Prediction of naturally-occurring, industrially-induced and total trans fatty acids in butter, dairy spreads and Cheddar cheese using vibrational spectroscopy and multivariate data analysis

peer-reviewedThis study investigated the use of vibrational spectroscopy [near infrared (NIR), Fourier-transform mid-infrared (FT-MIR), Raman] and multivariate data analysis for (1) quantifying total trans fatty acids (TT), and (2) separately predicting naturally-occurring (NT; i.e., C16:1 t9; C18:1 trans-n, n = 6 … 9, 10, 11; C18:2 trans) and industrially-induced trans fatty acids (IT = TT – NT) in Irish dairy products, i.e., butter (n = 60), Cheddar cheese (n = 44), and dairy spreads (n = 54). Partial least squares regression models for predicting NT, IT and TT in each type of dairy product were developed using FT-MIR, NIR and Raman spectral data. Models based on NIR, FT-MIR and Raman spectra were used for the prediction of NT and TT content in butter; best prediction performance achieved a coefficient of determination in validation (R2V) ∼ 0.91–0.95, root mean square error of prediction (RMSEP) ∼ 0.07–0.30 for NT; R2V ∼ 0.92–0.95, RMSEP ∼ 0.23–0.29 for TT.This project was funded by the Irish Department of Agriculture, Food and the Marine as part of CheeseBoard 2015. Ming Zhao is a Teagasc Walsh Fellow

A Preliminary Evaluation of the Ability of Keratotic Tissue to Act as a Prognostic Indicator of Hip Fracture Risk

Studies have shown that Raman spectroscopic analysis of fingernail clippings can help differentiate between post-menopausal women who have and who have not suffered a fracture. However, all studies to date have been retrospective in nature, comparing the proteins in nails sourced from women, post-fracture. The objective of this study was to investigate the potential of a prospective test for hip fracture based on spectroscopic analysis of nail tissue. Archived toenail samples from post-menopausal women aged 50 to 63 years in the Nurses\u27 Health Study were obtained and analysed by Raman spectroscopy. Nails were matched case-controls sourced from 161 women; 82 who underwent a hip fracture up to 20 years after nail collection and 81 age-matched controls. A number of clinical risk factors (CRFs) from the Fracture Risk Assessment (FRAX) tool had been assessed at toenail collection. Using 80% of the spectra, models were developed for increasing time periods between nail collection and fracture. Scores were calculated from these models for the other 20% of the sample and the ability of the score to predict hip fracture was tested in model with and without the CRFs by comparing the odds ratios (ORs) per 1 SD increase in standardised predictive values. The Raman score successfully distinguished between hip fracture cases and controls. With only the score as a predictor, a statistically significant OR of 2.2 (95% confidence interval [CI]: 1.5-3.1) was found for hip fracture for up to 20 years after collection. The OR increased to 3.8 (2.6-5.4) when the CRFs were added to the model. For fractures limited to 13 years after collection, the OR was 6.3 (3.0-13.1) for the score alone. The test based on Raman spectroscopy has potential for identifying individuals who may suffer hip fractures several years in advance. Higher powered studies are required to evaluate the predictive capability of this test

A Preliminary Evaluation of the Ability of Keratotic Tissue to Act as a Prognostic Indicator of Hip Fracture Risk

Studies have shown that Raman spectroscopic analysis of fingernail clippings can help differentiate between post-menopausal women who have and who have not suffered a fracture. However, all studies to date have been retrospective in nature, comparing the proteins in nails sourced from women, post-fracture. The objective of this study was to investigate the potential of a prospective test for hip fracture based on spectroscopic analysis of nail tissue. Archived toenail samples from post-menopausal women aged 50 to 63 years in the Nurses’ Health Study were obtained and analysed by Raman spectroscopy. Nails were matched case-controls sourced from 161 women; 82 who underwent a hip fracture up to 20 years after nail collection and 81 age-matched controls. A number of clinical risk factors (CRFs) from the Fracture Risk Assessment (FRAX) tool had been assessed at toenail collection. Using 80% of the spectra, models were developed for increasing time periods between nail collection and fracture. Scores were calculated from these models for the other 20% of the sample and the ability of the score to predict hip fracture was tested in model with and without the CRFs by comparing the odds ratios (ORs) per 1 SD increase in standardised predictive values. The Raman score successfully distinguished between hip fracture cases and controls. With only the score as a predictor, a statistically significant OR of 2.2 (95% confidence interval [CI]: 1.5-3.1) was found for hip fracture for up to 20 years after collection. The OR increased to 3.8 (2.6-5.4) when the CRFs were added to the model. For fractures limited to 13 years after collection, the OR was 6.3 (3.0-13.1) for the score alone. The test based on Raman spectroscopy has potential for identifying individuals who may suffer hip fractures several years in advance. Higher powered studies are required to evaluate the predictive capability of this test

Raman Spectroscopy as a Predictive Tool for Monitoring Osteoporosis Therapy in a Rat Model of Postmenopausal Osteoporosis

Pharmacological therapy of osteoporosis reduces bone loss and risk of fracture in patients. Modulation of bone mineral density cannot explain all effects. Other aspects of bone quality affecting fragility and ways to monitor them need to be better understood. Keratinous tissue acts as surrogate marker for bone protein deterioration caused by oestrogen deficiency in rats. Ovariectomised rats were treated with alendronate (ALN), parathyroid hormone (PTH) or estrogen (E2). MicroCT assessed macro structural changes. Raman spectroscopy assessed biochemical changes. Micro CT confirmed that all treatments prevented ovariectomy-induced macro structural bone loss in rats. PTH induced macro structural changes unrelated to ovariectomy. Raman analysis revealed ALN and PTH partially protect against molecular level changes to bone collagen (80% protection) and mineral (50% protection) phases. E2 failed to prevent biochemical change. The treatments induced alterations unassociated with the ovariectomy; increased beta sheet with E2, globular alpha helices with PTH and fibrous alpha helices with both ALN and PTH. ALN is closest to maintaining physiological status of the animals, while PTH (comparable protective effect) induces side effects. E2 is unable to prevent molecular level changes associated with ovariectomy. Raman spectroscopy can act as predictive tool for monitoring pharmacological therapy of osteoporosis in rodents. Keratinous tissue is a useful surrogate marker for the protein related impact of these therapies. The results demonstrate utility of surrogates where a clear systemic causation connects the surrogate to the target tissue. It demonstrates the need to assess broader biomolecular impact of interventions to examine side effects. [Figure not available: see full text.]

Raman Spectroscopy Predicts the Link between Claw Keratin and Bone Collagen Structure in a Rodent Model of Oestrogen Deficiency

Osteoporosis is a common disease characterized by reduced bone mass and an increased risk of fragility fractures. Low bone mineral density is known to significantly increase the risk of osteoporotic fractures; however, the majority of non-traumatic fractures occur in individuals with a bone mineral density too high to be classified as osteoporotic. Therefore, there is an urgent need to investigate aspects of bone health, other than bone mass, that can predict the risk of fracture. Here, we successfully predicted association between bone collagen and nail keratin in relation to bone loss due to oestrogen deficiency using Raman spectroscopy. Raman signal signature successfully discriminated between ovariectomised rats and their sham controls with a high degree of accuracy for the bone (sensitivity 89%, specificity 91%) and claw tissue (sensitivity 89%, specificity 82%). When tested in an independent set of claw samples the classifier gave 92% sensitivity and 85% specificity. Comparison of the spectral changes occurring in the bone tissue with the changes occurring in the keratin showed a number of common features that could be attributed to common changes in the structure of bone collagen and claw keratin. This study established that systemic oestrogen deficiency mediates parallel structural changes in both the claw (primarily keratin) and bone proteins (primarily collagen). This strengthens the hypothesis that nail keratin can act as a surrogate marker of bone protein status where systemic processes induce changes

Quantification of calcium in infant formula using laser-induced breakdown spectroscopy (LIBS), Fourier transform mid-infrared (FT-IR) and Raman spectroscopy combined with chemometrics including data fusion

peer-reviewedLaser-induced breakdown spectroscopy (LIBS), Fourier transform mid-infrared (FT-IR) and Raman spectroscopy combined with chemometrics were investigated to quantify calcium (Ca) content in infant formula powder (INF). INF samples (n = 51) with calcium content levels (ca. 6.5–30 mg Ca/100 kJ) were prepared in accordance with the guidelines of Commission Directive 2006/125/EC. Atomic absorption spectroscopy (AAS) was used as the reference method for Ca content determination. To predict Ca content in INF samples, partial least squares regression (PLSR) models that developed based on LIBS, Raman and FT-IR spectral data, respectively. The model developed using LIBS data achieved the best performance for the quantification of Ca content in INF (R2 (cross-validation (CV))-0.99, RMSECV-0.29 mg/g; R2 (prediction (P))-1, RMSEP-0.63 mg/g). PLSR models that developed based on data fusion of Raman and FT-IR spectral features obtained the second best performance (R2CV-0.97, RMSECV-0.38 mg/g; R2P-0.97, RMSEP-0.36 mg/g). This study demonstrated the potential of LIBS, FT-IR and Raman spectroscopy to accurately quantify Ca content in INF.Department of Agriculture, Food and the Marine, Irelan

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability