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Mapping maize water stress status and monitoring its spatial variability at a farm scale are a prerequisite for precision irrigation. High-resolution multispectral images acquired from an unmanned aerial vehicle (UAV) were used to evaluate the applicability of the data in mapping water stress status of maize under different levels of deficit irrigation at the late vegetative, reproductive and maturation growth stages. Canopy temperature, field air temperature and relative humidity obtained by a handheld infrared thermometer and a portable air temperature/relative humidity meter were used to establish a crop water stress index (CWSI) empirical model under the weather conditions in Ordos, Inner Mongolia, China. Nine vegetation indices (VIs) related to crop water stress were derived from the UAV multispectral imagery and used to establish CWSI inversion models. The results showed that non-water-stressed baseline had significant difference in the reproductive and maturation stages with an increase of 2.1 °C, however, the non-transpiring baseline did not change significantly with an increase of 0.1 °C. The ratio of transformed chlorophyll absorption in reflectance index (TCARI) and renormalized difference vegetation index (RDVI), and the TCARI and soil-adjusted vegetation index (SAVI) had the best correlations with CWSI. R2 values were 0.47 and 0.50 for TCARI/RDVI and TCARI/SAVI at the reproductive and maturation stages, respectively; and 0.81 and 0.80 for TCARI/RDVI and TCARI/SAVI at the late reproductive and maturation stages, respectively. Compared to CWSI calculated by on-site measurements, CWSI values retrieved by VI-CWSI regression models established in this study had more abilities to assess the field variability of crop and soil. This study demonstrates the potentiality of using high-resolution UAV multispectral imagery to map maize water stress.

The rapid, accurate, and economical estimation of crop above-ground biomass at the farm scale is crucial for precision agricultural management. The unmanned aerial vehicle (UAV) remote-sensing system has a great application potential with the ability to obtain remote-sensing imagery with high temporal-spatial resolution. To verify the application potential of consumer-grade UAV RGB imagery in estimating maize above-ground biomass, vegetation indices and plant height derived from UAV RGB imagery were adopted. To obtain a more accurate observation, plant height was directly derived from UAV RGB point clouds. To search the optimal estimation method, the estimation performances of the models based on vegetation indices alone, based on plant height alone, and based on both vegetation indices and plant height were compared. The results showed that plant height directly derived from UAV RGB point clouds had a high correlation with ground-truth data with an R2 value of 0.90 and an RMSE value of 0.12 m. The above-ground biomass exponential regression models based on plant height alone had higher correlations for both fresh and dry above-ground biomass with R2 values of 0.77 and 0.76, respectively, compared to the linear regression model (both R2 values were 0.59). The vegetation indices derived from UAV RGB imagery had great potential to estimate maize above-ground biomass with R2 values ranging from 0.63 to 0.73. When estimating the above-ground biomass of maize by using multivariable linear regression based on vegetation indices, a higher correlation was obtained with an R2 value of 0.82. There was no significant improvement of the estimation performance when plant height derived from UAV RGB imagery was added into the multivariable linear regression model based on vegetation indices. When estimating crop above-ground biomass based on UAV RGB remote-sensing system alone, looking for optimized vegetation indices and establishing estimation models with high performance based on advanced algorithms (e.g., machine learning technology) may be a better way.

To identify drought-tolerant crop cultivars or achieve a balance between water use and yield, accurate measurements of crop water stress are needed. In this study, the canopy temperature (Tc) of maize at the late vegetative stage was extracted from high-resolution red–green–blue (RGB, 1.25 cm) and thermal (7.8 cm) images taken by an unmanned aerial vehicle (UAV). To reduce the number of parameters for crop water stress monitoring, four simple methods that require only Tc were identified: Tc, degrees above non-stress, standard deviation of Tc, and variation coefficient of Tc. The ground-truth temperatures obtained using a handheld infrared thermometer were used to calibrate the temperature obtained from the UAV thermal images and to evaluate the Tc extraction results. Measured leaf stomatal conductance values were used to evaluate the performance of the four Tc-based crop water stress indicators. The results showed a strong correlation between ground-truth Tc and Tc extracted by the red–green ratio index (RGRI)-Otsu method proposed in this study, with a coefficient of determination of 0.94 ( n = 15) and root mean square error value of 0.7°C. The RGRI-Otsu method was most accurate for estimating temperatures around 32.9°C, but the magnitude of residuals increased above and below this value. This phenomenon may be attributable to changes in canopy cover (leaf curling) under water stress, resulting in changes in the proportion of exposed sunlit soil in UAV thermal orthophotographs. Therefore, to improve the accuracy of maize canopy detection and extraction, optimal methods and better strategies for eliminating mixed pixels are needed. This study demonstrates the potential of using high-resolution UAV RGB images to supplement UAV thermal images for the accurate extraction of maize Tc.

The detection of apple leaf diseases plays a crucial role in ensuring crop health and yield. However, due to variations in lighting and shadow, as well as the complex relationships between perceptual fields and target scales, current detection methods face significant challenges. To address these issues, we propose a new model called YOLO-Leaf. Specifically, YOLO-Leaf utilizes Dynamic Snake Convolution (DSConv) for robust feature extraction, employs BiFormer to enhance the attention mechanism, and introduces IF-CIoU to improve bounding box regression for increased detection accuracy and generalization ability. Experimental results on the FGVC7 and FGVC8 datasets show that YOLO-Leaf significantly outperforms existing models in terms of detection accuracy, achieving mAP50 scores of 93.88% and 95.69%, respectively. This advancement not only validates the effectiveness of our approach but also highlights its practical application potential in agricultural disease detection.

To examine the effectiveness of psychoeducational interventions on depression, anxiety, and health-related quality of life (HRQOL) for people undergoing maintenance hemodialysis (MHD). This review used systematic review and meta-analysis as the research design. Nine databases, including PubMed, Web of Science, Embase, CINAHL Complete, Cochrane Library, CNKI, WanFang, VIP, and Chinese Biomedical Literature Database, were searched from the inception to the 8th of July 2023. Two reviewers independently identified randomized controlled trials (RCT) examining the effects of psychoeducational interventions on MHD patients. Fourteen studies involving 1134 MHD patients were included in this review. The results of meta-analyses showed that psychoeducational intervention had significant short-term (< 1 m) (SMD: -0.87, 95% CI: -1.54 to -0.20,  = 0.01, I = 91%; 481 participants), and medium-term (1-3 m) (SMD: -0.29, 95% CI: -0.50 to -0.08,  = 0.01, I = 49%; 358 participants) on anxiety in MHD patients, but the effects could not be sustained at longer follow-ups. Psychoeducational interventions can also have short-term (< 1 m) (SMD: -0.65, 95% CI: -0.91 to -0.38,  < 0.00001, I = 65%; 711 participants) and medium-term (1-3 m) (SMD: -0.42, 95% CI: -0.76 to -0.09,  = 0.01, I = 69%; 489 participants) effects in reducing depression levels in MHD patients. Psychoeducational interventions that use coping strategies, goal setting, and relaxation techniques could enhance the QOL in MHD patients in the short term (< 1 m) (SMD: 0.86, 95% CI: 0.42 to 1.30,  = 0.02, I = 86%; 241 participants). Psychoeducational interventions have shown great potential to improve anxiety, depression, and quality of life in patients with MHD at the short- and medium-term follow-ups. CRD42023440561.

Background Though esophageal cancer is three to four times more common among males than females worldwide, this type of cancer still ranks in the top incidence among women, even more than the female specific cancer types. The occurrence is currently attributed to extrinsic factors, including tobacco use and alcohol consumption. However, limited attention has been given to gender-specific intrinsic genetic factors, especially in female. Methods We re-annotated a large cohort of microarrays on 179 ESCC patients and identified female-specific differently expressed lncRNAs. The associations between FMR1-AS1 and the risk and prognosis of ESCC were examined in 206 diagnosed patients from eastern China and validated in 188 additional patients from southern China. The effects of FMR1-AS1 on the malignant phenotypes on female ESCC cells were detected in vitro and in vivo. ChIRP-MS, reporter gene assays and EMSA were conducted to identify the interaction and regulation among FMR1-AS1 , TLR7 and NFκB. Results We found FMR1-AS1 expression is exclusively altered and closely associated with the level of sXCI in female ESCC patients, and its overexpression may correlate to poor clinical outcome. ChIRP-MS data indicate that FMR1-AS1 could be packaged into exosomes and released into tumor microenvironment. Functional studies demonstrated that FMR1-AS1 could bind to endosomal toll-like receptor 7 (TLR7) and activate downstream TLR7-NFκB signaling, promoting the c-Myc expression, thus inducing ESCC cell proliferation, anti-apoptosis and invasion ability. Exosome incubation and co-xenograft assay indicate that FMR1-AS1 exosomes may secreted from ESCC CSCs, transferring stemness phenotypes to recipient non-CSCs in tumor microenvironment. Furthermore, we also found a correlation between the serum levels of FMR1-AS1 and the overall survival (OS) of the female ESCC patients. Conclusions Our results highlighted exosomal FMR1-AS1 in maintaining CSC dynamic interconversion state through the mechanism of activating TLR7-NFκB signaling, upregulating c-Myc level in recipient cells, which may be taken as an attractive target approach for advancing current precision cancer therapeutics in female patients.

Cancer cells develop multiple strategies to evade T cell-mediated killing. On one hand, cancer cells may preferentially rely on certain amino acids for rapid growth and metastasis. On the other hand, sufficient nutrient availability and uptake are necessary for mounting an effective T cell anti-tumor response in the tumor microenvironment (TME). Here we demonstrate that tumor cells outcompete T cells for cystine uptake due to high Slc7a11 expression. This competition induces T-cell exhaustion and ferroptosis, characterized by diminished memory formation and cytokine secretion, increased PD-1 and TIM-3 expression, as well as intracellular oxidative stress and lipid-peroxide accumulation. Importantly, either Slc7a11 deletion in tumor cells or intratumoral cystine supplementation improves T cell anti-tumor immunity. Mechanistically, cystine deprivation in T cells disrupts glutathione synthesis, but promotes CD36 mediated lipid uptake due to dysregulated cystine/glutamate exchange. Moreover, enforced expression of glutamate-cysteine ligase catalytic subunit (Gclc) promotes glutathione synthesis and prevents CD36 upregulation, thus boosting T cell anti-tumor immunity. Our findings reveal cystine as an intracellular metabolic checkpoint that orchestrates T-cell survival and differentiation, and highlight Gclc as a potential therapeutic target for enhancing T cell anti-tumor function.

Soon after the isolation of graphene, it was discovered that the charge carriers in monolayer and bilayer sheets exhibit exotic Berry phases of π and 2 π respectively. Now, magnetotransport measurements suggest the sequence continues in trilayer graphene, with charge carriers that exhibit a Berry phase of 3 π . The linear dispersion of the low-energy electronic structure of monolayer graphene supports chiral quasiparticles that obey the relativistic Dirac equation and have a Berry phase of π (refs  1 , 2 ). In bilayer graphene 3 , the shape of the energy bands is quadratic, and its quasiparticles have a chiral degree, l =2, and a Berry phase of 2 π . These characteristics are usually determined from quantum Hall effect (QHE) measurements in which the Berry phase causes shifts in Shubnikov–de Haas (SdH) resistance oscillations. The QHE in graphene also exhibits an unconventional sequence of plateaux of Hall conductivity, σ x y , with quantized steps of 4 e 2 / h , except for the first plateau, where it is governed by the Berry phase. Here, we report magnetotransport measurements in ABC-stacked trilayer graphene, and their variation with carrier density, magnetic field and temperature. Our results provide the first evidence of the presence of l =3 chiral quasiparticles with cubic dispersion, predicted to occur in ABC-stacked trilayer graphene 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 . The SdH oscillations we observe suggest Landau levels with four-fold degeneracy, a Berry phase of 3 π , and the marked increase of cyclotron mass near charge neutrality. We also observe the predicted unconventional sequence of QHE plateaux, σ x y =±6 e 2 / h , ±10 e 2 / h , and so on.

HighlightsThe characteristics of Prussian blue analogues PBAs in different aqueous systems are analyzed.The relationship between structure and performance of PBAs is summarized.The measures to improve electrochemical property of PBAs are proposed.In the applications of large-scale energy storage, aqueous batteries are considered as rivals for organic batteries due to their environmentally friendly and low-cost nature. However, carrier ions always exhibit huge hydrated radius in aqueous electrolyte, which brings difficulty to find suitable host materials that can achieve highly reversible insertion and extraction of cations. Owing to open three-dimensional rigid framework and facile synthesis, Prussian blue analogues (PBAs) receive the most extensive attention among various host candidates in aqueous system. Herein, a comprehensive review on recent progresses of PBAs in aqueous batteries is presented. Based on the application in different aqueous systems, the relationship between electrochemical behaviors (redox potential, capacity, cycling stability and rate performance) and structural characteristics (preparation method, structure type, particle size, morphology, crystallinity, defect, metal atom in high-spin state and chemical composition) is analyzed and summarized thoroughly. It can be concluded that the required type of PBAs is different for various carrier ions. In particular, the desalination batteries worked with the same mechanism as aqueous batteries are also discussed in detail to introduce the application of PBAs in aqueous systems comprehensively. This report can help the readers to understand the relationship between physical/chemical characteristics and electrochemical properties for PBAs and find a way to fabricate high-performance PBAs in aqueous batteries and desalination batteries.

HighlightsZero capacity fading after over 3000 cycles at 1 C.Only 6.4% capacity is lost when rate is increased by 50 times.Diffusion mechanism of formation and fracture of hydrogen bonds is proposed.Aqueous ammonium ion batteries are regarded as eco-friendly and sustainable energy storage systems. And applicable host for NH4+ in aqueous solution is always in the process of development. On the basis of density functional theory calculations, the excellent performance of NH4+ insertion in Prussian blue analogues (PBAs) is proposed, especially for copper hexacyanoferrate (CuHCF). In this work, we prove the outstanding cycling and rate performance of CuHCF via electrochemical analyses, delivering no capacity fading during ultra-long cycles of 3000 times and high capacity retention of 93.6% at 50 C. One of main contributions to superior performance from highly reversible redox reaction and structural change is verified during the ammoniation/de-ammoniation progresses. More importantly, we propose the NH4+ diffusion mechanism in CuHCF based on continuous formation and fracture of hydrogen bonds from a joint theoretical and experimental study, which is another essential reason for rapid charge transfer and superior NH4+ storage. Lastly, a full cell by coupling CuHCF cathode and polyaniline anode is constructed to explore the practical application of CuHCF. In brief, the outstanding aqueous NH4+ storage in cubic PBAs creates a blueprint for fast and sustainable energy storage.