{
  "abstract": "IntroductionIn vivo, temporal, and personalized data on immunological-antibiotic interactions may provide richer, earlier information that improves infection treatment. To test this hypothesis, we applied a proof-of-concept approach to evaluate a non-reductionist methodology.\n\nMethodsA non-reductionist, data-driven, pattern recognition-based combinatorial method that captures relationships was evaluated with blood leukocyte data collected from 401 individuals from Greece [n=331] and the US [n=70] who experienced sepsis, pneumonia, endocarditis, tuberculosis, syphilis, skin and soft tissue, intra-abdominal, or urinary tract infections associated with meningitis.\n\nResultsWhile ambiguity was observed when variables were measured in isolation by a reductionist alternative, ambiguity was prevented and hidden information was uncovered when complex dynamics were assessed by the non-reductionist method. The combinatorial approach grouped together observations that displayed similar immune profiles, distinguished those with different mortality risks, identified antibiotics that modulated specific leukocytes, differentiated two types of non-responsiveness (associated or not associated with antibiotics), and facilitated earlier and personalized evaluation of therapies. For instance, in tuberculosis, blood monocytes were modulated by isoniazid-related antimicrobials.\n\nDiscussionAcross numerous syndromes, the non-reductionist method extracted more information from the same data than the reductionist alternative. If corroborated, non-reductionist methodologies may promote research and support personalized medicine.",
  "abstract_shown": true,
  "affiliations": [
    "Mayo Clinic: Mayo Clinic's Campus in Florida"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "name": "M. J. Iandiorio"
    },
    {
      "name": "A. Ioannidis"
    },
    {
      "affs": [
        0
      ],
      "name": "P. Kempaiah"
    },
    {
      "name": "F. O. Fasina"
    },
    {
      "name": "P. D. Madaki"
    },
    {
      "name": "J. C. Fazio"
    },
    {
      "name": "M. M. Fasina"
    },
    {
      "name": "A. P. Rojas Gil"
    },
    {
      "name": "S. Chatzipanagiotou"
    },
    {
      "name": "G. Gerotziafas"
    },
    {
      "name": "A. L. Hoogesteijn"
    },
    {
      "name": "J. M. Fair"
    },
    {
      "name": "A. L. Rivas"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/866ngmfyk3f46.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.24.26363858",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.09.24.26363858v1.full",
  "id": "866ngmfyk3f46",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.09.24.26363858v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "infectious diseases"
    ],
    [
      "openalex",
      "2713|Sepsis Diagnosis and Treatment"
    ]
  ],
  "openalex": "W7214369583",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.09.24.26363858v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/866ngmfyk3f46.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:25Z",
      "native_id": "10.64898/2026.09.24.26363858",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.09.24.26363858v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:infectious diseases",
      "subfield": "infectious-disease"
    }
  ],
  "title": "Toward personalized and longitudinal antibiograms--a proof-of-concept for in vivo assessments of immunological-antibiotic-bacterial interactions",
  "title_text": "Toward personalized and longitudinal antibiograms--a proof-of-concept for in vivo assessments of immunological-antibiotic-bacterial interactions",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:25Z",
  "url": "https://research.draconitic.com/paper/866ngmfyk3f46",
  "venue": "medRxiv",
  "versions": []
}