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In recent years, the sweet potato cultivar Jishu 25 has exhibited good characteristics for starch processing in northern China. The storage root dry matter yields of this cultivar can exceed one ton per mu (1/15 of a hectare) at nitrogen (N) rates of 60-90 kg ha-1 based on soil nutrient content. However, the effect of N fertilizer on the physicochemical properties of starches isolated from this cultivar has not been reported. In order to evaluate these effects, three different N rates, 0 (control, N0), 75 (N1), and 150 kg ha-1 (N2), were selected for a field experiment in 2017. The results showed that N1 exhibited the highest storage root yield and starch yield. Compared to the control group, N fertilizer significantly increased the total starch content while no significant difference was found in these between the N1 and N2 groups. The amylose (AM) content was highest in the N2 group and lowest in the N0 group. In addition, N fertilizer exhibited no significant effects on the values of [D(v, 0.9)], D [4, 3] and D [3, 2]. Compared to the control group, N1 demonstrated significantly higher setback viscosity (SV), while N2 showed significantly higher peak viscosity (PV), cold paste viscosity (CPV) and SV. However, there were no significant differences in the hot paste viscosity (HPV), peak time and pasting temperature between the N1 and N2 groups. For the thermal properties of starch, there were no significant differences in peak temperature (Tp), conclusion temperature (Tc) or gelatinization enthalpy (ΔH) between the N1 and N2 groups. Overall, for the starch samples of cultivar Jishu 25, N fertilizer exerts significant effects on the starch content, AM content and viscosity properties but little effect on the particle size distribution and ΔH. 75 kg N ha-1 can easily lead to substantial planting benefits from the high storage root yield, dry matter yield and total starch content of this cultivar.

Background Negative feelings, such as anxiety and depression, are common in patients with cancer. Our aim was to investigate the prevalence of malnutrition and distress in cancer patients and to examine the relationship between them. Materials and methods We did a cross-sectional study in West China hospital, China, using adapted questionnaires derived from Patient-Generated Subjective Global Assessment (PG-SGA), Nutritional Risk Screening 2002 (NRS2002) and Distress Thermometer (DT). We also focused on the factors associated with distress. Results We found that psychological distress in cancer patients was common, with 39.5% patients suffering from distress. The mean score of PG-SGA was 3.37 (0–6), and 39.1% patients had malnutrition when using 4 as a cut-off value. Meanwhile, the mean score of NRS2002 was 1.91 (0–11), and 25.8% patients presented with malnutrition when using 3 as the cut-off value. Higher scores of nutritional risks confirmed by PG-SGA ( r  = 0.148, p  < 0.001) and NRS2002 ( r  = 0.142, p  < 0.001) were significantly correlated with higher levels of psychological stress. Conclusion Malnutrition was correlated with psychological stress in cancer patients. Early intervention in the mental problems and nutrition was meaningful, which could improve the psychological statuses of cancer patients.

Ferroptosis, an iron-dependent regulated cell death mechanism, holds significant promise as a therapeutic strategy in oncology. In the current study, we explored the regulatory effects of epigallocatechin gallate (EGCG), a prominent polyphenol in green tea, on ferroptosis and its potential therapeutic implications for non-small cell lung cancer (NSCLC). Treatment of NSCLC cell lines with varying concentrations of EGCG resulted in a notable suppression of cell proliferation, as evidenced by a reduction in Ki67 immunofluorescence staining. Western blot analyses demonstrated that EGCG treatment led to a decrease in the expression of glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) while increasing the levels of acyl-CoA synthetase long-chain family member 4 (ACSL4). These molecular changes were accompanied by an increase in intracellular iron, malondialdehyde (MDA), and reactive oxygen species (ROS), alongside ultrastructural alterations characteristic of ferroptosis. Through small RNA sequencing and RT-qPCR, transfer RNA-derived small RNA 13502 (tsRNA-13502) was identified as a significant target of EGCG action, with its expression being upregulated in NSCLC tissues compared to adjacent non-tumorous tissues. EGCG was found to modulate the ferroptosis pathway by downregulating tsRNA-13502 and altering the expression of key ferroptosis regulators (GPX4/SLC7A11 and ACSL4), thereby promoting the accumulation of iron, MDA, and ROS, and ultimately inducing ferroptosis in NSCLC cells. This study elucidates EGCG’s multifaceted mechanisms of action, underscoring the modulation of ferroptosis as a viable therapeutic approach for enhancing NSCLC treatment outcomes.

Lung adenocarcinoma (LUAD) is a major cause of cancer-related mortality globally. Proliferating cells, crucial components of the tumor immune microenvironment (TIME), play a significant role in cancer progression and immunotherapy response. Herein, we utilized multi-omics data and employed a multifaceted approach to delineate the proliferating cell landscape in LUAD. The Scissor algorithm was applied to identify Scissor+ proliferating cell genes associated with prognosis. An integrative machine learning program, comprising 111 algorithms, was developed to construct a Scissor+ proliferating cell risk score (SPRS). The SPRS model demonstrated superior performance in predicting prognosis and clinical outcomes compared to 30 previously published models. The role of SPRS and five pivotal genes in immunotherapy response was evaluated, and their expression was experimentally verified. Multifactorial analysis confirmed SPRS as an independent prognostic factor affecting LUAD patient survival. High- and low-SPRS groups exhibited different biological functions and immune cell infiltration in the TIME. High SPRS patients showed resistance to immunotherapy but increased sensitivity to chemotherapeutic and targeted therapeutic agents. Our study elucidates the dynamics of proliferating cells in LUAD, enhancing prognostic accuracy and highlighting the potential of SPRS and its constituent genes for personalized therapeutic interventions.

To study the carbon components in indoor and outdoor PM 2.5 , the samples of PM 2.5 were collected from Nankai University in December 2015. The contents of eight carbon components were analyzed to use the thermo-optical reflection method. The results indicated that organic carbon (OC) mass concentration was 17.01, 19.48 and 18.92 µg/m 3 in outdoor, dormitory and laboratory; elemental carbon (EC) mass concentration was 7.97, 3.56 and 3.53 µg/m 3 in outdoor, dormitory and laboratory; and the total carbon aerosol was the proportion of more than 23% of PM 2.5 samples. Lower wind speed and higher relative humidity were helpful to the accumulation of PM 2.5 . The ratio of OC/EC was > 2, and the SOC/OC ratio was > 30%, indicating that SOC was a crucial component indoors and outdoors. About 72% and 85% of the outdoor OC entering dormitory and laboratory environment, and about 59% and 71% of the outdoor EC entering dormitory and laboratory environment. Factor analysis of the eight carbon fractions indicated that the sources of OC and EC in outdoor, dormitory and laboratory is different.

Background Accurately evaluating the water status of walnuts in different growth stages is fundamental to implementing deficit irrigation strategies and improving the yield of walnuts. The crop water stress index (CWSI) based on the canopy temperature is one of the most commonly used tools for current research on plant water monitoring. However, the suitability and effectiveness of using the CWSI as an indicator of the walnut water status under field conditions are still unclear. This paper focuses on walnut orchards in Northwest China using synchronous monitoring of the canopy temperature, meteorological parameters, and water physiological parameters of walnut trees under both full irrigation and deficit irrigation treatments. The aim is to test the effectiveness of the simplified crop water stress index (CWSI s ) and the theoretical crop water stress index (CWSI t ) in tracking the diurnal and daily variations of the water conditions in walnut orchards. Results The CWSI s can reflect the diurnal and daily changes in the water status of walnut orchards. It was found that the CWSI s at 12:00 local time had the best performance in tracking the daily changes in the water status. Compared to the daily averaged CWSI calculated using the measured transpiration (CWSI Tr_day ), the correlation coefficient, index of agreement, and root mean squared error between the CWSI s and CWSI Tr_day were 0.82, 0.94, and 0.11, respectively. However, due to the calculation errors of the aerodynamic resistance in walnut trees, the CWSI t was unable to track the diurnal variations in the water status in walnut orchards and the degree of water stress was underestimated. In addition, the variations in minimum canopy resistance in the various growth stages of walnut orchards may also affect the accuracy of the CWSI t in terms of indicating the seasonal changes in the water status. Conclusions The CWSI s provides a non-destructive, quickly and effective method for monitoring the water status of walnuts. However, the results of this study suggest that the effects of aerodynamic resistance parameterization and variations in minimum canopy resistance in the various growth stages of walnut orchards in the CWSI t calculation should be noted.

Juglans leaf necrosis (JLN) is a physiological disease primarily associated with abiotic stressors such as high temperatures, drought, and soil salinity, though biotic factors may also exacerbate its severity. It is a global concern affecting walnut production in multiple regions, including Xinjiang, China. In recent years, climate change, shifting agricultural practices, and disease transmission have increased its incidence, severely affecting tree growth, yield, and quality. Traditional field-based monitoring is labor-intensive and often inaccurate, underscoring the need for advanced remote sensing. To provide fast and objective monitoring, we used hyperspectral and high-resolution RGB imagery acquired by an unmanned aerial vehicle (UAV) to track JLN from June to September 2024 in southern Xinjiang. Five survey rounds captured the progression of disease severity. Among 17 vegetation indices, the modified red edge simple ratio (MRESRI), carotenoid reflectance index 1 (CRI1), and photochemical reflectance index (PRI) were the most informative for severity mapping. A Random Forest classifier achieved 86% overall accuracy and a Cohen’s kappa of 0.825. Spatial patterns showed persistent hotspots in low-lying areas, near roads, and in dense stands. These findings provide an effective, scalable approach for early detection and severity assessment, enabling timely, targeted interventions. Adoption of UAV-based hyperspectral monitoring can improve field surveillance, optimize resource allocation, and support sustainable walnut production.

What are the main findings? An efficient monitoring model integrating UAV hyperspectral imagery and machine learning was developed for detecting walnut leaf scorch. The Genetic Algorithm-optimized SVM model (GA-SVM) achieved the highest predictive performance (R[sup.2] = 0.6302, RMSE = 0.0629, MAE = 0.0480). What are the implications of the main findings? Offers a rapid and precise tool for the detection and precision management of walnut leaf scorch. The UAV-based approach enables site-specific disease detection, improves monitoring efficiency, and reduces reliance on costly manual ground surveys. Walnut (Juglans regia L.), a critical economic species, experiences substantial declines in fruit quality and yield due to Walnut Leaf Scorch (WLS). This issue is particularly severe in the Xinjiang Uygur Autonomous Region (XUAR)—one of Asia’s leading walnut-producing regions. To mitigate the disease, timely and efficient monitoring approaches for detecting infected trees and quantifying their disease severity are in urgent demand. In this study, we explored the feasibility of developing a predictive model for the precise quantification of WLS severity. First, five 4-mu (1 mu = 0.067 ha) sample plots were established to identify infected individual trees, from which the WLS Disease Index (DI) was calculated for each tree. Concurrently, hyperspectral data of individual trees were acquired via an unmanned aerial vehicle (UAV) platform. Second, DI estimation models were developed based on the Random Forest (RF) and Support Vector Machine (SVM) algorithms, with each algorithm optimized using either Grid Search (GS) or a Genetic Algorithm (GA). Finally, four integrated models (GS-RF, GA-RF, GS-SVM, and GA-SVM) were constructed and systematically compared. The results showed that the Genetic Algorithm-optimized SVM model (GA-SVM) exhibited the highest predictive accuracy and robustness, achieving a coefficient of determination (R[sup.2]) of 0.6302, a Root Mean Square Error (RMSE) of 0.0629, and a Mean Absolute Error (MAE) of 0.0480. Our findings demonstrate the great potential of integrating UAV-based hyperspectral remote sensing with optimized machine learning algorithms for WLS monitoring, thus offering a novel technical approach for the macroscopic, rapid, and non-destructive surveillance of this disease.

This work described the one-pot synthesis of orange pectin encapsulated Fe3O4 nanoparticles (Fe 3 O 4 @Pectin NPs) which is prepared by co-precipitation of Fe(II/(III) ions in alkaline solution mediated by pectin. This process led to formation of magnetic nanoparticles within the network of pectin. Physicochemical characterization of the as-synthesized Fe 3 O 4 @Pectin NPs was carried out through Fourier transformed infrared spectroscopy (FT-IR), electron microscopy (SEM and TEM), energy dispersive X-ray spectroscopy (EDX), vibrating sample magnetometer (VSM) and X-ray diffraction (XRD). The in vitro cytotoxic and anti-liver cancer effects of biologically synthesized Fe 3 O 4 @Pectin NPs against pleomorphic hepatocellular carcinoma (SNU-387), hepatic ductal carcinoma (LMH/2A), morris hepatoma (McA-RH7777), and novikoff hepatoma (N1-S1 Fudr) cancer cell lines were assessed. The anti-liver cancer properties of the Fe 3 O 4 @Pectin NPs could significantly remove pleomorphic hepatocellular carcinoma (SNU-387), hepatic ductal carcinoma (LMH/2A), morris hepatoma (McA-RH7777), and novikoff hepatoma (N1-S1 Fudr) cancer cell lines in a time and concentration-dependent manner by MTT assay. The IC 50 of the Fe 3 O 4 @Pectin NPs were 8, 13, 10, and 7 µg/mL against pleomorphic hepatocellular carcinoma (SNU-387), hepatic ductal carcinoma (LMH/2A), morris hepatoma (McA-RH7777), and novikoff hepatoma (N1-S1 Fudr) cancer cell lines. The antioxidant activity of Fe 3 O 4 @Pectin NPs was determined by DPPH method. The Fe 3 O 4 @Pectin NPs showed the high antioxidant activity according to the IC 50 value. It seems that the anti-human liver cancer effect of recent nanoparticles is due to their antioxidant effects.