Validation of Correction Algorithms for Near-IR Analysis of Human Milk in an Independent Sample Set-Effect of Pasteurization

Impact of Holder Pasteurization and Preanalytical Handling Techniques on Fat Concentration in Donor Human Milk: A Scoping Review

BACKGROUND

Donor human milk (DHM) is an essential source of nutrition among high-risk infants (e.g., premature and low-birth weight). Holder pasteurization, a common step in DHM processing, is known to partially alter the composition of DHM; however, the impact on fat composition is historically inconsistent.

OBJECTIVES

This scoping review aimed to broadly review the literature on the impact of Holder pasteurization on the fat content in DHM, with a focus on preanalytical sample mixing.

METHODS

A systematic search of original, peer-reviewed research articles was conducted on 11 July, 2022. Articles were included if they compared matched raw (control) and Holder-pasteurized human milk samples and measured total lipids, cholesterol, and individual classes of fatty acids. Article review and selection was conducted by 2 independent reviewers.

RESULTS

The search yielded 26 original, peer-reviewed research articles published between 1978 and 2022. Overall methodology varied considerably between studies. When study methods described any mixing for collecting raw milk, 1 (17%) of the 6 of studies reported a small change in total fat concentration following pasteurization (<5%). Alternatively, among studies that did not describe methods for mixing raw milk to ensure a representative sample, 10 (56%) of the 18 reported a significant change (≥± 5%) in total fat concentration, with changes ranging from -28.6% to +19.4%.

CONCLUSIONS

This review suggests that inconsistent findings regarding the impact of Holder pasteurization on fat may be related to study methodologies, particularly preanalytical sample mixing. More research considering the role of preanalytical handling procedures and methodologies is necessary to help clarify the impact of Holder pasteurization on human milk composition.

The Influence of Oligosaccharides when Measuring Lactose and Total Carbohydrates in Human Milk and Comparison of Methods

BACKGROUND

Understanding how human milk impacts growth requires valid analytical methods for quantifying the composition. Lactose, the most abundant constituent in human milk and a predominant source of energy, is often assessed using methods borrowed from the bovine dairy industry. However, the carbohydrate matrices of bovine and human milk are quite different, especially as they relate to human milk oligosaccharides (HMOs), each with a terminal lactose unit that may influence analytical methods.

OBJECTIVES

Our goals were to determine the extent to which HMOs influence common analytical methods for measuring carbohydrates in human milk and to compare common methods for measuring lactose.

METHODS

Two sets of experiments were performed. In the first set, native and HMO-spiked human milk samples (n = 16 each) were assessed and compared using 4 methods: AOAC 2006.06 (based on the Megazyme enzymatic assay), BioVision enzymatic assay, ultraperformance LC with MS, and infrared analysis. In the second set, human milk samples (n = 20) were assessed using 2 methods approved for measuring lactose in bovine milk: AOAC 984.22 that uses high-performance LC and refractive index detection and AOAC 2006.06 prepared using both volume and weighted dilutions.

RESULTS

Native and HMO-spiked samples were not significantly different in lactose using AOAC 2006.06 and ultraperformance LC with MS but were significantly different using BioVision (mean difference = 0.2 g/dL; 95% CI: 0.1, 0.4; P = 0.005). Total carbohydrate measurements assessed using infrared were also higher after HMO spiking (mean difference = 0.4 g/dL; 95% CI: 0.3, 0.6; P < 0.001). Only AOAC methods 984.22 and 2006.06 for measuring lactose were very highly correlated (r > 0.90, P < 0.001).

CONCLUSIONS

AOAC methods 984.22 and 2006.06 are comparable for measuring lactose in human milk and are not influenced by HMOs. HMOs influence other enzymatic methods as well as infrared analysis, which leads to an overestimate of energy values. J Nutr 2023;x:xx.

Human Milk Processing and Its Effect on Protein and Leptin Concentrations

(1) Background: For the storage of human milk (HM), freezing, thawing, and/or pasteurization are routinely used in neonatal intensive care units. We aimed to analyze the effects of different HM processing types on the nutritional contents in HM, adipose tissue, and the neuroprotection markers leptin and adiponectin. (2) Methods: HM samples from 136 mothers of preterm and term infants (gestational age 23 + 0 to 41 + 6) were collected and divided into four groups: (i) fresh HM, (ii) fresh pasteurized HM, (iii) thawed HM, and (iv) thawed pasteurized HM. The macronutrients were analyzed by mid-infrared transmission spectroscopy and the adiponectin and leptin were analyzed by high-sensitivity adiponectin and leptin enzyme-linked immunosorbent assay (ELISA). (3) Results: No significant differences were observed in the protein, carbohydrate, or fat concentrations between the HM processing types. The leptin levels were significantly lower after pasteurization in comparison to HM without pasteurization (p < 0.001). The protein levels in extremely preterm HM were significantly lower compared to those in moderate/late preterm HM and term HM (p < 0.05). (4) Conclusions: HM processing had an impact on leptin concentrations but no effect on the protein level. These data support the use of unpasteurized human milk for preterm infants’ nutrition and normal brain development. The protein levels of the milk of mothers from preterm compared to full-term infants differed, underlining the importance of individualized target fortification.

Characterization and Viability Prediction of Commercial Probiotic Supplements under Temperature and Concentration Conditioning Factors by NIR Spectroscopy

The quality of probiotics has been associated with bacteria and yeast strains’ contents and their stability against conditioning factors. Near-infrared spectroscopy (NIRS), as a non-destructive, fast, real-time, and cost-effective analytical technique, can provide some advantages over more traditional food quality control methods in quality evaluation. The aim of our study was to evaluate the applicability of NIRS to the characterization and viability prediction of three commercial probiotic food supplement powders containing lactic acid bacteria (LAB) subjected to concentration and temperature conditioning factors. For each probiotic, 3 different concentrations were considered, and besides normal preparation (25 °C, control), samples were subjected to heat treatment at 60 or 90 °C and left to cool down until reaching room temperature prior to further analysis. Overall, after applying chemometrics to the NIR spectra, the obtained principal component analysis-based linear discriminant analysis (PCA-LDA) classification models showed a high accuracy in both recognition and prediction. The temperature has an important impact on the discrimination of samples. According to the concentration, the best models were identified for the 90 °C temperature treatment, reaching 100% average correct classification for recognition and over 90% for prediction. However, the prediction accuracy decreased substantially at lower temperatures. For the 25°C temperature treatment, the prediction accuracy decreased to nearly 60% for 2 of the 3 probiotics. Moreover, according to the temperature level, both the recognition and prediction accuracies were close to 100%. Additionally, the partial least square regression (PLSR) model achieved respectable values for the prediction of the colony-forming units (log CFU/g) of the probiotic samples, with a determination coefficient for prediction (R2Pr) of 0.82 and root mean square error for prediction (RMSEP) of 0.64. The results of our study show that NIRS is a fast, reliable, and promising alternative to the conventional microbiology technique for the characterization and prediction of the viability of probiotic supplement drink preparations.

Infrared analyzers for the measurement of breastmilk macronutrient content in the clinical setting

INTRODUCTION

There is growing interest in the possibility of measuring the macronutrient content of human milk. Several studies that intend to validate commercially available human milk analyzers have been published with inconsistent results. This review will focus on currently available, verified methodologies for analyzing macronutrients in human milk.

AREAS COVERED

A literature search was conducted in the PubMed database. Five milk analyzers were chosen to be included in this review: MIRIS (Uppsala, Sweden) (seven articles found), Calais (Cleveland, United States) (four articles), SpectraStar (Brookfield, United States) (four articles), MilkoScan (Hillerdo, Denmark) (two articles), and Delta LactoScope (Stockholm, Sweden) (one article). The following information was extracted from published manuscripts: measuring device, sample preparation, purpose of the study, type of macronutrients studied, results, and conclusions.

EXPERT OPINION

Infrared spectroscopy can be an accurate and reliable technology for assessing the macronutrient content of human milk, specifically crude protein, and total fat. However, an optimal handling of samples, the development of standardized quality-control protocols, and an improvement in calibration procedures are required before the full implementation of infrared technology in neonatal units.

Individualized target fortification of breast milk with protein, carbohydrates, and fat for preterm infants: A double-blind randomized controlled trial

BACKGROUND & AIMS

In preterm infants, natural variation of breast milk composition makes it difficult to achieve recommended macronutrient intakes with standard fortification. Evidence suggests that nutritional deficiency induces poor postnatal growth. This study investigates impacts of target fortification on preterm growth and metabolism by adjusting breast milk macronutrients.

METHODS

This study was conducted as a single-centre, double-blind, randomized controlled trial for infants <30 gestational weeks. The control group received standard fortification and the intervention group received standard plus target fortification adding modular protein, lipids, and carbohydrates. Breast milk content was measured 3x/week using a validated near-infrared bedside spectrometer (NIRS). Modulars were added to achieve recommended values. To assess total nutrient intake, all 2810 native breast milk samples were analyzed - protein and fat using bedside-NIRS, lactose using tandem mass spectrometry (UPLC-MS/MS). Body composition was measured using air displacement plethysmography. Primary outcome was weight gain during the first 21 days of intervention.

RESULTS

Baseline characteristics, morbidities, and total fluid intake were not different between groups (intervention n = 52, control n = 51). The intervention group infants had higher macronutrient intakes, weight gain (21.2 ± 2.5 vs 19.3 ± 2.4 g/kg/d, mean difference: 1.9 g/kg/d, 95% CI: 0.9 - 2.9), and body weight. Infants in the intervention group from mothers with below-average breast milk protein content showed greatest impact on weight at 36 weeks (2580 ± 280 g vs 2210 ± 300 g), length, head circumference, fat, and fat-free mass. Also, feeding intolerance was less frequent, blood urea was higher, and triglycerides were lower.

CONCLUSIONS

This study provides evidence that target fortification of breast milk with low macronutrient content enhances the quality of nutrition and growth and is feasible in clinical routine.

Accuracy and Reliability of Infrared Analyzers for Measuring Human Milk Macronutrients in a Milk Bank Setting

BACKGROUND

Infrared (IR) analysis is an emerging technology that may be a useful tool for milk banks to manage the nutrient variability in donor human milk.

OBJECTIVE

To evaluate the accuracy, reliability, and comparability of commercial infrared analyzers for measuring human milk macronutrients in a milk bank setting.

METHODS

Three nonprofit milk banks received blinded test kits of human milk that had been assessed using reference methods. Four infrared instruments were used to measure macronutrients as follows: 1 filtered mid-IR, 2 Fourier-transformed full-spectra mid-IR, and 1 near-IR. Twenty-five unique samples were read concurrently for the accuracy arm. An identical sample was read daily for 1 mo for the reliability arm.

RESULTS

Values for R 2 describing relationships with reference methods for total fat, crude protein, and lactose, were as follows: filtered mid-IR, 0.98, 0.94, and 0.48; Fourier-transformed full-spectra mid-IR, 0.97, 0.93, and 0.36 for instrument 1 and 0.98, 0.98, and 0.31 for instrument 2; and near-IR 0.93, 0.93, and 0.12. There was no significant difference between instruments for crude protein and total fat measurements. There were significant differences in carbohydrate measurements between instruments. For 1 mo of daily measurements in the reliability arm, CVs for filtered mid-IR were ≤4.6%, for Fourier-transformed full spectra mid-IR were ≤1.7%, and for near-IR were ≤5.1%.

CONCLUSIONS

Infrared analysis is an accurate and reliable method for measuring crude protein and total fat in a milk bank setting. Carbohydrate measurements are less accurate and are significantly different between instruments, which will likely lead to differences in derived calorie values.

Milk analysis using milk analyzers in a standardized setting (MAMAS) study: A multicentre quality initiative

BACKGROUND

Human milk analyzers are increasingly used to rapidly measure the macronutrient content in breast milk for individual target fortification, to reduce the risk of postnatal growth restriction. However, many milk analyzers are used without calibration, validation or quality assurance.

AIMS

To investigate measurement quality between different human milk analyzers, to test whether accuracy and precision of devices can be improved by establishing individual calibration curves, and to assess long-term stability of measurements, following good clinical laboratory practice (GCLP).

METHODS

Sets of identical breast milk samples were sent to 13 participating centres in North America and Europe, for a total of 15 devices. The study included 3 sets of samples: A) initial assessment of the device's performance consisting of 10 calibration samples with random replicates; B) long term stability and quality control consisting of 2 batches of samples to be measured every time before the device is used, over 6 months; C) ring trial consisting of 2 samples to be measured monthly. The devices tested were Unity SpectraStar (n = 5) and MIRIS Human Milk Analyzer (n = 10).

RESULTS

There are significant variations in accuracy and precision between different milk analyzers' fat, protein and lactose measurements. However, the accuracy of measurements can be improved by establishing individual correction algorithms. Repeated measurements are more robust when coming from a larger batch volume. Long term stability also varies between devices.

CONCLUSION

The variations in measurements between devices are clinically significant and would impact both daily dietary prescriptions, and the outcomes of clinical studies assessing the effect of targeted adjustment of nutrient intake in preterm babies. This study shows that it is crucial to follow GCLP when using milk analyzers to ensure proper measurement of macronutrients, similar to what is required of other medical devices.

Transmission infrared spectroscopy for rapid quantification of fat, protein, and lactose concentrations in human milk

OBJECTIVE

To develop partial least squares regression (PLSR) calibration models in combination with transmission infrared (TIR) spectroscopy for rapid and optimal quantification of human milk macronutrient concentrations.

STUDY DESIGN

Human milk samples (n = 306) were characterized simultaneously by reference chemical analytical methods and TIR spectroscopy. Reference macronutrient concentrations were linked to pre-processed spectra and divided into two (training and test) sets. PLSR was used to develop trial calibration models using training set, and the test set was used to assess the accuracy of the trial analytical methods.

RESULTS

For the methods selected as optimal, the concordance correlation coefficients between reference and TIR-based methods were 0.93 for fat, 0.96 for protein, and 0.52 for lactose. The Bland-Altman plots showed no evidence of systematic bias between TIR and reference methods.

CONCLUSIONS

TIR spectroscopy provides the basis for accurate and rapid quantification of human milk fat and protein concentrations but is less accurate for measuring lactose concentration.

"Bed Side" Human Milk Analysis in the Neonatal Intensive Care Unit: A Systematic Review

Human milk analyzers can measure macronutrient content in native breast milk to tailor adequate supplementation with fortifiers. This article reviews all studies using milk analyzers, including (i) evaluation of devices, (ii) the impact of different conditions on the macronutrient analysis of human milk, and (iii) clinical trials to improve growth. Results lack consistency, potentially due to systematic errors in the validation of the device, or pre-analytical sample preparation errors like homogenization. It is crucial to introduce good laboratory and clinical practice when using these devices; otherwise a non-validated clinical usage can severely affect growth outcomes of infants.

Infrared analyzers for breast milk analysis: fat levels can influence the accuracy of protein measurements

Background:

Currently, there is a growing interest in lacto-engineering in the neonatal intensive care unit, using infrared milk analyzers to rapidly measure the macronutrient content in breast milk before processing and feeding it to preterm infants. However, there is an overlap in the spectral information of different macronutrients, so they can potentially impact the robustness of the measurement. In this study, we investigate whether the measurement of protein is dependent on the levels of fat present while using an infrared milk analyzer.

Methods:

Breast milk samples (n=25) were measured for fat and protein content before and after being completely defatted by centrifugation, using chemical reference methods and near-infrared milk analyzer (Unity SpectraStar) with two different calibration algorithms provided by the manufacturer (released 2009 and 2015).

Results:

While the protein content remained unchanged, as measured by elemental analysis, measurements by infrared milk analyzer show a difference in protein measurements dependent on fat content; high fat content can lead to falsely high protein content. This difference is less pronounced when measured using the more recent calibration algorithm.

Conclusions:

Milk analyzer users must be cautious of their devices’ measurements, especially if they are changing the matrix of breast milk using more advanced lacto-engineering.