Search Results (6,896)

We present an analysis of high-resolution, near-infrared (NIR) spectra relative to the solar transit of Venus of 5–6 June 2012, as observed with the Facility Infrared Spectropolarimeter (FIRS) at the Dunn Solar Telescope in New Mexico. These observations offer the unique opportunity to probe the upper layers (above ∼84 km in altitude) of a thick, CO₂-dominated atmosphere with the transmission spectroscopy technique—a proxy for future studies of highly-irradiated atmospheres of Earth-sized exoplanets. We were able to directly observe absorption lines from the two most abundant CO₂ isotopologues, and from the main isotopologue of CO in the retrieved spectrum of Venus. Furthermore, we performed a cross-correlation analysis of the transmission spectrum using transmission templates generated with petitRADTRANS. With the cross-correlation technique, it was possible to confirm detections of both CO₂ isotopologues and CO. Additionally, we retrieved a tentative cross-correlation signal for O₃ on Venus. We demonstrate the feasibility of high-resolution, ground-based observations to study the chemical inventory of planetary atmospheres, employing techniques commonly used in exoplanet characterization. Full article

Objectives: The present prospective study aimed to compare near-infrared light reflection (NIRI) and bitewing radiographs (BWR) images to detect proximal caries in primary teeth. Methods: 71 children underwent routine BWR, and scans were performed using an intra-oral scanner (iTero Element 5D, Align Technology, Tempe, AZ, USA), including a near-infrared light source (850 nm) and sensor. Five specialist pediatric dentists examined the NIRI and BWR images. Results: The average participant age was 7.8 years. A total of 1004 proximal surfaces of primary molars and canines were examined, 209 carious lesions were detected on BWR, and 227 on NIRI. Comparison between all carious lesions detected on BWR and NIRI: Sensitivity (53.6%); Specificity (85.5%); Positive Predictive Value (PPV) (49.3%); Negative Predictive Value (NPV) (87.5%). Comparison between carious lesions involving the DEJ detected on BWR and at any level in NIRI: Sensitivity (61%); Specificity (83.4%), PPV (36.6%); NPV (93.2%). Comparison between enamel-only carious lesions detected on BWR and all lesions detected using NIRI: Sensitivity (44.8%); Specificity (85.5%); PPV (20.7%); NPV (94.8%). Conclusions: No additional diagnostic information can be gleaned from BWR if initial caries lesions in the enamel are not detected by clinical examination or in images from a NIRI scanner, making BWR unnecessary. Full article

Background: This study examines genetic variations in the systemic oxygen transport cascade during exhaustive exercise in physically trained tactical athletes. Research goal: To update the information on the distribution of influence of eleven polymorphisms in ten genes, namely ACE (rs1799752), AGT (rs699), MCT1 (rs1049434), HIF1A (rs11549465), COMT (rs4680), CKM (rs8111989), TNC (rs2104772), PTK2 (rs7460 and rs7843014), ACTN3 (rs1815739), and MSTN (rs1805086)—on the connected steps of oxygen transport during aerobic muscle work. Methods: 251 young, healthy tactical athletes (including 12 females) with a systematic physical training history underwent exercise tests, including standardized endurance running with a 12.6 kg vest. Key endurance performance metrics were assessed using ergospirometry, blood sampling, and near-infrared spectroscopy of knee and ankle extensor muscles. The influence of gene polymorphisms on the above performance metrics was analyzed using Bayesian analysis of variance. Results: Subjects exhibited good aerobic fitness (maximal oxygen uptake (VO₂max): 4.3 ± 0.6 L min⁻¹, peak aerobic power: 3.6 W ± 0.7 W kg⁻¹). Energy supply-related gene polymorphisms rs1799752, rs4680, rs1049434, rs7843014, rs11549465, and rs8111989 did not follow the Hardy–Weinberg equilibrium. Polymorphisms in genes that regulate metabolic and contractile features were strongly associated with variability in oxygen transport and metabolism, such as body mass-related VO₂ (rs7843014, rs2104772), cardiac output (rs7460), total muscle hemoglobin content (rs7460, rs4680), oxygen saturation in exercised muscle (rs1049434), and respiration exchange ratio (rs7843014, rs11549465) at first or secondary ventilatory thresholds or VO₂max. Moderate influences were found for mass-related power output. Conclusions: The posterior distribution of effects from genetic modulators of aerobic metabolism and muscle contractility mostly confirmed prior opinions in the direction of association. The observed genetic effects of rs4680 and rs1049434 indicate a crucial role of dopamine- and lactate-modulated muscle perfusion and oxygen metabolism during running, suggesting self-selection in Swiss tactical athletes. Full article

Background/Objectives: Necrotizing enterocolitis (NEC), a devastating neonatal gastrointestinal disease mostly seen in preterm infants, lacks accurate prediction despite known risk factors. This hinders the possibility of applying targeted preventive therapies. This study explores the use of vital signs, including cerebral and splanchnic oxygenation, measured with near-infrared spectroscopy in early NEC prediction. Methods: Several machine learning algorithms were trained on data from very preterm patients (<30 weeks gestational age). Time Series FeatuRe Extraction on the basis of scalable hypothesis tests (TSFRESH) extracted significant features from the vital signs of the first 5 postnatal days. We present the F1-scores and area under the precision-recall curve (AUC-PR) of the models. The contribution of separate vital signs to the selected TSFRESH features was also determined. Results: Among 267 patients, 32 developed NEC Bell’s stage > 1. Using a 1:4 NEC:control ratio, support vector machine and logistic regression predicted NEC better than extreme gradient boosting regarding the F1-score (0.82, 0.82, 0.76, resp., p = 0.001) and AUC-PR (0.82, 0.83, 0.77, resp., p < 0.001). Splanchnic and cerebral oxygenation contributed most to the prediction (40.1% and 24.8%, resp.). Conclusions: Using vital signs, we predicted NEC in the first 5 postnatal days with an F1-score up to 0.82. Splanchnic and cerebral oxygenation were the most contributing vital predictors. This pioneering effort in early NEC prediction using vital signs underscores the potential for targeted preventive measures and also emphasizes the need for additional data in future studies. Full article

The direct detection of singlet-state oxygen (¹O₂) constitutes the holy grail dosimetric method for type-II photodynamic therapy (PDT), a goal that can be quantified using multispectral singlet oxygen near-infrared luminescence dosimetry (MSOLD). The optical properties of tissues, specifically their scattering and absorption coefficients, play a crucial role in determining how the treatment and luminescence light are attenuated. Variations in these properties can significantly impact the spatial distribution of the treatment light and hence the generation of singlet oxygen and the detection of singlet oxygen luminescence signals. In this study, we investigated the impact of varying optical properties on the detection of ¹O₂ luminescence signals during Photofrin-mediated PDT in tissue-mimicking phantoms. For comparison, we also conducted Monte Carlo (MC) simulations under the same conditions. The experimental and simulations are substantially equivalent. This study advances the understanding of MSOLD during PDT. Full article

Glioblastoma (GB) is among the most aggressive and difficult-to-treat brain tumors, with a median survival of only 12–15 months despite maximal treatments, including surgery, radiotherapy, and chemotherapy. Extensive surgical resection improves survival in glioblastoma patients; however, achieving complete resection is often hindered by limitations in neurosurgical guidance technologies for accurate tumor margin detection. Recent advancements in fluorescence-guided surgery (FGS) and imaging techniques have significantly enhanced the precision and extent of glioblastoma resections. This study evaluates the impact of NIR fluorescence imaging on tumor visualization, surgical precision, cost-effectiveness, and patient survival. A systematic review of PubMed, Scopus, Google Scholar, and Embase was conducted to identify studies on the role of NIR fluorescence in glioblastoma surgery. A total of 135 studies were included, comprising 10 reviews, three clinical studies, 10 randomized controlled trials (RCTs), 10 preclinical studies, and four case reports, all focused on NIR fluorescence imaging in glioblastoma surgery. The findings indicate that NIR fluorescence imaging significantly improves tumor visualization, resulting in an 18–22% increase in gross total resection (GTR) rates in clinical studies. NIR fluorescence provides continuous real-time feedback, minimizing repeat imaging, reducing operational costs, and increasing GTR. These improvements contribute to better patient outcomes, including extended progression-free survival, improved overall survival, and reduced postoperative neurological deficits. This review underscores the potential of NIR imaging to establish a new standard for intraoperative glioblastoma management. Full article

This paper presents a novel approach to material classification using short-wave infrared (SWIR) imaging, aimed at applications where differentiating visually similar objects based on material properties is essential, such as in autonomous driving. Traditional vision systems, relying on visible spectrum imaging, struggle to distinguish between objects with similar appearances but different material compositions. Our method leverages SWIR’s distinct reflectance characteristics, particularly for materials containing moisture, and demonstrates a significant improvement in accuracy. Specifically, SWIR data achieved near-perfect classification results with an accuracy of 99% for distinguishing real from artificial objects, compared to 77% with visible spectrum data. In object detection tasks, our SWIR-based model achieved a mean average precision (mAP) of 0.98 for human detection and up to 1.00 for other objects, demonstrating its robustness in reducing false detections. This study underscores SWIR’s potential to enhance object recognition and reduce ambiguity in complex environments, offering a valuable contribution to material-based object recognition in autonomous driving, manufacturing, and beyond. Full article

To evaluate the radiometric performance of top-of-atmosphere reflectance images, Deep Convective Clouds (DCCs) can be used as temporally, spatially and spectrally stable targets. The DCCs method has been developed more than 20 years ago and applied recently to Sentinel-2 and Sentinel-3 sensors. In this paper, among other developments, we built a new methodology upon those existing by using the bootstrap method and spectral band adjustment factors computed with the Hyper-Spectral Imager (HSI) from the Environmental Mapping and Analysis Program (EnMAP). This methodology is applied to the two Multi-Spectral Imager (MSI) instruments onboard Sentinel-2A and 2B, but also the two Operational Land Imager (OLI) instruments onboard Landsat 8 and 9, from visible wavelength at 442 nm to shortwave-infrared at 2200 nm, using images with a ground resolution spanning from 10 m to 60 m. The results demonstrate the good inter-calibration of MSI units A and B, which are within one percent of relative difference on average between January 2022 and June 2024 for all visible, near-infrared and shortwave-infrared bands, except for the band at 1375 nm for which saturation prevents the use of the method. Similarly, OLI and OLI-2 are found to have a relative difference on the same period lower than one percent for all 30 m resolution bands. Evaluation of the relative difference between the MSI sensors and the OLI sensors with the DCCs method gives values lower than three percent. Finally, these validation results are compared to those obtained with Pseudo-Invariant Calibration Sites (PICSs) over Libya-4: an agreement better than two percent is found between the DCCs and PICSs methods. Full article

Background/Objectives: Many lasers applied in skin rejuvenation protocols show emissions with wavelengths falling in the red or near-infrared (NIR) bands. To obtain further in vitro data on the potential therapeutic benefits regarding rejuvenation, we employed a 675 nm laser wavelength on cultured human dermal fibroblasts to understand the mechanisms involved in the skin rejuvenation process’s signaling pathways by analyzing cytoskeletal proteins, extracellular matrix (ECM) components, and membrane integrins. Methods: Normal human dermal fibroblasts (NHDFs) were irradiated with a 675 nm laser 24 h after seeding, and immunofluorescence microscopy and Western blotting were applied. Results: The results demonstrate that the laser treatment induces significant changes in human dermal fibroblasts, affecting cytoskeleton organization and the production and reorganization of ECM molecules. The cell response to the treatment appears to predominantly involve paxillin-mediated signaling pathways. Conclusions: These changes suggest that laser treatment can potentially improve the structure and function of skin tissue, with interesting implications for treating skin aging. Full article

With climate change and the intensification of human activity, drought event frequency has increased, affecting the Gross Primary Production (GPP) of terrestrial ecosystems. Accurate estimation of the GPP and in-depth exploration of its response mechanisms to drought are essential for understanding ecosystem stability and developing strategies for climate change adaptation. Combining remote sensing technology and machine learning is currently the mainstream method for estimating the GPP in terrestrial ecosystems, which can eliminate the uncertainty of model parameters and errors in input data. This study employed extreme gradient boosting, random forest (RF), and light use efficiency models. Additionally, we integrated solar-induced chlorophyll fluorescence (SIF), near-infrared reflectance of vegetation, and the leaf area index (LAI) to construct various GPP estimation models. The standardised precipitation evapotranspiration index (SPEI) was utilised at various timescales to analyse the relationship between the GPP and SPEI during dry years. Moreover, the potential pathways and coefficients of environmental factors that influence GPP were explored using structural equation modelling. Our key findings include the following: (1) the model combining the SIF and RF algorithms exhibits higher accuracy and applicability in estimating vegetation GPP in the arid zone of Xinjiang, with an overall accuracy (MODIS R²) of 0.775; (2) the vegetation in Xinjiang had different response characteristics to different timescales of drought, in which the optimal timescale for GPP to respond to drought was 9 months, with a mean correlation coefficient of 0.244 between grass land GPP and SPEI09, indicating high sensitivity; (3) using structural equation modelling, we found that temperature and precipitation can affect GPP both directly and indirectly through LAI. This study provides a reliable tool for estimating the GPP in Xinjiang, and its methodology and conclusions are important references for similar environments. In addition, this study bridges the research gap in drought response to GPP at different timescales, and the potential influence mechanism of natural factors on GPP provides a scientific basis for early warning of drought and ecosystem management. Further validation using a longer time series is required to confirm the robustness of the model. Full article

Water content is one of the most critical characteristics in plant physiological development. Therefore, this information is a crucial factor in determining the water stress conditions of vegetation, which is essential for assessing the wildfire risk and land management decision-making. Remote sensing can be vital for obtaining information over large, limited access areas with global coverage. This is important since conventional techniques for collecting vegetation water content are expensive, time-consuming, and spatially limited. This work aims to evaluate the vegetation live fuel moisture content (LFMC) seasonal variability using a multiscale remote sensing approach, particularly on rockroses, the Cistus ladanifer species, a Western Mediterranean basin native species with wide spatial distribution, over the Herdade da Mitra at the University of Évora, Portugal. This work used four dataset sources, collected monthly between June 2022 and July 2023: (i) Vegetation samples used to calculate the LFMC; (ii) Vegetation reflectance spectral signature using the portable spectroradiometer FieldSpec HandHeld-2 (HH2); (iii) Multispectral optical imagery obtained from the Multispectral Instrument (MSI) sensor onboard the Sentinel-2 satellite; and (iv) Multispectral optical imagery derived from a camera onboard an Unmanned Aerial Vehicle Phantom 4 Multispectral (P4M). Several temporal analyses were performed based on datasets from different sensors and on their intercomparison. Furthermore, the Random Forest (RF) classifier, a machine learning model, was used to estimate the LFMC considering each sensor approach. MSI sensor presented the best results (R² = 0.94) due to the presence of bands on the Short-Wave Infrared Imagery region. However, despite having information only in the Visible and Near Infrared spectral regions, the HH2 presents promising results (R² = 0.86). This suggests that by combining these spectral regions with a RF classifier, it is possible to effectively estimate the LFMC. This work shows how different spatial scales, from remote sensing observations, affect the LFMC estimation through machine learning techniques. Full article

Postharvest internal disorders (IDs) in mango fruit present a significant challenge to the industry, with their underlying causes still unclear. This study investigated the relationship between fruit maturity and the susceptibility of vapor heat-treated (VHT) ‘B74’ mangoes to IDs in three experiments. In the first experiment, fruit were categorized into three maturity groups based on dry matter content (DMC): <15%, 15–17%, and >17%, using a handheld near-infrared device. Half of the fruit in each group underwent VHT, while the remainder were untreated controls. Flesh cavity with white patches (FCWP) was the only disorder observed exclusively in VHT fruit. The incidence and severity of FCWP was significantly higher (p < 0.05) in fruit with <15% DMC, with 12.4% incidence and a severity score of 0.2 on a 0–3 scale (0: healthy and 3: severely affected), compared to more mature fruit. In the second experiment, the fruits were harvested at early and late maturity stages, with average DMC values of 14.5% and 17.4%, respectively. The fruit was subjected to no VHT, VHT, and VHT following a 12 h pre-conditioning period at 37 ± 1 °C. Consistent with the first experiment, FCWP was observed only in VHT fruit, with early-harvested fruit displaying a significantly higher (p < 0.05) FCWP incidence (26.9%) and severity (0.3) compared to late-harvested fruit (8.3% incidence and 0.1 severity). Pre-conditioning significantly reduced FCWP, particularly in early-harvested fruit. In the third experiment, fruit maturity sorted based on density was assessed, followed by VHT and simulated sea freight under controlled (CA) and ambient atmospheres. Fruit density did not effectively differentiate maturity considering DMC as a maturity indicator. Storage conditions significantly reduced (p < 0.05) flesh browning incidence from 71.1% under ambient conditions to 33.3% under CA. This study highlights fruit maturity as a key factor in the susceptibility of ‘B74’ mangoes to postharvest IDs following VHT. Therefore, sorting fruit based on DMC at harvest or at the packing facility prior to VHT serves as a valuable decision support for reducing IDs in VHT fruit. Further research will explore advanced technologies to enable rapid and efficient fruit sorting based on DMC. Full article

Background/Objectives: Previous studies have shown that neuromuscular electrical stimulation (NMES), while expensive, can provide some of the health benefits of exercise to people who cannot exercise their legs normally. The aim of this study was to quantify the increases in muscle metabolism in four muscles of the legs of able-bodied individuals with NMES. Methods: Healthy college-aged students were tested. NMES of four muscle groups was performed with inexpensive stimulators and reusable tin foil electrodes. The biceps femoris, vastus lateralis, medial gastrocnemius, and tibialis anterior muscles on one leg were stimulated for ten minutes with twitch stimulations at the highest comfortable stimulation current. Muscle metabolism was measured using the slope of oxygen consumption measured with near-infrared spectroscopy (NIRS) during 5 s of cuff ischemia. Results: Initial studies found fold increases in muscle metabolism above rest of 8.9 ± 8.6 for the vastus lateralis, 7.9 ± 11.9 for the biceps femoris, 6.6 ± 7.8 for the medial gastrocnemius, and 4.9 ± 3.9 for the tibialis anterior. Some participants were able to obtain large increases in muscle metabolism, while other participants had lower increases. Conclusions: The ability to produce large increases in metabolism has the potential to allow NMES to replace or augment exercise to improve health in people who cannot otherwise exercise. The devices used were inexpensive and could be adapted for easy use by a wide range of individuals. Full article

The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested in discriminating pesticide-free against pesticide-treated lettuce plants. Two commercial fungicides (mancozeb and fosetyl-al) and two insecticides (deltamethrin and imidacloprid) were applied as spray solutions at the recommended rates on baby leaf lettuce plants. Untreated-control plants were sprayed with water. Reflectance data in the wavelength range 400–2500 nm were captured on leaf samples until harvest on the 10th day upon pesticide application, as well as after 4 and 8 days during post-harvest storage at 5 °C. In addition, biochemical components in leaf tissue were also determined during storage, such as antioxidant enzymes’ activities (peroxidase [POD], catalase [CAT], and ascorbate peroxidase [APX]), along with malondialdehyde [MDA] and hydrogen peroxide [H₂O₂] content. Partial least square discriminant analysis (PLSDA) combined with feature-selection techniques was implemented, in order to classify baby lettuce tissue into pesticide-free or pesticide-treated ones. The genetic algorithm (GA) and the variable importance in projection (VIP) scores identified eleven distinct regions and nine specific wavelengths that exhibited the most significant effect in the detection models, with most of them in the near-infrared region of the electromagnetic spectrum. According to the results, the classification accuracy of discriminating pesticide-treated against non-treated lettuce leaves ranged from 94% to 99% in both pre-harvest and post-harvest periods. Although there were no significant differences in enzyme activities or H₂O₂, the MDA content in pesticide-treated tissue was greater than in untreated ones, implying that the chemical spray application probably induced a stress response in the plant that was disclosed with the reflected energy. In conclusion, vis/NIR spectroscopy appears as a promising, reliable, rapid, and non-destructive tool in distinguishing pesticide-free from pesticide-treated lettuce products. Full article

A series of copolymers containing a thermo-responsive biocompatible first block of poly[di(ethylene glycol) methyl ether methacrylate)-co-(oligo(ethylene glycol) methyl ether methacrylate], P(DEGMA-co-OEGMA) were chain-extended to incorporate either poly(N-isopropylacrylamide), PNIPAAm or poly(N-isopropylacrylamide-co-butyl acrylate), P(NIPAAm-co-BA) as second thermo-responsive block using reversible addition–fragmentation chain transfer (RAFT) polymerization. P(DEGMA-co-OEGMA)-b-PNIPAAm copolymers showed two response temperatures at 33 and 43 °C in an aqueous solution forming stable aggregates at 37 °C. In contrast, P(DEGMA-co-OEGMA)-b-P(NIPAAm-co-BA) copolymers showed aggregation below room temperature due to the shift in response temperature provoked by the presence of hydrophobic butyl acrylate (BA) units, and shrinkage upon heating up to body temperature, while maintaining the second response temperature above 40 °C. The terminal trithiocarbonate group of the block copolymers was modified to a thiol functionality and used to stabilize gold nanorods (GNRDs) via the “grafting to” approach. The Localized Surface Plasmon Resonance (LSPR) absorption band of GNRDs with an aspect ratio of 3.9 (length/diameter) was located at 820 nm after surface grafting with block copolymers showing a hydrodynamic diameter of 160 nm at 37 °C. On the other hand, the stability of the P(DEGMA-co-OEGMA)-b-PNIPAAm@GNRDs and P(DEGMA-co-OEGMA)-b-P(NIPAAm-co-BA)@GNRDs nanohybrids was monitored for 8 days; where the LSPR absorption band did not shift or show any broadening. Aqueous dispersed nanohybrids were irradiated with a near-infrared laser (300 mW), where the temperature of the surroundings increased 16 °C after 16 min, where conditions for no precipitation were determined. These tailored temperature-responsive nanohybrids represent interesting candidates to develop drug nanocarriers for photo-thermal therapies. Full article