Breath ketone testing: a new biomarker for diagnosis and therapeutic monitoring of diabetic ketosis

Structural elucidation of derivatives of polyfunctional metabolites after methyl chloroformate derivatization by high-resolution mass spectrometry gas chromatography. Application to microbiota metabolites

Metabolomics has become an essential discipline in the study of microbiome, emerging gas chromatography coupled to mass spectrometry as the most mature, robust, and reproducible analytical technique. Silylation is the most widely used chemical derivatization strategy, although it has some limitations. In this regard, alkylation by alkyl chloroformate offers some advantages, such as a rapid reaction, milder conditions, better reproducibility, and the generation of more stable derivatives. However, commercial spectral libraries do not include many of the alkyl derivatives, mainly for polyfunctional metabolites, which can form multiple derivatives. That introduces a huge bias in untargeted metabolomics leading to common errors such as duplicates, unknowns, misidentifications, wrong assignations, and incomplete results from which non-reliable findings and conclusions will be retrieved. For this reason, the purpose of this study is to overcome these shortcomings and to expand the knowledge of metabolites in general and especially those closely related to the gut microbiota through the thorough study of the reactivity of the different functional groups in real matrix derivatized by methyl chloroformate, a common representative alkylation reagent. To this end, a systematic workflow has been developed based on exhaustive structural elucidation, along with computational simulation, and taking advantage of the high sensitivity and high-resolution gas chromatography-mass spectrometry. Several empirical rules have been established according to chemically different entities (free fatty acids, amino acids, polyols, sugars, amines, and polyfunctional groups, etc.) to predict the number of derivatives formed from a single metabolite, as well as their elution order and structure. In this work, some methyl chloroformate derivatives not previously reported as well as the mechanisms to explain them are given. Extremely important is the interconversion of E- and Z- geometric isomers of unsaturated dicarboxylic acids (case of fumaric-maleic and case of citraconic-mesaconic acids), or the formation of cycled derivatives for amino acids, as well as common metabolites, as in the case of serine and cysteine, and many others.

Antidiabetic effect of Ardisia elliptica extract and its mechanisms of action in STZ-NA-induced diabetic rat model via 1H-NMR-based metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Ardisia elliptica Thunb. (AE) (Primulaceae) is a medicinal plant found in the Malay Peninsula and has been traditionally used to treat diabetes. However, limited studies to date in providing scientific evidence to support the antidiabetic efficacy of this plant by in-vitro and in-vivo models.

AIM OF THE STUDY

To investigate the anti-hyperglycemic potential of AE through in-vitro enzymatic activities and streptozotocin-nicotinamide (STZ-NA) induced diabetic rat models using proton-nuclear magnetic resonance (1H-NMR)-based metabolomics approach.

MATERIALS AND METHODS

Anti-α-amylase and anti-α-glucosidase activities of the hydroethanolic extracts of AE were evaluated. The absolute quantification of bioactive constituents, using ultra-high performance liquid chromatography (UHPLC) was performed for the most active extract. Three different dosage levels of the AE extract were orally administered for 4 weeks consecutively in STZ-NA induced diabetic rats. Physical assessments, biochemical analysis, and an untargeted 1H-NMR-based metabolomics analysis of the urine and serum were carried out on the animal model.

RESULTS

Type 2 diabetes mellitus (T2DM) rat model was successfully developed based on the clear separation observed between the STZ-NA induced diabetic and normal non-diabetic groups. Discriminating biomarkers included glucose, citrate, succinate, allantoin, hippurate, 2-oxoglutarate, and 3-hydroxybutyrate, as determined through an orthogonal partial least squares-discriminant analysis (OPLS-DA) model. A treatment dosage of 250 mg/kg body weight (BW) of standardized 70% ethanolic AE extract mitigated increase in serum glucose, creatinine, and urea levels, providing treatment levels comparable to that obtained using metformin, with flavonoids primarily contribute to the anti-hyperglycemic activities. Urinary metabolomics disclosed that the following disturbed metabolism pathways: the citrate cycle (TCA cycle), butanoate metabolism, glycolysis and gluconeogenesis, pyruvate metabolism, and synthesis and degradation of ketone bodies, were ameliorated after treatment with the standardized AE extract.

CONCLUSIONS

This study demonstrated the first attempt at revealing the therapeutic effect of oral treatment with 250 mg/kg BW of standardized AE extract on chemically induced T2DM rats. The present study provides scientific evidence supporting the ethnomedicinal use of Ardisia elliptica and further advances the understanding of the fundamental molecular mechanisms affected by this herbal antidote.

Diabetes noninvasive diagnostics and monitoring through volatile biomarkers analysis in the exhaled breath using optical absorption spectroscopy

The review is aimed on the analysis the abilities of noninvasive diagnostics and monitoring of diabetes mellitus (DM) and DM-associated complications through volatile molecular biomarkers detection in the exhaled breath. The specific biochemical reactions in the body of DM patients and their associations with volatile molecular biomarkers in the breath are considered. The applications of optical spectroscopy methods, including UV, IR, and terahertz spectroscopy for DM-associated volatile molecular biomarkers measurements, are described. The applications of similar technique combined with machine learning methods in DM diagnostics using the profile of DM-associated volatile molecular biomarkers in exhaled air or "pattern-recognition" approach are discussed.

Artificial Neural Processing-Driven Bioelectronic Nose for the Diagnosis of Diabetes and Its Complications

Diabetes and its complications affect the younger population and are associated with a high mortality rate; however, early diagnosis can contribute to the selection of appropriate treatment regimens that can reduce mortality. Although diabetes diagnosis via exhaled breath has great potential for early diagnosis, research on such diagnosis is restricted to disease detection, requiring in-depth examination to diagnose and classify diseases and their complications. This study demonstrates the use of an artificial neural processing-based bioelectronic nose to accurately diagnose diabetes and classify diabetic types (type I and II) and their complications, such as heart disease. Specifically, an M13 phage-based electronic nose (e-nose) is used to explore the features of subjects with diabetes at various levels of cellular and organismal organization (cells, liver organoids, and mice). Exhaled breath samples are collected during culturing and exposed to the phage-based e-nose. Compared with cells, liver organoids cultured under conditions mimicking a diabetic environment display properties that closely resemble the characteristics of diabetic mice. Using neural pattern separation, the M13 phage-based e-nose achieves a classification success rate of over 86% for four conditions in mice, namely, type 1 diabetes, type 2 diabetes, diabetic cardiomyopathy, and cardiomyopathy.

Influence of anti-obesity strategies on brain function in health and review: A review

The aim of this review was to investigate in the literature the application of strategies such as low carbohydrate diet (LCD), ketogenic diet (KD) and intermittent fasting (IF) and their effects on the CNS. We performed a narrative review of the literature. The search was specifically carried out in PubMed, selecting articles in English, which had the following keywords: obesity, central nervous system, low carb diet, ketogenic diet and intermittent fasting, using the narrative review methodology. The studies found show that the benefits of the LCD, KD and IF strategies, at the CNS level, have a strong influence on the mechanisms of hunger and satiety, as well as on the reduction of food reward and show improvement in memory and mood influenced by the interventions.

Deep Learning Image Analysis of Nanoplasmonic Sensors: Toward Medical Breath Monitoring

Sensing biomarkers in exhaled breath offers a potentially portable, cost-effective, and noninvasive strategy for disease diagnosis screening and monitoring, while high sensitivity, wide sensing range, and target specificity are critical challenges. We demonstrate a deep learning-assisted plasmonic sensing platform that can detect and quantify gas-phase biomarkers in breath-related backgrounds of varying complexity. The sensing interface consisted of Au/SiO₂ nanopillars covered with a 15 nm metal-organic framework. A small camera was utilized to capture the plasmonic sensing responses as images, which were subjected to deep learning signal processing. The approach has been demonstrated at a classification accuracy of 95 to 98% for the diabetic ketosis marker acetone within a concentration range of 0.5-80 μmol/mol. The reported work provides a thorough exploration of single-sensor capabilities and sets the basis for more advanced utilization of artificial intelligence in sensing applications.

Volatile organic compounds from exhaled breath in schizophrenia

OBJECTIVES

This study aims to find out whether volatile organic compounds (VOCs) from exhaled breath differ significantly between patients with schizophrenia and healthy controls and whether it might be possible to create an algorithm that can predict the likelihood of suffering from schizophrenia.

METHODS

To test this theory, a group of patients with clinically diagnosed acute schizophrenia as well as a healthy comparison group has been investigated, which have given breath samples during awakening response right after awakening, after 30 min and after 60 min. The VOCs were measured using Proton-Transfer-Reaction Mass Spectrometry.

RESULTS

By applying bootstrap with mixed model analysis (n = 1000), we detected 10 signatures (m/z 39, 40, 59, 60, 69, 70, 74, 85, 88 and 90) showing reduced concentration in patients with schizophrenia compared to healthy controls. These could safely discriminate patients and controls and were not influenced by smoking. Logistic regression forward method achieved an area under the receiver operating characteristic curve (AUC) of 0.91 and an accuracy of 82% and a machine learning approach with bartMachine an AUC of 0.96 and an accuracy of 91%.

CONCLUSION

Breath gas analysis is easy to apply, well tolerated and seems to be a promising candidate for further studies on diagnostic and predictive clinical utility.

Postop Complication With Euglycemic Diabetic Ketoacidosis in a Patient Receiving Empagliflozin

Euglycemic diabetic ketoacidosis (EDKA) is an uncommon diabetic complication with increasing prevalence and is associated with the use of sodium-glucose co-transporter 2 inhibitors (SGLT2i). We report the case of a 77-year-old female patient with type 2 diabetes mellitus, treated with metformin/linagliptin and empagliflozin, who initiated a slurred speech and altered level of consciousness in the postoperative period of a cholecystectomy. On observation, the patient presented with Kussmaul breathing and mucosal dryness and was ketotic. Laboratory exams showed metabolic acidosis with an elevated anion gap, normoglycemia, and positive ketonemia. Fluid replacement with dextrose solution and continuous insulin infusion were initiated, with progressive clinical and laboratory improvement. On discharge, she showed resolution of symptoms, and empagliflozin was discontinued from her usual medication. Despite the warnings of European and American medical agencies in 2015/2016, EDKA remains a challenging diagnosis due to its unspecific and insidious symptoms.

Breath Analysis in Children with Ketogenic Glycogen Storage Diseases

(1) Background: The treatment goal of ketogenic glycogen storage diseases (GSDs) is appropriate control of hypoglycemia and other disturbances such as dyslipidemia. Monitoring and treatment of ketosis are known to improve outcomes. We used breath analysis to identify volatile organic compounds (VOCs) that correlate with serum ketones in order to provide a non-invasive method of monitoring ketosis. (2) Methods: Consecutive children with ketogenic GSDs were recruited from a single center during routine admission to monitor serum glucose and ketone levels. Five breath samples were collected from every patient at the same time of blood draws. SIFT-mass spectrometry was used to analyze breath samples. Univariate linear mixed-effects regression models for 22 known VOCs and either serum ketones or glucose were performed. (3) Results: Our cohort included 20 patients aged 5–15 years with a mean BMI of 20 kg/m2 (72% tile). Most patients had GSD type 0 (35%), while 25% had type IX. VOCs that showed a significant correlation with serum ketone levels included acetone (p < 0.0001), trimethylamine (p < 0.0001), pentane (p = 0.0001), 3-methylhexane (p = 0.0047), and carbon disulfide (p = 0.0499). No correlation was found between serum glucose and any VOC. (4) Conclusions: Breath analysis is a promising noninvasive tool that can be used to predict ketone serum levels in patients with GSD.

Potential Clinical Applications for Continuous Ketone Monitoring in the Hospitalized Patient with Diabetes

PURPOSE OF REVIEW

In this review, the authors discuss potential clinical applications for continuous ketone monitoring (CKM) in a broad continuum of clinical settings from pre-hospital care and the emergency department to acute inpatient management and post-discharge follow-up.

RECENT FINDINGS

Though in its early stages, the concept of a novel continuous ketone sensing technology exerts great potential for use in the detection and hospital management of DKA, namely to overcome diagnostic barriers associated with ketoacidosis in patients with diabetes and obtain real-time BOHB levels, which may be useful in understanding both patients' response to treatment and DKA trajectory. Peri- and intra-operative use of CKM technology can potentially be applied in a number of urgent and elective surgical procedures frequently underwent by patients with diabetes and in the observation of patients during peri-operative fasting. In transitional care management, CKM technology could potentially facilitate patients' safe transition through levels of care, following hospital discharge from a DKA episode. This evaluation of the literature presents the potential advantages of adopting CKM and integrating this technology into the care algorithm of patients at risk for ketoacidosis.

Continuous Ketone Monitoring Consensus Report 2021

This article is the work product of the Continuous Ketone Monitoring Consensus Panel, which was organized by Diabetes Technology Society and met virtually on April 20, 2021. The panel consisted of 20 US-based experts in the use of diabetes technology, representing adult endocrinology, pediatric endocrinology, advanced practice nursing, diabetes care and education, clinical chemistry, and bioengineering. The panelists were from universities, hospitals, freestanding research institutes, government, and private practice. Panelists reviewed the medical literature pertaining to ten topics: (1) physiology of ketone production, (2) measurement of ketones, (3) performance of the first continuous ketone monitor (CKM) reported to be used in human trials, (4) demographics and epidemiology of diabetic ketoacidosis (DKA), (5) atypical hyperketonemia, (6) prevention of DKA, (7) non-DKA states of fasting ketonemia and ketonuria, (8) potential integration of CKMs with pumps and automated insulin delivery systems to prevent DKA, (9) clinical trials of CKMs, and (10) the future of CKMs. The panelists summarized the medical literature for each of the ten topics in this report. They also developed 30 conclusions (amounting to three conclusions for each topic) about CKMs and voted unanimously to adopt the 30 conclusions. This report is intended to support the development of safe and effective continuous ketone monitoring and to apply this technology in ways that will benefit people with diabetes.

Biomarkers and Detection Platforms for Human Health and Performance Monitoring: A Review

Human health and performance monitoring (HHPM) is imperative to provide information necessary for protecting, sustaining, evaluating, and improving personnel in various occupational sectors, such as industry, academy, sports, recreation, and military. While various commercially wearable sensors are on the market with their capability of "quantitative assessments" on human health, physical, and psychological states, their sensing is mostly based on physical traits, and thus lacks precision in HHPM. Minimally or noninvasive biomarkers detectable from the human body, such as body fluid (e.g., sweat, tear, urine, and interstitial fluid), exhaled breath, and skin surface, can provide abundant additional information to the HHPM. Detecting these biomarkers with novel or existing sensor technologies is emerging as critical human monitoring research. This review provides a broad perspective on the state of the art biosensor technologies for HHPM, including the list of biomarkers and their physiochemical/physical characteristics, fundamental sensing principles, and high-performance sensing transducers. Further, this paper expands to the additional scope on the key technical challenges in applying the current HHPM system to the real field.

Heterologous expression, characterization and evolution prediction of a diaphorase from Geobacillus sp. Y4.1MC1

β-hydroxybutyric acid is the most sensitive indicator in ketoacidosis detection, and accounts for nearly 78% of the ketone bodies. Diaphorase is commonly used to detect the β-hydroxybutyric acid in clinical diagnosis. However, the extraction of diaphorase from animal myocardium is complex and low-yield, which is not convenient for large-scale production. In this study, a diaphorase from Geobacillus sp. Y4.1MC1 was efficiently heterologous expressed and purified in E. coli with a yield of 110 mg/L culture. The optimal temperature and pH of this recombinant diaphorase (rDIA) were 55 °C and 6.5, respectively. It was proved that rDIA was a dual acid- and thermo-stable enzyme, and which showed much more accurate detection of β-hydroxybutyric acid than the commercial enzyme. Additionally, we also investigated the molecular interaction of rDIA with the substrate, and the conformation transition in different pH values by using homology modeling and molecular dynamics simulation. The results showed that 141-161 domain of rDIA played important role in the structure changes and conformations transmission at different pH values. Moreover, it was predicted that F105W, F105R, and M186R mutants were able to improve the binding affinity of rDIA, and A2Y, P35F, Q36D, N210L, F211Y mutants were benefit for the stability of rDIA.

A ZnO/ZnFe2O4 n–n heterojunction and Au loading synergistically improve the sensing performance of acetone

Response of an AAZF sensor to real breath samples from healthy volunteers and diabetic patients.

Virtual Sensor Array Based on Butterworth-Van Dyke Equivalent Model of QCM for Selective Detection of Volatile Organic Compounds

Recently virtual sensor arrays (VSAs) have been developed to improve the selectivity of volatile organic compound (VOC) sensors. However, most reported VSAs rely on detecting single property change of the sensing material after their exposure to VOCs, thus resulting in a loss of much valuable information. In this work, we propose a VSA with the high dimensionality of outputs based on a quartz crystal microbalance (QCM) and a sensing layer of MXene. Changes in both mechanical and electrical properties of the MXene film are utilized in the detection of the VOCs. We take the changes of parameters of the Butterworth-van Dyke model for the QCM-based sensor operated at multiple harmonics as the responses of the VSA to various VOCs. The dimensionality of the VSA's responses has been expanded to four independent outputs, and the responses to the VOCs have shown good linearity in multidimensional space. The response and recovery times are 16 and 54 s, respectively. Based on machine learning algorithms, the proposed VSA accurately identifies different VOCs and mixtures, as well as quantifies the targeted VOC in complex backgrounds (with an accuracy of 90.6%). Moreover, we demonstrate the capacity of the VSA to identify "patients with diabetic ketosis" from volunteers with an accuracy of 95%, based on the detection of their exhaled breath. The QCM-based VSA shows great potential for detecting VOC biomarkers in human breath for disease diagnosis.

A ketogenic diet protects DBA/1 and Scn1aR1407X/+ mice against seizure-induced respiratory arrest independent of ketosis

Patients with uncontrolled epilepsy have a high risk of sudden unexpected death in epilepsy (SUDEP). Seizure-induced respiratory arrest (S-IRA) is thought to be the determining cause of death in many cases of SUDEP. The goal of the present study was to use Scn1aR1407X/+ (Dravet Syndrome, DS) and DBA/1 mice to determine: (1) the effect of a ketogenic diet (KD) on S-IRA and (2) the relationship between serum ketones and the protective effect of a KD. Ketogenic diet treatment significantly decreased spontaneous seizure-induced mortality in DS mice compared to control (8% vs 39%, p = 0.0021). This protective effect was not abolished when ketosis was prevented by supplementing the KD with glucose (10% mortality, p = 0.0007). In DBA/1 mice, the latency to onset of S-IRA due to audiogenic seizures was delayed from 7.6 to 20.8 seconds by a KD on treatment day (TD) 7 compared to control (p < 0.0001), an effect that was reversed on TD14 when mice were crossed over to a control diet on TD7. β-Hydroxybutyrate (BHB) levels were significantly decreased in DBA/1 mice on a KD supplemented with glucose (p = 0.0038), but the protective effect was maintained. Our findings show that a KD decreases SUDEP in DS mice and increases the latency to audiogenic S-IRA in DBA/1 mice. In both mouse models, a KD was protective against S-IRA. This effect may be due in part to specific dietary components rather than generation of ketone bodies.

Effect of short-term ketogenic diet on end-tidal carbon dioxide

BACKGROUND & AIMS

Previous studies have shown that end-tidal carbon dioxide (EtCO₂) is lower with the presence of supraphysiological ketones as in the case of chronic ketogenic diet (KD) and diabetic ketoacidosis (DKA). This study aimed to determine changes in EtCO₂ upon short term KD.

METHODS

Healthy subjects were screened not to have conditions that exerts abnormal EtCO₂ nor contraindicated for KD. Subjects underwent seven days of KD while the EtCO2 and blood ketone (beta-hydroxybutyrate; β-OHB) parameters were sampled at day zero (t0) and seven (t7) of ketosis respectively. Statistically, the t-test and Pearson's coefficient were conducted to determine the changes and correlation of both parameters.

RESULTS

12 subjects completed the study. The mean score ± standard deviation (SD) for EtCO₂ were 35.08 ± 3.53 and 35.67 ± 3.31 mm Hg for t0 and t7 respectively. The mean score ±SD for β-OHB were 0.07 ± 0.08 and 0.87 ± 0.84 mmol/L for t0 and t7 respectively. There was no significant difference of EtCO₂ between the period of study (p > 0.05) but the β-OHB increased during t7 (p < 0.05). There was also no correlation between the parameters.

CONCLUSIONS

These findings suggest that EtCO₂ may not be utilized to determine short term nutritional ketosis.

Effects of Reduced Carbohydrate Intake after Sprint Exercise on Breath Acetone Level

Assessment of breath acetone level may be an alternative procedure to evaluate change in fat metabolism. The purpose of the present study was to investigate the effect of insufficient carbohydrate (CHO) intake after sprint exercise on breath acetone level during post-exercise. Nine subjects conducted two trials, consisting of either reduced CHO trial (LOW trial) or normal CHO trial (NOR trial). In each trial, subjects visited to laboratory at 7:30 following an overnight fast to assess baseline breath acetone level. They commenced repeated sprint exercise from 17:00. After exercise, isoenergetic meals with different doses of CHO (LOW trial; 18% for CHO, 27% for protein, 55% for fat, NOR trial; 58% for CHO, 14% for protein, 28% for fat) were served. Breath acetone level was also monitored immediately before and after exercise, 1 h, 3 h, 4 h, and 15 h (on the following morning) after completing exercise. A significant higher breath acetone level was observed in LOW trial than in NOR trial 4 h after completion of exercise (NOR trial; 0.66 ppm, LOW trial; 0.9 ppm). However, breath acetone level did not differ on the following morning between two trials. Therefore, CHO intake following an exhaustive exercise affects breath acetone level during early phase of post-exercise.

Breath Acetone Measurement-Based Prediction of Exercise-Induced Energy and Substrate Expenditure

The purpose of our study was to validate a newly developed breath acetone (BrAce) analyzer, and to explore if BrAce could predict aerobic exercise-related substrate use. Six healthy men ran on a treadmill at 70% of maximal oxygen consumption (VO_2max) for 1 h after two days of a low-carbohydrate diet. BrAce and blood ketone (acetoacetate (ACAC), beta-hydroxybutyrate (BOHB)) levels were measured at baseline and at different time points of post-exercise. BrAce values were validated against blood ketones and respiratory exchange ratio (RER). Our results showed that BrAce was moderately correlated with BOHB (r = 0.68, p < 0.01), ACAC (r = 0.37, p < 0.01) and blood ketone (r = 0.60, p < 0.01), suggesting that BrAce reflect blood ketone levels, which increase when fat is oxidized. Furthermore, BrAce also negatively correlated with RER (r = 0.67, p < 0.01). In our multiple regression analyses, we found that when BMI and VO_2max were added to the prediction model in addition to BrAce, R² values increased up to 0.972 at rest and 0.917 at 1 h after exercise. In conclusion, BrAce level measurements of our BrAce analyzer reflect blood ketone levels and the device could potentially predict fat oxidation.

The correlation between breath acetone and blood betahydroxybutyrate in individuals with type 1 diabetes

Ketone testing is an important element of the self-management of illness in type 1 diabetes. The aim of the present study was to see if a breath test for acetone could be used to predict quantitatively the levels of the ketone betahydroxybutyrate in the blood of those with type 1 diabetes, and thus be used as an alternative to capillary testing for ketones. Simultaneous capillary ketones and breath acetone were measured in 72 individuals with type 1 diabetes attending a diabetes clinic and on 9 individuals admitted to hospital with diabetic ketoacidosis. Capillary blood measurements ranged from 0.1 mmol l^-1 (the lower limit of the ketone monitor) to over 7 mmol l^-1, with breath acetone varying between 0.25 and 474 parts per million by volume. The two variables were found to be correlated and allowed modelling to be carried out which separated breath acetone levels into three categories corresponding to normal, elevated and 'at risk' levels of blood ketones. The results on this limited set of participants suggest that a breath acetone test could be a simple, non-invasive substitute for capillary ketone measurement in type 1 diabetes.

Characterization of a high-resolution breath acetone meter for ketosis monitoring

Background

The ketone bodies beta-hydroxybutyrate (BHB) and acetone are endogenous products of fatty acid metabolism. Although ketone levels can be monitored by measuring either blood BHB or breath acetone, determining the precise correlation between these two measurement methods has been challenging. The purpose of this study is to characterize the performance of a novel portable breath acetone meter (PBAM) developed by Readout, Inc., to compare single versus multiple daily ketone measurements, and to compare breath acetone (BrAce) and blood BHB measurements.

Methods

We conducted a 14-day prospective observational cohort study of 21 subjects attempting to follow either a low-carbohydrate/ketogenic or a standard diet. Subjects were asked to concurrently measure both blood BHB and BrAce five times per day and report the results using an online data entry system. We evaluated the utility of multiple daily measurements by calculating the coefficient of variation (CV) for each daily group of measurements. We calculated the correlation between coincident BrAce and blood BHB measurements using linear ordinary least squares regression analysis. We assessed the ability of the BrAce measurement to accurately predict blood BHB states using receiver operating characteristic (ROC) analysis. Finally, we calculated a daily ketone exposure (DKE) using the area under the curve (AUC) of a ketone concentration versus time graph and compared the DKE of BrAce and blood BHB using linear ordinary least squares regression.

Results

BrAce and blood BHB varied throughout the day by an average of 44% and 46%, respectively. The BrAce measurement accurately predicted whether blood BHB was greater than or less than the following thresholds: 0.3 mM (AUC = 0.898), 0.5 mM (AUC = 0.854), 1.0 mM (AUC = 0.887), and 1.5 mM (AUC = 0.935). Coincident BrAce and blood BHB measurements were moderately correlated with R² = 0.57 (P < 0.0001), similar to literature reported values. However, daily ketone exposures, or areas under the curve, for BrAce and blood BHB were highly correlated with R² = 0.80 (P < 0.0001).

Conclusions

The results validated the performance of the PBAM. The BrAce/BHB correlation was similar to literature values where BrAce was measured using highly accurate lab instruments. Additionally, BrAce measurements using the PBAM can be used to predict blood BHB states. The relatively high daily variability of ketone levels indicate that single blood or breath ketone measurements are often not sufficient to assess daily ketone exposure for most users. Finally, although single coincident blood and breath ketone measurements show only a moderate correlation, possibly due to the temporal lag between BrAce and blood BHB, daily ketone exposures for blood and breath are highly correlated.

Factors influencing breath analysis results in patients with diabetes mellitus

Breath analysis is used to detect the composition of exhaled gas. As a quick and non-invasive detection method, breath analysis provides deep insights into the progression of various kinds of diseases, especially those with metabolism disorders. Abundant information on volatile compounds in diabetic patients has been studied in numerous articles in the literature. However, exhaled gas in diabetic patients can be altered by various complications. So far, little attention has been paid to this alteration. In our paper, we found that under air pollution conditions, diabetic patients exhale more nitric oxide. Diabetic patients with heart failure exhale more acetone than those without heart failure. After ¹³C-labeled glucose intake, patients infected with Helicobacter pylori exhaled more ¹³C and less ¹⁸O than those without infection. Exhalation with chronic kidney disease changes volatile organic compounds on a large scale. Diabetic patients with ketoacidosis exhale more acetone than those without ketoacidosis. Some specific volatile organic compounds also emanate from diabetic feet. By monitoring breath frequency, diabetic patients with obstructive sleep apnea syndrome exhibit a unique breath pattern and rhythm as compared with other diabetic patients, and sleep apnea is prevalent among diabetic patients. In addition to clinical findings, we analyzed the underlying mechanisms at the levels of molecules, cells and whole bodies, and provided suggestions for further studies.

Analysis of Paper-Based Colorimetric Assays With a Smartphone Spectrometer

We report on the adaptation of a smartphone's rear-facing camera to function as a spectrometer that measures the spectrum of light scattered by common paper-based assay test strips. We utilize a cartridge that enables a linear series of test pads in a single strip to be swiped past the read head of the instrument while the phone's camera records video. The strip is housed in a custom-fabricated cartridge that slides through the instrument to facilitate illumination with white light from the smartphone's flash LED that is directed through an optical fiber. We demonstrate the ability to detect subtle changes in the scattered spectrum that enables quantitative analysis of single-analyte and multi-analyte strips. The demonstrated capability can be applied to broad classes of paper-based assays in which visual observation of colored strips is not sufficiently quantitative, and for which analysis of red-green-blue pixel values of a camera image are not capable of measuring complex scattered spectra.

Diabetes alert dogs: a narrative critical overview

Owing to their virtually incomparable olfactory apparatus and the mutual loving relationship with man, the use of dogs for assisting humans in many activities has become commonplace. Dogs have been used for long for livestock herding, hunting and pulling. More recently, they have been employed for servicing or assisting people with disabilities, for rescuing, for pet therapy and, last but not least, for detecting a vast array of volatile organic compounds related to drugs, narcotics, explosives and foods. Although cancer detection seems the most distinguished use of “man’s best friends” in science and medicine, increasing emphasis is being placed on their capacity to perceive chemical changes or human expressions associated with harmful, even life-threating, blood glucose variations. The evidence available in the current scientific literature attests that diabetes alerting dogs (DADs) have a heterogeneous efficiency for warning owners of episodes of hypoglycemia or hyperglycemia, with sensitivities and specificities ranging between 0.29–0.80 and 0.49–0.96, respectively. Although the adoption of DADs seems effective for improving the quality of life of many diabetics patients, some important drawbacks can be highlighted. These typically include adoption and keeping expenditures, lack of certification or accreditation of dog providers, poor harmonization of training procedures, significant inter-breed, intra-breed and intra-dog variabilities, wide-ranging alert behaviors, ability of owners to identify dog’s alerts, as well as lack of quality assessment of a dog’s “diagnostic” performance. Overcoming many of these limitations shall probably make DADs more efficient tools for improving diabetes management.

Hepatocyte-specific Sirt6 deficiency impairs ketogenesis

Sirt6 is an NADH (NAD⁺)-dependent deacetylase with a critical role in hepatic lipid metabolism. Ketogenesis is controlled by a signaling network of hepatic lipid metabolism. However, how Sirt6 functions in ketogenesis remains unclear. Here, we demonstrated that Sirt6 functions as a mediator of ketogenesis in response to a fasting and ketogenic diet (KD). The KD-fed hepatocyte-specific Sirt6 deficiency (HKO) mice exhibited impaired ketogenesis, which was due to enhanced Fsp27 (fat-specific induction of protein 27), a protein known to regulate lipid metabolism. In contrast, overexpression of Sirt6 in mouse primary hepatocytes promoted ketogenesis. Mechanistically, Sirt6 repressed Fsp27β expression by interacting with Crebh (cAMP response element-binding protein H) and preventing its recruitment to the Fsp27β gene promoter. The KD-fed HKO mice also showed exacerbated hepatic steatosis and inflammation. Finally, Fsp27 silencing rescued hypoketonemia and other metabolic phenotypes in KD-fed HKO mice. Our data suggest that the Sirt6-Crebh-Fsp27 axis is pivotal for hepatic lipid metabolism and inflammation. Sirt6 may be a pharmacological target to remedy metabolic diseases.

Metabolomics applied to the discovery of tuberculosis and diabetes mellitus biomarkers

Tuberculosis (TB) and diabetes mellitus Type 2 (DM2) are two diseases as ancient as they are harmful to human health. The outcome for both diseases in part depends on immune and metabolic individual responses. DM2 is increasing yearly, mainly due to environmental, genetic and lifestyle habits. There are multiple evidence that DM2 is one of the most important risk factor of becoming infected with TB or reactivating latent TB. Mass spectrometry-based metabolomics is an important tool for elucidating the metabolites and metabolic pathways that influence the immune responses to M. tuberculosis infection during diabetes. We provide an up-to-date review highlighting the importance and benefit of metabolomics for identifying biomarkers as candidate molecules for diagnosis, disease activity or prognosis.

Pregnancy Ketonemia and Development of the Fetal Central Nervous System

Glucose is the major source of energy for the human brain which in turn uses ketone bodies as a supplement for energy deficit in glucose cell deficiency conditions. Pregnancy complicated by gestational diabetes is a condition associated with significantly increased risk of ketonemia development. The data available proves a changing influence of ketones on the central nervous system during fetal life and in adults as well. Ketone bodies freely pass through the placenta. They can affect fetal growth and organ damage development, especially the central nervous system. As agreed in the current recommendation of the diabetes associations, it is not obligatory for the attending doctor to conduct a routine inspection of ketone bodies during diabetes treatment in pregnancy. This article is a literature review of ketones' effect on the central nervous system and an attempt to initiate discussion whether we should consider including ketonemia assessment into the standard care package for pregnant women with diabetes and begin some research on the explanation of its influence on fetal development.

Enantiomeric Effect of d-Amino Acid Substitution on the Mechanism of Action of α-Helical Membrane-Active Peptides

V13K, a 26-residue peptide, has been shown to have strong antimicrobial activity, negligible hemolytic activity, and significant anticancer activity. In the present work, V13K was used as the framework to investigate the influence of helicity, as influenced by d-amino acid substitutions in the center of the peptide polar and non-polar faces of the amphipathic helix, on biological activity. The antibacterial and anticancer activities of the peptides were investigated. Atomic force microscopy and other biophysical methods were used to investigate the effect of peptide helicity on biological activity. The results showed the importance of suitable and rational modification of membrane-active peptides, based on helicity, in optimizing potential biological activity.

Metabolomic analysis of urine with Nuclear Magnetic Resonance spectroscopy in patients with idiopathic sudden sensorineural hearing loss: A preliminary study

OBJECTIVE

Idiopathic sudden sensorineural hearing loss is a frequent emergency, with unknown aetiology and usually treated with empiric therapy. Steroids represent the only validated treatment but prognosis is unpredictable and the possibility to select the patients who will not respond to steroids could avoid unnecessary treatments. Metabolomic profiling of the biofluids target the analysis of the final product of genic expression and enzymatic activity, defining the biochemical phenotype of a whole biologic system.

METHODS

We studied the metabolomics of the urine of a cohort of patients with idiopathic sudden sensorineural hearing loss, correlating the metabolic profiles with the clinical outcomes. Metabolomic profiling of urine samples was performed by ¹H Nuclear Magnetic Resonance spectroscopy in combination with multivariate statistical approaches.

RESULTS

26 patients were included in the study: 5 healthy controls, 13 patients who did not recover after treatment at 6 months while the remaining 8 patients recovered from the hearing loss. The orthogonal partial least square-discriminant analysis score plot showed a significant separation between the two groups, responders and non-responders after steroid therapy, R²Y of 0.83, Q² of 0.38 and p value <0.05. The resulting metabolic profiles were characterized by higher levels of urinary B-Alanine, 3-hydroxybutyrate and Trimethylamine N-oxide, and lower levels of Citrate and Creatinine in patients with worst outcome.

CONCLUSION

Idiopathic sudden sensorineural hearing loss is a specific disease with unclear systemic changes, but our data suggest that there are different types of this disorder or patients predisposed to effective action of steroids allowing the recover after treatment.

Diet-induced and mono-genetic obesity alter volatile organic compound signature in mice

The prevalence of obesity is still rising in many countries, resulting in an increased risk of associated metabolic diseases. In this study we aimed to describe the volatile organic compound (VOC) patterns symptomatic for obesity. We analyzed high fat diet (HFD) induced obese and mono-genetic obese mice (global knock-in mutation in melanocortin-4 receptor MC4R-ki). The source strengths of 208 VOCs were analyzed in ad libitum fed mice and after overnight food restriction. Volatiles relevant for a random forest-based separation of obese mice were detected (26 in MC4R-ki, 22 in HFD mice). Eight volatiles were found to be important in both obesity models. Interestingly, by creating a partial correlation network of the volatile metabolites, the chemical and metabolic origins of several volatiles were identified. HFD-induced obese mice showed an elevation in the ketone body acetone and acrolein, a marker of lipid peroxidation, and several unidentified volatiles. In MC4R-ki mice, several yet-unidentified VOCs were found to be altered. Remarkably, the pheromone (methylthio)methanethiol was found to be reduced, linking metabolic dysfunction and reproduction. The signature of volatile metabolites can be instrumental in identifying and monitoring metabolic disease states, as shown in the screening of the two obese mouse models in this study. Our findings show the potential of breath gas analysis to non-invasively assess metabolic alterations for personalized diagnosis.

Measuring breath acetone for monitoring fat loss: Review

OBJECTIVE

Endogenous acetone production is a by-product of the fat metabolism process. Because of its small size, acetone appears in exhaled breath. Historically, endogenous acetone has been measured in exhaled breath to monitor ketosis in healthy and diabetic subjects. Recently, breath acetone concentration (BrAce) has been shown to correlate with the rate of fat loss in healthy individuals. In this review, the measurement of breath acetone in healthy subjects is evaluated for its utility in predicting fat loss and its sensitivity to changes in physiologic parameters.

RESULTS

BrAce can range from 1 ppm in healthy non-dieting subjects to 1,250 ppm in diabetic ketoacidosis. A strong correlation exists between increased BrAce and the rate of fat loss. Multiple metabolic and respiratory factors affect the measurement of BrAce. BrAce is most affected by changes in the following factors (in descending order): dietary macronutrient composition, caloric restriction, exercise, pulmonary factors, and other assorted factors that increase fat metabolism or inhibit acetone metabolism. Pulmonary factors affecting acetone exchange in the lung should be controlled to optimize the breath sample for measurement.

CONCLUSIONS

When biologic factors are controlled, BrAce measurement provides a non-invasive tool for monitoring the rate of fat loss in healthy subjects.

Acetone as biomarker for ketosis buildup capability--a study in healthy individuals under combined high fat and starvation diets

Background

Ketogenic diets are high fat and low carbohydrate or very low carbohydrate diets, which render high production of ketones upon consumption known as nutritional ketosis (NK). Ketosis is also produced during fasting periods, which is known as fasting ketosis (FK). Recently, the combinations of NK and FK, as well as NK alone, have been used as resources for weight loss management and treatment of epilepsy.

Methods

A crossover study design was applied to 11 healthy individuals, who maintained moderately sedentary lifestyle, and consumed three types of diet randomly assigned over a three-week period. All participants completed the diets in a randomized and counterbalanced fashion. Each weekly diet protocol included three phases: Phase 1 - A mixed diet with ratio of fat: (carbohydrate + protein) by mass of 0.18 or the equivalence of 29% energy from fat from Day 1 to Day 5. Phase 2- A mixed or a high-fat diet with ratio of fat: (carbohydrate + protein) by mass of approximately 0.18, 1.63, or 3.80 on Day 6 or the equivalence of 29%, 79%, or 90% energy from fat, respectively. Phase 3 - A fasting diet with no calorie intake on Day 7. Caloric intake from diets on Day 1 to Day 6 was equal to each individual’s energy expenditure. On Day 7, ketone buildup from FK was measured.

Results

A statistically significant effect of Phase 2 (Day 6) diet was found on FK of Day 7, as indicated by repeated analysis of variance (ANOVA), F(2,20) = 6.73, p < 0.0058. Using a Fisher LDS pair-wise comparison, higher significant levels of acetone buildup were found for diets with 79% fat content and 90% fat content vs. 29% fat content (with p = 0.00159**, and 0.04435**, respectively), with no significant difference between diets with 79% fat content and 90% fat content. In addition, independent of the diet, a significantly higher ketone buildup capability of subjects with higher resting energy expenditure (R² = 0.92), and lower body mass index (R² = 0.71) was observed during FK.

Electronic supplementary material

The online version of this article (doi:10.1186/s12937-015-0028-x) contains supplementary material, which is available to authorized users.