PubMed

Methods Mol Biol. 2025;2891:67-89. doi: 10.1007/978-1-0716-4334-1_4.ABSTRACTMetabolomics data analysis includes, next to the preprocessing, several additional repetitive tasks that can however be heavily dataset dependent or experiment setup specific due to the vast heterogeneity in instrumentation, protocols, or also compounds/samples that are being measured. To address this, various toolboxes and software packages in Python or R have been and are being developed providing researchers and analysts with bioinformatic/chemoinformatic tools to create their own workflows tailored toward their specific needs. This chapter presents tools and example workflows for common tasks focusing on the functionality provided by R packages developed as part of the RforMassSpectrometry initiative. These tasks include, among others, examples to work with chemical formulae, handle and process mass spectrometry data, or calculate similarities between fragment spectra.PMID:39812977 | DOI:10.1007/978-1-0716-4334-1_4

Methods Mol Biol. 2025;2891:53-66. doi: 10.1007/978-1-0716-4334-1_3.ABSTRACTMetabolic profiling performed using untargeted metabolomics of different, complex biological samples aims to apply agnostic/holistic, hypothesis-free, analysis of the small molecules that are present in the analyzed sample. This approach has been the center of major investments and dedicated efforts from the research community for many years. However, limitations and challenges remain, particularly with regard to the validation and the quality of the obtained results. This has led to increasing community engagement, with the formation of think tanks, the establishment of working groups, and the many seminars on quality control (QC) in metabolomics. Here we describe a quality control (QC) protocol used to monitor LC-MS-based metabolomics analysis. A key target is the monitoring of analytical precision. This methodology is described for the analysis of urine but can be applied to different biological matrices, such as various biofluids, cell, and tissue extracts.PMID:39812976 | DOI:10.1007/978-1-0716-4334-1_3

Methods Mol Biol. 2025;2891:15-51. doi: 10.1007/978-1-0716-4334-1_2.ABSTRACTMetabolic profiling (untargeted metabolomics) aims for a global unbiased analysis of metabolites in a cell or biological system. It remains a highly useful research tool used across various analytical platforms. Incremental improvements across multiple steps in the analytical process may have large consequences for the end quality of the data. Thus, this chapter concentrates on which aspects of quality assurance can be implemented by a lab in the (pre-)analytical stages of the analysis to improve the overall end quality of their data. The scope of this chapter is limited to liquid-chromatography-mass spectrometry (LC-MS)-based profiling, which is one of the most widely utilized platforms, although the general principles are applicable to all metabolomics experiments.PMID:39812975 | DOI:10.1007/978-1-0716-4334-1_2

Methods Mol Biol. 2025;2891:1-14. doi: 10.1007/978-1-0716-4334-1_1.ABSTRACTMetabolic profiling continues to develop, and research is now conducted on this topic globally in hundreds of laboratories, from small groups up to national centers and core facilities. Here we briefly provide a perspective on the current status and challenges facing metabolic phenotyping (metabonomics/metabolomics) and consider future directions for this important area of biomarker and systems biology research.PMID:39812974 | DOI:10.1007/978-1-0716-4334-1_1

Appl Biochem Biotechnol. 2025 Jan 15. doi: 10.1007/s12010-024-05138-4. Online ahead of print.ABSTRACTCyanobacteria are advantageous hosts for industrial applications toward achieving sustainable society due to their unique and superior properties such as atmospheric CO2 fixation via photosynthesis. However, cyanobacterial productivities tend to be weak compared to heterotrophic microbes. To enhance them, it is necessary to understand the fundamental metabolic mechanisms unique to cyanobacteria. In cyanobacteria, NADPH and ATP regenerated by linear and cyclic electron transfers using light energy are consumed by CO2 fixation in a central metabolic pathway. The previous study demonstrated that the strain deleted a part of respiratory chain complex (ΔndhF1) perturbed NADPH levels and photosynthetic activity in Synechocystis sp. PCC 6803. It is expected that disruption of ndhF1 would result in a decrease in the function of cyclic electron transfer, which controls the ATP/NAD(P)H production ratio properly. In this study, we evaluated the effects of ndhF1 deletion on central metabolism and photosynthesis by 13C-metabolic flux analysis. As results of culturing the control and ΔndhF1 strains in a medium containing [1,2-13C] glucose and estimating the flux distribution, CO2 fixation rate by RuBisCO was decreased to be less than half in the ΔndhF1 strain. In addition, the regeneration rate of NAD(P)H and ATP by the photosystem, which can be estimated from the flux distribution, also decreased to be less than half in the ΔndhF1 strain, whereas no significant difference was observed in ATP/NAD(P)H production ratio between the control and the ΔndhF1 strains. Our result suggests that the ratio of utilization of cyclic electron transfer is not reduced in the ΔndhF1 strain unexpectedly.PMID:39812922 | DOI:10.1007/s12010-024-05138-4

Acta Diabetol. 2025 Jan 15. doi: 10.1007/s00592-024-02428-5. Online ahead of print.ABSTRACTOBJECTIVE: The objective is to investigate the differences in urinary organic acid (OA) profiles and metabolism between healthy control (HC) pregnant women and those with gestational diabetes mellitus (GDM) during the second trimester and third trimester of pregnancy.METHODS: A total of 66 HC pregnant women and 32 pregnant women with GDM were assessed for 107 hydrophilic metabolites in urine samples collected during the second and third trimester of pregnancy using tandem mass spectrometry. The urine OA profiles for each group were obtained, and metabolomic analysis and discussion were conducted.RESULTS: This study identified a total of 50 metabolic biomarkers. In the third trimester of pregnancy, short-chain dicarboxylic acids (DCAs) and tryptophan (Trp)-related metabolites were significantly upregulated in the urine of both the HC group and the GDM group. Comparatively, the glycine (Gly) levels and related synthetic precursor metabolites were lower in the GDM2 group. The overall dietary polyphenol metabolic intermediates level in the GDM group was lower than in the HC group. Among the pathways enriched for differentially expressed metabolites, the predominant metabolic pathway in the GDM group was the citric acid cycle. In contrast, in the HC group, it was the metabolism of alanine, aspartate, and glutamate.CONCLUSIONS: The study reveals the differences in metabolomics between pregnant women with HC and those with GDM, identifying several metabolites associated with the occurrence and development of GDM. Demonstrating the presence of abnormal mitochondrial and peroxisomal functions at the metabolite level in GDM will contribute to future exploration of the condition.PMID:39812790 | DOI:10.1007/s00592-024-02428-5

Funct Integr Genomics. 2025 Jan 15;25(1):14. doi: 10.1007/s10142-024-01524-7.ABSTRACTLarge-scale, pan-cancer analysis is enabled by data driven knowledge bases that link tumor molecular profiles with phenotypes. A debilitating cancer-related phenotype is skeletal muscle loss, or cachexia, which occurs partly from tumor products secreted into circulation. Using the LinkedOmicsKB knowledge base assembled from the Clinical Proteomics Tumor Analysis Consortium proteogenomic analysis, along with catalogs of human secretome proteins, ligand-receptor pairs and molecular signatures, we sought to identify candidate pan-cancer proteins secreted to blood that could regulate skeletal muscle phenotypes in multiple solid cancers. Tumor proteins having significant pan-cancer associations with muscle were referenced against secretome proteins secreted to blood from the Human Protein Atlas, then verified as increased in paired tumor vs. normal tissues in pan-cancer manner. This workflow revealed seven secreted proteins from cancers afflicting kidneys, head and neck, lungs and pancreas that classified as protein-binding activity modulator, extracellular matrix protein or intercellular signaling molecule. Concordance of these biomarkers with validated molecular signatures of cachexia and senescence supported relevance to muscle and cachexia disease biology, and high tumor expression of the biomarker set associated with lower overall survival. In this article, we discuss avenues by which skeletal muscle and cachexia may be regulated by these candidate pan-cancer proteins secreted to blood, and conceptualize a strategy that considers them collectively as a biomarker signature with potential for refinement by data analytics and radiogenomics for predictive testing of future risk in a non-invasive, blood-based panel amenable to broad uptake and early management.PMID:39812750 | DOI:10.1007/s10142-024-01524-7

Microbiol Resour Announc. 2025 Jan 15:e0099724. doi: 10.1128/mra.00997-24. Online ahead of print.ABSTRACTmpactR automates pre-processing of liquid chromatography-tandem mass spectrometry (LC-MS/MS) data from microbiological samples to correct mispicked peaks, resolve inter-sample variation in abundance across technical replicates, account for in-source ion fragmentation, and remove background noise to yield high-quality mass spectrometry features. The package is available through CRAN and GitHub.PMID:39812609 | DOI:10.1128/mra.00997-24

Acta Otolaryngol. 2025 Jan 15:1-14. doi: 10.1080/00016489.2024.2445738. Online ahead of print.ABSTRACTBACKGROUND: Noise-induced hearing loss (NIHL) is a kind of acquired sensorineural hearing loss and has shown an increasing incidence in recent years. Hence, elucidating the exact pathophysiological mechanisms and proposing effective treatment and prevention methods become the top priority. Though a great number of researches have been carried out on NIHL, few of them were focused on metabolites.AIMS/OBJECTIVES: To reveal the metabolomic changes in cochlear fluid after noise injury and search for underlying inner ear biomarkers of NIHL.MATERIAL AND METHODS: In this study, cochlea fluid extracted from guinea pigs after impulse noise exposure were subjected to GC-MS and LC-MS untargeted metabolomics analysis.RESULTS: After impulse noise exposure, 62 significantly changed metabolites in guinea pig cochlea fluid were screened out and deoxyribose 1-phosphate was selected as the key metabolite and underlying biomarker for NIHL. KEGG pathway analysis showed that oxidative phosphorylation, glycerophospholipid metabolism, pyrimidine metabolism and pentose phosphate pathway were significantly changed at all observed time points after noise.CONCLUSIONS AND SIGNIFICANCE: This study effectively promoted the application of metabolomics in hearing research. The pathophysiology process of NIHL in the inner ear was closely connected with oxidative phosphorylation, glycerophospholipid metabolism, pyrimidine metabolism and pentose phosphate pathway and deoxyribose 1-phosphate could be the biomarker for NIHL.PMID:39812472 | DOI:10.1080/00016489.2024.2445738

Physiol Genomics. 2025 Jan 15. doi: 10.1152/physiolgenomics.00040.2024. Online ahead of print.ABSTRACTPurpose: The study aimed to verify the physiological and metabolic parameters associated with the time to task failure (TTF) during cycling exercise performed within the severe-intensity domain. Methods: Forty-five healthy and physically active males participated in two independent experiments. In experiment 1, after a graded exercise test, participants underwent constant work rate cycling efforts (CWR) at 115% of peak power output to assess neuromuscular function (Potentiated twitch) pre- and post-exercise. Experiment 2 was similarl to experiment 1, but with physiological (respiratory parameters, energetic pathway contribution) and metabolic parameters in the blood (gasometry and blood lactate responses) and vastus lateralis muscle tissue (target metabolomic analysis, glycogen content, muscle pH and buffering capacity in vitro) measured instead of neuromuscular function. Results: Experiment 1 evidenced a significant decrease in muscle force with instauration of peripheral fatigability indices and no change in central fatigue indices. Severe-intensity domain exercise in Experiment 2 was accompanied by changes in physiological and metabolic parameters and in blood and muscle parameters. However, the TTF was associated with oxidative contribution (r=0.811, p<0.001), as well as anaerobic capacity (r=0.554, p=0.027), muscle buffering capacity (r=0.792, p=0.035), phosphagen energy contribution (r=0.583, p=0.017), and carnitine changes (r=0.855, p=0.016), but no correlated with electromyographic response, blood acid-base balance, and muscular glycogen content and pH. Conclusion: TTF during CWR exercise within the severe-intensity domain is likely explained by a combination of interacting mechanisms, with oxidative and phosphagen contributions, and muscle buffering capacity suggested as the main peripherals limiting factors to exercise within this exercise intensity domain.PMID:39812441 | DOI:10.1152/physiolgenomics.00040.2024

ACS Appl Mater Interfaces. 2025 Jan 15. doi: 10.1021/acsami.4c17563. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) is a common malignancy and generally develops from liver cirrhosis (LC), which is primarily caused by the chronic hepatitis B (CHB) virus. Reliable liquid biopsy methods for HCC screening in high-risk populations are urgently needed. Here, we establish a porous silicon-assisted laser desorption ionization mass spectrometry (PSALDI-MS) technology to profile metabolite information hidden in human serum in a high throughput manner. Serum metabolites can be captured in the pore channel of APTES-modified porous silicon (pSi) particles and well-preserved during storage or transportation. Furthermore, serum metabolites captured in the APTES-pSi particles can be directly detected on the LDI-MS without the addition of an organic matrix, thus greatly accelerating the acquisition of metabolic fingerprints of serum samples. The PSALDI-MS displays the capability of high throughput (5 min per 96 samples), high reproducibility (coefficient of variation <15%), high sensitivity (LOD ∼ 1 pmol), and high tolerance to background salt and proteins. In a multicenter cohort study, 1433 subjects including healthy controls (HC), CHB, LC, and HCC volunteers were enrolled and nontargeted serum metabolomic analysis was performed on the PSALDI-MS platform. After the selection of feature metabolites, a stepwise diagnostic model for the classification of different liver disease stages was constructed by the machine learning algorithm. In external testing, the accuracy of 91.2% for HC, 71.4% for CHB, 70.0% for LC, and 95.3% for HCC was achieved by chemometrics. Preliminary studies indicated that the diagnostic model constructed from serum metabolic fingerprint also displays good predictive performance in a prospective observation. We believe that the combination of PSALDI-MS technology and machine learning may serve as an efficient tool in clinical practice.PMID:39812132 | DOI:10.1021/acsami.4c17563

Physiol Plant. 2025 Jan-Feb;177(1):e70055. doi: 10.1111/ppl.70055.ABSTRACTMelatonin (MLT) is an indole derivative that exhibits hormone-like activities in plants, regulating multiple aspects of growth and development. Due to its role in mitigating oxidative stress and facilitating osmoprotectant accumulation, MLT enhances abiotic stress tolerance, although the pathways and metabolic mechanisms involved remain unclear despite being studied in various crops. This work aimed to investigate the changes elicited by the exogenous MLT application at different concentrations (10, 50, 150 μM) and its role in mitigating the salinity stress in Lactuca sativa L. through metabolomics and phenotyping approaches. Our results clearly indicated that MLT increases photosynthetic efficiency at high dosage (150 μM) at either early or late salinity stress conditions (p < 0.01). Untargeted metabolomics provided insight into the significant effect of salinity and MLT (p < 0.01 in both cases, according to multivariate chemometrics), mediated by a broad reprogramming involving secondary metabolism, phytohormones, fatty acids and amino acids biosynthesis. In detail, 150 μM MLT induced an adjustment of the phytohormones profile to reduce the salinity-induced damages. Our findings support the well-known potential of melatonin in alleviating salinity stress. These findings address existing challenges in studying the molecular effects of MLT in mitigating abiotic stress, providing insights into the biochemical pathways that drive its effectiveness. In this sense, further research is acknowledged to provide a multidisciplinary high throughput perspective leading to its exploitation in a wide range of crops of agricultural and economic importance.PMID:39812119 | DOI:10.1111/ppl.70055

Elife. 2025 Jan 15;14:e97982. doi: 10.7554/eLife.97982. Online ahead of print.ABSTRACTBackground: The role of circulating metabolites on child development is understudied. We investigated associations between children's serum metabolome and early childhood development (ECD).Methods: Untargeted metabolomics was performed on serum samples of 5,004 children aged 6-59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children's milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥ 1. The interaction between significant metabolites and the child's age was tested.Results: Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child's nutritional status, diet quality, and infant age. Cresol sulfate (β = -0.07; adjusted-p < 0.001), hippuric acid (β = -0.06; adjusted-p < 0.001), phenylacetylglutamine (β = -0.06; adjusted-p < 0.001), and trimethylamine-N-oxide (β = -0.05; adjusted-p = 0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged -1 SD: β = -0.05; p =0.01; +1 SD: β = 0.05; p =0.02) and methylhistidine (-1 SD: β = - 0.04; p =0.04; +1 SD: β = 0.04; p =0.03).Conclusion: Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays.Funding: Supported by the Brazilian Ministry of Health and the Brazilian National Research Council.PMID:39812094 | DOI:10.7554/eLife.97982

Curr Rheumatol Rev. 2025 Jan 13. doi: 10.2174/0115733971329652241119060025. Online ahead of print.ABSTRACTGouty arthritis is a common arthritic disease caused by the deposition of monosodium urate crystals in the joints and the tissues around it. The main pathogenesis of gout is the inflammation caused by the deposition of monosodium urate crystals. Omics studies help us evaluate global changes in gout during recent years, but most studies used only a single omics approach to illustrate the mechanisms of gout. In this review, we review the genomics, transcriptomics, epigenetics, proteomics, and metabolomics of gout, observing that different genes, DNA methylation, miRNAs, LncRNAs, circRNAs, proteins, and metabolites are found between hyperuricemia, acute gout arthritis, and chronic gout arthritis, and some of them are associated with disease activity, prognosis or treatment, which help us broaden our understanding of the pathogenesis and provide important clues for valuable biomarkers. To our knowledge, this is the first study that combines all omics studies from genomics to metabolomics and may serve as a reference for future studies to identify the key underlying pathways in gout.PMID:39812052 | DOI:10.2174/0115733971329652241119060025

Curr Cardiol Rev. 2025 Jan 13. doi: 10.2174/011573403X334382241210064101. Online ahead of print.ABSTRACTPlatelets, tiny cell fragments measuring 2-4 μm in diameter without a nucleus, play a crucial role in blood clotting and maintaining vascular integrity. Abnormalities in platelets, whether genetic or acquired, are linked to bleeding disorders, increased risk of blood clots, and cardiovascular diseases. Advanced proteomic techniques offer profound insights into the roles of platelets in hemostasis and their involvement in processes such as inflammation, metastasis, and thrombosis. This knowledge is vital for drug development and identifying diagnostic markers for platelet activation. Platelet activation is an exceptionally rapid process characterized by various posttranslational modifications, including protein breakdown and phosphorylation. By utilizing multiomics technologies and biochemical methods, researchers can thoroughly investigate and define these posttranslational pathways. The absence of a nucleus in platelets significantly simplifies mass spectrometry-based proteomics and metabolomics, as there are fewer proteins to analyze, streamlining the identification process. Additionally, integrating multiomics approaches enables a comprehensive examination of the platelet proteome, lipidome, and metabolome, providing a holistic understanding of platelet biology. This multifaceted analysis is critical for elucidating the complex mechanisms underpinning platelet function and dysfunction. Ultimately, these insights are crucial for advancing therapeutic strategies and improving diagnostic tools for platelet-related disorders and cardiovascular diseases. The integration of multi-omics technologies is paving the way for a deeper understanding of platelet mechanisms, with significant implications for biomedical research and clinical applications.PMID:39812040 | DOI:10.2174/011573403X334382241210064101

J Agric Food Chem. 2025 Jan 15;73(2):1725-1738. doi: 10.1021/acs.jafc.4c08975. Epub 2024 Dec 30.ABSTRACTPhenolic compounds (PC) were analyzed by UHPLC-ESI-QTOF-MSE in two sorghum genotypes, harvested in two growing seasons (GS) at five distinct days after flowering (DAF) to evaluate how genotype/GS influences the PC synthesis and antioxidant capacity during grain growth. Total phenolic contents were strongly correlated with antioxidant capacity (r > 0.9, p < 0.05). Globally, 97 PC were annotated, including 20 PC found irrespective of the grain developmental stage and genotype/GS. The phenolic profile clearly differs between stages: phenolic acids were the most abundant class in early stages (50%), and flavonoid accumulation becomes predominant in late ones (3/5 of total ion abundance). Dimeric and trimeric tannins were identified even in 10DAF grains. Chemometry revealed great PC variability between genotypes (27%) and important biomarkers of GS differentiation (e.g., ferulic acid). This work can input open databases of PC and paves the way to understand biosynthetic pathways of PC in sorghum and future sorghum selection.PMID:39811928 | DOI:10.1021/acs.jafc.4c08975

Am J Physiol Gastrointest Liver Physiol. 2025 Jan 15. doi: 10.1152/ajpgi.00227.2024. Online ahead of print.ABSTRACTAppetite, as the internal drive for food intake, is often dysregulated in a broad spectrum of conditions associated with over- and under-nutrition across the lifespan. Appetite regulation is a complex, integrative process comprising psychological and behavioral events, peripheral and metabolic inputs, and central neurotransmitter and metabolic interactions. The microbiota-gut-brain axis has emerged as a critical mediator of multiple physiological processes, including energy metabolism, brain function, and behavior. Therefore, the role of the microbiota-gut-brain axis in appetite and obesity is receiving increased attention. Omics approaches such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics in appetite and weight regulation offer new opportunities for featuring obesity phenotypes. Furthermore, gut microbiota-targeted approaches such as pre- pro- post- and synbiotic, personalized nutrition, and fecal microbiota transplantation are novel avenues for precision treatments. The aim of this narrative review is (1) to provide an overview of the role of the microbiota-gut-brain-axis in appetite regulation across the lifespan and (2) to discuss the potential of omics and gut microbiota-targeted approaches to deepen understanding of appetite regulation and obesity.PMID:39811913 | DOI:10.1152/ajpgi.00227.2024

Front Neurol. 2024 Dec 19;15:1500737. doi: 10.3389/fneur.2024.1500737. eCollection 2024.ABSTRACTINTRODUCTION: Neonatal seizures are the most common clinical manifestation of neurological dysfunction in newborns, with an incidence ranging from 1 to 5‰. However, the therapeutic efficacy of current pharmacological treatments remains suboptimal. This study aims to utilize genetically modified hamsters with hypertriglyceridaemia (HTG) to investigate the effects of elevated triglycerides on neuronal excitability and to elucidate the underlying mechanisms. The ultimate goal is to identify novel therapeutic targets for the treatment of neonatal seizures.METHODS: Acute seizure models were established both in vivo and ex vivo using wild-type and Apolipoprotein C2 knockout (Apoc2 -/-) hamsters. The frequency of tonic-clonic seizures was recorded. Excitatory postsynaptic potentials (EPSPs) and evoked action potentials (eAPs) of pyramidal neurons in the frontal cortex were measured. Fatty acid metabolomic analysis was conducted on microdialysate from the frontal cortex tissue post-seizure, and mRNA expression changes were also assessed.RESULTS: Apoc2 -/- hamsters exhibited a reduced frequency of tonic-clonic seizures and diminished EPSP and eAP in comparison to wild-type hamsters. Following seizure induction, free palmitic acid levels in the frontal cortex dialysate significantly decreased, while the expression of palmitoyl acyltransferase 14 (ZDHHC14) in the frontal cortex tissue was higher in Apoc2 -/- hamsters than in wild-type hamsters. Additionally, the amplitude of transient outward potassium currents (IA) in cortical neurons of Apoc2 -/- hamsters was observed to be elevated compared to wild-type hamsters.CONCLUSION: Hypertriglyceridemic Apoc2 -/- hamsters exhibited reduced seizure frequency and decreased cortical neuron excitability. The upregulation of ZDHHC14, leading to increased IA, may be a crucial mechanism underlying the observed seizure protection.PMID:39811454 | PMC:PMC11730077 | DOI:10.3389/fneur.2024.1500737

Heliyon. 2024 Dec 18;11(1):e41184. doi: 10.1016/j.heliyon.2024.e41184. eCollection 2025 Jan 15.ABSTRACTMicrobiome-metabolome association analysis is critical to reveal the key pairs of gut microbiota and metabolites for discovery of the microbial biomarkers in chronic diseases. However, the characteristics of microbiome data, such as zero inflation, over dispersion, may impair the confidence of association analysis between microbiome and metabolome data. The objectives of this study are to evaluate the strengths and weaknesses of existing statistical methods and to develop a computational framework tailored to the unique characteristics of microbiome data. We designed a computational framework called Integrated Statistical Correlation Analysis for Zero-Inflated Microbiome data (ISCAZIM) that takes account of complicated microbiome data characteristics, including zero inflation rates (ZIRs), dispersion and correlation patterns. ISCAZIM first benchmarked prevalent statistical correlation methods, Pearson, Spearman, zero inflated negative binomial (ZINB) model, mutual information and Maximal Information Coefficient. ISCAZIM then classifies the correlation pattern to linear or non-linear and applies the correlation method according to the ZIRs status. Applying to multiple real-world microbiome-metabolomics data, ISCAZIM is overall more accurate than using a single method with more truly significant association pairs included. Therefore, ISCAZIM will significantly facilitate the association analysis using zero-inflated microbiome data for multi-omics integration.PMID:39811376 | PMC:PMC11730854 | DOI:10.1016/j.heliyon.2024.e41184

Heliyon. 2024 Dec 19;11(1):e41390. doi: 10.1016/j.heliyon.2024.e41390. eCollection 2025 Jan 15.ABSTRACTBevacizumab is widely used in various clinical indications, but investigations into its optimal dosage for treating CNS metastases remain limited. The BEEP regimen, comprising bevacizumab, etoposide, and cisplatin, has recently demonstrated promising clinical outcomes for patients with breast cancer brain metastasis (BCBM) or leptomeningeal metastasis (LM). This study aimed to evaluate the exposure-response relationship of bevacizumab in BCBM patients and to explore the improved CNS penetration of chemotherapy by bevacizumab with LM patients. Twenty-two BCBM patients and six LM patients receiving the BEEP regimen were enrolled. For BCBM patients, blood samples were drawn at trough level of cycles 1 and 6 to investigate the association between bevacizumab concentrations and clinical outcomes. For LM patients, plasma and cerebrospinal fluid (CSF) concentrations of bevacizumab and etoposide were measured to investigate the enhancement of etoposide penetration provided by bevacizumab. Concentration evaluation revealed that bevacizumab plasma concentrations substantially varied between individuals. Additionally, concentrations increased after 6 cycles, indicating bevacizumab accumulation during treatment. Although bevacizumab concentrations did not associate with therapeutic response and progression-free survival, patients with higher bevacizumab concentrations exhibited longer overall survival (adjusted HR 0.78; p = 0.039). Furthermore, a positive correlation was observed between time-weighted average concentration of plasma bevacizumab and CSF penetration of etoposide on day 2 (post-bevacizumab) relative to day 1 (pre-bevacizumab) (r = 0.83; p = 0.042). These findings offer valuable insights into the application of therapeutic drug monitoring of bevacizumab to improve survival outcomes in BCBM patients. Further studies are warranted to determine the optimal bevacizumab concentration.PMID:39811374 | PMC:PMC11731468 | DOI:10.1016/j.heliyon.2024.e41390