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Spatial transcriptomics (ST) technologies allow for comprehensive characterization of gene expression patterns in the context of tissue microenvironment. However, accurately identifying domains with spatial coherence in both gene expression and histology in situ and effectively integrating data from multi-sample remains challenging. Here, we propose ResST, a graph self-supervised residual learning model based on graph neural network and Margin Disparity Discrepancy (MDD) theory. ResST aggregates gene expression, biological effects, spatial location, and morphological information to capture nonlinear relationships between a cell and surrounding cells for spatial domain identification. Also, ResST integrates multiple ST datasets and aligns latent embeddings based on MDD theory for correcting batch effects. Results show that ResST identifies continuous spatial domains at a finer scale in ten ST datasets acquired with different technologies. Moreover, ResST efficiently integrated data from multiple tissue sections vertically or horizontally while correcting batch effects. Overall, ResST demonstrates exceptional performance in analyzing ST datasets. A graph self-supervised residual learning framework (ResST) for natural domain identification and data integration of spatial transcriptomics. [ABSTRACT FROM AUTHOR]

Investigating factors involved in the alleviation of the toxic effects of heavy metals (HMs) on plants is regarded as one of the important research concerns in the environmental field. The southern regions of China are severely impacted by human-induced heavy metal (HM) contamination, which poses an impediment to growth and productivity of bamboo (Indocalamus latifolius) plants. This necessitates the investigation of the effects of HMs on growth and physiological properties of bamboo. Therefore, the aim of the study was to evaluate some gas exchange and growth parameters in two-year-old bamboo species under HMs stress. A greenhouse-based experiment was conducted at Nanjing Forestry University, where the bamboo plant was treated with three HMs (Cu, Pb, and Zn) at four different concentrations (0, 500, 1000, and 2000 mg kg-1). The results illustrated that excessive HMs (1000 and 2000 mg kg-1) triggered a decline in a number of photosynthetic-related indices including the rate of photosynthesis (μmol CO2 m-2 s-1), intercellular CO2 concentration (μmol CO2 mol-1), conductance to H2O (mol H2O m-2 s-1), and net assimilation as well as transpiration. Morphological indices were also depressed as a result of the adverse influence of HMs, leading to decreased shoot length (10 to 73%) and reduced number of emerged plants (6 to 57%). Also, the results indicated that Pb had the greatest harmful impact on the growth indices. [ABSTRACT FROM AUTHOR]

To investigate the effects of water column nutrient loading on epiphytic bacteria, we determined the abundance and community composition of epiphytic bacteria on the submerged macrophyte Vallisneria natans (Lour.) Hara during the growth season (June-October) under four different nutrient concentrations (nitrogen (N)-phosphorus (P) in mg L−1: 0.5-0.05, 1.0-0.1, 5.0-0.5, 10.0-1.0; hereafter NP-1, NP-2, NP-3, NP-4, respectively), using epifluorescence microscopy method and terminal restriction fragment length polymorphism (T-RFLP) analysis, respectively. Relative to low nutrient conditions (NP-1), there was no significant effect on the epiphytic bacterial community, and even a decrease in the number of epiphytic bacteria, which linked to the well growth status of host macrophytes at moderate nutrient conditions (NP-2). However, further nutrient enrichment induced significant increase in the abundance of epiphytic bacteria, and marked changes in the community structures of epiphytic bacteria. Furthermore, at high nutrient conditions, epiphytic bacterial communities varied widely temporally, and were not stable compared with those at the lower nutrient conditions. These results indicated that the effects of nutrient enrichment on epiphytic bacteria were nonlinear and dependent on the nutrient concentrations in the water. [ABSTRACT FROM AUTHOR]

A new fluorescence labeling reagent 2-(12-benzo[ b]acridin-5(12 H)-yl)-acetohydrazide (BAAH) has been designed for fatty acids labeling. Eleven fatty acids containing seven saturated and four unsaturated fatty acids were used to evaluate the analytical potential of this reagent. The labeling reaction of BAAH with fatty acids was completed at 85 °C for 60 min using 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide hydrochloride (EDC·HCl) as the condensing agent. Separation of the derivatized fatty acids was carried out on a reversed-phase Thermo Hypersil Gold C18 column (4.6 mm × 250 mm, 5 μm) in combination with a gradient elution with a good baseline resolution. The fluorescence excitation and emission wavelengths were set at λ 280 and λ 510 nm, respectively. The identification was carried out by the online APCI-MS in positive-ion detection mode. Linear correlation coefficients for all fatty acid derivatives were of >0.9994. Detection limits, at a signal-to-noise ratio of 3:1, were 3.89-12.5 nmol L for the labeled fatty acids. The developed method was successfully applied to the accurate determination of fatty acids in five traditional Chinese herbs with satisfactory results. [ABSTRACT FROM AUTHOR]

Bamboo forests cover a remarkable area of Chinese forestland. Recently, titanium dioxide nanoparticles (TiO2 NPs) have been used for plant protection against abiotic stress. In this study, an in vitro tissue culture experiment was conducted to determine the impact of titanium on plant tolerance to two different heavy metals (Cu and Pb). Bamboo plants (Arundinaria pygmaea L.) were grown using five concentrations of TiO2 NPS (0, 50, 80, 100, and 150 µM) without or with 100 µM Cu and 100 µM Pb for 30 days. The results showed that while Cu and Pb increased the generation of Reactive oxygen species (ROS) compounds in plants, TiO2 NP treatments played a positive role in reducing oxidative stress, as indicated by the decrease in ROS compounds, the extent of lipoperoxidation, and soluble proteins. On the other hand, the use of TiO2 NPs increased the total antioxidant capacity, chlorophyll content and general plant biomass. Moreover, the addition of TiO2 NPs significantly reduced Cu, and Pb accumulation in roots, stems, and shoots. We concluded that TiO2 NPs have the ability to reduce oxidative stress in plants by increasing the antioxidant capacity, improving the level of injury, and protecting cell membranes via reducing lipoperoxidation (reduction of Malondialdehyde (MDA) content). However, the results indicated that the efficiency of TiO2 NPs was related to the type and concentration of heavy metal, as TiO2 NPs were more effective for Cu than Pb. Additionally, a high concentration of TiO2 NPs resulted in the greatest enhancement in plant growth and development under heavy metal stress. [ABSTRACT FROM AUTHOR]

The recent emerging evidence reveals that titanium dioxide nanoparticles (TiO2 NPs) can be used as a wastewater treatment. This study provides new information about the possible detoxification role of TiO2 NPs as a wastewater treatment in plants under heavy metal stress, with an emphasis on the mechanisms involved. Here, we investigated the effects of TiO2 NPs as one wastewater treatment on a bamboo species (Arundinaria pygmaea L.) under in vitro Cadmium (Cd) toxicity conditions. A factorial experiment was conducted in a completely randomized design with four replications of four concentrations of Cd (50, 100, 200, and 300 µM) alone and in combination with 100 and 200 µM TiO2 NPs as two wastewater treatments, as well as a control treatment. The results indicated that TiO2 NPs concentrations enhanced enzymatic and non-enzymatic antioxidant activities and proline accumulation as well as reducing hydrogen peroxide (H2O2), superoxide radical (O2•−), and malondialdehyde (MDA) levels, which led to improved photosynthetic parameters with an eventual increase in plant biomass as compared to the control treatment. Therefore, TiO2 NPs improved the photosynthetic parameters of bamboo under Cd toxicity, which led to an increase in plant biomass. We concluded that the wastewater treatments of TiO2 NPs improved bamboo biomass through the scavenging of reactive oxygen species (ROS) compounds (H2O2 and O2•−), which was induced by the stimulation of the antioxidant capacity of the plant. TiO2 also protected cell membranes by reducing lipoperoxidation in bamboo under Cd toxicity. The concentration of 200 µM TiO2 NPs had the most impact in reducing Cd toxicity. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the relationship between the thickness of the uterine muscle layer at placenta attachment and postpartum hemorrhage, and to evaluate the predictive value of this thickness in identifying high-risk patients. It provides a theoretical basis for early identification and screening of pregnant women at high risk of postpartum hemorrhage, and reduces the occurrence of serious complications of postpartum hemorrhage., Method: A total of 378 pregnant women admitted to the Second People's Hospital of Shantou City from January to December 2021 were enrolled in this study. High-risk patients were defined as those with a uterine muscle layer thickness at placenta attachment greater than 2.5 cm, as measured by transabdominal ultrasound. Postpartum blood loss and hemoglobin changes were measured before and after delivery. Stratified analysis was conducted based on various patient characteristics, and the predictive value of the thickness was determined using ROC curve analysis. By providing the specific criteria for defining high-risk patients, readers can better understand the methodology used in this study., Results: The linear regression analysis showed a significant negative correlation between the thickness of the uterine muscle layer at placenta attachment and postpartum blood loss at 2 hours (t value = -6.9848, P = 1.33E-11 < .05). There was also a significant negative correlation between the thickness and hemoglobin changes before and after delivery (t value = -2.242, P = .026 < .05). These findings indicate a robust association between uterine muscle layer thickness and both postpartum blood loss and hemoglobin changes. ROC curve analysis revealed that the thickness of the uterine muscle layer at placenta attachment had predictive value for postpartum hemorrhage. This suggests that measuring the thickness of the uterine muscle layer can serve as a reliable predictor for identifying women at risk of postpartum hemorrhage. Additionally, stratified analysis showed that the thickness had significant predictive value in certain subgroups of patients., Conclusion: The findings of this study demonstrate that the thickness of the uterine muscle layer at placenta attachment is a critical indicator for predicting postpartum hemorrhage. Specifically, the study shows a robust negative correlation between uterine muscle layer thickness and postpartum blood loss, as well as significant predictive value for identifying high-risk patients for postpartum hemorrhage. These results have important practical implications for clinical practice. With early identification of high-risk groups based on uterine muscle layer thickness measurements, clinicians can implement interventions to reduce the incidence and severity of postpartum hemorrhage, which may lead to improved patient outcomes and reduced healthcare costs. Overall, this study provides a theoretical basis for the development of targeted prevention strategies and risk management protocols, which may help reduce serious complications of postpartum hemorrhage and improve maternal and neonatal health.