Machine Learning in Nutrition Research

Advances in Nutrition, Journal Year: 2022, Volume and Issue: 13(6), P. 2573 - 2589

Published: Sept. 27, 2022

Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods data analysis. The characteristics machine learning (ML) make it suitable for such analysis thus lend itself as an alternative tool to deal this nature. ML has already been applied important problem areas nutrition, obesity, metabolic health, malnutrition. Despite this, experts often without understanding ML, which limits its application therefore potential solve open questions. current article aims bridge knowledge gap by supplying researchers a resource facilitate use their research. is first explained distinguished from existing solutions, key examples applications literature provided. Two case studies domains particularly applicable, precision metabolomics, then presented. Finally, framework outlined guide interested integrating into work. By acting can refer, we hope support integration modern

Language: Английский

---

The Crosstalk between Gut Microbiota and Nervous System: A Bidirectional Interaction between Microorganisms and Metabolome

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(12), P. 10322 - 10322

Published: June 19, 2023

Several studies have shown that the gut microbiota influences behavior and, in turn, changes immune system associated with symptoms of depression or anxiety disorder may be mirrored by corresponding microbiota. Although composition/function intestinal appears to affect central nervous (CNS) activities through multiple mechanisms, accurate epidemiological evidence clearly explains connection between CNS pathology and dysbiosis is not yet available. The enteric (ENS) a separate branch autonomic (ANS) largest part peripheral (PNS). It composed vast complex network neurons which communicate via several neuromodulators neurotransmitters, like those found CNS. Interestingly, despite its tight connections both PNS ANS, ENS also capable some independent activities. This concept, together suggested role played microorganisms metabolome onset progression neurological (neurodegenerative, autoimmune) psychopathological (depression, disorders, autism) diseases, large number investigations exploring functional physiopathological implications microbiota/brain axis.

Language: Английский

---

Chronic kidney disease and gut microbiota

Heliyon, Journal Year: 2023, Volume and Issue: 9(8), P. e18991 - e18991

Published: Aug. 1, 2023

Chronic kidney disease (CKD) refers to a range of various pathophysiological processes correlated with abnormal renal function and progressive loss in GFR. Just as dysbiosis altered pathology the gut are accompanied hypertension, which is significant CKD risk factor. Gut patients associated an elevated levels uremic toxins, turn increases progression. According research results, gut-kidney axis has role formation stones, also IgAN. A number researchers have categorized microbiota enterotypes, others, skeptical theory suggested biomarkers describe taxa that related lifestyle, nutrition, status. Metabolome-microbiome studies been used investigate interactions host-gut terms involvement metabolites these yielded promising results. The correlation between requires further multi-omic researches. Also, regard systems biology, on communication network proteins transporters such SLC ABC, can help us achieve deeper understanding gut-liver-kidney thus provide new horizons treatment patients. Probiotic-based approach reduce poisoning, accomplished by swallowing microbes those catalyze URS gut. If comprehensive carried out, we will know about probiotics impact slowing failure progression reducing inflammatory markers.

Language: Английский

---

Maintained imbalance of triglycerides, apolipoproteins, energy metabolites and cytokines in long-term COVID-19 syndrome patients

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 14

Published: May 9, 2023

Background Deep metabolomic, proteomic and immunologic phenotyping of patients suffering from an infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have matched a wide diversity clinical symptoms potential biomarkers for disease 2019 (COVID-19). Several studies described the role small as well complex molecules such metabolites, cytokines, chemokines lipoproteins during in recovered patients. In fact, after SARS-CoV-2 viral almost 10-20% experience persistent post 12 weeks recovery defined long-term COVID-19 (LTCS) or long post-acute (PACS). Emerging evidence revealed that dysregulated immune system persisting inflammation could be one key drivers LTCS. However, how these biomolecules altogether govern pathophysiology is largely underexplored. Thus, clear understanding parameters within integrated fashion predict course would help to stratify LTCS This even allow elucidation mechanistic course. Methods study comprised subjects (n=7; longitudinal), (n=33), Recov (n=12), no history positive testing (n=73). 1 H-NMR-based metabolomics IVDr standard operating procedures verified phenotyped all blood samples by quantifying 38 metabolites 112 lipoprotein properties. Univariate multivariate statistics identified NMR-based cytokine changes. Results Here, we report on analysis serum/plasma NMR spectroscopy flow cytometry-based cytokines/chemokines quantification We lactate pyruvate were significantly different either healthy controls (HC) Subsequently, correlation group only among cytokines amino acids histidine glutamine uniquely attributed mainly pro-inflammatory cytokines. Of note, triglycerides several (apolipoproteins Apo-A1 A2) demonstrate COVID-19-like alterations compared HC. Interestingly, distinguished mostly their phenylalanine, 3-hydroxybutyrate (3-HB) glucose concentrations, illustrating imbalanced energy metabolism. Most present at low levels HC except IL-18 chemokine, which tended higher Conclusion The identification plasma will better other diseases ongoing severity

Language: Английский

---

Imaging Evaluation of Intervertebral Disc Degeneration and Painful Discs—Advances and Challenges in Quantitative MRI

Diagnostics, Journal Year: 2022, Volume and Issue: 12(3), P. 707 - 707

Published: March 14, 2022

In recent years, various quantitative and functional magnetic resonance imaging (MRI) sequences have been developed used in clinical practice for the diagnosis of patients with low back pain (LBP). Until now, T2-weighted (T2WI), a visual qualitative evaluation method, has to diagnose intervertebral disc (IVD) degeneration. However, this method limitations terms reproducibility inter-observer agreement. Moreover, T2WI observations do not directly relate LBP. Therefore, new such as T2 mapping, T1ρ MR spectroscopy alternative methods. These MRIs can evaluate anatomical physiological changes IVD degeneration more detail than conventional T2WI. values obtained from these still correlate LBP, there is need widespread use techniques that are specific symptoms pain. paper, we review state-of-the-art methodologies future challenges MRI an diagnostic tool painful discs.

Language: Английский

---

NMR in Metabolomics: From Conventional Statistics to Machine Learning and Neural Network Approaches

Applied Sciences, Journal Year: 2022, Volume and Issue: 12(6), P. 2824 - 2824

Published: March 9, 2022

NMR measurements combined with chemometrics allow achieving a great amount of information for the identification potential biomarkers responsible precise metabolic pathway. These kinds data are useful in different fields, ranging from food to biomedical including health science. The investigation whole set metabolites sample, representing its fingerprint considered condition, is known as metabolomics and may take advantage statistical tools. new frontier adopt self-learning techniques enhance clustering or classification actions that can improve predictive power over large amounts data. Although machine learning already employed metabolomics, deep artificial neural networks approaches were only recently successfully applied. In this work, we give an overview underlying wide range opportunities perform accurate assignment quantification.Various actual challenges discussed, such proper architectures model accuracy.

Language: Английский

---

Fingerprinting and profiling in metabolomics of biosamples

Progress in Nuclear Magnetic Resonance Spectroscopy, Journal Year: 2023, Volume and Issue: 138-139, P. 105 - 135

Published: Oct. 18, 2023

Language: Английский

---

Hyperpolarized NMR metabolomics

Current Opinion in Chemical Biology, Journal Year: 2023, Volume and Issue: 74, P. 102307 - 102307

Published: April 23, 2023

Language: Английский

---

Emerging biotechnologies for evaluating disruption of stress, sleep, and circadian rhythm mechanism using aptamer-based detection of salivary biomarkers

Biotechnology Advances, Journal Year: 2022, Volume and Issue: 59, P. 107961 - 107961

Published: April 13, 2022

Language: Английский

---

The role of phosphatidylcholine 34:1 in the occurrence, development and treatment of ulcerative colitis

Acta Pharmaceutica Sinica B, Journal Year: 2022, Volume and Issue: 13(3), P. 1231 - 1245

Published: Sept. 13, 2022

Lipid homeostasis is considered to be related intestinal metabolic balance, while its role in the pathogenesis and treatment of ulcerative colitis (UC) remains largely unexplored. The present study aimed identify target lipids occurrence, development UC by comparing lipidomics patients, mice colonic organoids with corresponding healthy controls. Here, multi-dimensional based on LC-QTOF/MS, LC-MS/MS iMScope systems were constructed used decipher alteration lipidomic profiles. results indicated that patients often accompanied dysregulation lipid homeostasis, which triglycerides phosphatidylcholines significantly reduced. Notably, phosphatidylcholine 34:1 (PC34:1) was characterized high abundance closely correlation disease. Our also revealed down-regulation PC synthase PCYT1α Pemt caused modeling main factor leading reduction PC34:1, exogenous PC34:1 could greatly enhance fumarate level via inhibiting transformation glutamate N-acetylglutamate, thus exerting an anti-UC effect. Collectively, our not only supplies common technologies strategies for exploring metabolism mammals, but provides opportunities discovery therapeutic agents biomarkers UC.

Language: Английский

---