Over the past several decades, high-resolution brain imaging, blood and cerebrospinal fluid analyses, and other advanced technologies have changed diagnosis from an exercise depending primarily on the history and physical examination to a computer- and online resource-aided process that relies on larger and larger quantities of data. In addition, randomized controlled trials (RCT) at a population level have led to many new drugs and devices to treat neurological disease, including disease-modifying therapies. We are now at a crossroads. Combinatorially profound increases in data about individuals has led to an alternative to population-based RCTs. Genotyping and comprehensive "deep" phenotyping can sort individuals into smaller groups, enabling precise medical decisions at a personal level. In neurology, precision medicine that includes prediction, prevention and personalization requires that genomic and phenomic information further incorporate imaging and behavioral data. In this article, we review the genomic, phenomic, and computational aspects of precision medicine for neurology. After defining biological markers, we discuss some applications of these "-omic" and neuroimaging measures, and then outline the role of computation and ultimately brain simulation. We conclude the article with a discussion of the relation between precision medicine and value-based care.
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http://dx.doi.org/10.1016/j.arr.2024.102632 | DOI Listing |
J Neuroinflammation
January 2025
Department of Neurology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Yishan Road 600, Shanghai, 200233, China.
Background: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder worldwide, and microglia are thought to play a central role in neuroinflammatory events occurring in AD. Chemerin, an adipokine, has been implicated in inflammatory diseases and central nervous system disorders, yet its precise function on microglial response in AD remains unknown.
Methods: The APP/PS1 mice were treated with different dosages of chemerin-9 (30 and 60 µg/kg), a bioactive nonapeptide derived from chemerin, every other day for 8 weeks consecutively.
BMC Surg
January 2025
Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Purpose: To evaluate the efficacy of an enhanced recovery after surgery (ERAS) strategy for upper tract urothelial carcinoma (UTUC) patients undergoing laparoscopic radical nephroureterectomy (LRNU).
Methods: 90 patients who received LRNU at Zhongnan Hospital of Wuhan University between January 2018 and July 2022 were retrospectively analyzed, including 43 in the ERAS group and 47 in the pre-ERAS group. The clinical features, postoperative complications, length of hospital stay (LOS), and hospital expenditures of the two groups were compared via t-test, Mann-Whitney test, and Chi-square test.
J Transl Med
January 2025
Structure of Innovative Therapies for Abdominal Metastases, Istituto Nazionale Tumori di Napoli, IRCCS "G. Pascale", via M. Semmola, Naples, 80131, Italy.
BMC Med Imaging
January 2025
Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
Background: Benign and malignant breast tumors differ in their microvasculature morphology and distribution. Histologic biomarkers of malignant breast tumors are also correlated with the microvasculature. There is a lack of imaging technology for evaluating the microvasculature.
View Article and Find Full Text PDFNat Med
January 2025
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China.
The delivery of accurate diagnoses is crucial in healthcare and represents the gateway to appropriate and timely treatment. Although recent large language models (LLMs) have demonstrated impressive capabilities in few-shot or zero-shot learning, their effectiveness in clinical diagnosis remains unproven. Here we present MedFound, a generalist medical language model with 176 billion parameters, pre-trained on a large-scale corpus derived from diverse medical text and real-world clinical records.
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