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Accurately monitoring Canopy Nitrogen Concentration (CNC) is a prerequisite for precision nitrogen (N) fertiliser management at the farm scale with carbon and N budgeting across the landscape and ecosystems. While many spectral indices have been proposed for CNC monitoring, their applicability and accuracy are often adversely affected by confounding factors such as aboveground biomass (AGB), crop type, growth stages, and environmental conditions, limiting their broader application and adoption; with AGB being one of the most dominant signals and confounding factors at canopy scale. The confounding effect can become more challenging as AGB is also physiologically linked with CNC across the growth stages. Additionally, the interplay between index form, selection of optimal wavebands and their bandwidths remains poorly understood for CNC index design. This study proposes robust and cost-effective 2- and 4-waveband multispectral (MS) CNC indices applicable across a wide range of crop conditions. We collected 449 canopy reflectance spectra (400–980 nm) together with corresponding CNC and AGB measurements across four growth stages of ryegrass (winter and summer), and five growth stages of barley (winter-spring) in Victoria, Australia, in 2018 and 2019. All possible waveband (400–980 nm) combinations revealed that the best combination varied between seasons and crop types. However, the visible spectrum, particularly the blue region, presented high and consistent performance. Bandwidths of 10–40 nm outperformed either very narrow (2 nm) or very broad bandwidths (80 nm). The newly developed 2-waveband index (416 and 442 nm with 10-nm bandwidth; R2 = 0.75 and NRMSE = 0.2) and 4-waveband index (512, 440, 414 and 588 nm with 40-nm bandwidth; R2 = 0.81 and NRMSE = 0.17) exhibited the best performance, while validation with an independent dataset (from a different growing period to those used in the model development) obtained NRMSE values of 0.25 and 0.24, respectively. The 4-waveband index provides enhanced performance and permits use of broader bandwidths than its 2-waveband counterpart. [ABSTRACT FROM AUTHOR]

A multispectral camera records image data in various wavelengths across the electromagnetic spectrum to acquire additional information that a conventional camera fails to capture. With the advent of high-resolution image sensors and color filter technologies, multispectral imagers in the visible wavelengths have become popular with increasing commercial viability in the last decade. However, multispectral imaging in longwave infrared (LWIR, 8–14 μm) is still an emerging area due to the limited availability of optical materials, filter technologies, and high-resolution sensors. Images from LWIR multispectral cameras can capture emission spectra of objects to extract additional information that a human eye fails to capture and thus have important applications in precision agriculture, forestry, medicine, and object identification. In this work, we experimentally demonstrate an LWIR multispectral image sensor with three wavelength bands using optical elements made of an aluminum (Al)-based plasmonic filter array sandwiched in germanium (Ge). To realize the multispectral sensor, the filter arrays are then integrated into a three-dimensional (3D) printed wheel stacked on a low-resolution monochrome thermal sensor. Our prototype device is calibrated using a blackbody and its thermal output has been enhanced with computer vision methods. By applying a state-of-the-art deep learning method, we have also reconstructed multispectral images to a better spatial resolution. Scientifically, our work demonstrates a versatile spectral thermography technique for detecting target signatures in the LWIR range and other advanced spectral analyses. [ABSTRACT FROM AUTHOR]

The fabrication of highly porous cell-loaded structures in tissue engineering applications has been a challenging issue because non-porous cell-laden struts can cause severe cell necrosis in the middle region owing to poor transport of nutrients and oxygen. In this study, we propose a versatile handheld 3D printer for the effective fabrication of porous cell-laden methacrylated gelatin (GelMa) with high porosity (≈97%) by air injection and a bubble-making system using mesh filters through which a mixture of air/GelMa bioink is passed. In particular, the pore size and foamability of the cell constructs could be manipulated using various processing parameters (rheological properties of GelMa, filter size and number, and air-bioink volume ratio). To demonstrate the feasibility of the cell construct as a tissue engineering substitute for muscle regeneration, in vitro cellular activities and in vivo regeneration ability of human adipose stem cells were assessed. The in vitro results demonstrated that the human adipose stem cells (hASCs) fabricated using the handheld 3D printer were alive and well-proliferated. Furthermore, the in vivo results showed that the hASCs-constructs directly printed from the handheld 3D printer showed significant restoration of functionality and efficient muscle regeneration in the volumetric muscle loss model of mice. Based on these results, the fabrication method of the porous cell-laden construct could be a promising tool for regenerating muscle tissues. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) bioprinting is a highly effective technique for fabricating cell-loaded constructs in tissue engineering. However, the versatility of fabricating precise and complex cell-loaded hydrogels is limited owing to the poor crosslinking ability of cell-containing hydrogels. Herein, we propose an optic-fiber-assisted bioprinting (OAB) process to efficiently crosslink methacrylated hydrogels. By selecting appropriate processing conditions for the photo-crosslinking technique, we fabricated biofunctional cell-laden structures including methacrylated gelatin (Gelma), collagen, and decellularized extracellular matrix. To apply the method to skeletal muscle regeneration, cell-laden Gelma constructs were processed with a functional nozzle having a topographical cue and an OAB process that could induce a uniaxial alignment of C2C12 and human adipose stem cells (hASCs). Significantly higher degrees of cell alignment and myogenic activities in the cell-laden Gelma structure were observed compared with those in the cell construct that was printed using a conventional crosslinking method. Moreover, an in vivo regenerative potential was observed in volumetric muscle defects in a mouse model. The hASC-laden construct significantly induced greater muscle regeneration than the cell construct without topographical cues. Based on the results, the newly designed bioprinting process can prove to be highly effective in fabricating biofunctional cell-laden constructs for various tissue engineering applications. [ABSTRACT FROM AUTHOR]

Animal models have been utilized to understand the pathogenesis of Zellweger spectrum disorders (ZSDs); however, the link between clinical manifestations and molecular pathways has not yet been clearly established. We generated peroxin 5 homozygous mutant zebrafish (pex5−/−) to gain insight into the molecular pathogenesis of peroxisome dysfunction. pex5−/− display hallmarks of ZSD in humans and die within one month after birth. Fasting rapidly depletes lipids and glycogen in pex5−/− livers and expedites their mortality. Mechanistically, deregulated mitochondria and mechanistic target of rapamycin (mTOR) signaling act together to induce metabolic alterations that deplete hepatic nutrients and accumulate damaged mitochondria. Accordingly, chemical interventions blocking either the mitochondrial function or mTOR complex 1 (mTORC1) or a combination of both improve the metabolic imbalance shown in the fasted pex5−/− livers and extend the survival of animals. In addition, the suppression of oxidative stress by N-acetyl L-cysteine (NAC) treatment rescued the apoptotic cell death and early mortality observed in pex5−/−. Furthermore, an autophagy activator effectively ameliorated the early mortality of fasted pex5−/−. These results suggest that fasting may be detrimental to patients with peroxisome dysfunction, and that modulating the mitochondria, mTORC1, autophagy activities, or oxidative stress may provide a therapeutic option to alleviate the symptoms of peroxisomal diseases associated with metabolic dysfunction. [ABSTRACT FROM AUTHOR]

Irrigation water is an expensive and limited resource and optimal scheduling can boost water efficiency. Scheduling decisions often need to be made several days prior to an irrigation event, so a key aspect of irrigation scheduling is the accurate prediction of crop water use and soil water status ahead of time. This prediction relies on several key inputs including initial soil water status, crop conditions and weather. Since each input is subject to uncertainty, it is important to understand how these uncertainties impact soil water prediction and subsequent irrigation scheduling decisions. This study aims to develop an uncertainty-based analysis framework for evaluating irrigation scheduling decisions under uncertainty, with a focus on the uncertainty arising from short-term rainfall forecasts. To achieve this, a biophysical process-based crop model, APSIM (The Agricultural Production Systems sIMulator), was used to simulate root-zone soil water content for a study field in south-eastern Australia. Through the simulation, we evaluated different irrigation scheduling decisions using ensemble short-term rainfall forecasts. This modelling produced an ensemble of simulations of soil water content, as well as ensemble simulations of irrigation runoff and drainage. This enabled quantification of risks of over- and under-irrigation. These ensemble estimates were interpreted to inform the timing of the next irrigation event to minimize both the risks of stressing the crop and/or wasting water under uncertain future weather. With extension to include other sources of uncertainty (e.g., evapotranspiration forecasts, crop coefficient), we plan to build a comprehensive uncertainty framework to support on-farm irrigation decision-making. [ABSTRACT FROM AUTHOR]

A simple predictive biomarker for fatty liver disease is required for individuals with insulin resistance. Here, we developed a supervised machine learning-based classifier for fatty liver disease using fecal 16S rDNA sequencing data. Based on the Kangbuk Samsung Hospital cohort (n = 777), we generated a random forest classifier to predict fatty liver diseases in individuals with or without insulin resistance (n = 166 and n = 611, respectively). The model performance was evaluated based on metrics, including accuracy, area under receiver operating curve (AUROC), kappa, and F1-score. The developed classifier for fatty liver diseases performed better in individuals with insulin resistance (AUROC = 0.77). We further optimized the classifiers using genetic algorithm. The improved classifier for insulin resistance, consisting of ten microbial genera, presented an advanced classification (AUROC = 0.93), whereas the improved classifier for insulin-sensitive individuals failed to distinguish participants with fatty liver diseases from the healthy. The classifier for individuals with insulin resistance was comparable or superior to previous methods predicting fatty liver diseases (accuracy = 0.83, kappa = 0.50, F1-score = 0.89), such as the fatty liver index. We identified the ten genera as a core set from the human gut microbiome, which could be a diagnostic biomarker of fatty liver diseases for insulin resistant individuals. Collectively, these findings indicate that the machine learning classifier for fatty liver diseases in the presence of insulin resistance is comparable or superior to commonly used methods. [ABSTRACT FROM AUTHOR]

The pathways that impact longevity in the wake of dietary restriction (DR) remain still ill-defined. Most studies have focused on nutrient limitation and perturbations of energy metabolism. We showed that the L-threonine was elevated in Caenorhabditis elegans under DR, and that L-threonine supplementation increased its healthspan. Using metabolic and transcriptomic profiling in worms that were fed with RNAi to induce loss of key candidate mediators. L-threonine supplementation and loss-of-threonine dehydrogenaseincreased the healthspan by attenuating ferroptosis in a ferritin-dependent manner. Transcriptomic analysis showed that FTN-1 encoding ferritin was elevated, implying FTN-1 is an essential mediator of longevity promotion. Organismal ferritin levels were positively correlated with chronological aging and L-threonine supplementation protected against age-associated ferroptosis through the DAF-16 and HSF-1 pathways. Our investigation uncovered the role of a distinct and universal metabolite, L-threonine, in DR-mediated improvement in organismal healthspan, suggesting it could be an effective intervention for preventing senescence progression and age-induced ferroptosis. How dietary restriction increases longevity is still not fully understood. Here, the authors demonstrate that L-threonine is an essential mediator of dietary restriction that prevents age-induced ferroptosis and that dietary supplementation promotes healthy ageing. [ABSTRACT FROM AUTHOR]

Angiotensin II (AngII) has potent cardiac hypertrophic effects mediated through activation of hypertrophic signaling like Wnt/β-Catenin signaling. In the current study, we examined the role of protein arginine methyltransferase 7 (PRMT7) in cardiac function. PRMT7 was greatly decreased in hypertrophic hearts chronically infused with AngII and cardiomyocytes treated with AngII. PRMT7 depletion in rat cardiomyocytes resulted in hypertrophic responses. Consistently, mice lacking PRMT7 exhibited the cardiac hypertrophy and fibrosis. PRMT7 overexpression abrogated the cellular hypertrophy elicited by AngII, while PRMT7 depletion exacerbated the hypertrophic response caused by AngII. Similar with AngII treatment, the cardiac transcriptome analysis of PRMT7-deficient hearts revealed the alteration in gene expression profile related to Wnt signaling pathway. Inhibition of PRMT7 by gene deletion or an inhibitor treatment enhanced the activity of β-catenin. PRMT7 deficiency decreases symmetric dimethylation of β-catenin. Mechanistic studies reveal that methylation of arginine residue 93 in β-catenin decreases the activity of β-catenin. Taken together, our data suggest that PRMT7 is important for normal cardiac function through suppression of β-catenin activity. [ABSTRACT FROM AUTHOR]