Near-infrared hyperspectral imaging and robust statistics for in vivo non-melanoma skin cancer and actinic keratosis characterisation.

One of the most common forms of cancer in fair skinned populations is Non-Melanoma Skin Cancer (NMSC), which primarily consists of Basal Cell Carcinoma (BCC), and cutaneous Squamous Cell Carcinoma (SCC). Detecting NMSC early can significantly improve treatment outcomes and reduce medical costs. Similarly, Actinic Keratosis (AK) is a common skin condition that, if left untreated, can develop into more serious conditions, such as SCC. Hyperspectral imagery is at the forefront of research to develop non-invasive techniques for the study and characterisation of skin lesions. This study aims to investigate the potential of near-infrared hyperspectral imagery in the study and identification of BCC, SCC and AK samples in comparison with healthy skin. Here we use a pushbroom hyperspectral camera with a spectral range of ≈ 900 to 1600 nm for the study of these lesions. For this purpose, an ad hoc platform was developed to facilitate image acquisition. This study employed robust statistical methods for the identification of an optimal spectral window where the different samples could be differentiated. To examine these datasets, we first tested for the homogeneity of sample distributions. Depending on these results, either traditional or robust descriptive metrics were used. This was then followed by tests concerning the homoscedasticity, and finally multivariate comparisons of sample variance. The analysis revealed that the spectral regions between 900.66-1085.38 nm, 1109.06-1208.53 nm, 1236.95-1322.21 nm, and 1383.79-1454.83 nm showed the highest differences in this regard, with <1% probability of these observations being a Type I statistical error. Our findings demonstrate that hyperspectral imagery in the near-infrared spectrum is a valuable tool for analyzing, diagnosing, and evaluating non-melanoma skin lesions, contributing significantly to skin cancer research.

An automatic parathyroid recognition and segmentation model based on deep learning of near-infrared autofluorescence imaging.

INTRODUCTION: Near-infrared autofluorescence imaging (NIFI) can be used to identify parathyroid gland (PG) during surgery. The purpose of the study is to establish a new model, help surgeons better identify, and protect PGs. METHODS: Five hundred and twenty three NIFI images were selected. The PGs were recorded by NIFI and marked with artificial intelligence (AI) model. The recognition rate for PGs was calculated. Analyze the differences between surgeons of different years of experience and AI recognition, and evaluate the diagnostic and therapeutic efficacy of AI model. RESULTS: Our model achieved 83.5% precision and 57.8% recall in the internal validation set. The visual recognition rate of AI model was 85.2% and 82.4% on internal and external sets. The PG recognition rate of AI model is higher than that of junior surgeons (p < 0.05). CONCLUSIONS: This AI model will help surgeons identify PGs, and develop their learning ability and self-confidence.

Geographical discrimination of Paw San rice cultivated in different regions of Myanmar using near-infrared spectroscopy, headspace-gas chromatography-ion mobility spectrometry and chemometrics.

Paw San rice, also known as "Myanmar pearl rice", is considered the highest quality rice in Myanmar. There are considerable differences in terms of the premium commercial value of Paw San rice, which is an incentive for fraud, e.g. adulteration with cheaper rice varieties or mislabelling its geographical origin. Shwe Bo District is one of the most popular rice growing areas in the Sagaing region of Myanmar which produces the most valued and highly priced Paw San rice (Shwe Bo Paw San). The verification of the geographical origin of Paw San rice is not readily undertaken in the rice supply chain because the existing analytical approaches are time-consuming and expensive. Therefore, there is a need for rapid, robust and cost-effective analytical techniques for monitoring the authenticity and geographical origin of Paw San rice. In this 4-year study, two rapid screening techniques, Fourier-transform near-infrared (FT-NIR) spectroscopy and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), coupled with chemometric modelling, were applied and compared for the regional differentiation of Paw San rice. In addition, low-level fusion of the FT-NIR and HS-GC-IMS data was performed and its effect on the discriminative power of the chemometric models was assessed. Extensive model validation, including the validation using independent samples from a different production year, was performed. Furthermore, the effect of the sample preparation technique (grinding versus no sample preparation) on the performance of the discriminative model, obtained with FT-NIR spectral data, was assessed. The study discusses the suitability of FT-NIR spectroscopy, HS-GC-IMS and the combination of both approaches for rapid determination of the geographical origin of Paw San rice. The results demonstrated the excellent potential of the FT-NIR spectroscopy as well as HS-GC-IMS for the differentiation of Paw San rice cultivated in two distinct geographical regions. The OPLS-DA model, built using FT-NIR data of rice from 3 production years, achieved 96.67% total correct classification rate of an independent dataset from the 4th production year. The DD-SIMCA model, built using FT-NIR data of ground rice, also demonstrated the highest performance: 94% sensitivity and 97% specificity. This study has demonstrated that FT-NIR spectroscopy can be used as an accessible, rapid and cost-effective screening tool to discriminate between Paw San rice cultivated in the Shwe Bo and Ayeyarwady regions of Myanmar.

Clinicopathological factors associated with sentinel lymph node detection in non-small-cell lung cancer.

BACKGROUND: Mapping of the pulmonary lymphatic system by near-infrared (NIR) fluorescence imaging might not always identify the first lymph node relay. The aim of this study was to determine the clinicopathologic factors allowing the identification of sentinel lymph nodes (SLNs) by NIR fluorescence imaging in thoracic surgery for non-small-cell lung cancer (NSCLC). METHODS: We conducted a retrospective review of 92 patients treated for suspected or confirmed cN0 lung cancer with curative intent who underwent an intraoperative injection of indocyanine green (ICG) either by direct peritumoral injection or by endobronchial injection using electromagnetic navigational bronchoscopy (ENB). After exclusion of patients for technical failure, benign disease and metastasis, we analyzed the clinicopathologic findings of 65 patients treated for localized-stage NSCLC, comparing the group with identification of SLNs (SLN-positive group) with the group without identification of SLNs (SLN-negative group). RESULTS: Forty-eight patients (73.8%) were SLN-positive. Patients with SLN positivity were more frequently female (50%) than the SLN-negative patients were (11.8%) (p = 0.006). The mean value of diffusing capacity for carbon monoxide (DLCO) was lower among the patients in the SLN-negative group (64.7% ± 16.7%) than the SLN-positive group (77.6% ± 17.2%, p < 0.01). The ratio of forced expiratory volume in one second to forced vital capacity (FEV1/FCV) was higher in the SLN-positive group (69.0% vs. 60.8%, p = 0.02). Patients who were SLN-negative were characterized by a severe degree of emphysema (p = 0.003). There was no significant difference in pathologic characteristics. On univariate analyses, age, female sex, DLCO, FEV1/FVC, degree of emphysema, and tumor size were significantly associated with SLN detection. On multivariate analysis, DLCO > 75% (HR = 4.92, 95% CI: 1.27-24.7; p = 0.03) and female sex (HR = 5.55, 95% CI: 1.25-39.33; p = 0.04) were independently associated with SLN detection. CONCLUSIONS: At a time of resurgence in the use of the sentinel lymph node mapping technique in the field of thoracic surgery, this study enabled us to identify, using multivariate analysis, two predictive factors for success: DLCO > 75% and female sex. Larger datasets are needed to confirm our results.

Distinct patterns of metabolic motor cortex activity for phantom and residual limb pain in people with amputations: A functional near-infrared spectroscopy study.

BACKGROUND: Phantom pain limb (PLP) has gained more attention due to the large number of people with amputations around the world and growing knowledge of the pain process, although its mechanisms are not completely understood. OBJECTIVES: The aim of this study was to understand, in patients with amputations, the association between PLP and residual limb pain (RLP), and the brain metabolic response in cortical motor circuits, using functional near-infrared spectroscopy (fNIRS). METHODS: Sixty participants were recruited from the rehabilitation program in São Paulo, Brazil. Included patients were aged over 18 years, with traumatic unilateral lower-limb amputation, with PLP for at least 3 months after full recovery from amputation surgery. PLP and RLP levels were measured using visual analogue scales. fNIRS was performed during motor execution and motor mirror tasks for 20 s. In order to highlight possible variables related to variation in pain measures, univariate linear regression analyses were performed for both experimental conditions, resulting in four fNIRS variables (two hemispheres x two experimental conditions). Later, in order to test the topographic specificity of the models, eight multivariate regression analyses were performed (two pain scales x two experimental conditions x two hemispheres), including the primary motor cortex (PMC) related channel as an independent variable as well as five other channels related to the premotor area, supplementary area, and somatosensory cortex. All models were controlled for age, sex, ethnicity, and education. RESULTS: We found that: i) there is an asymmetric metabolic activation during motor execution and mirror task between hemispheres (with a predominance that is ipsilateral to the amputated limb), ii) increased metabolic response in the PMC ipsilateral to the amputation is associated with increased PLP (during both experimental tasks), while increased metabolic response in the contralateral PMC is associated with increased RLP (during the mirror motor task only); ii) increased metabolic activity of the ipsilateral premotor region is associated with increased PLP during the motor mirror task; iii) RLP was only associated with higher metabolic activity in the contralateral PMC and lower metabolic activity in the ipsilateral inferior frontal region during motor mirror task, but PLP was associated with higher metabolic activity during both tasks. CONCLUSION: These results suggest there is both task and region specificity for the association between the brain metabolic response and the two different types of post-amputation pain. The metabolic predominance that is ipsilateral to the amputated limb during both tasks was associated with higher levels of PLP, suggesting a cortical motor network activity imbalance due to potential interhemispheric compensatory mechanisms. The present work contributes to the understanding of the underlying topographical patterns in the motor-related circuits associated with pain after amputations.

Machine Learning-based Deep Analysis of Human Blood using NIR Spectrophotometry Signatures.

BACKGROUND: Non-invasive bio-diagnostics are essential for providing patients with safer treatment. In this subject, significant growth is attained for noninvasive anaemia detection in terms of Hb concentration by means of spectroscopic and image analysis. The lower satisfaction rate is found due to inconsistent results in various patient settings. OBJECTIVE: This observational study aims to present an adaptable point-of-care Near-Infrared (NIR) spectrophotometric approach with a constructive Machine Learning (ML) algorithm for monitoring Haemoglobin (Hb) concentration by considering dominating influencing factors into account. METHODS: To accomplish this objective, 121 subjects (19.2-55.4 years) were enrolled in the study, having a wide range of Hb concentrations (8.2-17.4 g/dL) obtained from two standard Laboratory analyzers. To inspect the performance, the unique dimensionality reduction approaches are applied with numerous regression models using 5-fold cross-validation. RESULTS: The optimum accuracy is found using support vector regression (SVR) and mutual information having 3 independent features i.e. Pearson correlation (r)= 0.79, standard deviation (SD)= 1.07 g/dL, bias=-0.13 g/dL and limits of agreement (LoA)=-2.22 to 1.97 g/dL. Additionally, comparability between two standard laboratory analyzers is found as; r=0.97, SD=0.50 g/dL, bias=0.21 g/dL, and LoA= -0.77 to 1.19 g/dL. CONCLUSION: The precision of ±1 g/dL in 5-fold cross-validation ensures the same performance irrespective of different age groups, gender, BMI, smoking level, drinking level, and skin type. The outcomes with the offered NIR sensing system and an exclusive ML algorithm can accelerate its' requirement at remote locative rural areas and critical care units where continuous Hb monitoring is compulsory.

Application of UV-Vis-NIR and FTIR spectroscopy coupled with chemometrics for quality prediction of katsuobushi based on the number of smoking treatments.

Katsuobushi, a smoked, dried skipjack tuna, is a traditional Japanese food additive with a unique flavor and taste. Gas chromatography mass spectrometry (GC-MS), fourier transform infrared (FTIR), and ultraviolet-visible-near infrared spectroscopy (UV-Vis-NIR) combined with chemometric methods were evaluated the quality of katsuobushi according to the number of smoking treatments. Using GC-MS, 46 metabolites were identified and five metabolites were selected as key compounds. All samples were classified according to their smoking number via principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA) and hierarchical cluster analysis (HCA) of the FTIR and NIR spectra. Partial least squares regression (PLSR) analysis revealed that the FTIR and NIR spectra were highly correlated with the metabolites by GC-MS. These results demonstrated the potential of using the FTIR and NIR spectroscopy combined with chemometrics to assess the quality of katsuobushi based on the smoking treatments, with NIR spectroscopy showed particularly promising.

Second sensor to improve near-infrared spectroscopy flap monitor utility: A prospective study.

OBJECTIVE: This study assesses whether use of continuous noninvasive near-infrared spectroscopy (NIRS) sensor on head and neck free flap (FF) with a second sensor on nonoperated tissue improves distinction between systemic hypoperfusion and FF compromise. METHODS: Single-institution, prospective study of patients undergoing head and neck FF reconstruction from December 2018 to April 2020. FFs were continuously monitored using NIRS on a monitor paddle with a second (control) sensor on the shoulder. Crude StO2 and percent change in StO2 were compared between the FF and control sensors on each patient, and percent change and percent difference between the control and the monitor paddle were documented to assess for congruity. Sentinel events (e.g., hypotension and hematoma) were documented to assess the association with change in StO2. These events and timing of StO2 changes were noted to assess associations with change in StO2. RESULTS: A total of 48 patients had complete data. Donor sites included 35 soft-tissue FFs and 13 fibula FFs. Average StO2 was 73.7 ± 5.5 for FFs and 71.4 ± 5.0 for control sensors. There were seven sentinel events during the study. At the time of the events, StO2 dropped significantly more for the FF than the control sensor (FF = 52.2% drop; control = 6.2% drop; p = .016). NIRS signal denoted change prior to changes in implantable arterial Doppler in all cases. CONCLUSIONS: The addition of a second sensor when using NIRS as a primary modality for FF monitoring may improve distinction between FF compromise events and systemic hypoperfusion. By increasing accuracy of the monitor, there is a potential for decreased resident burden and decreased use of higher level of care nursing, which could reduce overall costs.

Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning.

Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by the need for additional stains, time, personnel and resources. Vibrational spectroscopy is a novel technique that offers an alternative atraumatic approach, with short scan times, while providing metabolic and morphological data. This review evaluates vibrational spectroscopy for the assessment of fibrosis, with a focus on point-of-care capabilities. OVID Medline, Embase and Cochrane databases were systematically searched using PRISMA guidelines for search terms including vibrational spectroscopy, human tissue and fibrosis. Studies were stratified based on imaging modality and tissue type. Outcomes recorded included tissue type, machine learning technique, metrics for accuracy and author conclusions. Systematic review yielded 420 articles, of which 14 were relevant. Ten of these articles considered mid-infrared spectroscopy, three dealt with Raman spectroscopy and one with near-infrared spectroscopy. The metrics for detecting fibrosis were Pearson correlation coefficients ranging from 0.65-0.98; sensitivity from 76-100%; specificity from 90-99%; area under receiver operator curves from 0.83-0.98; and accuracy of 86-99%. Vibrational spectroscopy identified fibrosis in myeloproliferative neoplasms in bone, cirrhotic and hepatocellular carcinoma in liver, end-stage heart failure in cardiac tissue and following laser ablation for acne in skin. It also identified interstitial fibrosis as a predictor of early renal transplant rejection in renal tissue. Vibrational spectroscopic techniques can therefore accurately identify fibrosis in a range of human tissues. Emerging data show that it can be used to quantify, classify and provide data about the nature of fibrosis with a high degree of accuracy with potential scope for point-of-care use.

Visualization Materials Using Silicon-Based Optical Nanodisks (ViSiON) for Enhanced NIR Imaging in Ophthalmology.

ViSiON (visualization materials composed of silicon-based optical nanodisks) is presented, which offers a unique optical combination of near-infrared (NIR) optical properties and biodegradability. Initially, numerical simulations are conducted to calculate the total extinction and scattering effects of ViSiON by the diameter-to-thickness ratio, predicting precise control over its scattering properties in the NIR region. A top-down patterning technique is employed to synthesize ViSiON with accurate diameter and thickness control. ViSiON with a 50 nm thickness exhibits scattering properties over 400 times higher than that of 30 nm, rendering it suitable as a contrast agent for optical coherence tomography (OCT), especially in ophthalmic applications. Furthermore, ViSiON possesses inherent biodegradability in media, with ≈95% degradation occurring after 48 h, and the degradation rate can be finely tuned based on the quantity of protein coating applied to the surface. Subsequently, the OCT imaging capability is validated even within vessels smaller than 300 µm, simulating retinal vasculature using a retinal phantom. Then, using an ex ovo chick embryo model, it is demonstrated that ViSiON enhances the strength of protein membranes by 6.17 times, thereby presenting the potential for ViSiON as an OCT imaging probe capable of diagnosing retinal diseases.

Near-infrared spectroscopy as a novel method of ex vivo bladder cancer tissue characterisation.

OBJECTIVE: To evaluate near-infrared (NIR) spectroscopy in differentiating between benign and malignant bladder pathologies ex vivo immediately after resection, including the grade and stage of malignancy. PATIENTS AND METHODS: A total of 355 spectra were measured on 71 bladder specimens from patients undergoing transurethral resection of bladder tumour (TURBT) between April and August 2022. Scan time was 5 s, undertaken using a portable NIR spectrometer within 10 min from excision. Specimens were then sent for routine histopathological correlation. Machine learning models were applied to the spectral dataset to construct diagnostic algorithms; these were then tested for their ability to predict the histological diagnosis of each sample using its NIR spectrum. RESULTS: A two-group algorithm comparing low- vs high-grade urothelial cancer demonstrated 97% sensitivity, 99% specificity, and the area under the receiver operating characteristic curve (AUC) was 0.997. A three-group algorithm predicting stages Ta vs T1 vs T2 achieved 97% sensitivity, 92% specificity, and the AUC was 0.996. CONCLUSIONS: This first study evaluating the diagnostic potential of NIR spectroscopy in urothelial cancer shows that it can be accurately used to assess tissue in an ex vivo setting immediately after TURBT. This offers point-of-care assessment of bladder pathology, with potential to influence the extent of resection, reducing both the need for re-resection where invasive disease may be suspected, and also the potential for complications where extent of diagnostic resection can be limited. Further studies utilising fibre-optic probes offer the potential for in vivo assessment.

Assessment of microcirculatory alteration by a vascular occlusion test using near-infrared spectroscopy in pediatric cardiac surgery: effect of cardiopulmonary bypass.

OBJECTIVES: Cardiopulmonary bypass cause microcirculatory alterations. Near infrared spectroscopic measurement of tissue oxygen saturation and vascular occlusion test are novel technologies for assessing the microcirculatory function of peripheral tissue specifically in patients undergoing cardiac surgery with cardiopulmonary bypass.Our study aimed to evaluate dynamic microcirculatory function using the vascular occlusion testing during cardiac surgery in pediatric patients. METHODS: 120 pediatric patients were scheduled. Children had continuous regional oxygen saturation monitoring using near infrared spectroscopy and vascular occlusion test. Vascular occlusion test was performed five times; before induction (T1), after induction (T2), then during cardiopulmonary bypass with full flow (T3), after the termination of CPB (T4) and after sternum closure (T5). RESULTS: Basal value was the lowest at T3 and this value was significantly different among measurements (p < 0,01).Values for maximum and minimum tissue oxygen saturation were the lowest at T3 (83,4 and 52,9%).The occlusion slope varied significantly among measurements (p < 0,01).Reperfusion slopes were significantly different among measurements (p < 0,01) with a further progressive decrease in reperfusion slope with duration of cardiopulmonary bypass. CONCLUSION: Microcirculatory function can assessed using VOT with forearm Near-infrared spectroscopy derived variables during cardiopulmonary bypass in pediatric cardiac surgery. Noninvasive assessment of microcirculatory perfusion during cardiopulmonary bypass can further help evaluate and improve circulatory support techniques. TRIAL REGISTRATION: The research Project was registered at ClinicalTrials.gov (NCT06191913).

Comparison of ATR-FTIR and NIR spectroscopy for identification of microplastics in biosolids.

Biosolids are considered a potentially major input of microplastics (MPs) to agricultural soils. Our study aims to identify the polymeric origin of MPs extracted from biosolid samples by comparing their Attenuated Total Reflection (ATR) - Fourier-transform infrared (FTIR) spectra with the corresponding near-infrared (NIR) spectra. The reflectance spectra were preprocessed by Savitzky-Golay (SG), first derivative (FD) and compared with analogous spectra acquired on a set of fifty-two selected commercial plastic (SCP) materials collected from readily available products. According to the results portrayed in radar chart and built from both ATR-FTIR and NIR spectral datasets, the MPs showed high correlations with polymers such as polyethylene (LDPE, HDPE), polyethylene terephthalate (PET), polystyrene (PS), polypropylene (PP) and polyamide (PA), determined in SCP samples. Each unknown MP sample had on average three or more links to several types of SCP, according to the correlation coefficients for each polymer ranging from 0.7 up to 1. The comparison analysis classified the majority of MPs as composed mainly by LDPE/HDPE, according to the top correlation coefficients (r > 0.90). PP and PET were better identified with NIR than ATR-FTIR. In contrast to ATR-FTIR analysis, NIR was unable to identify PS. Based on these results, the primary sources of MPs in the biosolids could be identified as discarded consumer packaging (containers, bags, bottles) and fibers from laundry, disposable glove, and cleaning cloth. SYNOPSIS: Microplastics (MPs) are considered contaminants of emerging concern. This study compares two simple and fast spectroscopy techniques to identify microplastics in the biosolid matrix.

Molecular Engineering of Bright NIR-I/NIR-II Nanofluorophores for High-Resolution Bioimaging and Tumor Detection in Vivo.

A comprehensive approach for the construction of NIR-I/NIR-II nanofluorophores with exceptional brightness and excellent chemo- and photostability has been developed. This study first confirmed that the amphiphilic molecules with stronger hydrophobic moieties and weaker hydrophilic moieties are superior candidates for constructing brighter nanofluorophores, which are attributed to its higher efficiency in suppressing the intramolecular charge transfer/aggregation-caused fluorescence quenching of donor-acceptor-donor type fluorophores. The prepared nanofluorophore demonstrates a fluorescence quantum yield exceeding 4.5% in aqueous solution and exhibits a strong NIR-II tail emission up to 1300 nm. The superior performance of the nanofluorophore enabled the achievement of high-resolution whole-body vessel imaging and brain vessel imaging, as well as high-contrast fluorescence imaging of the lymphatic system in vivo. Furthermore, their potential for highly sensitive fluorescence detection of tiny tumors in vivo has been successfully confirmed, thus supporting their future applications in precise fluorescence imaging-guided surgery in the early stages of cancer.

Continuous Monitoring of Buried Free Bone Flap Microcirculation Using a Near-Infrared Spectroscopy System.

SUMMARY: Postoperative evaluation of free flaps remains a challenging task. The current accepted standard for diagnosis of vascular compromise remains clinical observation. In recent years, near-infrared spectroscopy (NIRS) has been widely used as a noninvasive objective monitoring tool for postoperative evaluation of soft-tissue flaps. However, methods for monitoring bone flaps remain inadequate. In this study, NIRS was applied for the first time to monitor free buried bone flaps that were used for mandibular reconstruction. The penetrating property of NIRS was used to measure the tissue oxygenation index (TOI) of deep tissues, which reflected the microcirculatory status of the tissues. Changes in TOI values were monitored continuously in 59 cases of free bone flaps up to 72 hours after surgery. Five cases of vascular compromise were noted by clinical observation. Two fibula flaps were total failures, one of which showed a sharp decrease in TOI value to 45% in a short period of time; the other showed a continual gradual decrease to 55%. The observed sudden (<50%) and continuous (>10%) decreases in TOI values suggest that more attention should be paid to revision surgical procedures. The authors conclude that NIRS holds promise as an objective and valid method for clinical evaluation of buried bone flaps.

Contraction intensity affects NIRS-derived skeletal muscle oxidative capacity but not its relationships to mitochondrial protein content or aerobic fitness.

To further refine the near-infrared spectroscopy (NIRS)-derived measure of skeletal muscle oxidative capacity in humans, we sought to determine whether the exercise stimulus intensity affected the τ value and/or influenced the magnitude of correlations with in vitro measures of mitochondrial content and in vivo indices of exercise performance. Males (n = 12) and females (n = 12), matched for maximal aerobic fitness per fat-free mass, completed NIRS-derived skeletal muscle oxidative capacity tests for the vastus lateralis following repeated contractions at 40% (τ40) and 100% (τ100) of maximum voluntary contraction, underwent a skeletal muscle biopsy of the same muscle, and performed multiple intermittent isometric knee extension tests to task failure to establish critical torque (CT). The value of τ100 (34.4 ± 7.0 s) was greater than τ40 (24.2 ± 6.9 s, P < 0.001), but the values were correlated (r = 0.688; P < 0.001). The values of τ40 (r = -0.692, P < 0.001) and τ100 (r = -0.488, P = 0.016) correlated with myosin heavy chain I percentage and several markers of mitochondrial content, including COX II protein content in whole muscle (τ40: r = -0.547, P = 0.006; τ100: r = -0.466, P = 0.022), type I pooled fibers (τ40: r = -0.547, P = 0.006; τ100: r = -0.547, P = 0.006), and type II pooled fibers (τ40: r = -0.516, P = 0.009; τ100: r = -0.635, P = 0.001). The value of τ40 (r = -0.702, P < 0.001), but not τ100 (r = -0.378, P = 0.083) correlated with critical torque (CT); however, neither value correlated with W' (τ40: r = 0.071, P = 0.753; τ100: r = 0.054, P = 0.812). Overall, the NIRS method of assessing skeletal muscle oxidative capacity is sensitive to the intensity of skeletal muscle contraction but maintains relationships to whole body fitness, isolated limb critical intensity, and mitochondrial content regardless of intensity.NEW & NOTEWORTHY Skeletal muscle oxidative capacity measured using near-infrared spectroscopy (NIRS) was lower following high-intensity compared with low-intensity isometric knee extension contractions. At both intensities, skeletal muscle oxidative capacity was correlated with protein markers of mitochondrial content (in whole muscle and pooled type I and type II muscle fibers) and critical torque. These findings highlight the importance of standardizing contraction intensity while using the NIRS method with isometric contractions and further demonstrate its validity.

Activatable Near-Infrared Versatile Fluorescent and Chemiluminescent Dyes Based on the Dicyanomethylene-4H-pyran Scaffold: From Design to Imaging and Theranostics.

Activatable fluorescent and chemiluminescent dyes with near-infrared emission have indispensable roles in the fields of bioimaging, molecular prodrugs, and phototheranostic agents. As one of the most popular fluorophore scaffolds, the dicyanomethylene-4H-pyran scaffold has been applied to fabricate a large number of versatile activatable optical dyes for analytes detection and diseases diagnosis and treatment by virtue of its high photostability, large Stokes shift, considerable two-photon absorption cross-section, and structural modifiability. This review discusses the molecular design strategies, recognition mechanisms, and both in vitro and in vivo bio-applications (especially for diagnosis and therapy of tumors) of activatable dicyanomethylene-4H-pyran dyes. The final section describes the current shortcomings and future development prospects of this topic.

Feasibility of Autofluorescence Using Overlay Imaging for the Detection of Parathyroid Glands: Defining Standards.

BACKGROUND: The aim of this study is to define standards for the use of near-infrared autofluorescence (NIRAF)-based overlay imaging via EleVision IR (Medtronic, Dublin, Ireland) and to evaluate its clinical applicability. PATIENTS AND METHODS: This prospective study included 189 patients who had undergone open thyroid and/or parathyroid surgery and in whom EleVision IR was applied to visualize at least one parathyroid gland (PG) between January 2021 and May 2022 in a tertiary referral care center. Whether the PGs were first localized by the surgeon or by overlay imaging was noted. Handling of the device, application time and duration, distance, infrared intensity (IR%), and the angle of each measurement were analyzed. In thyroidectomies, the specimens were subsequently scanned for further PGs. NIRAF patterns and intensities were described. RESULTS: Overall, 543 PGs were analyzed in 158 (83.6%) surgeries of thyroid glands (TGs) and in 49 (25.9%) surgeries for hyperparathyroidism. In 111 (58.7%) patients, identical numbers of PGs were detected by the surgeon and by overlay imaging. While a larger number of PGs was identified by the surgeon in 48 (25.4%) patients, overlay imaging served to detect more PGs in 30 (15.9%) cases. In four (2.1%) patients, PGs were visualized post-thyroidectomy due to their autofluorescence on the specimen. NIRAF-based overlay imaging was applied to depict the PGs early on after exposure by the surgeon. The ideal distance for the measurement ranged between 8 and 12 cm with an angle of 90° and a mean IR% of 34.5% (± 17.6). CONCLUSIONS: Considering the standard operating procedures, NIRAF-based overlay imaging can be used as an adjunct tool for intraoperative localization.

Near-infrared reflectance spectroscopy for rapid prediction of biochemical methane potential of wastewater wasted sludge.

The information of biochemical methane potential (BMP) of wasted sludge is essential to ensure the stable operation of sludge management processes. However, conventional anaerobic digestion (AD) approach for BMP test is time-consuming and labour-intensive. Currently, the technique of Near Infrared Spectroscopy (NIRS) is gaining prominence in the biogas production within AD process. Previous studies mostly focused on predicting BMP values for fibrous plant biomass and solid waste, with only a limited number of studies attempting to apply NIRS to obtain BMP values across a wide array of wasted sludge types. To obtain BMP values for this diverse range of wasted sludge efficiently and accurately, it is imperative to develop precise models for assessing BMP values using NIRS. In this study, the possibility of using NIRS to predict the BMP values of wasted sludge was evaluated. A total of 70 sludge samples from different sources were investigated to develop a BMP-prediction model by correlating the measured BMP values with the obtained NIR spectra. As a result, a reliable and successful BMP-prediction model was established with the determination coefficient of 0.90, residual prediction deviation of 3.50 and low root mean square error of prediction of 36.8 mL CH4/g VS. This BMP-prediction model is satisfactory for predicting BMP values of various types of sludge. It could provide support for plant operators to make decisions rapidly, thereby improving the process efficiency and optimizing sludge management procedures.