Tumor Abnormality-Oriented Nanomedicine Design.

Anticancer nanomedicines have been proven effective in mitigating the side effects of chemotherapeutic drugs. However, challenges remain in augmenting their therapeutic efficacy. Nanomedicines responsive to the pathological abnormalities in the tumor microenvironment (TME) are expected to overcome the biological limitations of conventional nanomedicines, enhance the therapeutic efficacies, and further reduce the side effects. This Review aims to quantitate the various pathological abnormalities in the TME, which may serve as unique endogenous stimuli for the design of stimuli-responsive nanomedicines, and to provide a broad and objective perspective on the current understanding of stimuli-responsive nanomedicines for cancer treatment. We dissect the typical transport process and barriers of cancer drug delivery, highlight the key design principles of stimuli-responsive nanomedicines designed to tackle the series of barriers in the typical drug delivery process, and discuss the "all-into-one" and "one-for-all" strategies for integrating the needed properties for nanomedicines. Ultimately, we provide insight into the challenges and future perspectives toward the clinical translation of stimuli-responsive nanomedicines.

Polylevodopa nanoplatform for lateral flow immunochromatography assay of SARS-CoV-2 and influenza A virus.

At the end of 2019, an unprecedented outbreak of novel coronavirus pneumonia ravaged the global landscape, inflicting profound harm upon society. Following numerous cycles of transmission, we find ourselves in an epoch where the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coexists alongside influenza viruses (Flu A). Swift and accurate diagnosis of SARS-CoV-2 and Flu A is imperative to stem the spread of these maladies and administer appropriate treatment. Presently, colloidal gold-based lateral flow immunoassays (Au-LFIAs) constructed through electrostatic adsorption are beset by challenges such as diminished sensitivity and feeble binding stability. In this context, we propose the adoption of black polylevodopa nanoparticles (PLDA NPs) featuring abundant carboxyl groups as labeling nanomaterials in LFIA to bolster the stability and sensitivity of SARS-CoV-2 antigens and influenza A virus identifications. The engineered PLDA-LFIAs exhibit the capacity to detect SARS-CoV-2 and Flu A within 30 min, boasting a detection threshold of 5 pg/ml for the SARS-CoV-2 antigen and 0.1 ng/ml for the Flu A H1N1 antigen, thereby underscoring their heightened sensitivity relative to Au-LFIAs. These PLDA-LFIAs hold promise for the early detection of SARS-CoV-2 and Flu A, underscoring the potential of PLDA NPs as a discerning labeling probe to heighten the sensitivity of LFIA across diverse applications.

Role of Micelle Size in Cell Transcytosis-Based Tumor Extravasation, Infiltration, and Treatment Efficacy.

Transcytosis-based active transport of cancer nanomedicine has shown great promise for enhancing its tumor extravasation and infiltration and antitumor activity, but how the key nanoproperties of nanomedicine, particularly particle size, influence the transcytosis remains unknown. Herein, we used a transcytosis-inducing polymer, poly[2-(N-oxide-N,N-diethylamino)ethyl methacrylate] (OPDEA), and fabricated stable OPDEA-based micelles with different sizes (30, 70, and 140 nm in diameter) from its amphiphilic block copolymer, OPDEA-block-polystyrene (OPDEA-PS). The study of the micelle size effects on cell transcytosis, tumor extravasation, and infiltration showed that the smallest micelles (30 nm) had the fastest transcytosis and, thus, the most efficient tumor extravasation and infiltration. So, the 7-ethyl-10-hydroxyl camptothecin (SN38)-conjugated OPDEA micelles of 30 nm had much enhanced antitumor activity compared with the 140 nm micelles. These results are instructive for the design of active cancer nanomedicine.

Multifunctional Nanoassembly for MRI-Trackable Dendritic Cell Dependent and Independent Photoimmunotherapy.

Immunotherapy has emerged as a triumph in the treatment of malignant cancers. Nevertheless, current immunotherapeutics are insufficient in addressing tumors characterized by tumor cells' inadequate antigenicity and the tumor microenvironment's low immunogenicity (TME). Herein, we developed a novel multifunctional nanoassembly termed FMMC through the self-assembly of indoleamine 2,3-dioxygenase 1 (IDO-1) inhibitor 1-methyl-tryptophan prodrug (FM), Ce6, and ionic manganese (Mn2+) via noncovalent interactions. The laser-ignited FMMC treatment could induce effective immunogenic cell death and activate the STING/MHC-I signaling pathway, thus deeply sculpting the tumor-intrinsic antigenicity to achieve dendritic cell (DC)-dependent and -independent T cell responses against tumors. Meanwhile, by inhibiting IDO-1, FMMC could lead to immunosuppressive TME reversion to an immunoactivated one. FMMC-based phototherapy led to the up-regulation of programmed death-ligand 1 (PD-L1), enhancing the sensitivity of tumors to anti-PD-1 therapy. Furthermore, the incorporation of Mn2+ into FMMC resulted in an augmented longitudinal relaxivity and enhanced the MRI for monitoring the growth of primary tumors and lung metastases. Collectively, the superior reprogramming performance of immunosuppressive tumor cells and TME, combined with excellent anticancer efficacy and MRI capability, made FMMC a promising immune nanosculptor for cancer theranostics.

Highly Sensitive Imaging of Tumor Metastasis Based on the Targeting and Polarization of M2-like Macrophages.

Tumor-associated macrophages, especially M2-like macrophages, are extensively involved in tumor growth and metastasis, suppressing the innate immunity to help tumor cells escape and reshaping the microenvironment to help metastatic cells grow. However, in vivo, real-time visualized migration of M2-like macrophages has never been explored to monitor the tumor metastasis process. Herein, we prepared an M2-like macrophage-targeting nitric oxide (NO)-responsive nanoprobe (NRP@M-PHCQ) consisting of an amphiphilic block copolymer with mannose and hydroxychloroquine (HCQ) moieties (denoted as M-PHCQ) and a NO-responsive NIR-II probe (denoted as NRP). The mannose moieties provided M2-like macrophage-targeting capacity, and the HCQ moieties polarized M2-like macrophages to M1-like ones with enhanced NO secretion. Consequently, NRP@M-PHCQ was lit up by the secreted NO to visualize the migration and polarization of M2-like macrophages in real time. In vivo metastasis imaging with NRP@M-PHCQ successfully tracked early tumor metastasis in the lymph nodes and the lungs with high sensitivity, even superior to Luci-labeled bioluminescence imaging, suggesting the extensive distribution and critical role of M2-like macrophages in tumor metastasis. In general, this work provided a new strategy to sensitively image metastatic tumors by tracking the polarization of M2-like macrophages and visually disclosed the critical role of M2-like macrophages in early tumor metastasis.

Artificial intelligence-enhanced epileptic seizure detection by wearables.

OBJECTIVE: Wrist- or ankle-worn devices are less intrusive than the widely used electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom-developed deep-learning seizure detection models, we demonstrate the detection of a broad range of seizure types by wearable signals. METHODS: Patients admitted to the epilepsy monitoring unit were enrolled and asked to wear wearable sensors on either wrists or ankles. We collected patients' electrodermal activity, accelerometry (ACC), and photoplethysmography, from which blood volume pulse (BVP) is derived. Board-certified epileptologists determined seizure onset, offset, and types using video and EEG recordings per the International League Against Epilepsy 2017 classification. We applied three neural network models-a convolutional neural network (CNN) and a CNN-long short-term memory (LSTM)-based generalized detection model and an autoencoder-based personalized detection model-to the raw time-series sensor data to detect seizures and utilized performance measures, including sensitivity, false positive rate (the number of false alarms divided by the total number of nonseizure segments), number of false alarms per day, and detection delay. We applied a 10-fold patientwise cross-validation scheme to the multisignal biosensor data and evaluated model performance on 28 seizure types. RESULTS: We analyzed 166 patients (47.6% female, median age = 10.0 years) and 900 seizures (13 254 h of sensor data) for 28 seizure types. With a CNN-LSTM-based seizure detection model, ACC, BVP, and their fusion performed better than chance; ACC and BVP data fusion reached the best detection performance of 83.9% sensitivity and 35.3% false positive rate. Nineteen of 28 seizure types could be detected by at least one data modality with area under receiver operating characteristic curve > .8 performance. SIGNIFICANCE: Results from this in-hospital study contribute to a paradigm shift in epilepsy care that entails noninvasive seizure detection, provides time-sensitive and accurate data on additional clinical seizure types, and proposes a novel combination of an out-of-the-box monitoring algorithm with an individualized person-oriented seizure detection approach.

Natural Polyphenols-Platinum Nanocomplexes Stimulate Immune System for Combination Cancer Therapy.

Nanocarriers have been employed extensively to enhance drug delivery efficacy and reduce the side effect. However, carrier materials for drug delivery have challenging aspects, including safety concerns, low drug content, complexity in preparation, and low reproducibility. Herein, we propose a facile, universal, and green preparation way to use natural polyphenols to build platinum nanocomplex with stable structure, proper size, and high Pt content. The nanocomplexes are constructed by metal-polyphenol coordination using natural polyphenols and 1,2-diaminocyclohexane-Pt (II), enabling dual-responsive drug release behavior. For proof of concept, we demonstrate the antitumor activity of the Pt nanocomplex using a representative tannic acid-Pt nanocomplex (denoted as PTI). PTI can induce intensive tumor cell apoptosis, trigger immunogenic cell death (ICD), remarkably promote cytotoxic T lymphocytes (CTLs) infiltration in tumors, and significantly reduce immunosuppression of the tumor microenvironments, thus stimulating potent antitumor immune responses and showing effective antitumor activity by synergizing immune checkpoint blockade (ICB) therapy.

Aminopeptidase N-Responsive Conjugates with Tunable Charge-Reversal Properties for Highly Efficient Tumor Accumulation and Penetration.

Tumor enzyme-responsive charge-reversal carriers can induce efficient transcytosis and lead to efficient tumor infiltration and potent anticancer efficacy. However, the correlations of molecular structure with charge-reversal property, tumor penetration, and drug delivery efficiency are unknown. Herein, aminopeptidase N (APN)-responsive conjugates were synthesized to investigate these correlations. We found that the monomeric unit structure and the polymer chain structure determined the enzymatic hydrolysis and charge-reversal rates, and accordingly, the transcytosis and tumor accumulation and penetration of the APN-responsive conjugates. The conjugate with moderate APN responsiveness balanced the in vitro transcytosis and in vivo overall drug delivery process and achieved the best tumor delivery efficiency, giving potent antitumor efficacy. This work provides new insight into the design of tumor enzyme-responsive charge-reversal nanomedicines for efficient cancer drug delivery.

Hydrophobicity Effects of γ-Glutamyl Transpeptidase-Responsive Polymers on the Catalytic Activity and Transcytosis Efficacy.

Active transcytosis has recently sparked great interest in drug delivery as a novel route for tumor extravasation and infiltration. However, the rational design of transcytosis-inducing nanomedicines remains challenging. We recently demonstrated that the γ-glutamyl transpeptidase (GGT)-responsive polymer cationization induced efficient adsorption-mediated transcytosis (AMT). However, it remains unclear how the nanomedicines' physicochemical properties influence the GGT-responsive cationization and induced transcytosis behaviors. Herein, through a combination of experimental techniques and molecular dynamics (MD) simulations, we find that the random copolymers with high hydrophobic monomers tend to form compact structures accessible to the catalytic site of GGT, leading to a fast cationization and thus high transcytosis efficiency, while the homopolymers of the hydrophilic GGT-sensitive monomers have elongated structures unable to enter the active site and thus exhibit poor GGT sensitivity. As a result, the more hydrophobic polymer-drug conjugates with high camptothecin contents exhibit higher GGT-responsive activity, which in turn leads to faster cationization and cellular internalization, enhanced tumor infiltration, and more potent antitumor activity. These findings indicate the hydrophobicity is a main parameter determining the GGT catalytic activity and transcytosis efficiency of the GGT-activatable co(homo)polymers, providing guidelines for the rational design of GGT-induced charge reversal carriers for transcytotic nanomedicines.

Spatially variant deblur and image enhancement in a single multimode fiber imaged by deep learning.

A single multimode fiber has been applied in minimally invasive endoscopy with wavefront shaping for biological research such as brain imaging. Most of the fibers, such as step-index and graded-index multimode fibers, give rise to spatially variant blur due to limits on the numerical aperture and collection efficiency. Routines to solve this problem are based on iterative algorithms, which are often slow and computer-intense. We developed a method to synthesize datasets for driving a deep learning network to deblur and denoise the spatially variant degraded image. This approach is fast (5 ms), up to three orders of magnitude faster than the iterative way. Furthermore, our method can be applied to different types of fiber endoscopy, and two types of fiber are tested here. The performance is verified on fluorescence beads and three kinds of biological tissue sections in the experiment, demonstrating effectiveness in image enhancement.

Glutathione-Responsive Magnetic Nanoparticles for Highly Sensitive Diagnosis of Liver Metastases.

Liver metastasis (LM) occurs in various cancers, and its early and accurate diagnosis is of great importance. However, the detection of small LMs is still a great challenge because of the subtle differences between normal liver tissue and small metastases. Herein, we prepare glutathione (GSH)-responsive hyaluronic acid-coated iron oxide nanoparticles (HIONPs) for highly sensitive diagnosis of LMs through a facile one-pot method. HIONPs greatly enhance the signal of MRI in tumor metastases as T1 contrast agent (CA), whereas they substantially decrease the signal of liver as T2 CA as they aggregate into clusters upon the high GSH in liver. Consequently, MRI contrasted by HIONPs clearly distinguishes metastatic tumors (bright) from surrounding liver tissues (dark). HIONPs with superior LM contrasting capability and facile synthesis are very promising for clinical translation and indicate a new strategy to develop an ultrasensitive MRI CA for LM diagnosis that exploits high GSH level in the liver.

Molecularly Precise, Bright, Photostable, and Biocompatible Cyanine Nanodots as Alternatives to Quantum Dots for Biomedical Applications.

Fluorescent imaging with fluorophores has become a powerful way to explore complex biological systems and visualize nanoparticles for drug delivery. However, it is challenging to develop fluorophores with ideal physical and optical properties. We report a method to synthesize cyanine nanodots with a single-molecule structure, well-defined particle size, customizable fluorescent spectrum, and bright and stable fluorescence. These cyanine nanodots are acquired by the divergent synthesis of cyanine-dye-cored polylysine (PLL) dendrimers. We demonstrated the feasibility of the method by synthesizing cyanine 3 (Cy3), cyanine 5 (Cy5), or cyanine 7 (Cy7) cored single-molecule nanodots up to eight generations with a size of around 11 nm. We show that these cyanine nanodots are capable of multiple biomedical applications, including multicolor cellular tracing and cancer imaging. These cyanine nanodots possess many merits of organic dots and quantum dots that are promising for future application.

Seizure detection using wearable sensors and machine learning: Setting a benchmark.

OBJECTIVE: Tracking seizures is crucial for epilepsy monitoring and treatment evaluation. Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may miss seizures. Wearable devices may be better tolerated and more suitable for long-term ambulatory monitoring. This study evaluates the seizure detection performance of custom-developed machine learning (ML) algorithms across a broad spectrum of epileptic seizures utilizing wrist- and ankle-worn multisignal biosensors. METHODS: We enrolled patients admitted to the epilepsy monitoring unit and asked them to wear a wearable sensor on either their wrists or ankles. The sensor recorded body temperature, electrodermal activity, accelerometry (ACC), and photoplethysmography, which provides blood volume pulse (BVP). We used electroencephalographic seizure onset and offset as determined by a board-certified epileptologist as a standard comparison. We trained and validated ML for two different algorithms: Algorithm 1, ML methods for developing seizure type-specific detection models for nine individual seizure types; and Algorithm 2, ML methods for building general seizure type-agnostic detection, lumping together all seizure types. RESULTS: We included 94 patients (57.4% female, median age = 9.9 years) and 548 epileptic seizures (11 066 h of sensor data) for a total of 930 seizures and nine seizure types. Algorithm 1 detected eight of nine seizure types better than chance (area under the receiver operating characteristic curve [AUC-ROC] = .648-.976). Algorithm 2 detected all nine seizure types better than chance (AUC-ROC = .642-.995); a fusion of ACC and BVP modalities achieved the best AUC-ROC (.752) when combining all seizure types together. SIGNIFICANCE: Automatic seizure detection using ML from multimodal wearable sensor data is feasible across a broad spectrum of epileptic seizures. Preliminary results show better than chance seizure detection. The next steps include validation of our results in larger datasets, evaluation of the detection utility tool for additional clinical seizure types, and integration of additional clinical information.

Effect of Cationic Charge Density on Transcytosis of Polyethylenimine.

The adsorption-mediated transcytosis (AMT) induced by the electrostatic interaction between the positively charged surface of carriers and negatively charged cell membrane is a new paradigm enabling nanomedicine's tumor extravasation and infiltration. However, little is known about the correlation between the carrier's charge density and its AMT-induced tumor infiltration efficiency. Herein, we investigate the effect of the cationic polymer's charge on the AMT-induced tumor penetration ability using in vitro multilayer tumor spheroids (MTSs). A cationic polymer, polyethylenimine (PEI), is amidized with acetic anhydride to obtain acetylated PEIs (AcPEIs) with different cationic charge densities. As the amidization ratio increases, the AcPEIs' cytotoxicity, zeta potential, and cell-binding affinity significantly decrease. Notably, not only does the weak cell binding (AcPEIs with high acetylation degrees) lead to slow endocytosis and inefficient transcytosis, so does the strong cell-binding PEI. The PEI with 24% acetylation (AcPEI24%) is found to have the highest transcytosis efficiency because its balanced cell-binding affinity triggers fast adsorption-mediated endocytosis. The subsequent Golgi apparatus/endoplasmic reticulum-mediated exocytosis via extracellular vesicles leads to highly effective transcellular delivery and tumor penetration in MTSs. Therefore, the drug carrier's surface cationic charge density critically influences its AMT-induced tumor penetration efficiency. This study provides mechanistic insights into the design of drug-delivery systems with active transcytosis for improved tumor penetration and enhanced therapeutic efficiency.

Pairwise Registration Algorithm for Large-Scale Planar Point Cloud Used in Flatness Measurement.

In this paper, an optimized three-dimensional (3D) pairwise point cloud registration algorithm is proposed, which is used for flatness measurement based on a laser profilometer. The objective is to achieve a fast and accurate six-degrees-of-freedom (6-DoF) pose estimation of a large-scale planar point cloud to ensure that the flatness measurement is precise. To that end, the proposed algorithm extracts the boundary of the point cloud to obtain more effective feature descriptors of the keypoints. Then, it eliminates the invalid keypoints by neighborhood evaluation to obtain the initial matching point pairs. Thereafter, clustering combined with the geometric consistency constraints of correspondences is conducted to realize coarse registration. Finally, the iterative closest point (ICP) algorithm is used to complete fine registration based on the boundary point cloud. The experimental results demonstrate that the proposed algorithm is superior to the current algorithms in terms of boundary extraction and registration performance.

Scar Tissue-Targeting Polymer Micelle for Spinal Cord Injury Treatment.

Spinal cord injury (SCI) is a devastating disorder, leading to permanent motor and sensory deficit. Despite recent advances in neurosciences, the treatment efficacy on SCI patients remains unsatisfactory, mainly due to the poor accumulation, short retention, and lack of controlled release of therapeutics in lesion tissue. Herein, an injured spinal cord targeting prodrug polymer micelle is built. An esterase-responsive bond is used to link apocynin (APO) monomer, because of the enhanced esterase activity found in microglia cells after activation, which ensures a controlled degradation of APO prodrug (Allyloxypolyethyleneglycol-b-poly [2-(((4-acetyl-2-methoxyphenoxy)carbonyl)oxy)ethyl methacrylate], APEG-PAPO or PAPO) by activated microglia cells. A scar tissue-homing peptide (cysteine-alanine-glutamine-lysine, CAQK) is introduced to the PAPO to endow the polymer micelle the lesion tissue-targeting ability. As a result, this CAQK-modified prodrug micelle (cPAM) exhibits an improved accumulation and prolonged retention in lesion tissue compared to the control micelle. The cPAM also leads to superior tissue protection and sustained motor function recovery than the control groups in a mouse model of SCI. In conclusion, the cPAM induces an effective treatment of SCI by the lesion tissue specific delivery of the prodrug polymer via its robust scar binding effect, making the scar tissue a drug releasing platform for sustained treatment of SCI.

[2]Pseudorotaxane-Based Supramolecular Optical Indicator for the Visual Detection of Cellular Cyanide Excretion.

Cyanide is extremely hazardous to living organisms and the environment. Owing to its wide range of applications and high toxicity, the development of functional materials for cyanide detection and sensing is highly desirable. Host-guest complexation between bis(p-phenylene)-34-crown-10 H and N-methylacridinium salt G remarkably decreases the detection limit for cyanide anions compared with that of the guest itself. The [2]pseudorotaxane selectively recognizes the cyanide anion with high optical sensitivity as a result of the nucleophilic addition of the cyanide anion at the 9-position of G. The host-guest complexation is further incorporated into supramolecular materials for the visual detection of cyanide anions, especially the detection of cellular cyanide excretion with a detection limit of 0.6 µm. This supramolecular method provides an extremely distinct strategy for the visual detection of cyanide anions.

Drug-binding albumins forming stabilized nanoparticles for efficient anticancer therapy.

Albumin is a serum transport protein, which has been utilized as a carrier for a variety of drugs to improve their delivery efficiency and to obtain favorable pharmacokinetic profiles. However, natural albumin possesses only a few high-affinity binding sites for a limited number of drugs. This results in deficiencies in drug-loading and serum stability, and consequently, in impaired therapeutic efficacy. Herein, BSA was modified with different isothiocyanate conjugates (BSA-ITCs), which self-assembled with paclitaxel (PTX) to produce BSA-ITCs/PTX nanoparticles. Among these BSA-ITCs, phenethyl isothiocyanate (PEITC)-modified BSA (BSA-PEITC35) conjugates effectively loaded PTX and formed highly stable BSA-PEITC35/PTX nanoparticles. Molecular modeling studies suggested that PEITC groups in BSA-PEITC35 can significantly lower the PTX binding free energy. BSA-PEITC35/PTX showed enhanced stability, prolonged blood circulation and increased tumor accumulation than unmodified BSA/PTX, and exerted more potent antitumor activity than both BSA/PTX and Abraxane in subcutaneous mouse tumor models after intravenous administration.

Zinc phthalocyanine encapsulated in polymer micelles as a potent photosensitizer for the photodynamic therapy of osteosarcoma.

Zinc phthalocyanine (ZnPc) is a highly potent second-generation photosensitizer for cancer photodynamic therapy (PDT) with attractive photo-physical and photo-chemical properties. However, poor solubility and strong trend of crystallization prevent it from loading in most of drug delivery systems and hamper its further application. Herein, to overcome this problem, an amphiphilic block copolymer poly(ethylene glycol)-poly[2-(methylacryloyl)ethylnicotinate] (PEG-PMAN) with aromatic nicotinate is used to load ZnPc for their π-π interactions. The formed PEG-PMAN/ZnPc nanoparticle (PPZ) dramatically increases reactive oxygen species production in osteosarcoma cells after light irradiation, causes mitochondrial injury and promotes cell cycle arrest at G2/M, leading to a 100-fold cytotoxicity improvement comparing with free ZnPc. The excellent therapeutic effectiveness and safety of PPZ are also proved by in vivo experiments operating on osteosarcoma model. The finding above indicates that PPZ has promising clinical applications as a next-generation photosensitizer in PDT of osteosarcoma.

[Biomass Compositional Analysis Using Sparse Partial Least Squares Regression and Near Infrared Spectrum Technique].

Forest bio-fuel, a new type renewable energy, has attracted increasing attention as a promising alternative. In this study, a new method called Sparse Partial Least Squares Regression (SPLS) is used to construct the proximate analysis model to analyze the fuel characteristics of sawdust combining Near Infrared Spectrum Technique. Moisture, Ash, Volatile and Fixed Carbon percentage of 80 samples have been measured by traditional proximate analysis. Spectroscopic data were collected by Nicolet NIR spectrometer. After being filtered by wavelet transform, all of the samples are divided into training set and validation set according to sample category and producing area. SPLS, Principle Component Regression (PCR), Partial Least Squares Regression (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO) are presented to construct prediction model. The result advocated that SPLS can select grouped wavelengths and improve the prediction performance. The absorption peaks of the Moisture is covered in the selected wavelengths, well other compositions have not been confirmed yet. In a word, SPLS can reduce the dimensionality of complex data sets and interpret the relationship between spectroscopic data and composition concentration, which will play an increasingly important role in the field of NIR application.