Review of short-wave infrared spectroscopy and imaging methods for biological tissue characterization

Dynamically monitoring lymphatic and vascular systems in physiological and pathological conditions of a swine model via a portable NIR-II imaging system with ICG

Objective: NIR-II imaging with indocyanine green (ICG) has been clinically used in liver tumor resection. However, few data are available concerning the application of ICG-NIR-II in lymphatic and vascular systems in clinic. To expand the application and promote the clinical translation of this approach, we aimed to investigate the feasibility of ICG-NIR-II imaging for monitoring both lymphatic and vascular systems in physiological and pathological conditions using a swine model and compared it to ICG-NIR-I imaging. Methods: we constructed a portable NIR-II imaging system suitable for large animals. Different simulated clinical scenarios in lymphatic and vascular systems of pigs, including lymphatic drainage, lymphorrhea, lymphatic obstruction, lymphatic reconstruction in flaps, venous thrombus formation and vascular anastomosis were modeled to evaluate the reliability of our NIR-II imaging system and the imaging quality of ICG in the NIR-I/II window. Results: Under different simulated clinical scenarios, our portable NIR-II imaging system showed good reliability for pigs. With the help of the portable imaging system, dynamical visualization of lymph vessels, lymph nodes and blood vessels of pigs in different clinical scenarios could be achieved in NIR-II imaging by using the tail fluorescence of ICG. Moreover, ICG-NIR-II imaging has lower background fluorescence and higher resolution than ICG-NIR-I imaging. Conclusions: We demonstrated the first application of a portable NIR-II imaging system for dynamically monitoring both lymphatic and vascular systems in physiological and pathological conditions using a swine model. Our study indicates that ICG-NIR-II imaging be a promising approach for the diagnosis of malfunctions in lymphatic and vascular systems and the surgical navigation of microsurgery and reconstructive surgery.

Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra

The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues and to determine whether an extended wavelength range (450-1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100% and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important.

Deep Learning Combined with Hyperspectral Imaging Technology for Variety Discrimination of Fritillaria thunbergii

Traditional Chinese herbal medicine (TCHM) plays an essential role in the international pharmaceutical industry due to its rich resources and unique curative properties. The flowers, stems, and leaves of Fritillaria contain a wide range of phytochemical compounds, including flavonoids, essential oils, saponins, and alkaloids, which may be useful for medicinal purposes. Fritillaria thunbergii Miq. Bulbs are commonly used in traditional Chinese medicine as expectorants and antitussives. In this paper, a feasibility study is presented that examines the use of hyperspectral imaging integrated with convolutional neural networks (CNN) to distinguish twelve (12) Fritillaria varieties (n = 360). The performance of support vector machines (SVM) and partial least squares-discriminant analysis (PLS-DA) was compared with that of convolutional neural network (CNN). Principal component analysis (PCA) was used to assess the presence of cluster trends in the spectral data. To optimize the performance of the models, cross-validation was used. Among all the discriminant models, CNN was the most accurate with 98.88%, 88.89% in training and test sets, followed by PLS-DA and SVM with 92.59%, 81.94% and 99.65%, 79.17%, respectively. The results obtained in the present study revealed that application of HSI in conjunction with the deep learning technique can be used for classification of Fritillaria thunbergii varieties rapidly and non-destructively.

Model-based characterization platform of fiber optic extended-wavelength diffuse reflectance spectroscopy for identification of neurovascular bundles

SIGNIFICANCE

Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements.

AIM

The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications.

APPROACH

A model-based platform consisting of an ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses.

RESULTS

EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus.

CONCLUSIONS

Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications.

Heterojunction bilayers serving as a charge transporting interlayer reduce the dark current and enhance photomultiplication in organic shortwave infrared photodetectors

Previous approaches to induce photomultiplication in organic diodes have increased the photosignal but lacked control over reducing background noise. This work presents a new interlayer design based on a heterojunction bilayer that concurrently enables photomultiplication and suppresses the dark current in organic shortwave infrared detectors to improve the overall detectivity. The heterojunction bilayer consists of a hole-transporting material copper thiocyanate and an electron-transporting material tin oxide, and this combination offers the ability to block charge injection in the dark. Under illumination, the bilayer promotes trap-assisted photomultiplication by lowering the tunneling barrier and amplifying the photocurrent through the injection of multiple carriers per absorbed photon. Upon incorporating the heterojunction interlayer in photodiodes and upconversion imagers, the devices achieve an external quantum efficiency up to 560% and a detectivity of 3.5 × 10⁹ Jones. The upconversion efficiency of the imager doubles with a 1.7 fold improvement in contrast compared to the imager without the heterojunction interlayer. The new interlayer design is generalizable to work with different organic semiconductors, making it attractive and easy to integrate with emerging organic infrared systems.

Temporal and spatial summation of laser heat stimuli in cultured nociceptive neurons of the rat

We studied the efficacy of a near-infrared laser (1475 nm) to activate rat dorsal root ganglion (DRG) neurons with short punctate radiant heat pulses (55 µm diameter) and investigated temporal and spatial summation properties for the transduction process for noxious heat at a subcellular level. Strength-duration curves (10–80 ms range) indicated a minimum power of 30.2mW for the induction of laser-induced calcium transients and a chronaxia of 13.9 ms. However, threshold energy increased with increasing stimulus duration suggesting substantial radial cooling of the laser spot. Increasing stimulus duration demonstrated suprathreshold intensity coding of calcium transients with less than linear gains (Stevens exponents 0.29/35mW, 0.38/60mW, 0.46/70mW). The competitive TRPV1 antagonist capsazepine blocked responses to short near-threshold stimuli and significantly reduced responses to longer duration suprathreshold heat. Heating 1/3 of the soma of a neuron was sufficient to induce calcium transients significantly above baseline (p < 0.05), but maximum amplitude was only achieved by centering the laser over the entire neuron. Heat-induced calcium increase was highest in heated cell parts but rapidly reached unstimulated areas reminiscent of spreading depolarization and opening of voltage-gated calcium channels. Full intracellular equilibrium took about 3 s, consistent with a diffusion process. In summary, we investigated transduction mechanisms for noxious laser heat pulses in native sensory neurons at milliseconds temporal and subcellular spatial resolution and characterized strength duration properties, intensity coding, and spatial summation within single neurons. Thermal excitation of parts of a nociceptor spread via both membrane depolarization and intracellular calcium diffusion.

Management of fluorescent organic/inorganic nanohybrids for biomedical applications in the NIR-II region

Biomedical fluorescence imaging in the second near-infrared (NIR-II, 100-1700 nm) window provides great potential for visualizing physiological and pathological processes, owing to the reduced tissue absorption, scattering, and autofluorescence. Various types of NIR-II probes have been reported in the past decade. Among them, NIR-II organic/inorganic nanohybrids have attracted widespread attention due to their unique properties by integrating the advantages of both organic and inorganic species. Versatile organic/inorganic nanohybrids provide the possibility of realizing a combination of functions, controllable size, and multiple optical features. This tutorial review summarizes the reported organic and inorganic species in nanohybrids, and their biomedical applications in NIR-II fluorescence and lifetime imaging. Finally, the challenges and outlook of organic/inorganic nanohybrids in biomedical applications are discussed.

Ultra-fast detail enhancement for a short-wave infrared image

Image detail enhancement is critical to the performance of short-wave infrared (SWIR) imaging systems, especially to the long-range systems. However, the existing high-performance infrared (IR) image enhancement methods typically have difficulty in meeting the requirements of the imaging system with high resolution and high frame rate. In this paper, we propose an ultra-fast and simple SWIR image detail enhancement method based on the difference of Gaussian (DoG) filter and plateau equalization. Our method consists of efficient edge detail information extraction and histogram equalization. The experimental results demonstrated that the proposed method achieves outstanding enhancement performance with a frame rate around 50 fps for 1280×1024 SWIR images.

Shortwave infrared spatial frequency domain imaging for non-invasive measurement of tissue and blood optical properties

SIGNIFICANCE

The shortwave infrared (SWIR) optical window (∼900 to 2000 nm) has attracted interest for deep tissue imaging due to the lower scattering of light. SWIR spatial frequency domain imaging (SWIR SFDI) provides wide-field tissue optical property measurements in this wavelength band. Key design and performance characteristics, such as portability, wavelength selection, measurement resolution, and the effect of skin have not yet been addressed for SWIR SFDI.

AIM

To fabricate and characterize a SWIR SFDI system for clinical use.

APPROACH

The optimal choice of wavelengths was identified based on optical property uncertainty estimates and imaging depth. A compact light-emitting diode-based dual wavelength SWIR SFDI system was fabricated. A two-layer inverse model was developed to account for the layered structure of skin. Performance was validated using tissue-simulating phantoms and in-vivo measurements from three healthy subjects.

RESULTS

The SWIR SFDI system had a μs' resolution of at least 0.03  mm  -  1 at 880 nm and 0.02  mm  -  1 at 1100 nm. The two-layer inverse model reduced the error in deeper layer μs' extractions by at least 24% in the phantom study. The two-layer model also increased the contrast between superficial vessels and the surrounding tissue for in-vivo measurements.

CONCLUSION

The clinic-ready SWIR SFDI device is sensitive to small optical property alterations in diffuse media, provides enhanced accuracy in quantifying optical properties in the deeper layers in phantoms, and provided enhanced contrast of subcutaneous blood vessels.

Safety of use of the ENDOSWIR near-infrared optical imaging device on human tissues: prospective blind study

Cancer surgery requires removing the tumor tissue in necessary and sufficient quantities. Spectral optical imaging in the short-wave infrared (900-1700 nm) could provide an intraoperative guidance to the surgeon based on the absorption of the tissues without contrast agent. Our objective was to ensure the safety of our ENDOSWIR device on human tissues. Histological analysis of fresh human tonsils exposed to the SWIR light or not was compared and showed no histological differences. This demonstrates the safety of using the SWIR device on human tissues and allows us to initiate a clinical study for the resection of tumors intraoperatively.

Reflectance spectroscopy and machine learning as a tool for the categorization of twin species based on the example of the Diachrysia genus

In our work we used noninvasive point reflectance spectroscopy in the range from 400 to 2100 nm coupled with machine learning to study scales on the brown and golden iridescent areas on the dorsal side of the forewing of Diachrysia chrysitis and D. stenochrysis. We used our approach to distinguish between these species of moths. The basis for the study was a statistically significant collection of 95 specimens identified based on morphological feature and gathered during 23 years in Poland. The numerical part of an experiment included two independent discriminant analyses: stochastic and deterministic. The more sensitive stochastic approach achieved average compliance with the species identification made by entomologists at the level of 99-100%. It demonstrated high stability against the different configurations of training and validation sets, hence strong predictors of Diachrysia siblings distinctiveness. Both methods resulted in the same small set of relevant features, where minimal fully discriminating subsets of wavelengths were three for glass scales on the golden area and four for the brown. The differences between species in scales primarily concern their major components and ultrastructure. In melanin-absent glass scales, this is mainly chitin configuration, while in melanin-present brown scales, melanin reveals as an additional factor.

Blue LED-pumped intense short-wave infrared luminescence based on Cr3+-Yb3+-co-doped phosphors

The growing demand for spectroscopy applications in the areas of agriculture, retail and healthcare has led to extensive research on infrared light sources. The ability of phosphors to absorb blue light from commercial LED and convert the excitation energy into long-wavelength infrared luminescence is crucial for the design of cost-effective and high-performance phosphor-converted infrared LEDs. However, the lack of ideal blue-pumped short-wave infrared (SWIR) phosphors with an emission peak longer than 900 nm greatly limits the development of SWIR LEDs using light converter technology. Here we have developed a series of SWIR-emitting materials with high luminescence efficiency and excellent thermal stability by co-doping Cr³⁺-Yb³⁺ ion pairs into Lu_0.2Sc_0.8BO₃ host materials. Benefitting from strong light absorption of Cr³⁺ in the blue waveband and very efficient Cr³⁺→Yb³⁺ energy transfer, the as-synthesized Lu_0.2Sc_0.8BO₃:Cr³⁺,Yb³⁺ phosphor emits intense SWIR light in the 900-1200 nm from Yb³⁺ under excitation with blue light at ~460 nm. The optimized phosphor presents an internal quantum yield of 73.6% and the SWIR luminescence intensity at 100 °C can still keep 88.4% of the starting value at 25 °C. SWIR LED prototype device based on Lu_0.2Sc_0.8BO₃:Cr³⁺,Yb³⁺ phosphor exhibits exceptional luminescence performance, delivering SWIR radiant power of 18.4 mW with 9.3% of blue-to-SWIR power conversion efficiency and 5.0% of electricity-to-SWIR light energy conversion efficiency at 120 mA driving current. Moreover, under the illumination of high-power SWIR LED, covert information identification and night vision lighting have been realized, demonstrating a very bright prospect for practical applications.

High Spatial and Temporal Resolution NIR-IIb Gastrointestinal Imaging in Mice

Conventional biomedical imaging modalities, including endoscopy, X-rays, and magnetic resonance, are invasive and insufficient in spatial and temporal resolutions for gastrointestinal (GI) tract imaging to guide prognosis and therapy. Here we report a noninvasive method based on lanthanide-doped nanocrystals with ∼1530 nm fluorescence in the near-infrared-IIb window (NIR-IIb, 1500-1700 nm). The rational design of nanocrystals have led to an absolute quantum yield (QY) up to 48.6%. Further benefiting from the minimized scattering through the NIR-IIb window, we enhanced the spatial resolution to ∼1 mm in GI tract imaging, which is ∼3 times higher compared with the near-infrared-IIa (NIR-IIa, 1000-1500 nm) method. The approach also realized a high temporal resolution of 8 frames per second; thus the moment of mice intestinal peristalsis can be captured. Furthermore, with a light-sheet imaging system, we demonstrated a three-dimensional (3D) imaging on the GI tract. Moreover, we successfully translated these advances to diagnose inflammatory bowel disease.

Color Dependence Analysis in a CNN-Based Computer-Aided Diagnosis System for Middle and External Ear Diseases

Artificial intelligence-assisted otologic diagnosis has been of growing interest in the scientific community, where middle and external ear disorders are the most frequent diseases in daily ENT practice. There are some efforts focused on reducing medical errors and enhancing physician capabilities using conventional artificial vision systems. However, approaches with multispectral analysis have not yet been addressed. Tissues of the tympanic membrane possess optical properties that define their characteristics in specific light spectra. This work explores color wavelengths dependence in a model that classifies four middle and external ear conditions: normal, chronic otitis media, otitis media with effusion, and earwax plug. The model is constructed under a computer-aided diagnosis system that uses a convolutional neural network architecture. We trained several models using different single-channel images by taking each color wavelength separately. The results showed that a single green channel model achieves the best overall performance in terms of accuracy (92%), sensitivity (85%), specificity (95%), precision (86%), and F1-score (85%). Our findings can be a suitable alternative for artificial intelligence diagnosis systems compared to the 50% of overall misdiagnosis of a non-specialist physician.

SIMPA: an open-source toolkit for simulation and image processing for photonics and acoustics

SIGNIFICANCE

Optical and acoustic imaging techniques enable noninvasive visualisation of structural and functional properties of tissue. The quantification of measurements, however, remains challenging due to the inverse problems that must be solved. Emerging data-driven approaches are promising, but they rely heavily on the presence of high-quality simulations across a range of wavelengths due to the lack of ground truth knowledge of tissue acoustical and optical properties in realistic settings.

AIM

To facilitate this process, we present the open-source simulation and image processing for photonics and acoustics (SIMPA) Python toolkit. SIMPA is being developed according to modern software design standards.

APPROACH

SIMPA enables the use of computational forward models, data processing algorithms, and digital device twins to simulate realistic images within a single pipeline. SIMPA's module implementations can be seamlessly exchanged as SIMPA abstracts from the concrete implementation of each forward model and builds the simulation pipeline in a modular fashion. Furthermore, SIMPA provides comprehensive libraries of biological structures, such as vessels, as well as optical and acoustic properties and other functionalities for the generation of realistic tissue models.

RESULTS

To showcase the capabilities of SIMPA, we show examples in the context of photoacoustic imaging: the diversity of creatable tissue models, the customisability of a simulation pipeline, and the degree of realism of the simulations.

CONCLUSIONS

SIMPA is an open-source toolkit that can be used to simulate optical and acoustic imaging modalities. The code is available at: https://github.com/IMSY-DKFZ/simpa, and all of the examples and experiments in this paper can be reproduced using the code available at: https://github.com/IMSY-DKFZ/simpa_paper_experiments.

Near-infrared excitation/emission microscopy with lanthanide-based nanoparticles

Near-infrared optical imaging offers some advantages over conventional imaging, such as deeper tissue penetration, low or no autofluorescence, and reduced tissue scattering. Lanthanide-doped nanoparticles (LnNPs) have become a trend in the field of photoactive nanomaterials for optical imaging due to their unique optical features and because they can use NIR light as excitation and/or emission light. This review is focused on NaREF₄ NPs and offers an overview of the state-of-the-art investigation in their use as luminophores in optical microscopy, time-resolved imaging, and super-resolution nanoscopy based on, or applied to, LnNPs. Secondly, whenever LnNPs are combined with other nanomaterial or nanoparticle to afford nanohybrids, the characterization of their physical and chemical properties is of current interest. In this context, the latest trends in optical microscopy and their future perspectives are discussed.

Sensor-based phenotyping of above-ground plant-pathogen interactions

Plant pathogens cause yield losses in crops worldwide. Breeding for improved disease resistance and management by precision agriculture are two approaches to limit such yield losses. Both rely on detecting and quantifying signs and symptoms of plant disease. To achieve this, the field of plant phenotyping makes use of non-invasive sensor technology. Compared to invasive methods, this can offer improved throughput and allow for repeated measurements on living plants. Abiotic stress responses and yield components have been successfully measured with phenotyping technologies, whereas phenotyping methods for biotic stresses are less developed, despite the relevance of plant disease in crop production. The interactions between plants and pathogens can lead to a variety of signs (when the pathogen itself can be detected) and diverse symptoms (detectable responses of the plant). Here, we review the strengths and weaknesses of a broad range of sensor technologies that are being used for sensing of signs and symptoms on plant shoots, including monochrome, RGB, hyperspectral, fluorescence, chlorophyll fluorescence and thermal sensors, as well as Raman spectroscopy, X-ray computed tomography, and optical coherence tomography. We argue that choosing and combining appropriate sensors for each plant-pathosystem and measuring with sufficient spatial resolution can enable specific and accurate measurements of above-ground signs and symptoms of plant disease.

Targeted multicolor in vivo imaging over 1,000 nm enabled by nonamethine cyanines

Recent progress has shown that using wavelengths between 1,000 and 2,000 nm, referred to as the shortwave-infrared or near-infrared (NIR)-II range, can enable high-resolution in vivo imaging at depths not possible with conventional optical wavelengths. However, few bioconjugatable probes of the type that have proven invaluable for multiplexed imaging in the visible and NIR range are available for imaging these wavelengths. Using rational design, we have generated persulfonated indocyanine dyes with absorbance maxima at 872 and 1,072 nm through catechol-ring and aryl-ring fusion, respectively, onto the nonamethine scaffold. Multiplexed two-color and three-color in vivo imaging using monoclonal antibody and dextran conjugates in several tumor models illustrate the benefits of concurrent labeling of the tumor and healthy surrounding tissue and lymphatics. These efforts are enabled by complementary advances in a custom-built NIR/shortwave-infrared imaging setup and software package for multicolor real-time imaging.

Assessment of diabetic small-fiber neuropathy by using short-wave infrared hyperspectral imaging

Among patients with type 2 diabetes mellitus (T2DM), the association between hyperspectral imaging (HSI) examination and diabetic neuropathy (DN) is ascertained using HSI of the feet using four types of spectral difference measurements. DN was evaluated by traditional Michigan Neuropathy Screening Instrument (MNSI), evaluation of painful neuropathy (ID-Pain, DN4) and sudomotor function by measuring electrochemical skin conductance (ESC). Of the 120 T2DM patients and 20 healthy adults enrolled, T2DM patients are categorized into normal sudomotor (ESC >60 μS) and sudomotor dysfunction (ESC ≤ 60 μS) groups. Spectral difference analyses reveal significant intergroup differences, whereas traditional examinations cannot distinguish between the two groups. HSI waveform reflectance gradually increases with disease severity, at 1400 to 1600 nm. The area under the curve (AUC) of receiver operating characteristic (ROC) analysis for abnormal ESC is ≥0.8 for all four HSI methods. HSI could be an objective, sensitive, rapid, noninvasive and remote approach to identify early small-fiber DN.

Ni2+-Doped Garnet Solid-Solution Phosphor-Converted Broadband Shortwave Infrared Light-Emitting Diodes toward Spectroscopy Application

Broadband shortwave infrared (SWIR) light-emitting diodes (LEDs), capable of advancing the next-generation solid-state smart invisible lighting technology, have sparked tremendous interest and will launch ground-breaking spectroscopy and instrumental applications. Nevertheless, the device performance is still suppressed by the low quantum efficiency and limited emission bandwidth of the critical phosphor layer. Herein, we report a high-performance Ni²⁺-doped garnet solid-solution broadband SWIR emitter centered at ∼1450 nm with a large full-width at half-maximum of ∼300 nm, thereby fabricating, for the first time, a directly excited Ni²⁺-doped garnet solid-solution phosphor-converted broadband SWIR LED device. A synergetic enhancement strategy, adding a fluxing agent and a charge compensator simultaneously, is proposed to deliver a more than 20-fold increase of the SWIR emission intensity and nearly 2-fold improvement of the thermal quenching behavior. The site occupation and mechanism behind the synergetic enhancement strategy are elucidated by a combination of experimental study and theoretical calculation. A prototype of the SWIR LED with a radiation flux of 1.25 mW is fabricated and utilized as an invisible SWIR light source to demonstrate the SWIR spectroscopy applications. This work not only opens a window to explore novel broadband SWIR phosphors but also provides a synergetic strategy to remarkably improve the performance of artificial SWIR LED light sources.

Aquaphotomics Research of Cold Stress in Soybean Cultivars with Different Stress Tolerance Ability: Early Detection of Cold Stress Response

The development of non-destructive methods for early detection of cold stress of plants and the identification of cold-tolerant cultivars is highly needed in crop breeding programs. Current methods are either destructive, time-consuming or imprecise. In this study, soybean leaves' spectra were acquired in the near infrared (NIR) range (588-1025 nm) from five cultivars genetically engineered to have different levels of cold stress tolerance. The spectra were acquired at the optimal growing temperature 27 °C and when the temperature was decreased to 22 °C. In this paper, we report the results of the aquaphotomics analysis performed with the objective of understanding the role of the water molecular system in the early cold stress response of all cultivars. The raw spectra and the results of Principal Component Analysis, Soft Independent Modeling of Class Analogies and aquagrams showed consistent evidence of huge differences in the NIR spectral profiles of all cultivars under normal and mild cold stress conditions. The SIMCA discrimination between the plants before and after stress was achieved with 100% accuracy. The interpretation of spectral patterns before and after cold stress revealed major changes in the water molecular structure of the soybean leaves, altered carbohydrate and oxidative metabolism. Specific water molecular structures in the leaves of soybean cultivars were found to be highly sensitive to the temperature, showing their crucial role in the cold stress response. The results also indicated the existence of differences in the cold stress response of different cultivars, which will be a topic of further research.

A preliminary study on the utilisation of near infrared spectroscopy to predict age and in vivo human metabolism

The objective of this study was to evaluate the ability of a portable near infrared (NIR) instrument to analyse different tissues in healthy individuals in vivo and relate the spectral data with age, resting metabolic rate (RMR), respiratory quotient (RQ), body fat (BF) and body mass index (BMI). A NIR (950-1600 nm) instrument was used to collect the spectra of different tissues and partial least squares (PLS) regression was used to relate the NIR with RMR, RQ, BF and BMI. Results shown that non-destructive techniques such as those based in vibrational spectroscopy have potential to be used as tools to better categorise and understand the complex inter-individual differences that determine interactions between physiology and nutrition.

Vibrational two-photon microscopy for tissue imaging: Short-wave infrared surface-enhanced resonance hyper-Raman scattering

Multiphoton microscopy using short-wave infrared (SWIR) radiation offers nondestructive and high-resolution imaging through tissue. Two-photon fluorescence (TPF), for example, is commonly employed to increase the penetration depth and spatial resolution of SWIR imaging, but the broad spectral peaks limit its multiplexing capabilities. Hyper-Raman scattering, the vibrational analog of TPF, yields spectral features on the order of 20 cm^-1 and reporter-functionalized noble metal nanoparticles (NPs) provide a platform for both hyper-Raman signal enhancement and selective targeting in biological media. Herein we report the first tissue imaging study employing surface-enhanced resonance hyper-Raman scattering (SERHRS), the two-photon analog of surface-enhanced resonance Raman scattering. Specifically, we employ multicore gold-silica NPs (Au@SiO₂ NPs) functionalized with a near infrared-resonant cyanine dye, 3,3'-diethylthiatricarbocyanine iodide as a SERHRS reporter. SWIR SERHRS spectra are efficiently acquired from mouse spleen tissue. SWIR SERHRS combines two-photon imaging advantages with narrow vibrational peak widths, presenting future applications of multitargeted bioimaging.

Smart Blood Vessel Detection System for Laparoscopic Surgery

Objective: Compared with traditional surgery, laparoscopic surgery offers the advantages of smaller scars and rapid recovery and has gradually become popular. However, laparoscopic surgery has the limitation of low visibility and a lack of touch sense. As such, a physician may unexpectedly damage blood vessels, causing massive bleeding. In clinical settings, Doppler ultrasound is commonly used to detect vascular locations, but this approach is affected by the measuring angle and bone shadow and has poor ability to distinguish arteries from veins. To tackle these problems, a smart blood vessel detection system for laparoscopic surgery is proposed. Methods: Based on the principle of near-infrared spectroscopy, the proposed instrument can access hemoglobin (HbT) parameters at several depths simultaneously and recognize human tissue type by using a neural network. Results: Using the differences in HbT and StO₂ between different tissues, vascular and avascular locations can be recognized. Moreover, a mechanically rotatable stick enables the physician to easily operate in body cavities. Phantom and animal experiments were performed to validate the system’s performance. Conclusion: The proposed system has high ability to distinguish vascular from avascular locations at various depths.

Dual near infrared emission in Ag2Se quantum dots via Pb doping for broadband mini light-emitting diodes

Dual emission almost covering the entire NIR-II region with the maximum full width at half maximum of 542 nm was achieved by doping small amounts of Pb ions into Ag2Se...

Synthesis and characterization of a uranium oxide hydrate framework with Sr(ii) ions: structural insights and mixed uranium valences

A uranium oxide hydrate framework with Sr(ii) ions was synthesized hydrothermally and characterized.

Monte Carlo Characterization of Short-Wave Infrared Optical Wavelengths for Biosensing Applications

Short-wave infrared (SWIR) spectroscopy has shown great promise in probing the composition of biological tissues. Currently there exists an enormous drive amongst researchers to design and develop SWIR-based optical sensors that can predict the concentration of various biomarkers non-invasively. However, there is limited knowledge regarding the interaction of SWIR light with vascular tissue, especially in terms of parameters like the optimal source-detector separation, light penetration depth, optical pathlength, etc., all of which are essential components in designing optical sensors. With the aim to determine these parameters, Monte Carlo simulations were carried out to examine the interaction of SWIR light with vascular skin. SWIR photons were found to penetrated only 1.3 mm into the hypodermal fat layer. The highest optical pathlength and penetration depths were seen at 1mm source-detector separation, and the lowest being 0.7mm. Although the optical pathlength varied significantly with increasing source-detector separation at SWIR wavelengths, penetration depth remained constant. This may explain why collecting optical spectra from depth of tissue at SWIR wavelengths is more challenging than collecting optical spectra from near-infrared wavelengths, where both the optical pathlength and penetration depth change rapidly with source-detector separation.

Changing the firing threshold for normal optic nerve axons by the application of infra-red laser light

Normal optic nerve axons exhibit a temperature dependence, previously explained by a membrane potential hyperpolarization on warming. We now report that near infra-red laser light, delivered via a fibre optic light guide, also affects axonal membrane potential and threshold, at least partly through a photo-thermal effect. Application of light to optic nerve, at the recording site, gave rise to a local membrane potential hyperpolarization over a period of about a minute, and increased the size of the depolarizing after potential. Application near the site of electrical stimulation reversibly raised current-threshold, and the change in threshold recorded over minutes of irradiation was significantly increased by the application of the Ih blocker, ZD7288 (50 µM), indicating Ih limits the hyperpolarizing effect of light. Light application also had fast effects on nerve behaviour, increasing threshold without appreciable delay (within seconds), probably by a mechanism independent of kinetically fast K+ channels and Na+ channel inactivation, and hypothesized to be caused by reversible changes in myelin function.

Proposal for a Skin Layer-Wise Decomposition Model of Spatially-Resolved Diffuse Reflectance Spectra Based on Maximum Depth Photon Distributions: A Numerical Study

In the context of cutaneous carcinoma diagnosis based on in vivo optical biopsy, Diffuse Reflectance (DR) spectra, acquired using a Spatially Resolved (SR) sensor configuration, can be analyzed to distinguish healthy from pathological tissues. The present contribution aims at studying the depth distribution of SR-DR-detected photons in skin from the perspective of analyzing how these photons contribute to acquired spectra carrying local physiological and morphological information. Simulations based on modified Cuda Monte Carlo Modeling of Light transport were performed on a five-layer human skin optical model with epidermal thickness, phototype and dermal blood content as variable parameters using (i) wavelength-resolved scattering and absorption properties and (ii) the geometrical configuration of a multi-optical fiber probe implemented on an SR-DR spectroscopic device currently used in clinics. Through histograms of the maximum probed depth and their exploitation, we provide numerical evidence linking the characteristic penetration depth of the detected photons to their wavelengths and four source–sensor distances, which made it possible to propose a decomposition of the DR signals related to skin layer contributions.

Signal properties of split-spectrum amplitude decorrelation angiography for quantitative optical coherence tomography-based velocimetry

Split-spectrum amplitude-decorrelation angiography (SSADA) is a noninvasive and three-dimensional angiographic technique with a microscale spatial resolution based on optical coherence tomography. The SSADA signal is known to be correlated with the blood flow velocity and the quantitative velocimetry with SSADA has been expected; however, the signal properties of SSADA are not completely understood due to lack of comprehensive investigations of parameters related to SSADA signals. In this study, phantom experiments were performed to comprehensively investigate the relation of SSADA signals with flow velocities, time separations, particle concentrations, signal-to-noise ratios, beam spot sizes, and viscosities, and revealed that SSADA signals reflect the spatial commonality within a coherence volume between adjacent A-scans.

Objective determination of peripheral edema in heart failure patients using short-wave infrared molecular chemical imaging

SIGNIFICANCE

Peripheral pitting edema is a clinician-administered measure for grading edema. Peripheral edema is graded 0, 1  +  , 2  +  , 3  +  , or 4  +  , but subjectivity is a major limitation of this technique. A pilot clinical study for short-wave infrared (SWIR) molecular chemical imaging (MCI) effectiveness as an objective, non-contact quantitative peripheral edema measure is underway.

AIM

We explore if SWIR MCI can differentiate populations with and without peripheral edema. Further, we evaluate the technology for correctly stratifying subjects with peripheral edema.

APPROACH

SWIR MCI of shins from healthy subjects and heart failure (HF) patients was performed. Partial least squares discriminant analysis (PLS-DA) was used to discriminate the two populations. PLS regression (PLSR) was applied to assess the ability of MCI to grade edema.

RESULTS

Average spectra from edema exhibited higher water absorption than non-edema spectra. SWIR MCI differentiated healthy volunteers from a population representing all pitting edema grades with 97.1% accuracy (N  =  103 shins). Additionally, SWIR MCI correctly classified shin pitting edema levels in patients with 81.6% accuracy.

CONCLUSIONS

Our study successfully achieved the two primary endpoints. Application of SWIR MCI to monitor patients while actively receiving HF treatment is necessary to validate SWIR MCI as an HF monitoring technology.

Broad Chiroptical Activity from Ultraviolet to Short-Wave Infrared by Chirality Transfer from Molecular to Micrometer Scale

Chiral nanomaterials provide a rich platform for versatile applications. Tuning the wavelength of polarization rotation maxima in the broad range including short-wave infrared (SWIR) is a promising candidate for infrared neural stimulation, imaging, and nanothermometry. However, the majority of previously developed chiral nanomaterials reveal the optical activity in a relatively shorter wavelength range (ultraviolet-visible, UV-vis), not in SWIR. Here, we demonstrate a versatile method to synthesize chiral copper sulfides using cysteine, as the stabilizer, and transferring the chirality from molecular- to the microscale through self-assembly. The assembled structures show broad chiroptical activity in the UV-vis-NIR-SWIR region (200-2500 nm). Importantly, we can tune the chiroptical activity by simply changing the reaction conditions. This approach can be extended to materials platforms for developing next-generation optical devices, metamaterials, telecommunications, and asymmetric catalysts.

MoS2/Graphene Photodetector Array with Strain-Modulated Photoresponse up to the Near-Infrared Regime

MoS₂, an emerging material in the field of optoelectronics, has attracted the attention of researchers owing to its high light absorption efficiency, even as an atomically thin layer. However, the covered spectra of the reported MoS₂-based photodetectors are restricted to the visible range owing to their electronic bandgap (∼1.9 eV). Strain engineering, which modulates the bandgap of a semiconductor, can extend the application coverage of MoS₂ to the infrared spectral range. The shrinkage of the bandgap because of the tensile strain on MoS₂ enhances the photoresponsivity in the visible range and extends its sensing capability beyond its fundamental absorption limit. Herein, we report a graphene/MoS₂/graphene metal-semiconductor-metal photodetector (PD) array with a strain-modulated photoresponse up to the spectral range of the near-infrared (NIR). The MoS₂ PD array on a flexible substrate was stretched in the biaxial direction to a tensile strain level of 1.19% using a pneumatic bulging process. The MoS₂-based line-scanning system was implemented by digitizing the output photocurrent of the strained MoS₂ linear array with a low-noise complementary metal-oxide-semiconductor (CMOS) readout integrated circuit (IC) and successfully captured vis-NIR images in foggy conditions. Therefore, we extended the application of the MoS₂ PD array to the NIR regime and demonstrated its use in real-life imaging systems.

Designing Donor-Acceptor Copolymers for Stable and High-Performance Organic Electrochemical Transistors

Organic electrochemical transistors (OECTs) are oft-used for bioelectronic applications, and a variety of OECT channel materials have been developed in recent years. However, the majority of these materials are still limited by long-term performance and stability challenges. To resolve these issues, we implemented a next-generation design of polymers for OECTs. Specifically, diketopyrrolopyrrole (DPP) building blocks were copolymerized with propylene dioxythiophene-based (Pro-based) monomers to create a donor-acceptor-type conjugated polymer (PProDOT-DPP). These PProDOT-DPP macromolecules were synthesized using a straightforward direct arylation polymerization synthetic route. The PProDOT-DPP polymer thin film exhibited excellent electrochemical response, low oxidation potential, and high crystallinity, as evidenced by spectroelectrochemical measurements and grazing incidence wide-angle X-ray scattering measurements. Thus, the resultant polymer thin films had high charge mobility and volumetric capacitance values (i.e., μC* as high as 310 F cm^-1 V^-1 s^-1) when they were used as the active layer materials in OECT devices, which places PProDOT-DPP among the highest performing accumulation-mode OECT polymers reported to date. The performance of the PProDOT-DPP thin films was also retained for 100 cycles and over 2000 s of ON-OFF cycling, indicating the robust stability of the materials. Therefore, this effort provides a clear roadmap for the design of electrochemically active macromolecules for accumulation-mode OECTs, where crystalline acceptor cores are incorporated into an all-donor polymer. We anticipate that this will ultimately inspire future polymer designs to enable OECTs with both high electrical performance and operational stability.

Near-Infrared Optical Spectroscopy In Vivo Distinguishes Subjects with Alzheimer's Disease from Age-Matched Controls

Background:

Medical imaging methods such as PET and MRI aid clinical assessment of Alzheimer’s disease (AD). Less expensive, less technically demanding, and more widely deployable technologies are needed to expand objective screening for diagnosis, treatment, and research. We previously reported brain tissue near-infrared optical spectroscopy (NIR) in vitro indicating the potential to meet this need.

Objective:

To determine whether completely non-invasive, clinical, NIR in vivo can distinguish AD patients from age-matched controls and to show the potential of NIR as a clinical screen and monitor of therapeutic efficacy.

Methods:

NIR spectra were acquired in vivo. Three groups were studied: autopsy-confirmed AD, control and mild cognitive impairment (MCI). A feature selection approach using the first derivative of the intensity normalized spectra was used to discover spectral regions that best distinguished “AD-alone” (i.e., without other significant neuropathology) from controls. The approach was then applied to other autopsy-confirmed AD cases and to clinically diagnosed MCI cases.

Results:

Two regions about 860 and 895 nm completely separate AD patients from controls and differentiate MCI subjects according to the degree of impairment. The 895 nm feature is more important in separating MCI subjects from controls (ratio-of-weights: 1.3); the 860 nm feature is more important for distinguishing MCI from AD (ratio-of-weights: 8.2).

Conclusion:

These results form a proof of the concept that near-infrared spectroscopy can detect and classify diseased and normal human brain in vivo. A clinical trial is needed to determine whether the two features can track disease progression and monitor potential therapeutic interventions.

In-silico investigation towards the non-invasive optical detection of blood lactate

This paper uses Monte Carlo simulations to investigate the interaction of short-wave infrared (SWIR) light with vascular tissue as a step toward the development of a non-invasive optical sensor for measuring blood lactate in humans. The primary focus of this work was to determine the optimal source-detector separation, penetration depth of light at SWIR wavelengths in tissue, and the optimal light power required for reliable detection of lactate. The investigation also focused on determining the non-linear variations in absorbance of lactate at a few select SWIR wavelengths. SWIR photons only penetrated 1.3 mm and did not travel beyond the hypodermal fat layer. The maximum output power was only 2.51% of the input power, demonstrating the need for a highly sensitive detection system. Simulations optimized a source-detector separation of 1 mm at 1684 nm for accurate measurement of lactate in blood.

Shortwave infrared-absorbing squaraine dyes for all-organic optical upconversion devices

Shortwave infrared (SWIR) optical sensing and imaging are essential to an increasing number of next-generation applications in communications, process control or medical imaging. An all-organic SWIR upconversion device (OUC) consists of an organic SWIR sensitive photodetector (PD) and an organic light-emitting diode (OLED), connected in series. OUCs directly convert SWIR to visible photons, which potentially provides a low-cost alternative to the current inorganic compound-based SWIR imaging technology. For OUC applications, only few organic materials have been reported with peak absorption past 1000 nm and simultaneous small absorption in the visible. Here, we synthesized a series of thermally stable high-extinction coefficient donor-substituted benz[cd]indole-capped SWIR squaraine dyes. First, we coupled the phenyl-, carbazole-, and thienyl-substituted benz[cd]indoles with squaric acid (to obtain the SQ dye family). We then combined these donors with the dicyanomethylene-substituted squaraine acceptor unit, to obtain the dicyanomethylene-functionalized squaraine DCSQ family. In the solid state, the absorbance of all dyes extended considerably beyond 1100 nm. For the carbazole- and thienyl-substituted DCSQ dyes, even the peak absorptions in solution were in the SWIR, at 1008 nm and 1014 nm. We fabricated DCSQ PDs with an external photon-to-current efficiency over 30%. We then combined the PD with a fluorescent OLED and fabricated long-term stable OUCs with peak sensitivity at 1020 nm, extending to beyond 1200 nm. Our OUCs are characterized by a very low dark luminance (<10^-2 cd m^-2 at below 6 V) in the absence of SWIR light, and a low turn-on voltage of 2 V when SWIR light is present.

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.

Single probe diffuse reflectance spectroscopy to assess the effect of sarcopoterium spinosum treatment on the cerebral tissue properties of ApoE knockout mouse

In this work, diffuse near-infrared light reflectance spectroscopy based on a single optical probe, contains central single collection fiber surrounded by a circular array of illumination fibers, was used to quantify cerebral tissue properties in ApoE knockout mice following Sarcopoterium spinosum treatment. Sarcopoterium spinosum, also known as Thorny burnet, is a Mediterranean plant widely used as a traditional therapy for the treatment of a variety of pathologies, primarily type 2 diabetes mellitus (T2D). While it's efficacy in the treatment of T2D, and of other components of metabolic syndrome, have already been validated by us, the aim of this study was to investigate the effects of Sarcopoterium spinosum extract (SSE) on dyslipidemia and vascular functions. We utilized ApoE deficient mice (ApoE^-/- , Atherosclerosis-prone apolipoprotein E-deficient), who have a severe impairment in plasma lipoprotein clearance and thus develop alterations in blood lipid profile and are highly susceptible to atherogenic plaque formation. A total of 34 male mice were divided into five groups representing various genetic, dietary, and treatment configurations. Optical measurements were used to assess changes in diffused reflectance spectra, optical properties (absorption and scattering), and cerebral tissue chromophore contents. Specifically, significant improvement in cerebral hemoglobin level was observed in ApoE KO mice, fed an artherogenic diet (ATD), upon SSE treatment. Biochemical and histological analyses of ApoE^-/- ATD mice showed elevated body weight and a high level of blood triglycerides, free fatty acids and cholesterol. In contrast, in SSE treated mice improvement was observed, suggesting beneficial effects of SSE. In ApoE^-/- ATD mice group a higher levels of deoxyhemoglobin was monitored indicating that the rate of oxygen release to the tissue is low. This was supported by decrease in oxygen saturation. It was also shown a reduction in water content in the brain of ApoE KO. Mice fed with the atherogenic diet demonstrated increased water content as compared to STD-fed ApoE KO mice, while SSE administration reversed the effect of the diet. To our knowledge, no such study has been reported before.

Visualization of quantitative lipid distribution in mouse liver through near-infrared hyperspectral imaging

Lipid distribution in the liver provides crucial information for diagnosing the severity of fatty liver and fatty liver-associated liver cancer. Therefore, a noninvasive, label-free, and quantitative modality is eagerly anticipated. We report near-infrared hyperspectral imaging for the quantitative visualization of lipid content in mouse liver based on partial least square regression (PLSR) and support vector regression (SVR). Analysis results indicate that SVR with standard normal variate pretreatment outperforms PLSR by achieving better root mean square error (15.3 mg/g) and higher determination coefficient (0.97). The quantitative mapping of lipid content in the mouse liver is realized using SVR.

Developing a New Method to Identify Flowering Dynamics of Rapeseed Using Landsat 8 and Sentinel-1/2

Identifying the rapeseed (Brassica napus L.) flowering dates are important for planting area estimation, growth monitoring, and yield estimation. However, there is currently a lack of data on rapeseed flowering dates at the parcel scale. In this study, a new spectral index (Normalized Rapeseed Flowering Index, NRFI) is proposed to detect rapeseed flowering dates from time series data generated from Landsat 8 OLI and Sentinel-2 sensors. This study also analyzed the feasibility of using the backscattering coefficients (VV, VH, and VV/VH) of Sentinel-1 to detect the flowering dates of rapeseed at the parcel scale. Based on the spectral and polarization characteristics of 718 rapeseed parcels collected in 2018, we developed a method to automatically identify peak flowering dates by the local maximum of NRFI series and the local minimum of VH and VV, along with the maximum of VV/VH. The results show that most of the peak flowering dates derived from Sentinel-1 and Sentinel-2 can be confirmed by the in-situ phenological observations at the Deutscher Wetterdienst (DWD) stations in Germany. The NRFI outperforms the Normalized Difference Yellow Index (NDYI) in identifying the peak flowering dates from Landsat 8. The derived medians of peak flowering dates by NRFI, NDYI (Sentinel-2), and VH are similar, while a systematic delay is observed by NDYI (Landsat 8). The method with the spectrum and backscattering coefficients will be a potential tool to identify crop flowering dynamics and map crop planting area.

Real-Time Monitoring of Yogurt Fermentation Process by Aquaphotomics Near-Infrared Spectroscopy

Automated quality control could have a substantial economic impact on the dairy industry. At present, monitoring of yogurt production is performed by sampling for microbiological and physicochemical measurements. In this study, Near-Infrared Spectroscopy (NIRS) is proposed for non-invasive automated control of yogurt production and better understanding of lactic acid bacteria (LAB) fermentation. UHT (ultra-high temperature) sterilized milk was inoculated with Bulgarian yogurt and placed into a quartz cuvette (1 mm pathlength) and test-tubes. Yogurt absorbance spectra (830-2500 nm) were acquired every 15 min, and pH, in the respective test-tubes, was measured every 30 min, during 8 h of fermentation. Spectral data showed substantial baseline and slope changes with acidification. These variations corresponded to respective features of the microbiological growth curve showing water structural changes, protein denaturation, and coagulation of milk. Moving Window Principal Component Analysis (MWPCA) was applied in the spectral range of 954-1880 nm to detect absorbance bands where most variations in the loading curves were caused by LAB fermentation. Characteristic wavelength regions related to the observed physical and multiple chemical changes were identified. The results proved that NIRS is a valuable tool for real-time monitoring and better understanding of the yogurt fermentation process.

Optical Absorption and Scattering Properties at 900-1650 nm and Their Relationships with Soluble Solid Content and Soluble Sugars in Apple Flesh during Storage

Soluble solid content (SSC) is regarded as the most significant internal quality associated with the taste and maturity in fruits. Evaluating the relationship between the optical properties and soluble sugars facilitates exploration of the mechanism of optical techniques in SSC assessment. In this research, absorption coefficient (μ_a) and reduced scattering coefficient (μ′_s) of Fuji apple during storage were obtained using automatic integrating sphere (AIS) at 905–1650 nm. Relationships between μ_a, μ′_s and SSC, and soluble sugars contents, were investigated. The result showed that SSC, the content of total soluble sugars (TSS), fructose, glucose and sucrose were all decreasing after storage, and the same trend appeared in the change of μ_a and μ′_s. In the whole wavelength range, both μ_a and μ′_s were positively related to SSC and soluble sugars contents. The correlations between μ_a and SSC, and soluble sugars contents, showed increasing tendencies with increasing wavelengths, while for μ′_s, correlations had the opposite trend. The strongest correlations between μ_a and SSC, and soluble sugars contents, were observed in the correlation of μ_a with sucrose, with an r of 0.934. Furthermore, a partial least square (PLS) model for sucrose based on μ_a was built with the coefficient of determination of prediction (R_p²) and the root mean square error of prediction (RMSEP) of 0.851 and 1.047, respectively. The overall results demonstrate that optical properties at the range of 905–1650 nm could be used to evaluate SSC of apples and this may due to the strong correlation between sucrose content and μ_a.

Millimeter-Deep Detection of Single Shortwave-Infrared-Emitting Polymer Dots through Turbid Media

Fluorescence imaging at longer wavelengths, especially in the shortwave-infrared (SWIR: 1000-1700 nm) region, leads to a substantial decrease in light attenuation, scattering, and background autofluorescence, thereby enabling enhanced penetration into biological tissues. The limited selection of fluorescent probes is a major bottleneck in SWIR fluorescence imaging. Here, we develop SWIR-emitting nanoparticles composed of donor-acceptor-type conjugated polymers. The bright SWIR fluorescence of the polymer dots (primarily attributable to their large absorption cross-section and high fluorescence saturation intensity (as high as 113 kW·cm^-2)) enables the unprecedented detection of single particles as small as 14 nm through millimeter-thick turbid media. Unlike most SWIR-emitting nanomaterials, which have an excited-state lifetime in the range of microseconds to milliseconds, our polymer dots exhibit a subnanosecond excited-state lifetime. These characteristics enable us to demonstrate new time-gated single-particle imaging with a high signal-to-background ratio. These findings expand the range of potential applications of single-particle deep-tissue imaging.

Nanoparticle-Based Sustainable Agriculture and Food Science: Recent Advances and Future Outlook

In the current scenario, it is an urgent requirement to satisfy the nutritional demands of the rapidly growing global population. Using conventional farming, nearly one third of crops get damaged, mainly due to pest infestation, microbial attacks, natural disasters, poor soil quality, and lesser nutrient availability. More innovative technologies are immediately required to overcome these issues. In this regard, nanotechnology has contributed to the agrotechnological revolution that has imminent potential to reform the resilient agricultural system while promising food security. Therefore, nanoparticles are becoming a new-age material to transform modern agricultural practices. The variety of nanoparticle-based formulations, including nano-sized pesticides, herbicides, fungicides, fertilizers, and sensors, have been widely investigated for plant health management and soil improvement. In-depth understanding of plant and nanomaterial interactions opens new avenues toward improving crop practices through increased properties such as disease resistance, crop yield, and nutrient utilization. In this review, we highlight the critical points to address current nanotechnology-based agricultural research that could benefit productivity and food security in future.

Monte Carlo Modeling of Shortwave-Infrared Fluorescence Photon Migration in Voxelized Media for the Detection of Breast Cancer

Recent progress regarding shortwave-infrared (SWIR) molecular imaging technology has inspired another modality of noninvasive diagnosis for early breast cancer detection in which previous mammography or sonography would be compensated. Although a SWIR fluorescence image of a small breast cancer of several millimeters was obtained from experiments with small animals, detailed numerical analyses before clinical application were required, since various parameters such as size as well as body hair differed between humans and small experimental animals. In this study, the feasibility of SWIR was compared against visible (VIS) and near-infrared (NIR) region, using the Monte Carlo simulation in voxelized media. In this model, due to the implementation of the excitation gradient, fluorescence is based on rational mechanisms, whereas fluorescence within breast cancer is spatially proportional to excitation intensity. The fluence map of SWIR simulation with excitation gradient indicated signals near the upper surface of the cancer, and stronger than those of the NIR. Furthermore, there was a dependency on the fluence signal distribution on the contour of the breast tissue, as well as the internal structure, due to the implementation of digital anatomical data for the Visible Human Project. The fluorescence signal was observed to become weaker in all regions including the VIS, the NIR, and the SWIR region, when fluorescence-labeled cancer either became smaller or was embedded in a deeper area. However, fluorescence in SWIR alone from a cancer of 4 mm diameter was judged to be detectable at a depth of 1.4 cm.