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Objective This study aims to elucidate the mechanisms by which nanovesicles (NVs) transport curcumin(CUR) across the blood–brain barrier to treat hypothalamic neural damage induced by heat stroke by regulating the expression of poly(c)-binding protein 2 (PCBP2). Methods Initially, NVs were prepared from macrophages using a continuous extrusion method. Subsequently, CUR was loaded into NVs using sonication, yielding engineered cell membrane Nanovesicles loaded with curcumin (NVs-CUR), which were characterized and subjected to in vitro and in vivo tracking analysis. Evaluations included assessing the toxicity of NVs-CUR using the MTT assay, evaluating neuroprotection of NVs-CUR against H 2 O 2 -induced oxidative stress damage in PC12 cells, examining effects on cell morphology and quantity, and detecting ferroptosis-related markers through Western blot and transmission electron microscopy (TEM). Proteomic analysis was conducted on PC12 cells treated with NVs (n = 3) and NVs-CUR (n = 3) to identify downstream key factors. Subsequently, the expression of key factors was modulated, and rescue experiments were performed to validate the impact of NVs-CUR through the regulation of key factor expression. Furthermore, a mouse model of hypothalamic neural damage induced by heat stroke was established, where CUR, NVs-CUR, and ferroptosis inducer Erastin were administered to observe mouse survival rates, conduct nerve function deficit scoring, perform histological staining, and measure levels of inflammation and oxidative stress factors in hypothalamic tissue. Results NVs-CUR was successfully prepared with excellent stability, serving as an advantageous drug delivery system that effectively targets brain injury sites or neurons both in vitro and in vivo. Subsequent in vitro cell experiments demonstrated the biocompatibility of NVs-CUR, showing superior protective effects against H 2 O 2 -induced PC12 cell damage and reduced ferroptosis compared to CUR. Moreover, in the mouse model of hypothalamic neural damage induced by heat stroke, NVs-CUR exhibited enhanced therapeutic effects. Proteomic analysis revealed that NVs-CUR exerted its effects through the regulation of key protein PCBP2; silencing PCBP2 reversed the protective effect of NVs-CUR on neural damage and its inhibition of ferroptosis. Additionally, NVs-CUR regulated solute carrier family 7 member 11 (SLC7A11) expression by PCBP2; overexpression of SLC7A11 reversed the promotion of neural damage and ferroptosis by silencing PCBP2. Animal experiments indicated that ferroptosis inducers reversed the improved survival and nerve function observed with NVs-CUR, silencing PCBP2 reversed the ameliorative effects of NVs-CUR on hypothalamic neural injury induced by heat stroke, and overexpression of SLC7A11 further reversed the adverse effects of silencing PCBP2 on hypothalamic neural injury induced by heat stroke. This suggests that NVs-CUR alleviates hypothalamic neural damage induced by heat stroke by targeting the PCBP2/SLC7A11 axis to reduce neuronal ferroptosis. Conclusion This study successfully developed engineered cell membrane NVs-CUR with neuron-targeting properties. NVs-CUR increased the expression of PCBP2, maintained the stability of SLC7A11 mRNA, reduced ferroptosis, and ultimately alleviated hypothalamic neuroinflammation induced by heatstroke. Graphical Abstract

The normalized difference vegetation index (NDVI) can depict the status of vegetation growth and coverage in grasslands, whereas coarse spatial resolution, cloud cover, and vegetation phenology limit its applicability in fine-scale research, especially in areas covering various vegetation or in fragmented landscapes. In this study, a methodology was developed for obtaining the 30 m annual maximum NDVI to overcome these shortcomings. First, the Landsat NDVI was simulated by fusing Landsat and MODIS NDVI by using the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), and then a single-peaked symmetric logistic model was employed to fit the Landsat NDVI data and derive the maximum NDVI in a year. The annual maximum NDVI was then used as a season-independent substitute to monitor grassland variation from 2001 to 2022 in a typical area covering the major vegetation types in the Qinghai Lake Basin. The major conclusions are as follows: (1) Our method for reconstructing the NDVI time series yielded higher accuracy than the existing dataset. The root mean square error (RMSE) for 91.8% of the pixels was less than 0.1. (2) The annual maximum NDVI from 2001 to 2022 exhibited spatial distribution characteristics, with higher values in the northern and southern regions and lower values in the central area. In addition, the earlier vegetation growth maximum dates were related to the vegetation type and accompanied by higher NDVI maxima in the study area. (3) The overall interannual variation showed a slight increasing trend from 2001 to 2022, and the degraded area was characterized as patches and was dominated by Alpine kobresia spp., Forb Meadow, whose change resulted from a combination of permafrost degradation, overgrazing, and rodent infestation and should be given more attention in the Qinghai Lake Basin.

The rapid proliferation of agricultural applications (apps) in China’s digital village initiative necessitates systematic evaluation of their functionality and accessibility. Regarding the agricultural pest control apps that can be searched in the Chinese market, this study collected and analyzed information using 18 variables, involving developers, languages, application systems, identified objects and functions. There were 158 apps that met the 11 mandatory features, and most of the applications were developed for Android and iOS systems. The functions, accuracy, response time and goals of agricultural apps are all important factors affecting the download and application of agricultural apps. Identification apps are in the initial stage, while comprehensive application apps are gradually increasing. Regional or National, even of crop-specific pest management apps are becoming mainstream. Case studies of prominent Chinese apps provide critical services such as disease diagnosis, pest control recommendations, and farm management solutions, leading to quantifiable benefits including reduced pesticide use, decreased crop losses, and increased farmer income in China. Agricultural applications accessible via smartphones have great potential in preventing crop losses and reducing pesticide use. The development of agricultural pest and disease control applications still has a long way to go, including precise assessment and potential risks during the implementation process. There is no doubt that against the backdrop of the continuous growth of the global population, these applications will facilitate the digital prevention and control of agricultural pests.

The simulation and prediction of coastline changes are of great significance for the development and scientific management of coastal zones. Coastline changes are difficult to capture completely but appear significantly periodic over a long time series. In this paper, the transformer model is used to learn the changing trend of the coastline so as to deduce the position of the coastline in the coming year. First, we use the distance regularization level set evolution (DRLSE) model for instantaneous waterline extraction (IWE) from preprocessed Landsat time-series images from 2010–2020 in Weitou Bay, China. Then, tidal correction (TC) is performed on the extracted instantaneous waterline dataset to obtain coastlines projected to a single reference tidal datum. Finally, the coastline datasets from 2010–2019 are used for model training, and the coastline in 2020 is used for accuracy assessment. Three precision evaluation methods, including receiver operating characteristic curve matching, the mean offset, and the root mean square error, were used to verify the predicted coastline data. The receiver operating characteristic curve was specifically designed and improved to evaluate the accuracy of the obtained coastline. Compared with the support vector regression (SVR) and long–short-term memory (LSTM) methods, the results showed that the coastline predicted by the transformer model was the closest to the accurate extracted coastline. The accuracies of the correct values corresponding to SVR, LSTM, and transformer models were 88.27%, 94.08%, and 98.80%, respectively, which indicated the accuracy of the coastline extraction results. Additionally, the mean offset and root mean square error were 0.32 pixels and 0.57 pixels, respectively. In addition, the experimental results showed that tidal correction is important for coastline prediction. Moreover, through field investigations of coastlines, the predicted results obtained for natural coastlines were more accurate, while the predicted results were relatively poor for some artificial coastlines that were intensely influenced by human activities. This study shows that the transformer model can provide natural coastline changes for coastal management.

Skin blood flux (SkBF) changes caused by drinking cold water are generally associated with vagal tone and osmotic factors in the digestive system. However, there is still a lack of relevant research on whether there are left and right differences in these SkBF change. In the current study, a total of 60 subjects were recruited. Skin blood perfusion of the bilateral lower extremities was recorded simultaneously before and after drinking saline of different temperatures saline by using Laser Doppler flowmetry (LDF). The electrogastrogram (EGG) was also monitored, and the dominant frequency of the EGG and heart rate variability were analyzed. The results indicated that after drinking saline, the laterality index of SkBF at the lower extremities was different and the laterality index changes of SkBF were mainly reflected in the frequency interval V (0.4–1.6 Hz). There was a weak negative correlation between the laterality index of endothelial NO-dependent component and change rate of root mean square of successive differences (RMSSD) after drinking 4 °C saline. However, after drinking 30 °C saline, there was a weak positive correlation between neurogenic component and RMSSD The distribution and regulation of bilateral blood flow are not symmetrical but exhibit a certain laterality.

Studying the variation in vegetation types within the source region of the Yellow River (SRYR) is of great significance for understanding the response of vegetation to climate change and human activities on the Qinghai-Tibet Plateau (QTP) permafrost. In order to understand the characteristics of the variation in vegetation associations in the SRYR under the influence of climate and human activities, two hyperspectral remote sensing images from HJ-1A in 2013 and OHS-3C in 2020 were used to extract the vegetation types located in the area south of Ngoring Lake, covering 437.11 km2 in Maduo County, from the perspective of vegetation associations. Here, the hybrid spectral CNN (HybridSN) model, which is dependent on both spatial and spectral information, was used for vegetation association classifications. On this basis, the variations in vegetation associations from 2013 to 2020 were studied using the transition matrix, and the variation in noxious weeds across different altitude and slope gradients was analyzed. As an example, Thermopsis lanceolata’s spatial distribution pattern and diffusion mechanism were analyzed. The results showed that (1) in addition to noxious weeds, herbage such as Poa poophagorum, Stipa purpurea, Kobresia humilis, and Carex moorcroftii increased, indicating that the overall ecological environment tended to improve, which may be attributed mainly to the development of a warm and humid climate. (2) Most of the noxious weeds were located at low altitudes with an area increase in the 4250–4400 m altitude range and a decrease in the 4400–4500 m altitude range. More attention should be given to the fact that the noxious weeds area increased from 2.88 km2 to 9.02 km2 between 2013 and 2020, which was much faster than that of herbage and may threaten local livestock development. (3) The Thermopsis lanceolate association characterized by an aggregated distribution tended to spread along roads, herdsmen sites, and degraded swamps, which were mainly affected by human activities and swamp degradation.

Polyculture is an effective way to achieve efficient utilization of nutrient resources in high-density intensive aquaculture systems. In order to study the optimal culture mode of Oreochromis niloticu, Aristichthys nobilis, and Cherax quadricarinatus, the budget of nitrogen and phosphorus in various polyculture systems (CH, CHC1, CHC2, CHC3) was studied with land-based enclosures. The results showed that all the three polyculture systems had higher total yields of cultured animals than the control group (two polyculture systems) (p < 0.05). The co-cultured organisms absorbed artificial feed or organic matter (such as plankton and sediment) from the polyculture system to different degrees. Feed was the main input of nitrogen (98.22–98.33%) and phosphorus (99.43–99.56%) in all systems. Considering the N and P outputs, 46.64–64.58% and 81.60–84.79%, respectively, accumulated in the sediment, and 34.43–52.55% and 14.89–17.30% of the N and P outputs, respectively, were harvested by aquaculture organisms. The pollution production coefficients of TN and TP in the O. niloticus polyculture ponds were 5.35–6.26 g/m2 and 1.17–1.61 g/m2, respectively. The TN production coefficients of O. niloticus and the ternary polyculture groups (CHC1, CHC2, and CHC3) were lower than that of the control group (CH). The TP production coefficients showed the opposite pattern. The N and P utilization efficiencies in the group with the optimal ratio of O. niloticus, A. nobilis, and C. quadricarinatus (4, 0.15, and 3 ind/m2, respectively) were 2.56–12.82% and 6.62–11.03% higher, respectively, compared with those of the other groups. The N utilization efficiency was effectively improved in this group with the optimum stocking density for the polyculture systems, resulting in improved ecological efficiency and economic benefits.

This study aimed to establish a traumatic hemorrhagic shock (THS) model in swine and examine pathophysiological characteristics in a dry-heat environment. Forty domestic Landrace piglets were randomly assigned to four study groups: normal temperature non-shock (NS), normal temperature THS (NTHS), desert dry-heat non-shock (DS), and desert dry-hot THS (DTHS) groups. The groups were exposed to either normal temperature (25°C) or dry heat (40.5°C) for 3 h. To induce THS, anesthetized piglets in the NTHS and DTHS groups were subjected to liver trauma and hypovolemic shock until death, and piglets in the NS and DS groups were euthanized at 11 h and 4 h, respectively. Body temperature, blood gas, cytokine production, and organ function were assessed before and after environmental exposure at 0 h and at every 30 min after shock to death. Hemodynamics was measured post exposure and post-shock at 0 h and at every 30 min after shock to death. Survival, body temperature, oxygen delivery, oxygen consumption, and cardiac output were significantly different for traumatic hemorrhagic shock in the dry-heat groups compared to those in the normal temperature groups. Lactic acid and IL-6 had a marked increase at 0.5 h, followed by a progressive and rapid increase in the DTHS group. Our findings suggest that the combined action of a dry-heat environment and THS leads to higher oxygen metabolism, poorer hemodynamic stability, and earlier and more severe inflammatory response with higher mortality.

Microcystin-LR (MC-LR) is a cyanobacterial metabolite produced during cyanobacterial blooms and is toxic to aquatic animals, and the liver is the main targeted organ of MC-LR. To comprehensively understand the toxicity mechanism of chronic exposure to environmental levels of MC-LR on the liver of fish, juvenile Nile tilapia were exposed to 0 μg/L (control), 1 μg/L (M1), 3 μg/L (M3), 10 μg/L (M10), and 30 μg/L (M30) MC-LR for 60 days. Then, the liver hepatotoxicity induced by MC-LR exposure was systematically evaluated via histological and biochemical determinations, and the underlying mechanisms were explored through combining analysis of biochemical parameters, multi-omics (transcriptome and metabolome), and gene expression. The results exhibited that chronic MC-LR exposure caused slight liver minor structural damage and lipid accumulation in the M10 group, while resulting in serious histological damage and lipid accumulation in the M30 group, indicating obvious hepatotoxicity, which was confirmed by increased toxicity indexes (i.e., AST, ALT, and AKP). Transcriptomic and metabolomic analysis revealed that chronic MC-LR exposure induced extensive changes in gene expression and metabolites in six typical pathways, including oxidative stress, apoptosis, autophagy, amino acid metabolism, primary bile acid biosynthesis, and lipid metabolism. Taken together, chronic MC-LR exposure induced oxidative stress, apoptosis, and autophagy, inhibited primary bile acid biosynthesis, and caused fatty deposition in the liver of Nile tilapia.

The upper reaches of the Taojia River have been impacted by unregulated logging linked to non-ferrous metal mining, resulting in significant mineral waste accumulation. Composting has shown promise in reducing heavy metal (HM) contamination in agricultural soils. This study included two segments: the first examined the effects of sheep manure (SM) and chicken manure (CM) with different concentrations on lead (Pb) dynamics in vegetable soils. The second applied the most effective method identified in segment one to assess Pb, cadmium (Cd), zinc (Zn), and copper (Cu) in soil, paddy, and straw in rice fields. Results showed that both compost types increased soil pH to mildly alkaline levels, with SM causing dose-dependent rises (insignificant between 2% and 5%) and CM inducing non-proportional alkalinity. CM compost significantly enhanced soil organic matter (SOM: 0.606–0.660 g/kg) compared to SM (0.414–0.495 g/kg). Total nitrogen (TN) spiked at 2% SM (0.172 g/kg) but plateaued until 10% SM (0.210 g/kg), while CM linearly increased TN with dosage. Total phosphorus (TP) rose proportionally with SM but remained unchanged under CM. For Pb immobilization, 5% SM reduced DTPA-Pb to 11.877 mg/kg, but 10% SM increased it (14.006 mg/kg), whereas 10% CM achieved optimal passivation (11.561 mg/kg). Correlation analyses linked compost dosage to SOM, TP, and available Pb (p < 0.05), with soil pH showing minimal direct influence. In rice fields, 10% CM elevated soil pH (7.10 vs. 6.71), TP, and total Zn/Cu/Pb/Cd but reduced Pb/Cd in paddy and straw. Heavy metal speciation revealed strong inter-state correlations (excluding exchangeable Pb), with soil pH and TP significantly influencing Zn, Cu, and Cd levels. These findings demonstrate CM compost’s dual role in improving fertility and mitigating Pb/Cd uptake, though Zn/Cu accumulation risks require careful management.