A stable low-temperature H2-production catalyst by crowding Pt on α-MoC.

The water-gas shift (WGS) reaction is an industrially important source of pure hydrogen (H2) at the expense of carbon monoxide and water1,2. This reaction is of interest for fuel-cell applications, but requires WGS catalysts that are durable and highly active at low temperatures3. Here we demonstrate that the structure (Pt1-Ptn)/α-MoC, where isolated platinum atoms (Pt1) and subnanometre platinum clusters (Ptn) are stabilized on α-molybdenum carbide (α-MoC), catalyses the WGS reaction even at 313 kelvin, with a hydrogen-production pathway involving direct carbon monoxide dissociation identified. We find that it is critical to crowd the α-MoC surface with Pt1 and Ptn species, which prevents oxidation of the support that would cause catalyst deactivation, as seen with gold/α-MoC (ref. 4), and gives our system high stability and a high metal-normalized turnover number of 4,300,000 moles of hydrogen per mole of platinum. We anticipate that the strategy demonstrated here will be pivotal for the design of highly active and stable catalysts for effective activation of important molecules such as water and carbon monoxide for energy production.

PI3Kγ maintains the self-renewal of acute myeloid leukemia stem cells by regulating the pentose phosphate pathway.

ABSTRACT: Acute myeloid leukemia (AML) is an aggressive hematological malignancy originating from transformed hematopoietic stem or progenitor cells. AML prognosis remains poor owing to resistance and relapse driven by leukemia stem cells (LSCs). Targeting molecules essential for LSC function is a promising therapeutic approach. The phosphatidylinositol 3-kinase (PI3K)/AKT pathway is often dysregulated in AML. We found that although PI3Kγ is highly enriched in LSCs and critical for self-renewal, it was dispensable for normal hematopoietic stem cells. Mechanistically, PI3Kγ-AKT signaling promotes nuclear factor erythroid 2-related factor 2 (NRF2) nuclear accumulation, which induces 6-phosphogluconate dehydrogenase (PGD) and the pentose phosphate pathway, thereby maintaining LSC stemness. Importantly, genetic or pharmacological inhibition of PI3Kγ impaired expansion and stemness of murine and human AML cells in vitro and in vivo. Together, our findings reveal a key role for PI3Kγ in selectively maintaining LSC function by regulating AKT-NRF2-PGD metabolic pathway. Targeting the PI3Kγ pathway may, therefore, eliminate LSCs without damaging normal hematopoiesis, providing a promising therapeutic strategy for AML.

Myelin repair of spinal cord injury in adult mice induced by treadmill training upregulated peroxisome proliferator-activated receptor gamma coactivator 1 alpha.

Growing evidence has proven the efficacy of physical exercise in remyelination and motor function performance after spinal cord injury (SCI). However, the molecular mechanisms of treadmill training on myelin repair and functional recovery after SCI have not yet been fully studied. Here, we explored the effect of treadmill training on upregulating peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC1α)-mediated myelin repair and functional recovery in a mouse model of thoracic T10 contusion injury. A 4-week treadmill training scheme was conducted on mice with SCI. The expression levels of oligodendrogenesis-related protein and PGC1α were detected by immunofluorescence, RNA fluorescence in situ hybridization and western blotting. Transmission electron microscopy (TEM) was used to observe myelin structure. The Basso Mouse Scale (BMS) and CatWalk automated gait analysis system were used for motor function recovery evaluation. Motor evoked potentials (MEPs) were also identified. In addition, adeno-associated virus (AAV)-mediated PGC1α knockdown in OLs was used to further unravel the role of PGC1α in exercise-induced remyelination. We found that treadmill training boosts oligodendrocyte precursor cells (OPCs) proliferation, potentiates oligodendrocytes (OLs) maturation, and increases myelin-related protein and myelin sheath thickness, thus impelling myelin repair and hindlimb functional performance as well as the speed and amplitude of nerve conduction after SCI. Additionally, downregulating PGC1α through AAV attenuated these positive effects of treadmill training. Collectively, our results suggest that treadmill training enhances remyelination and functional recovery by upregulating PGC1α, which should provide a step forward in the understanding of the effects of physical exercise on myelin repair.

NK92 cells and peripheral blood NK cells respond oppositely upon dasatinib treatment.

Natural killer (NK) cell is a valuable tool for immunotherapy in cancer treatment, both the cultured cell line NK92 and primary NK cells are widely studied and used in research and clinical trials. Clinical observations witnessed the improvement of patients' NK cells in terms of cell counts and cytotoxic activity upon dasatinib treatment, an approved drug for chronic myeloid leukaemia and Ph+ acute lymphocytic leukaemia. Several studies supported the clinical observations, yet others argued a detrimental effect of dasatinib on NK cells. Due to the complex conditions in different studies, the definite influence of dasatinib on NK92 and primary NK cells remains to be settled. Here, we used a well-defined in vitro system to evaluate the effects of dasatinib on NK92 cells and peripheral blood (PB)-NK cells. By co-culturing NK cells with dasatinib to test the cell counts and target cell-killing activities, we surprisingly found that the chemical influenced oppositely on these two types of NK cells. While dasatinib suppressed NK92 cell proliferation and cytotoxic activity, it improved PB-NK-killing tumour cells. RNA sequencing analysis further supported this finding, uncovering several proliferating and cytotoxic pathways responding invertedly between them. Our results highlighted an intrinsic difference between NK92 and PB-NK cells and may build clues to understand how dasatinib interacts with NK cells in vivo.

Soft classification and regression analysis of audiometric phenotypes of age-related hearing loss.

Age-related hearing loss has a complex etiology. Researchers have made efforts to classify relevant audiometric phenotypes, aiming to enhance medical interventions and improve hearing health. We leveraged existing pattern analyses of age-related hearing loss and implemented the phenotype classification via quadratic discriminant analysis (QDA). We herein propose a method for analyzing the exposure effects on the soft classification probabilities of the phenotypes via estimating equations. Under reasonable assumptions, the estimating equations are unbiased and lead to consistent estimators. The resulting estimator had good finite sample performances in simulation studies. As an illustrative example, we applied our proposed methods to assess the association between a dietary intake pattern, assessed as adherence scores for the dietary approaches to stop hypertension diet calculated using validated food-frequency questionnaires, and audiometric phenotypes (older-normal, metabolic, sensory, and metabolic plus sensory), determined based on data obtained in the Nurses' Health Study II Conservation of Hearing Study, the Audiology Assessment Arm. Our findings suggested that participants with a more healthful dietary pattern were less likely to develop the metabolic plus sensory phenotype of age-related hearing loss.

Transcriptome-wide identification of ARF gene family in medicinal plant Polygonatum kingianum and expression analysis of PkARF members in different tissues.

BACKGROUND: Polygonatum kingianum holds significant importance in Traditional Chinese Medicine due to its medicinal properties, characterized by its diverse chemical constituents including polysaccharides, terpenoids, flavonoids, phenols, and phenylpropanoids. The Auxin Response Factor (ARF) is a pivotal transcription factor known for its regulatory role in both primary and secondary metabolite synthesis. However, our understanding of the ARF gene family in P. kingianum remains limited. METHODS AND RESULTS: We employed RNA-Seq to sequence three distinct tissues (leaf, root, and stem) of P. kingianum. The analysis revealed a total of 31,558 differentially expressed genes (DEGs), with 43 species of transcription factors annotated among them. Analyses via gene ontology and the Kyoto Encyclopedia of Genes and Genomes demonstrated that these DEGs were predominantly enriched in metabolic pathways and secondary metabolite biosynthesis. The proposed temporal expression analysis categorized the DEGs into nine clusters, suggesting the same expression trends that may be coordinated in multiple biological processes across the three tissues. Additionally, we conducted screening and expression pattern analysis of the ARF gene family, identifying 12 significantly expressed PkARF genes in P. kingianum roots. This discovery lays the groundwork for investigations into the role of PkARF genes in root growth, development, and secondary metabolism regulation. CONCLUSION: The obtained data and insights serve as a focal point for further research studies, centred on genetic manipulation of growth and secondary metabolism in P. kingianum. Furthermore, these findings contribute to the understanding of functional genomics in P. kingianum, offering valuable genetic resources.

A Review on the Chemical Properties, Plant Sources, Anti-shock Effects, Pharmacokinetics, Toxicity, and Clinical Applications of Anisodamine.

Alkaloids are natural products that occur widely in many herbal plants. Anisodamine, widely present in the Solanaceae family, is an alkaloid extracted from the roots of the Anisodus tanguticus Maxim. It is an antagonist to M-choline receptors and exhibits diverse pharmacological effects, such as cholinolytic effect, calcium antagonist effect, anti-oxygenation effect. Anisodamine, a prominent constituent of the tropine alkaloid family, exhibits a range of pharmacological effects akin to those of atropine and scopolamine. owing to its low toxicity and moderate efficacy in clinical to wide applications, especially for varieties of shock treatment. However, there remains a dearth of research regarding the in vivo pharmacokinetics, mechanism of action, and toxicity of anisodamine. Consequently, this paper provides a comprehensive review of the anti-shock effects, toxicity, and pharmacokinetic characteristics of anisodamine to increase the understanding of its medicinal value, and provide reference and inspiration for the clinical application and further in-depth research of anisodamine.

De Novo Construction of Fluorophores via CO Insertion-Initiated Lactamization: A Chemical Strategy toward Highly Sensitive and Highly Selective Turn-On Fluorescent Probes for Carbon Monoxide.

Extensive studies in the last few decades have led to the establishment of CO as an endogenous signaling molecule and subsequently to the exploration of CO's therapeutic roles. In the current state, there is a critical conundrum in CO-related research: the extensive knowledge of CO's biological effects and yet an insufficient understanding of the quantitative correlations between the CO concentration and biological responses of various natures. This conundrum is partially due to the difficulty in examining precise concentration-response relationships of a gaseous molecule. Another reason is the need for appropriate tools for the sensitive detection and concentration determination of CO in the biological system. We herein report a new chemical approach to the design of fluorescent CO probes through de novo construction of fluorophores by a CO insertion-initiated lactamization reaction, which allows for ultra-low background and exclusivity in CO detection. Two series of CO detection probes have been designed and synthesized using this strategy. Using these probes, we have extensively demonstrated their utility in quantifying CO in blood, tissue, and cell culture and in cellular imaging of CO from exogenous and endogenous sources. The probes described will enable many biology and chemistry labs to study CO's functions in a concentration-dependent fashion with very high sensitivity and selectivity. The chemical and design principles described will also be applicable in designing fluorescent probes for other small molecules.

IGF-1 Combined with OPN Promotes Neuronal Axon Growth in Vitro Through the IGF-1R/Akt/mTOR Signaling Pathway in Lipid Rafts.

This study aims to investigate the effect of insulin-like growth factor 1 (IGF-1) combined with osteopontin (OPN) on the protein expression levels and growth of neuronal axons and its possible mechanism. In this study, IGF-1 combined with OPN promoted neuronal axon growth through the IGF-1R/Akt/mTOR signaling pathway in lipid rafts, and the effect was better than that of either agent alone. This effect was suppressed when given the mTOR inhibitor rapamycin or the lipid raft cholesterol extraction agent methyl-ß-cyclodextrin (M-ß-CD). Rapamycin could inhibit the expression of phosphorylated ribosomal S6 protein (p-S6) and phosphorylated protein kinase B (p-Akt) and limit axon growth. In addition to the above effects, M-ß-CD significantly downregulated the expression of phosphorylated insulin-like growth factor 1 receptor (p-IR). To further investigate the changes in lipid rafts when stimulated by different recombinant proteins, membrane lipid rafts were isolated to observe the changes by western blot. The expression levels of insulin-like growth factor 1 receptor (IR) and P-IR in the IGF-1 combined with OPN group were the highest. When M-ß-CD was administered to the lipid rafts of neurons, the enrichment of IR by IGF-1 combined with OPN was weakened, and the p-IR was decreased. Our study found that IGF-1 combined with OPN could promote axon growth by activating the IGF-1R/Akt/mTOR signaling pathway in neuronal lipid rafts.

Evaluation of Stem Rust Disease in Wheat Fields by Drone Hyperspectral Imaging.

Detecting plant disease severity could help growers and researchers study how the disease impacts cereal crops to make timely decisions. Advanced technology is needed to protect cereals that feed the increasing population using fewer chemicals; this may lead to reduced labor usage and cost in the field. Accurate detection of wheat stem rust, an emerging threat to wheat production, could inform growers to make management decisions and assist plant breeders in making line selections. A hyperspectral camera mounted on an unmanned aerial vehicle (UAV) was utilized in this study to evaluate the severity of wheat stem rust disease in a disease trial containing 960 plots. Quadratic discriminant analysis (QDA) and random forest classifier (RFC), decision tree classification, and support vector machine (SVM) were applied to select the wavelengths and spectral vegetation indices (SVIs). The trial plots were divided into four levels based on ground truth disease severities: class 0 (healthy, severity 0), class 1 (mildly diseased, severity 1-15), class 2 (moderately diseased, severity 16-34), and class 3 (severely diseased, highest severity observed). The RFC method achieved the highest overall classification accuracy (85%). For the spectral vegetation indices (SVIs), the highest classification rate was recorded by RFC, and the accuracy was 76%. The Green NDVI (GNDVI), Photochemical Reflectance Index (PRI), Red-Edge Vegetation Stress Index (RVS1), and Chlorophyll Green (Chl green) were selected from 14 SVIs. In addition, binary classification of mildly diseased vs. non-diseased was also conducted using the classifiers and achieved 88% classification accuracy. This highlighted that hyperspectral imaging was sensitive enough to discriminate between low levels of stem rust disease vs. no disease. The results of this study demonstrated that drone hyperspectral imaging can discriminate stem rust disease levels so that breeders can select disease-resistant varieties more efficiently. The detection of low disease severity capability of drone hyperspectral imaging can help farmers identify early disease outbreaks and enable more timely management of their fields. Based on this study, it is also possible to build a new inexpensive multispectral sensor to diagnose wheat stem rust disease accurately.

Isolation and identification of novel phenolic and lignan glycosides from Swertia davidii Franch.

Phytochemical analyses of Swertia davidii Franch. extracts using column chromatography and semi-preparative HPLC were performed. Two novel phenolic glycosides named swertiosides A and B (compounds 1 and 2, respectively) were isolated and characterized. Four known phenolic glycosides were also extracted (compounds 3-6). The structural characteristics of these novel compounds were analyzed using 1D, 2D NMR, and HRMS. All six compounds have never been isolated from this particular plant species before this study. Subsequent assessment of bioactive properties suggested that compounds 1 and 2 exhibited moderate levels of cytotoxicity.

Effects and mechanisms of extremely cold environment on body response after trauma.

With the outbreak of the Ukrainian crisis, extremely cold environment warfare has once again become the focus of international attention. People exposed to extremely cold environments may suffer from cold damage, further aggravate trauma, trigger high disability and mortality rates, and even cause serious sequelae. To declare the effects and mechanisms of the extremely cold environment on the body after trauma, this paper reviews, firstly, physiological reaction of human body in an extremely cold environment. Then, the post-traumatic body response in an extremely cold environment was introduced, and finally, the sequelae of trauma in extremely cold environment was further summarized in the paper. The results indicated that extremely cold environment can cause a series of damage to the body, especially the body after trauma. The extremely cold factor is a double-edged sword, showing a favorable and unfavorable side in different aspects. Moreover, in addition to the trauma suffered by the body, the subsequent sequelae such as cognitive dysfunction, anxiety, depression and even post-traumatic stress disorder may also be induced. The paper summarizes the human body's physiological response in an extremely cold environment, and declares the effects and mechanisms of the extremely cold environment on the body after trauma, which may provide a theoretical basis for effectively improving the level of combat trauma treatment in extremely cold regions.

Contribution of the LAC Genes in Fruit Quality Attributes of the Fruit-Bearing Plants: A Comprehensive Review.

Laccase genes produce laccase enzymes that play a crucial role in the production of lignin and oxidation reactions within plants. Lignin is a complex polymer that provides structure and toughness to the cell walls of numerous fruit plants. The LAC genes that encode laccase enzymes play vital roles in plant physiology, including the synthesis of pigments like PA that contribute to the colors of fruits, and in defending against pathogens and environmental stresses. They are crucial for fruit development, ripening, structural maintenance in plants, and adaptation to various environmental factors. As such, these genes and enzymes are essential for plant growth and development, as well as for various biotechnological applications in environmental remediation and industrial processes. This review article emphasizes the significance of genes encoding laccase enzymes during fruit growth, specifically pertaining to the strengthening of the endocarp through lignification. This process is crucial for ensuring fruit defense and optimizing seed scattering. The information gathered in this article will aid breeders in producing future fruit-bearing plants that are resistant to disease, cost-effective, and nutrient-rich.

A loss-of-function mutant allele of a glycosyl hydrolase gene has been co-opted for seed weight control during soybean domestication.

The resultant DNA from loss-of-function mutation can be recruited in biological evolution and development. Here, we present such a rare and potential case of "to gain by loss" as a neomorphic mutation during soybean domestication for increasing seed weight. Using a population derived from a chromosome segment substitution line of Glycine max (SN14) and Glycine soja (ZYD06), a quantitative trait locus (QTL) of 100-seed weight (qHSW) was mapped on chromosome 11, corresponding to a truncated ß-1, 3-glucosidase (ßGlu) gene. The novel gene hsw results from a 14-bp deletion, causing a frameshift mutation and a premature stop codon in the ßGlu. In contrast to HSW, the hsw completely lost ßGlu activity and function but acquired a novel function to promote cell expansion, thus increasing seed weight. Overexpressing hsw instead of HSW produced large soybean seeds, and surprisingly, truncating hsw via gene editing further increased the seed size. We further found that the core 21-aa peptide of hsw and its variants acted as a promoter of seed size. Transcriptomic variation in these transgenic soybean lines substantiated the integration hsw into cell and seed size control. Moreover, the hsw allele underwent selection and expansion during soybean domestication and improvement. Our work cloned a likely domesticated QTL controlling soybean seed weight, revealed a novel genetic variation and mechanism in soybean domestication, and provided new insight into crop domestication and breeding, and plant evolution.

GsERF1 enhances Arabidopsis thaliana aluminum tolerance through an ethylene-mediated pathway.

Ethylene response factor (ERF) transcription factors constitute a subfamily of the AP2/ERF superfamily in plants and play multiple roles in plant growth and development as well as in stress responses. In this study, the GsERF1 gene from the wild soybean BW69 line (an Al-resistant Glycine soja line) was rapidly induced in response to aluminum stress. Quantitative real-time PCR (qRT-PCR) analysis showed that the GsERF1 gene maintained a constitutive expression pattern and was induced in soybean in response to aluminum stress, with increased amounts of transcripts detected in the roots. The putative GsERF1 protein, which contains an AP2 domain, was located in the nucleus and maintained transactivation activity. In addition, under AlCl3 treatment, GsERF1 overexpression increased the relative growth rate of the roots of Arabidopsis and weakened the hematoxylin staining of hairy roots. Ethylene synthesis-related genes such as ACS4, ACS5 and ACS6 were upregulated in GsERF1 transgenic lines compared with the wild type under AlCl3 treatment. Furthermore, the expression levels of stress/ABA-responsive marker genes, including ABI1, ABI2, ABI4, ABI5 and RD29B, in the GsERF1 transgenic lines were affected by AlCl3 treatment, unlike those in the wild type. Taken together, the results indicated that overexpression of GsERF1 may enhance aluminum tolerance of Arabidopsis through an ethylene-mediated pathway and/or ABA signaling pathway, the findings of which lay a foundation for breeding soybean plants tolerant to aluminum stress.

Island Effect in Stretchable Inorganic Electronics.

Island-bridge architectures represent a widely used structural design in stretchable inorganic electronics, where deformable interconnects that form the bridge provide system stretchability, and functional components that reside on the islands undergo negligible deformations. These device systems usually experience a common strain concentration phenomenon, i.e., "island effect", because of the modulus mismatch between the soft elastomer substrate and its on-top rigid components. Such an island effect can significantly raise the surrounding local strain, therefore increasing the risk of material failure for the interconnects in the vicinity of the islands. In this work, a systematic study of such an island effect through combined theoretical analysis, numerical simulations and experimental measurements is presented. To relieve the island effect, a buffer layer strategy is proposed as a generic route to enhanced stretchabilities of deformable interconnects. Both experimental and numerical results illustrate the applicability of this strategy to 2D serpentine and 3D helical interconnects, as evidenced by the increased stretchabilities (e.g., by 1.5 times with a simple buffer layer, and 2 times with a ring buffer layer, both for serpentine interconnects). The application of the patterned buffer layer strategy in a stretchable light emitting diodes system suggests promising potentials for uses in other functional device systems.

An enhancing effect attributed to a nonsynonymous mutation in SOYBEAN SEED SIZE 1, a SPINDLY-like gene, is exploited in soybean domestication and improvement.

Soybean (Glycine max) was domesticated from its wild relative Glycine soja. One-hundred-seed weight is one of the most important domesticated traits determining soybean yield; however, its underlying genetic basis remains elusive. We characterized a soybean seed size 1 (sss1) mutant featuring large seeds compared to its wild-type background. Positional cloning revealed that the candidate gene GmSSS1 encoded a SPINDLY homolog and was co-located in a well-identified quantitative trait locus (QTL)-rich region on chromosome 19. Knocking out GmSSS1 resulted in small seeds, while overexpressing GmSSS1/Gmsss1 induced large seeds. Modulating GmSSS1/Gmsss1 in transgenic plants can positively influence cell expansion and cell division. Relative to GmSSS1, one mutation leading to an E to Q substitution at the 182nd residue in Gmsss1 conferred an enhancing effect on seed weight. GmSSS1 underwent diversification in wild-type and cultivated soybean, and the alleles encoding the Gmsss1-type substitution of 182nd -Q, which originated along the central and downstream parts of the Yellow River, were selected and expanded during soybean domestication and improvement. We cloned the causative gene for the sss1 mutant, which is linked with a seed weight QTL, identified an elite allele of this gene for increasing seed weight, and provided new insights into soybean domestication and breeding.

Adaptive response-dependent two-phase designs: Some results on robustness and efficiency.

Large cohort studies now routinely involve biobanks in which biospecimens are stored for use in future biomarker studies. In such settings, two-phase response-dependent sampling designs involve subsampling individuals in the cohort, assaying their biospecimen to measure an expensive biomarker, and using this data to estimate key parameters of interest under budgetary constraints. When analyses are based on inverse probability weighted estimating functions, recent work has described adaptive two-phase designs in which a preliminary phase of subsampling based on a standard design facilitates approximation of an optimal selection model for a second subsampling phase. In this article, we refine the definition of an optimal subsampling scheme within the framework of adaptive two-phase designs, describe how adaptive two-phase designs can be used when analyses are based on likelihood or conditional likelihood, and consider the setting of a continuous biomarker where the nuisance covariate distribution is estimated nonparametrically at the design stage and analysis stage as required; efficiency and robustness issues are investigated. We also explore these methods for the surrogate variable problem and describe a generalization to accommodate multiple stages of phase II subsampling. A study involving individuals with psoriatic arthritis is considered for illustration, where the aim is to assess the association between the biomarker MMP-3 and the development of joint damage.

Analytical methods for correlated data arising from multicenter hearing studies.

In epidemiological hearing studies, estimating the association between exposures and hearing loss using audiometrically-assessed hearing measurements is challenging due to the complex correlation structure in the clustered data, with clusters formed by the two ears of the same individual and the testing site and audiologist. We propose a linear mixed-effects model to take into account the multilevel correlation structures of the data. Both theoretically and in simulation studies, we compare single-ear linear regression models commonly used in published hearing loss studies with the proposed both-ears linear mixed models properly accounting for the multi-level correlations. Our findings include (1) when there are only participant-level covariates, the worse-ear linear regression models produce unbiased but typically less efficient estimators than the both-ear and average-ear approaches; (2) when there are ear-level confounders, the worse-ear method may lead to biased estimators and the average-ear method produces unbiased but typically less efficient estimators than the both-ear method; (3) the both-ear method may gain efficiency when additionally adjusting for testing sites and audiologists. As an illustrative example, we applied the single-ear and both-ear methods to assess aspirin-hearing association in the Nurses' Health Study II.

Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery.

Sugarcane is the main industrial crop for sugar production, and its growth status is closely related to fertilizer, water, and light input. Unmanned aerial vehicle (UAV)-based multispectral imagery is widely used for high-throughput phenotyping, since it can rapidly predict crop vigor at field scale. This study focused on the potential of drone multispectral images in predicting canopy nitrogen concentration (CNC) and irrigation levels for sugarcane. An experiment was carried out in a sugarcane field with three irrigation levels and five fertilizer levels. Multispectral images at an altitude of 40 m were acquired during the elongating stage. Partial least square (PLS), backpropagation neural network (BPNN), and extreme learning machine (ELM) were adopted to establish CNC prediction models based on various combinations of band reflectance and vegetation indices. The simple ratio pigment index (SRPI), normalized pigment chlorophyll index (NPCI), and normalized green-blue difference index (NGBDI) were selected as model inputs due to their higher grey relational degree with the CNC and lower correlation between one another. The PLS model based on the five-band reflectance and the three vegetation indices achieved the best accuracy (Rv = 0.79, RMSEv = 0.11). Support vector machine (SVM) and BPNN were then used to classify the irrigation levels based on five spectral features which had high correlations with irrigation levels. SVM reached a higher accuracy of 80.6%. The results of this study demonstrated that high resolution multispectral images could provide effective information for CNC prediction and water irrigation level recognition for sugarcane crop.