and flap coverage was successful in treating the infection. Laboratory investigation revealed cefiderocol resistance mediated by ISAba36 insertion into the siderophore receptor pirA.

Background It is a major clinical challenge to ensure the long-term function of transplanted kidneys. Specifically, the injury associated with cold storage (CS) of kidneys compromises the long-term function of the grafts after transplantation. Therefore, the molecular mechanisms underlying CS-related kidney injury are attractive therapeutic targets to prevent injury and improve long-term graft function. Previously, we found that constitutive proteasome function was compromised in rat kidneys after CS followed by transplantation. Here, we evaluated the role of the immunoproteasome (iproteasome), a proteasome variant, during CS followed by transplantation. Methods Established in vivo rat kidney transplant model with or without CS containing vehicle or iproteasome inhibitor (ONX 0914) was used in this study. The iproteasome function was performed using rat kidney homogenates and fluorescent-based peptide substrate specific to beta 5i subunit. Western blotting and quantitative RT-PCR were used to assess the subunit expression/level of the iproteasome (beta 5i) subunit. Results We demonstrated a decrease in the abundance of the beta 5i subunit of the iproteasome in kidneys during CS, but beta 5i levels increased in kidneys after CS and transplant. Despite the increase in beta 5i levels and its peptidase activity within kidneys, inhibiting beta 5i during CS did not improve graft function after transplantation. Summary These results suggest that the pharmacologic inhibition of immunoproteasome function during CS does not improve graft function or outcome. In light of these findings, future studies targeting immunoproteasomes during both CS and transplantation may define the role of immunoproteasomes on short-term and long-term kidney transplant outcomes.

Abstract Background. Doxorubicin (DOX) is a highly effective chemotherapy agent that is commonly used in combination with other chemotherapy regimens to treat a wide range of cancers, including 32% of breast cancer (BC) cases. Although DOX has greatly increased the number of long-term cancer survivors, some DOX recipients have experienced DOX-induced cardiotoxicity (DIC). Currently, there are no validated markers that can predict the early development of DIC. Cardiac troponin released by cardiomyocytes has been used in non-clinical studies as a marker of myocardial injury; however, the false positive rates are high, and the predictive value on cardiotoxicity is limited. Therefore, novel biomarkers of DIC are urgently needed to identify patients who are at an increased risk, allowing early detection of the cardiotoxicity before it causes permanent cardiac damage. Methods. Untargeted metabolomics profiling was performed for plasma samples from a cohort of 28 breast cancer patients who developed abnormal cardiac function (ABN) and those who maintained normal cardiac function (NML). Blood samples were collected before, during, and after DOX-containing chemotherapy. Using both baseline observations and pre-post changes, machine-learning techniques were used to identify metabolite markers that can be used as early indicators of DIC in BC patients. Area under the receiver operating characteristic curve was reported to evaluate the performance of significant metabolites, and metabolite set enrichment analysis (MSEA) and network analysis were used to extrapolate known associations between metabolites and diseases. Results. Significant separation of plasma metabolomics profiles between ABN and NML patients at baseline was observed. From 1,124 metabolites, abundance of 59 metabolites were found to differ between ABN and NML patients at baseline. Across all patients, levels of 78 metabolites changed between baseline and after the 1st chemotherapy cycle. Of the 6 metabolites identified in both baseline and pre-post data, ABN patients had higher levels of dicarboxylic acids suberate and sebacate derived from ω-oxidation of fatty acids at baseline than NML patients. Enrichment analysis on the metabolites from the pre-post analysis suggested myocardio injury and carnitine palmitoyltransferase deficiency. Network analysis of metabolite-disease interactions further suggests potential impact on neurological health after chemotherapy. Conclusion. The metabolomics phenotype identified is indicative of impaired beta-oxidation at baseline for ABN patients. In addition, our findings suggest neurotoxic effect from DOX, implicating the potential brain-heart axis involved behind the cardiotoxicity phenotype. Citation Format: Se-Ran Jun, Katherine Wallis, Reid D. Landes, Valentina K. Todorova, L. Joseph Su, Sam Makhoul, Ping-Ching Hsu. Metabolic phenotypes of doxorubicin-induced cardiotoxicity in breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3625.

Antimicrobial resistance (AMR) poses a significant global public health challenge, responsible for the rise in hospital-acquired infections and increased levels of illness and death. The misuse and overuse of antibiotics have played a role in fostering drug resistance among pathogens, creating a pressing need for effective strategies to predict AMR phe-notypes. Employing machine learning techniques has emerged as valuable tools in this endeavor, enabling the analysis of vast datasets to identify patterns and predict the resistance or susceptibility of microorganisms to specific antibiotics. The utilization of machine learning presents a promising approach to combat the growing threat of AMR, with the potential to significantly enhance patient outcomes. The objective of this study is to enhance AMR prediction employing machine learning techniques, leveraging insights from the cybersecurity domain due to the similarities between AMR and malware datasets. The approach involves employing k-mer frequency analysis and feature importance algorithms to extract significant features. The experimental outcomes highlight the following key findings: (1) Our approach demonstrates competitive performance, even with a small dataset; and (2) Utilizing 10-mers yields better outcomes than 7-mers. This research has shown that by applying cross-domain research methodologies and capitalizing on the shared characteristics among different datasets, the performance of AMR prediction can be improved.

Enterococcus faecium is a member of the gastrointestinal microbiota. Although its virulence is low in healthy, immunocompetent individuals, E. faecium has become the third leading cause of health care-associated infections in the United States.