Search Results (12,393)

Volatile composition is a core trait that determines the ornamental and application value of Rosa flowers. In the current study, the volatile profiles of freeze-dried Rosa gallica flowers were comprehensively characterized via gas chromatography-mass spectrometry (GC-MS), coupled with heatmap clustering, principal component analysis (PCA), and relative odor activity value (rOAV) determination. A total of 181 volatile compounds were identified, and distinct volatile profiles were observed between flower samples treated with headspace extraction (RG-HS) and solid-phase microextraction (RG-SPME). Alcohols were the dominant volatile class in RG-SPME, whereas aldehydes were abundant in the RG-HS group. In terms of aroma characteristics, RG-SPME presented stronger green, floral, citrus, and fatty odors, while RG-HS exhibited a more pronounced fruity note. Moreover, sulfurous and dairy notes were unique to RG-SPME and RG-HS, respectively. Additionally, 27 volatiles showed rOAV above one, with 2,3-butanedione and trans-citral having the greatest rOAV value of 100, were identified as the potential aroma-active contributors to butter-like and citrus odors in RG-HS and RG-SPME, respectively. These results provide a methodological reference for volatile profiling of R. gallica flowers, and support the selection of appropriate extraction methods for future research and resource utilization. Full article

Alterations in microbiota, transcript and metabolites are critical to intestinal homeostasis and host health. This study used a combination of 16s rRNA, transcriptome sequencing and liquid chromatography–mass spectrometry to investigate intestinal microbiota, genes and metabolic profiles in the ileum of Hu sheep fed broccoli extract. Here, we randomly allocated 14 Hu sheep to two diets: a basal diet without any supplementation (NC) and a basal diet supplemented with 200 mg/kg broccoli tail (BT). After 60 days of treatment, blood and jejunal samples were collected for serum biochemical indicators and multi-omics analysis. In this study, the extract of broccoli tails had a significant effect on the serum biochemical indicators, including white blood cells, red blood cells, mean corpuscular volume, mean corpuscular hemoglobin concentration, mean platelet volume, triglycerides and total protein in Hu sheep (p < 0.05). Transcriptomic analysis showed that the 672 differentially expressed genes between the NC and BT groups were primarily enriched in linoleic acid metabolism, steroid hormone biosynthesis, and cholesterol metabolism. Metabolomics analysis using Kyoto Encyclopedia of Genes and Genomes enrichment showed that the 41 differentially abundant metabolites were mainly enriched in bile secretion, vitamin B6 metabolism, and the mTOR signaling pathway. 16S rRNA sequencing results indicated that the extract of broccoli tails increased the relative abundance of Peptostreptococcaceae and decreased the relative abundance of Lachnospiraceae, Lachnospirales, and Bacteroidaceae. Integrated transcriptome, metabolome, and microbiome analysis showed that the gut microbiota and host transcriptomic changes may participate in systemic metabolic regulation by modulating amino acid metabolism, lipid signal transduction, nucleotide metabolism, and vitamin B6-related metabolic pathways. These findings demonstrate that the extract of broccoli tails modulates intestinal gene expression, systemic metabolism, and gut microbial ecology in Hu sheep, providing new insights into the utilization of agricultural byproducts as a functional feed supplement for ruminants. Full article

Background/Objectives: Niclosamide is an U.S. Food and Drug Administration (FDA)-approved antihelminthic drug with a long-established safety profile and demonstrated in vitro antiviral activity against Zika virus. Its evaluation for systemic indications has been limited by its poor oral bioavailability. This Phase I study assessed whether oral administration of the approved niclosamide formulation could achieve plasma concentrations comparable to those with reported antiviral activity. Methods: This single-center, open-label, randomized, two-period crossover Phase I study evaluated the safety, tolerability, and pharmacokinetics of oral niclosamide in healthy adult volunteers. Twelve participants received niclosamide 2 g once daily for three consecutive days under fed or fasted conditions, followed by crossover after a 14-day washout period. Plasma niclosamide concentrations were quantified using a validated Liquid Chromatography-Mass Spectrometry (LC–MS/MS) assay, and pharmacokinetic parameters were derived via non-compartmental analysis. Safety assessments included adverse event monitoring, clinical laboratory testing, vital signs, electrocardiograms, and physical examinations. Results: Nine participants per protocol completed the study. Niclosamide was safe and well tolerated under both fed and fasted conditions, with only mild to moderate, transient adverse events and no serious or severe events. Systemic exposure was markedly higher following fed administration, with mean maximum observed plasma concentration (C_max) and Area Under the Curve (AUC) values several-fold greater than those observed under fasted conditions. Under fed conditions, mean plasma niclosamide concentrations exceeded the reported in vitro Zika virus half-maximal inhibitory concentration (IC₅₀₎ (0.22 µM) for approximately 9 h post-dose on both Day 1 and Day 3. Fasted administration did not consistently achieve this exposure threshold. No unexpected accumulation was observed with repeated once-daily dosing. Conclusions: Oral niclosamide administered at the approved daily dose of 2 g is safe and well tolerated in healthy volunteers. Administration with food substantially enhances systemic exposure and transiently achieves plasma concentrations associated with in vitro antiviral activity against Zika virus. These findings support further development of optimized niclosamide formulations to achieve sustained systemic exposure for antiviral therapeutic applications. Full article

Background: H₂ gas inhalation has been proposed as a selective modulator of reactive oxygen species (ROS), potentially mitigating treatment-related oxidative damage. This study investigated the effects of adjunctive H₂ gas inhalation on serum metabolomic profiles and clinical toxicities in patients with LAHNC undergoing CCRT. Methods: Twenty patients were prospectively randomized to receive either standard CCRT alone (Group A) or CCRT combined with adjunctive H₂ gas inhalation (Group B). Serum samples collected before and after treatment were analyzed using untargeted ultra-high-performance liquid chromatography coupled with ion mobility quadrupole time-of-flight high-resolution mass spectrometry (UHPLC-IM-QTOF-HRMS)-based metabolomics. Results: One patient in Group B discontinued participation, leaving 19 patients for the final analysis. Patients receiving adjunctive H₂ gas inhalation tended to exhibit numerically lower frequencies of moderate treatment-related toxicities, fewer chemotherapy delays, and a shorter overall treatment duration than those receiving CCRT alone. Metabolomic profiling in the CCRT-alone group revealed exploratory alterations in metabolites associated with arginine metabolism, glutathione metabolism, and purine metabolism following treatment. Ornithine, uric acid, and tetrahydrodeoxycorticosterone were among the candidate discriminative metabolites with exploratory discriminatory performance after CCRT. In contrast, patients receiving adjunctive H₂ gas inhalation showed a more limited pattern of pathway mapping, with exploratory evidence from an illustrative single-hit pathway assignment suggesting possible involvement of purine metabolism. Altered uric acid levels together with changes in several lipid-related metabolites may collectively reflect metabolic responses associated with treatment-related oxidative stress during CCRT. Consistent with these findings, direct between-group comparison of within-subject changes (Δ = post − pre) indicated a numerically smaller reduction in serum uric acid levels in the adjunctive H₂ gas inhalation group; however, this difference did not reach statistical significance. Conclusions: Adjunctive H₂ gas inhalation during CCRT may be associated with reduced moderate treatment-related toxicities and exploratory changes in systemic metabolic profiles in patients with LAHNC. However, the study was not designed to evaluate oncological outcomes, and the metabolomic findings, particularly the pathway-level interpretations, should be considered exploratory because several pathway assignments were based on only one or a few mapped metabolites, together with the limited sample size, patient heterogeneity, and lack of independent external validation. Further validation in larger, independent cohorts using comprehensive between-group metabolomic analyses is warranted. Full article

Honey is a high-value food product that is vulnerable to adulteration with exogenous sugars, posing challenges for food authenticity and consumer protection. This study applied Stable Isotope Ratio Analysis (SIRA) to assess the authenticity of honey collected from three major honey-producing regions of Ghana (Volta, Bono and Bono East). A total of 28 honey samples were analysed by elemental analysis–isotope ratio mass spectrometry (EA-IRMS) to obtain carbon (δ¹³C), nitrogen (δ¹⁵N) and sulphur (δ³⁴S) isotope composition. Honey authenticity was evaluated according to AOAC Official Method 998.12 by comparing δ¹³C values of bulk honey and the corresponding protein fraction. The δ¹⁵N and δ³⁴S values in honey protein were used to investigate environmental and regional variability. Samples without detectable C4 adulteration exhibited δ¹³C_protein values consistent with C3 floral sources, whereas several samples showed Δδ¹³C values more negative than −1.0‰, indicating the presence of C4-derived sugars above the AOAC adulteration threshold. Calculated C4 sugar contents ranged from 8 to 12% in moderately adulterated samples to as high as 78–79% in severely adulterated samples, confirming substantial dilution with C4 sugars. Nitrogen and sulphur isotope ratios provide additional information on environmental and regional variability among the sampled regions. Principal Component Analysis revealed that the first two principal components (PC1 and PC2) accounted for 83.8% of the total variance 83.8% of the total variance and showed separation between samples with detectable C4 adulteration and those without, while highlighting regional isotopic differences. These results demonstrate that stable isotope analysis is an effective tool for detecting C4 sugar adulteration in honey and that the combined use of carbon, nitrogen and sulphur isotopes can provide additional information on environmental and regional variability. These findings provide preliminary isotopic data on honey collected from three major honey-producing regions of Ghana and support the application of the stable isotope approach for honey authenticity assessment and quality control. Full article

Background/Objectives: Tripterygium glycosides (TG) are used to treat inflammatory and autoimmune diseases, but their clinical application is limited by toxicity and the lack of process-responsive quality markers. This study examined whether roasting and dealkalization remodel the TG metabolite profile and alter the post-dose serum profile of circulating prototype constituents. Methods: Self-prepared TG, roasted TG (RTG), roasted–dealkalized TG (RDTG), and five marketed products were profiled by ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Seven representative compounds were quantified by validated high-performance liquid chromatography (HPLC). Rat serum after oral administration was analyzed to compare circulating prototype constituents. Results: We characterized 243 constituents in material samples and 63 circulating prototype constituents in serum. Roasting primarily reshapes the profiles of diterpenoids and triterpenoids. Celastrol was not detected in the RTG and RDTG material samples, nor in the corresponding single-time-point serum profiles under the current analytical conditions. In contrast, wilforlide A exhibited an increase in material samples. Dealkalization preferentially reduced alkaloid-related constituents, including wilforine in material samples and tripterygiumine T in serum. Conclusions: Integrated material profiling, targeted quantification, and serum prototype analysis identified candidate process-responsive markers for processed TG preparations. Because the serum study was based on relative signal intensities rather than full pharmacokinetics, these markers require further pharmacokinetic and toxicological validation. Full article

Background/Objectives: Styphnolobium japonicum cv. Jinhuai (SJvJ) represents a medicinal and edible plant whose metabolite composition is strongly shaped by its growing location. Current quality control methods mainly rely on rutin quantification, lacking comprehensive metabolic markers for origin discrimination. Therefore, this study aimed to profile interregional metabolic differences between Guangxi and Sichuan SJvJ flower buds, identify characteristic differential markers, and clarify relevant metabolic pathways, thereby guiding quality control, germplasm evaluation, and functional food development. Methods: Ultra-high performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) was employed to identify metabolites. The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Cancer HSP were applied to screen the key active ingredients of traditional Chinese medicine (TCM-KAIs) and disease-related pharmaceutical ingredients (PDRIs). Specifically, we targeted six highly prevalent human diseases and another five disorders based on therapeutic indications documented in the Chinese Pharmacopoeia. Multivariate analyses, such as principal component analysis, hierarchical clustering analysis, and other statistical methods, were applied to investigate differential metabolites. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was utilized for pathway enrichment analysis of marker metabolites. Results: In total, 1550 metabolites were identified across 12 categories, predominantly flavonoids. Additionally, 152 TCM-KAIs and 204 PDRIs against 11 diseases were screened. Multivariate analyses indicated that geographical origin was closely associated with observed metabolic variation among the tested samples: Guangxi samples accumulated higher lipids and nucleotides, whereas Sichuan samples showed higher levels of flavonoids and phenolic acids. Vanilloloside, protocatechuic acid-4-O-glucoside, and gallic acid-4-O-glucoside were identified as key inter-group biomarkers. KEGG enrichment analysis revealed enhanced metabolism of nucleotide/pyrimidine in Guangxi, whereas zeatin biosynthesis was upregulated in Sichuan, consistent with discrepancies in regional climatic patterns. Conclusions: This study established a more comprehensive metabolomic dataset for FBSJvJ. It also clarified the correlations between origin and quality and unraveled the underlying mechanisms. These findings facilitate origin authentication, standardized quality control, and rational exploitation of FBSJvJ as raw materials of functional foods. Full article

Peak annotation in Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) is a persistent bottleneck that typically requires the manual assignment of chemical formulas to hundreds of fragment ion peaks per spectrum. This work describes a physics-informed probabilistic framework that automates this task by combining five chemically motivated constraints—Gaussian mass accuracy, element composition priors, isotope pattern matching, nitrogen rule parity, and graded valence bounds—into a multiplicative belief score. We evaluate the framework on 643 ground-truth peaks from 151 compounds spanning both positive and negative ion modes, and we explicitly distinguish two regimes. As a scoring task—when the correct formula is present in the candidate list—the framework attains 52.3% Top-1 and 76.4% Top-3 accuracy, a 4.9-fold improvement over mass-only scoring. In fully automated end-to-end deployment, where candidates are generated de novo, Top-1 accuracy is 26.3%; the limiting factor is candidate generation rather than scoring, as only 46.5% of ground-truth formulas are currently produced by the database and combinatorial generator. Leave-One-Compound-Out Cross-Validation (59 compounds, 525 peaks) yields 51.8% Top-1 accuracy with fixed domain-knowledge weights, confirming generalization stability. Ablation analysis identifies element composition priors as the dominant non-mass constraint (−27.7 percentage points when removed), followed by isotope matching (−10.3 pp) and the nitrogen rule (−5.3 pp). The framework requires no labeled training spectra—relying instead on physically motivated priors and curated fragment databases—provides interpretable per-constraint scores (which represent relative rankings rather than calibrated probabilities), and supports polarity-specific configurations, offering a practical computational foundation for automated ToF-SIMS spectrum interpretation. Full article

An analytical method was established for the rapid determination of 45 pigments and preservatives in edible ink by ultra-high performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-MS/MS), which provides technical support for the composition analysis and industrial development of edible ink. The samples were easily extracted with 75% aqueous methanol solution and purified with a Captiva EMR-Lipid HF solid-phase extraction cartridge. After filtration through a polytetrafluoroethylene (PTFE) membrane, the analytes were determined by UHPLC-MS/MS under multiple reaction monitoring (MRM) mode in both positive and negative ion modes. Poroshell 120 AQ-C18 was selected as the analytical column, and valve switching timing control was adopted during the gradient elution process. The external standard method was used for quantitative analysis. In the established method, the 45 pigments and preservatives exhibited good linear relationships within the mass concentration range of 0.0002–200.0 μg/mL. The limits of detection (LOD) and limits of quantification (LOQ) were 0.0004–8.00 mg/kg and 0.001–20.00 mg/kg, respectively. Using 25% aqueous glycerol solution as the blank matrix, the recoveries of analytes at different spiked levels met the detection requirements. The established method is simple and rapid, and can be applied to the qualitative and quantitative detection of typical pigments and preservatives in edible ink. Full article

Background/Objectives: Oral squamous cell carcinoma (OSCC) remains clinically heterogeneous, and prognosis is not always fully explained by conventional clinicopathological parameters. Systemic inflammation and tumor metabolic alterations may provide complementary information on tumor biology. This study aimed to assess associations between preoperative inflammatory markers, isotope ratio mass spectrometry (IRMS)-derived tumor signatures, clinicopathological features, and survival outcomes in OSCC. Methods: This exploratory retrospective secondary analysis included 50 consecutive patients with surgically treated, histologically confirmed OSCC. Preoperative blood-based markers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), white blood cell count, lymphocyte count, and C-reactive protein, were retrieved from routine laboratory tests. Matched tumor, surgical margin, and healthy oral mucosa samples were analyzed by IRMS for δ¹³C, δ¹⁵N, carbon and nitrogen content, and [N]/[C] ratio. Associations with clinicopathological variables, nodal status, overall survival (OS), and disease-free survival (DFS) were evaluated using non-parametric tests, Spearman correlations, and Cox regression models. Results: Tumor tissue showed a consistent isotope and elemental phenotype compared with healthy mucosa, including higher nitrogen content, lower carbon content, increased [N]/[C] ratio, lower δ¹⁵N, and less negative δ¹³C values. NLR, PLR, SII, and CRP were not robustly associated with standard clinicopathological features after correction for multiple testing. Correlations between inflammatory and isotope-derived parameters were modest. Higher NLR was associated with worse OS and DFS and remained significant after adjustment for pathologic nodal status. Less negative tumor δ¹³C showed a potential adverse prognostic signal. Conclusions: Systemic inflammatory markers and IRMS-derived tumor signatures appear to reflect partly distinct biological domains in OSCC. NLR may provide accessible prognostic information, while tumor δ¹³C warrants further validation as a metabolic biomarker. Full article

Metabolic dysfunction-associated fatty liver disease (MAFLD) is now the leading cause of hepatocellular carcinoma (HCC) globally. HCC surveillance is currently restricted to patients with cirrhosis, leaving those without cirrhosis, who present with more advanced disease and poorer outcomes without adequate risk stratification tools. This study compared lipid profiles across MAFLD and MAFLD-related HCC (MAFLD-HCC) patients, with and without cirrhosis, to characterise metabolic dysregulation underlying non-cirrhotic MAFLD-HCC (ncMAFLD-HCC). Plasma and liver lipidomic profiles were obtained from 221 patients (140 MAFLD, 66 cirrhotic MAFLD-HCC (cMAFLD-HCC), and 15 ncMAFLD-HCC) using untargeted liquid chromatography mass spectrometry. Univariate, multivariable and enrichment analyses were performed for statistically determining the lipid profile difference between the groups. Seventy percent of lipid classes were more abundant in MAFLD than in ncMAFLD-HCC and cMAFLD-HCC. Multivariate analysis revealed distinct lipid profiles across the three groups in both plasma and liver. Over 100 lipid species including diglyceride (DAG), sphingomyelin (SM), triglyceride (TG), dihydroceramide (DHCer), and linoleic acid derivatives were differentially expressed in ncMAFLD-HCC versus MAFLD, with enrichment in pathways such as glycerolipid metabolism, G-protein signalling, MAPK signalling, EGFR-TKI resistance pathway, implicated in HCC development. ncMAFLD-HCC exhibits a distinct lipid signature, offering preliminary mechanistic insight and a foundation for non-invasive biomarker development. Full article

Herein, we present the synthesis of N-(4-fluorobenzyl)-N’-(4-fluorobenzylidene)-4-methylbenzenesulfonohydrazide. The compound has been thoroughly characterized through melting-point determination, ¹H and ¹³C NMR spectroscopy and mass spectrometry. The structure was unequivocally determined by X-ray analysis. The comprehensive analytical data obtained from these techniques confirm the successful preparation and structural integrity of the newly synthesized molecule. Full article

Background: Soil streptomycetes, particularly those isolated from extreme environments, are valuable sources of bioactive compounds. Their genomes encode a large number of biosynthetic gene clusters (BGCs), many of which can be simultaneously expressed. Methods: Molecular genetic methods were employed to identify Streptomyces anulatus 89 (Illumina NovaSeq 2 × 150 bp). Whole-genome phylogeny based on orthologous genes was employed using the Bacterial and Viral Bioinformatics Resource Centre services. Liquid chromatography–mass spectrometry analysis of biomass extract was carried out to identify antibiotics. Bioassays on cell lines were employed to evaluate the cytotoxicity and antitumor activity of the crude extract of the S. anulatus 89 strain. Results: Genome analysis identified 36 BGCs associated with secondary metabolites. The strain synthesized nactins, pladienolide, phenazinomycin, and 21-hydroxyoligomycin. The biomass extract demonstrated cytotoxicity against cancer cells and induced apoptosis. The A549 and A431 cell lines were the most sensitive. Changes in tumor cell morphology included rounding, shrinkage, increased granularity, and vacuolization. Conclusions: The ability of S. anulatus 89 to simultaneously synthesize different classes of anticancer antibiotics was reported. The investigated crude extract exhibited pronounced antitumor activity, making it a promising candidate for further studies. The underlying hypothesis suggested that strains with broad adaptive potential may serve as promising producers of natural products with antitumor properties. Full article

Depressive symptoms are common in older adults and may be influenced by environmental element exposure. This study evaluated associations of individual and mixed blood element concentrations with depressive symptoms in older adults. A total of 1302 community-dwelling adults aged ≥60 years were included in a 2022 cross-sectional survey, and 384 of them also participated in a 2016 survey. Whole-blood concentrations of 18 elements were measured by inductively coupled plasma mass spectrometry, and depressive symptoms were assessed using the GDS-30. Logistic regression, restricted cubic spline regression, weighted quantile sum regression, quantile g-computation, and Bayesian kernel machine regression were applied. In the longitudinal subcohort, baseline aluminum and vanadium concentrations were inversely associated with the remission of depressive symptoms. In the cross-sectional analysis, aluminum, strontium, and barium were positively associated with depressive symptoms, whereas magnesium was inversely associated. Mixture analyses suggested that the positive association of the aluminum–strontium–barium mixture with depressive symptoms was attenuated after magnesium was added to the model. These findings indicate that co-exposure to aluminum, strontium, and barium was positively associated with depressive symptoms, whereas magnesium was inversely associated and appeared to attenuate the observed mixture association. Full article

Objectives: To assess the feasibility and reproducibility of predicting antimicrobial resistance (AMR) in Escherichia coli from MALDI-TOF mass spectrometry data using a standardized, open-source machine learning (ML) workflow, we systematically compared four ML algorithms, evaluated the impact of culture conditions, extract storage, and spectral preprocessing on model performance, and validated results through nested cross-validation with statistical significance testing. Methods: A total of 282 clinical E. coli isolates were analyzed. Two MALDI-TOF MS datasets were generated from freshly cultured extracts (T₁) and recultured isolates one year later (T₃), yielding 4468 spectra. A third dataset from the T₁ extracts stored at −20 °C for one year (T₂) was evaluated for spectral stability but excluded from primary modeling likely due to storage-induced degradation. Protein spectra (m/z 2000–15,000) were preprocessed using an in-house developed MALDI-TOF preprocessing pipeline (MTPP) comprising variance stabilization, Savitzky–Golay smoothing, SNIP baseline correction, TIC normalization, LOWESS alignment, and MAD-based peak detection (SNR ≥ 3), yielding 121 m/z features. Four classifiers—Random Forest (RF), Logistic Regression, Support Vector Machine, and Gradient Boosting—were trained to predict resistance to 11 antibiotics using nested cross-validation: outer GroupShuffleSplit (5-fold, isolate-level) for evaluation and inner GroupKFold for recursive feature elimination (RFECV) and hyperparameter tuning (RandomizedSearchCV). Classification thresholds were optimized via the precision–recall curve. Model performance was assessed using AUROC, AUPRC, F1-score, Matthews Correlation Coefficient (MCC), and bootstrap 95% confidence intervals (1000 replicates). Pairwise model comparisons were tested with McNemar’s chi-squared test. Results: Among the 12 antibiotics included in the analysis (meropenem excluded for absence of resistance), resistance prevalence ranged from 1.1% (colistin) to 59.9% (amoxicillin). Colistin was subsequently also excluded from ML modeling due to insufficient resistant isolates (n = 3), leaving 11 antibiotics for prediction. The best predictive performance was observed for ciprofloxacin (AUROC 0.76 [95% CI 0.74–0.77]; F1 0.54; MCC 0.38) and ceftazidime (AUROC 0.68 [0.65–0.71]; F1 0.36; MCC 0.29), using 13 and 37 RFECV-selected features, respectively. Amoxicillin achieved the highest F1-score (0.76), driven by high recall (0.98) but modest AUROC (0.58). No meaningful predictive signal was detected for amikacin, cefepime, or tigecycline (AUROC ≤ 0.57, F1 ≤ 0.17), attributable to extreme class imbalance, and no robust multi-peak resistance signature was detected in this dataset. McNemar’s test confirmed that RF significantly outperformed Logistic Regression for all antibiotics (p < 0.01), while Gradient Boosting performed comparably to RF for ciprofloxacin (p = 0.17) and ceftazidime (p = 0.28). Frozen extracts (T₂) produced lower spectral similarity and were excluded from model training; the aligned T₁₊₃ dataset yielded the most stable performance across metrics. Conclusions: Machine learning analysis of MALDI-TOF spectra enables reproducible AMR prediction for selected antibiotics in E. coli, with ciprofloxacin and ceftazidime showing the strongest signal. Nested isolate-level cross-validation, multi-model comparison with statistical testing, and open-source code provide a transparent, reproducible foundation for integrating ML-assisted MALDI-TOF analysis into diagnostic AMR surveillance. Extract storage at −20 °C degrades spectral quality and should be avoided in ML training workflows. Full article