Length-free near infrared measurement of newborn malnutrition

A review on current diagnostic tools and potential optical absorption spectroscopy for HFMD detection

Hand, Foot, and Mouth Disease (HFMD) is an outbreak infectious disease that can easily spread among children under the age of five. The most common causative agents of HFMD are enterovirus 71 (EV71) and coxsackievirus A16 (CVA16), but infection caused by EV71 is more associated with fatalities due to severe neurological disorders. The present diagnosis methods rely on physical examinations by the doctors and further confirmation by laboratories detection methods such as viral culture and polymerase chain reaction. Clinical signs of HFMD infection and other childhood diseases such as chicken pox, and allergies are similar, yet the genetics and pathogenicity of the viruses are substantially different. Thus, there is an urgent need for an early screening of HFMD using an inexpensive and user-friendly device that can directly detect the causative agents of the disease. This paper reviews current HFMD diagnostic methods based on various target types, such as nucleic acid, protein, and whole virus. This was followed by a thorough discussion on the emerging sensing technologies for HFMD detection, including surface plasmon resonance, electrochemical sensor, and surface enhanced Raman spectroscopy. Lastly, optical absorption spectroscopic method was critically discussed and proposed as a promising technology for HFMD screening and detection.

Near-Infrared Spectroscopy as a Potential COVID-19 Early Detection Method: A Review and Future Perspective

The coronavirus disease 2019 (COVID-19) pandemic is a worldwide health anxiety. The rapid dispersion of the infection globally results in unparalleled economic, social, and health impacts. The pathogen that causes COVID-19 is known as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A fast and low-cost diagnosis method for COVID-19 disease can play an important role in controlling its proliferation. Near-infrared spectroscopy (NIRS) is a quick, non-destructive, non-invasive, and inexpensive technique for profiling the chemical and physical structures of a wide range of samples. Furthermore, the NIRS has the advantage of incorporating the internet of things (IoT) application for the effective control and treatment of the disease. In recent years, a significant advancement in instrumentation and spectral analysis methods has resulted in a remarkable impact on the NIRS applications, especially in the medical discipline. To date, NIRS has been applied as a technique for detecting various viruses including zika (ZIKV), chikungunya (CHIKV), influenza, hepatitis C, dengue (DENV), and human immunodeficiency (HIV). This review aims to outline some historical and contemporary applications of NIRS in virology and its merit as a novel diagnostic technique for SARS-CoV-2.

Efficient Broadband Near-Infrared CaMgGe2O6:Cr3+ Phosphor for pc-LED

Broadband near-infrared (NIR) phosphor-converted light-emitting diodes (pc-LEDs) are essential to integrate near-infrared spectrometers into mobile devices for the rapid and noninvasive detection of biological components. However, efficient broadband NIR phosphors with a peak emission wavelength longer than 800 nm are deficient. In this study, CaMgGe₂O₆:Cr³⁺ phosphor was prepared by a high-temperature solid-state reaction. The phosphor doped with 0.02Cr³⁺ showed an emission band at 845 nm with a broad bandwidth of 160 nm and a high quantum yield of 84% under 450 nm excitation. The broadband NIR pc-LED was fabricated using CaMgGe₂O₆:0.02Cr³⁺ phosphor based on a blue light-emitting diode (LED) chip. A photoelectric efficiency of 27.2% @ 10 mA and an NIR output power of 57.98 mW @ 100 mA were achieved, which are the highest values reported yet for broadband NIR pc-LEDs with a peak wavelength longer than 800 nm. Using the fabricated NIR pc-LED as the light source, the characteristic absorption spectra of some substances were obtained. All of the results indicated that the CaMgGe₂O₆:Cr³⁺ phosphor has considerable potential in near-infrared spectroscopic applications.

Model Development for Fat Mass Assessment Using Near-Infrared Reflectance in South African Infants and Young Children Aged 3-24 Months

Undernutrition in infants and young children is a major problem leading to millions of deaths every year. The objective of this study was to provide a new model for body composition assessment using near-infrared reflectance (NIR) to help correctly identify low body fat in infants and young children. Eligibility included infants and young children from 3–24 months of age. Fat mass values were collected from dual-energy x-ray absorptiometry (DXA), deuterium dilution (DD) and skin fold thickness (SFT) measurements, which were then compared to NIR predicted values. Anthropometric measures were also obtained. We developed a model using NIR to predict fat mass and validated it against a multi compartment model. One hundred and sixty-four infants and young children were included. The evaluation of the NIR model against the multi compartment reference method achieved an r value of 0.885, 0.904, and 0.818 for age groups 3–24 months (all subjects), 0–6 months, and 7–24 months, respectively. Compared with conventional methods such as SFT, body mass index and anthropometry, performance was best with NIR. NIR offers an affordable and portable way to measure fat mass in South African infants for growth monitoring in low-middle income settings.

Near-Infrared Spectroscopy to Monitor Nutritional Status of Neonates: A Review

The World Health Organization reported that half or more of all under five deaths were caused by undernutrition in developing countries, with the majority of these deaths occurring in the first week of life. Even if the undernourished neonates manage to survive, they are exposed to long-term health impacts, including obesity, cardiovascular disease, and hypertension. Along with those health-impacts they can be exposed to risks related to detrimental early development, such as physical impairment, stunting, brain dysfunction, and reduced cognitive development. Body fat percentage has been recognized to be closely associated with undernutrition in neonates. In this article, the potential of near infrared spectroscopy (NIRS), along with previous methods to measure body fat in neonates, is reviewed and discussed.

Near infrared spectroscopy for body fat sensing in neonates: quantitative analysis by GAMOS simulations

BACKGROUND

Under-nutrition in neonates is closely linked to low body fat percentage. Undernourished neonates are exposed to immediate mortality as well as unwanted health impacts in their later life including obesity and hypertension. One potential low cost approach for obtaining direct measurements of body fat is near-infrared (NIR) interactance. The aims of this study were to model the effect of varying volume fractions of melanin and water in skin over NIR spectra, and to define sensitivity of NIR reflection on changes of thickness of subcutaneous fat. GAMOS simulations were used to develop two single fat layer models and four complete skin models over a range of skin colour (only for four skin models) and hydration within a spectrum of 800-1100 nm. The thickness of the subcutaneous fat was set from 1 to 15 mm in 1 mm intervals in each model.

RESULTS

Varying volume fractions of water in skin resulted minimal changes of NIR intensity at ranges of wavelengths from 890 to 940 nm and from 1010 to 1100 nm. Variation of the melanin volume in skin meanwhile was found to strongly influence the NIR intensity and sensitivity. The NIR sensitivities and NIR intensity over thickness of fat decreased from the Caucasian skin to African skin throughout the range of wavelengths. For the relationship between the NIR reflection and the thickness of subcutaneous fat, logarithmic relationship was obtained.

CONCLUSIONS

The minimal changes of NIR intensity values at wavelengths within the ranges from 890 to 940 nm and from 1010 to 1100 nm to variation of volume fractions of water suggests that wavelengths within those two ranges are considered for use in measurement of body fat to solve the variation of hydration in neonates. The stronger influence of skin colour on NIR shows that the melanin effect needs to be corrected by an independent measurement or by a modeling approach. The logarithmic response obtained with higher sensitivity at the lower range of thickness of fat suggests that implementation of NIRS may be suited for detecting under-nutrition and monitoring nutritional interventions for malnutrition in neonates in resource-constrained communities.