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Photoelectrochemical (PEC) nanobiosensors integrate molecular (bio)recognition elements with semiconductor/plasmonic photoactive nanomaterials to produce measurable signals after light-induced reactions. Recent advancements in PEC nanobiosensors, using light-matter interactions, have significantly improved sensitivity, specificity, and signal-to-noise ratio in detecting (bio)analytes. Tunable nanomaterials activated by a wide spectral radiation window coupled to electrochemical transduction platforms have further improved detection by stabilizing and amplifying electrical signals. This work reviews PEC biosensors based on nanomaterials like metal oxides, carbon nitrides, quantum dots, and transition metal chalcogenides (TMCs), showing their superior optoelectronic properties and analytical performance for the detection of clinically relevant biomarkers. Furthermore, it highlights the innovative role of red light and NIR-activated PEC nanobiosensors in enhancing charge transfer processes, protecting them from biomolecule photodamage in vitro and in vivo applications. Overall, advances in PEC detection systems have the potential to revolutionize rapid and accurate measurements in clinical diagnostic applications. Their integration into miniaturized devices also supports the development of portable, easy-to-use diagnostic tools, facilitating point-of-care (POC) testing solutions and real-time monitoring.
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Técnicas Biossensoriais , Técnicas Eletroquímicas , Raios Infravermelhos , Técnicas Biossensoriais/métodos , Técnicas Eletroquímicas/métodos , Técnicas Eletroquímicas/instrumentação , Humanos , Nanoestruturas/química , Pontos Quânticos/química , Pontos Quânticos/efeitos da radiação , Animais , Processos Fotoquímicos , Biomarcadores/análiseRESUMO
Functional near-infrared spectroscopy (fNIRS) stands poised to revolutionize our understanding of auditory detection, speech perception, and language development in infants. In this study, we conducted a meticulous integrative review across Medline, Scopus, and LILACS databases, targeting investigations utilizing fNIRS to explore language-related features and cortical activation during auditory stimuli in typical infants. We included studies that used the NIRS technique to study language and cortical activation in response to auditory stimuli in typical infants between 0 and 3 years old. We used the ROBINS-I tool to assess the quality and the risk of bias in the studies. Our analysis, encompassing 66 manuscripts, is presented in standardized tables for streamlined data extraction. We meticulously correlated findings with children's developmental stages, delineating crucial insights into brain development and its intricate interplay with language outcomes. Although most studies have a high risk for overall bias, especially due to the high loss of data in NIRS studies, the low risk in the other domains is predominant and homogeneous among the studies. Highlighted are the unique advantages of fNIRS for pediatric studies, underscored by its innate suitability for use in children. This review accentuates fNIRS' capacity to elucidate the neural correlates of language processing and the sequential steps of language acquisition. From birth, infants exhibit abilities that lay the foundation for language development. The progression from diffuse to specific neural activation patterns is extremely influenced by exposure to languages, social interaction, and prosodic features and, reflects the maturation of brain networks involved in language processing. In conclusion, fNIRS emerges as an indispensable functional imaging modality, providing insights into the temporal dynamics of language acquisition and associated developmental milestones. This synthesis presents the pivotal role of fNIRS in advancing our comprehension of early language development and paves the way for future research endeavors in this domain.
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Near-infrared spectroscopy combined with vascular occlusion test (NIRS-VOT) is a reactive hyperemia technique for in vivo evaluation of skeletal muscle microvascular reactivity. Previous studies using NIRS-VOT have been shown to be able to detect impairments in microvascular function in high-risk cardiovascular disease populations, such as older individuals. It has been demonstrated that older individuals have slower reactive hyperemia compared with young individuals. Importantly, older individuals also show less desaturation during ischemia compared with young individuals. Based on these findings, it has been suggested that the slower reactive hyperemia observed in older individuals is explained by the lower desaturation during blood flow occlusion (reduced ischemic stimulus). This retrospective analysis compared reactive hyperemia in 36 young and 47 older tissue desaturation-matched individuals that underwent 5-min blood flow occlusion. Overall, we showed that older individuals have impaired reactive hyperemia compared with young when matching for the degree of desaturation and blood flow occlusion time. These findings provide evidence that lower tissue desaturation during ischemia is not a major determinant of impaired reactive hyperemia in older individuals.NEW & NOTEWORTHY Previous findings have suggested that aging-related impairment in skeletal muscle reactive hyperemia is majorly influenced by a lower degree of tissue desaturation during ischemia in older individuals compared with young individuals. In a retrospective analysis including 83 tissue desaturation-matched individuals, we show that the degree of tissue desaturation is not a major determinant of aging-related impairments in reactive hyperemia.
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Envelhecimento , Hiperemia , Microcirculação , Músculo Esquelético , Fluxo Sanguíneo Regional , Espectroscopia de Luz Próxima ao Infravermelho , Hiperemia/fisiopatologia , Músculo Esquelético/irrigação sanguínea , Músculo Esquelético/metabolismo , Músculo Esquelético/fisiopatologia , Humanos , Estudos Retrospectivos , Masculino , Envelhecimento/metabolismo , Envelhecimento/fisiologia , Idoso , Feminino , Adulto , Adulto Jovem , Pessoa de Meia-Idade , Fatores Etários , Isquemia/fisiopatologia , Isquemia/metabolismo , Oxigênio/sangue , Oxigênio/metabolismoRESUMO
OBJECTIVES: Studies exploring variations in peripheral muscle oxygenation and pressure pain thresholds (PPT) of masticatory muscles in individuals with Temporomandibular Disorders (TMDs) are limited. The purpose of this study was to compare variations in peripheral oxygenation of the masseter muscle; PPT of the masseter and temporal muscles and correlate peripheral muscle oxygenation and PPT of the masseter muscle in individuals with different types of TMDs. MATERIALS AND METHODS: Cross-sectional study involving 116 participants classified into three groups: muscle group (MG, n = 32), joint group (JG, n = 30) and muscle-joint group (MJG, n = 54). Individuals aged 26.97 ± 6.93, 68.97% female, 31,03% males were included. All participants were evaluated using the Diagnostic Criteria for Temporomandibular Disorders, Near-infrared spectroscopy (NIRS) for peripheral muscle oxygenation and pressure algometer for PPT. RESULTS: There was no difference in masseter muscle oxygenation among groups. In the masseter muscle, a weakly positive correlation was observed between PPT and variation in tissue saturation index in the MG (rho = 0.365) and JG (rho = 0.317). In addition, the MJG expressed lower PPT (p = 0.004) than JG, demonstrating that MJG had more pain in this muscle. CONCLUSIONS: MJG have lower PPT in the masseter muscle. Although the PPT is dependent on the type of TMDs, the correlation between PPT and oxygenation is weak. All TMDs groups evaluated (MG, JG, MJG) showed hemodynamic similarities of the masseter muscle. CLINICAL RELEVANCE: Understanding pain thresholds and the hemodynamic behavior of the masticatory muscles contributes to a more assertive physiotherapeutic assessment in TMDs, serving as a basis for careful and individualized interventions.
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Músculo Masseter , Medição da Dor , Limiar da Dor , Espectroscopia de Luz Próxima ao Infravermelho , Transtornos da Articulação Temporomandibular , Humanos , Masculino , Transtornos da Articulação Temporomandibular/fisiopatologia , Feminino , Estudos Transversais , Adulto , Limiar da Dor/fisiologia , Músculo Masseter/fisiopatologia , Dor Facial/fisiopatologia , Oxigênio/metabolismo , Músculo Temporal/fisiopatologiaRESUMO
Candida auris and Candida haemulonii are two emerging opportunistic pathogens that have caused an increase in clinical cases in the recent years worldwide. The differentiation of some Candida species is highly laborious, difficult, costly, and time-consuming depending on the similarity between the species. Thus, this study aimed to develop a new, faster, and less expensive methodology for differentiating between C. auris and C. haemulonii based on near-infrared (NIR) spectroscopy and multivariate analysis. C. auris CBS10913 and C. haemulonii CH02 were separated in 15 plates per species, and three isolated colonies of each plate were selected for Fourier transform near-infrared (FT-NIR) analysis, totaling 90 spectra. Subsequently, principal component analysis (PCA) and variable selection algorithms, including the successive projections algorithm (SPA) and genetic algorithm (GA) coupled with linear discriminant analysis (LDA), were employed to discern distinctive patterns among the samples. The use of PCA, SPA, and GA algorithms associated with LDA achieved 100% sensitivity and specificity for the discriminations. The SPA-LDA and GA-LDA algorithms were essential in selecting the variables (infrared wavelengths) of most importance for the models, which could be attributed to binding of cell wall structures such as polysaccharides, peptides, proteins, or molecules resulting from yeasts' metabolism. These results show the high potential of combined FT-NIR and multivariate analysis techniques for the classification of Candida-like fungi, which can contribute to faster and more effective diagnosis and treatment of patients affected by these microorganisms.
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The glucose level in the blood is measured through invasive methods, causing discomfort in the patient, loss of sensitivity in the area where the sample is obtained, and healing problems. This article deals with the design, implementation, and evaluation of a device with an ESP-WROOM-32D microcontroller with the application of near-infrared photospectroscopy technology that uses a diode array that transmits between 830 nm and 940 nm to measure glucose levels in the blood. In addition, the system provides a webpage for the monitoring and control of diabetes mellitus for each patient; the webpage is hosted on a local Linux server with a MySQL database. The tests are conducted on 120 people with an age range of 35 to 85 years; each person undergoes two sample collections with the traditional method and two with the non-invasive method. The developed device complies with the ranges established by the American Diabetes Association: presenting a measurement error margin of close to 3% in relation to traditional blood glucose measurement devices. The purpose of the study is to design and evaluate a device that uses non-invasive technology to measure blood glucose levels. This involves constructing a non-invasive glucometer prototype that is then evaluated in a group of participants with diabetes.
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Automonitorização da Glicemia , Glicemia , Diabetes Mellitus , Humanos , Idoso , Glicemia/análise , Pessoa de Meia-Idade , Adulto , Automonitorização da Glicemia/instrumentação , Automonitorização da Glicemia/métodos , Diabetes Mellitus/sangue , Idoso de 80 Anos ou mais , Masculino , Feminino , Espectroscopia de Luz Próxima ao Infravermelho/métodos , Espectroscopia de Luz Próxima ao Infravermelho/instrumentaçãoRESUMO
Gestational diabetes mellitus (GDM) is a hyperglycemic state that is typically diagnosed by an oral glucose tolerance test (OGTT), which is unpleasant, time-consuming, has low reproducibility, and results are tardy. The machine learning (ML) predictive models that have been proposed to improve GDM diagnosis are usually based on instrumental methods that take hours to produce a result. Near-infrared (NIR) spectroscopy is a simple, fast, and low-cost analytical technique that has never been assessed for the prediction of GDM. This study aims to develop ML predictive models for GDM based on NIR spectroscopy, and to evaluate their potential as early detection or alternative screening tools according to their predictive power and duration of analysis. Serum samples from the first trimester (before GDM diagnosis) and the second trimester (at the time of GDM diagnosis) of pregnancy were analyzed by NIR spectroscopy. Four spectral ranges were considered, and 80 mathematical pretreatments were tested for each. NIR data-based models were built with single- and multi-block ML techniques. Every model was subjected to double cross-validation. The best models for first and second trimester achieved areas under the receiver operating characteristic curve of 0.5768 ± 0.0635 and 0.8836 ± 0.0259, respectively. This is the first study reporting NIR-spectroscopy-based methods for the prediction of GDM. The developed methods allow for prediction of GDM from 10 µL of serum in only 32 min. They are simple, fast, and have a great potential for application in clinical practice, especially as alternative screening tools to the OGTT for GDM diagnosis.
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Artisanal cheeses are part of the heritage and identity of different countries or regions. In this work, we investigated the spectral variability of a wide range of traditional Brazilian cheeses and compared the performance of different spectrometers to discriminate cheese types and predict compositional parameters. Spectra in the visible (vis) and near infrared (NIR) region were collected, using imaging (vis/NIR-HSI and NIR-HSI) and conventional (NIRS) spectrometers, and it was determined the chemical composition of seven types of cheeses produced in Brazil. Principal component analysis (PCA) showed that spectral variability in the vis/NIR spectrum is related to differences in color (yellowness index) and fat content, while in NIR there is a greater influence of productive steps and fat content. Partial least squares discriminant analysis (PLSDA) models based on spectral information showed greater accuracy than the model based on chemical composition to discriminate types of traditional Brazilian cheeses. Partial least squares (PLS) regression models based on vis/NIR-HSI, NIRS, NIR-HSI data and HSI spectroscopic data fusion (vis/NIR + NIR) demonstrated excellent performance to predict moisture content (RPD > 2.5), good ability to predict fat content (2.0 < RPD < 2.5) and can be used to discriminate between high and low protein values (â¼1.5 < RPD < 2.0). The results obtained for imaging and conventional equipment are comparable and sufficiently accurate, so that both can be adapted to predict the chemical composition of the Brazilian traditional cheeses used in this study according to the needs of the industry.
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Queijo , Imageamento Hiperespectral , Análise de Componente Principal , Espectroscopia de Luz Próxima ao Infravermelho , Queijo/análise , Espectroscopia de Luz Próxima ao Infravermelho/métodos , Imageamento Hiperespectral/métodos , Brasil , Análise Discriminante , Análise dos Mínimos Quadrados , CorRESUMO
Significance: People with Parkinson's disease (PD) experience changes in fine motor skills, which is viewed as one of the hallmark signs of this disease. Due to its non-invasive nature and portability, functional near-infrared spectroscopy (fNIRS) is a promising tool for assessing changes related to fine motor skills. Aim: We aim to compare activation patterns in the primary motor cortex using fNIRS, comparing volunteers with PD and sex- and age-matched control participants during a fine motor task and walking. Moreover, inter and intrahemispheric functional connectivity (FC) was investigated during the resting state. Approach: We used fNIRS to measure the hemodynamic changes in the primary motor cortex elicited by a finger-tapping task in 20 PD patients and 20 controls matched for age, sex, education, and body mass index. In addition, a two-minute walking task was carried out. Resting-state FC was also assessed. Results: Patients with PD showed delayed hypoactivation in the motor cortex during the fine motor task with the dominant hand and delayed hyperactivation with the non-dominant hand. The findings also revealed significant correlations among various measures of hemodynamic activity in the motor cortex using fNIRS and different cognitive and clinical variables. There were no significant differences between patients with PD and controls during the walking task. However, there were significant differences in interhemispheric connectivity between PD patients and control participants, with a statistically significant decrease in PD patients compared with control participants. Conclusions: Decreased interhemispheric FC and delayed activity in the primary motor cortex elicited by a fine motor task may one day serve as one of the many potential neuroimaging biomarkers for diagnosing PD.
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INTRODUCTION: Perinatal asphyxia, a leading cause of neonatal mortality and neurological sequelae, necessitates early detection of pathophysiological neurologic changes during hypoxic-ischaemic encephalopathy (HIE). This study aimed to review published data on rScO2 monitoring during hypothermia treatment in neonates with perinatal asphyxia to predict short- and long-term neurological injury. METHODS: A systematic review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Study identification was performed through a search between November and December 2021 in the electronic databases PubMed, Embase, Lilacs, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL). The main outcome was short-term (Changes in brain magnetic resonating imaging) and long-term (In neurodevelopment) neurological injury. The study protocol was registered in PROSPERO (International Prospective Register of Systematic Reviews) with CRD42023395438. RESULTS: 380 articles were collected from databases in the initial search. Finally, 15 articles were selected for extraction and analysis of the information. An increase in rScO2 measured by NIRS (Near-infrared spectroscopy) at different moments of treatment predicts neurological injury. However, there exists a wide variability in the methods and outcomes of the studies. CONCLUSION: High rScO2 values were found to predict negative outcomes, with substantial discord among studies. NIRS is proposed as a real-time bedside tool for predicting brain injury in neonates with moderate to severe HIE.