A cross-omics data analysis strategy for metabolite-microbe pair identification.

Given the pivotal roles of metabolomics and microbiomics, numerous data mining approaches aim to uncover their intricate connections. However, the complex many-to-many associations between metabolome-microbiome profiles yield numerous statistically significant but biologically unvalidated candidates. To address these challenges, we introduce BiOFI, a strategic framework for identifying metabolome-microbiome correlation pairs (Bi-Omics). BiOFI employs a comprehensive scoring system, incorporating intergroup differences, effects on feature correlation networks, and organism abundance. Meanwhile, it establishes a built-in database of metabolite-microbe-KEGG functional pathway linking relationships. Furthermore, BiOFI can rank related feature pairs by combining importance scores and correlation strength. Validation on a dataset of cesarean-section infants confirms the strategy's validity and interpretability. The BiOFI R package is freely accessible at https://github.com/chentianlu/BiOFI.

Metabolic phenotyping reveals an emerging role of ammonia abnormality in Alzheimer's disease.

The metabolic implications in Alzheimer's disease (AD) remain poorly understood. Here, we conducted a metabolomics study on a moderately aging Chinese Han cohort (n = 1397; mean age 66 years). Conjugated bile acids, branch-chain amino acids (BCAAs), and glutamate-related features exhibited strong correlations with cognitive impairment, clinical stage, and brain amyloid-ß deposition (n = 421). These features demonstrated synergistic performances across clinical stages and subpopulations and enhanced the differentiation of AD stages beyond demographics and Apolipoprotein E ε4 allele (APOE-ε4). We validated their performances in eight data sets (total n = 7685) obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study and Memory and Aging Project (ROSMAP). Importantly, identified features are linked to blood ammonia homeostasis. We further confirmed the elevated ammonia level through AD development (n = 1060). Our findings highlight AD as a metabolic disease and emphasize the metabolite-mediated ammonia disturbance in AD and its potential as a signature and therapeutic target for AD.

Multi-omics studies reveal ameliorating effects of physical exercise on neurodegenerative diseases.

Introduction: Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease, are heavy burdens to global health and economic development worldwide. Mounting evidence suggests that exercise, a type of non-invasive intervention, has a positive impact on the life quality of elderly with neurodegenerative diseases. X-omics are powerful tools for mapping global biochemical changes in disease and treatment. Method: Three major databases were searched related to current studies in exercise intervention on neurodegenerative diseases using omics tools, including metabolomics, metagenomics, genomics, transcriptomics, and proteomics. Result: We summarized the omics features and potential mechanisms associated with exercise and neurodegenerative diseases in the current studies. Three main mechanisms by which exercise affects neurodegenerative diseases were summed up, including adult neurogenesis, brain-derived neurotrophic factor (BDNF) signaling, and short-chain fatty acids (SCFAs) metabolism. Conclusion: Overall, there is compelling evidence that exercise intervention is a feasible way of preventing the onset and alleviating the severity of neurodegenerative diseases. These studies highlight the importance of exercise as a complementary approach to the treatment and intervention of neurodegenerative diseases in addition to traditional treatments. More mechanisms on exercise interventions for neurodegenerative diseases, the specification of exercise prescriptions, and differentiated exercise programs should be explored so that they can actually be applied to the clinic.

Ultra-short long-period fiber grating based on a micro air-channel structure.

A new type of long-period fiber grating is proposed and demonstrated. The structure of the device consists of a few micro air-channels along a single-mode fiber, and is fabricated by using a femtosecond laser to inscribe a few groups of fiber inner waveguide arrays followed by hydrofluoric acid etching. The length of the long-period fiber grating is down to 600 µm, corresponding to only five grating periods. To the best of our knowledge, this is the shortest long-period fiber grating reported. The device has a good refractive index sensitivity of ∼587.08 nm/RIU (refractive index unit) in the refractive index range of 1.34-1.365 and a relatively small temperature sensitivity of ∼12.1 pm/°C, thus reducing the temperature cross-sensitivity. Such a device is expected to have promising photonic applications.