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Aims Sepsis‐associated encephalopathy (SAE) is a common but serious complication in septic survivors and often causes long‐term cognitive impairments. The role of RIPK3‐participated necroptosis in SAE remains obscured. STING is a key molecule in regulating necroptosis and apoptosis. However, there is uncertainty as to the mechanisms of STING in CLP‐induced SAE. The aim of this study was to investigate whether STING is involved in the underlying mechanism of SAE. Methods The contextual fear conditioning test (CFCT) assesses cognitive impairment. A transmission electron microscope (TEM) was used to notice the necroptosis. Western blotting and immunofluorescence labeling were applied for the observation of related proteins. Results The phosphorylated STING in the hippocampal neuron of SAE mice was significantly elevated. Knocking down STING inhibited necroptosis and attenuated cognitive impairment in SAE mice. Moreover, RIPK3−/− mice had less cognitive deficit in the SAE model. However, STING overexpression did not deteriorate cognitive impairment in RIPK3−/− mice with SAE, indicating that STING is upstream involved in necroptosis. Furthermore, PERK inhibition ameliorated cognitive deficits through a STING‐dependent pathway in SAE mice. Conclusion PERK‐STING‐RIPK3 pathway facilitates cognitive impairment by inducing neuronal necroptosis in the pathology of SAE, which provided a new therapeutic target in SAE treatment. This study is the first to elucidate the role of STING in SAE; additionally, the study demonstrates that the PERK‐STING‐RIPK3 pathway facilitates cognitive impairment by inducing neuronal necroptosis in the pathology of SAE, which provided a new therapeutic target in SAE treatment.

Recent studies have confirmed that increased intestinal permeability and gut-origin lipopolysaccharide (LPS) translocation are important causes of metabolic inflammation in type 2 diabetes (T2D), but there are no recognized therapies for targeting this pathological state. Scutellaria baicalensis and Coptis chinensis are a classic herbal pair often used to treat diabetes and various intestinal diseases, and repair of intestinal barrier damage may be at the core of their therapeutic mechanism. This study investigated the effects of oral administration of Scutellaria-Coptis (SC) on the intestinal mucosal barrier in diabetic rats and explored the underlying mechanism from the perspective of anti-inflammatory and gut microbiota-modulatory effects. The main results showed that, in addition to regulating glycolipid metabolism disorders and inhibiting serum inflammatory factors, SC could also upregulate the expression levels of the tight junction proteins claudin-1, occludin, and zonula occludens (ZO-1), significantly improve intestinal epithelial damage, and inhibit excessive LPS translocation into the blood circulation. Furthermore, it was found that SC could reduce the levels of the inflammatory factors interleukin-1β (IL-1β), IL-6, and tumour necrosis factor-α (TNF-α) in intestinal tissue and that the anti-inflammatory effects involved the TLR-4/TRIF and TNFR-1/NF-κB signalling pathways. Moreover, SC had a strong inhibitory effect on some potential enteropathogenic bacteria and LPS-producing bacteria, such as Proteobacteria, Enterobacteriaceae, Enterobacter, Escherichia-Shigella, and Enterococcus, and could also promote the proliferation of butyrate-producing bacteria, such as Lachnospiraceae and Prevotellaceae. Taken together, the hypoglycaemic effects of SC were related to the protection of the intestinal mucosal barrier, and the mechanisms might be related to the inhibition of intestinal inflammation and the regulation of the gut microbiota.

Soil moisture is a key environmental variable. There is a lack of software to facilitate non-specialists in estimating and analyzing soil moisture at the field scale. This study presents a new open-sourced R package mlhrsm, which can be used to generate Machine Learning-based high-resolution (30 to 500 m, daily to monthly) soil moisture maps and uncertainty estimates at selected sites across the contiguous USA at 0–5 cm and 0–1 m. The model is based on the quantile random forest algorithm, integrating in situ soil sensors, satellite-derived land surface parameters (vegetation, terrain, and soil), and satellite-based models of surface and rootzone soil moisture. It also provides functions for spatial and temporal analysis of the produced soil moisture maps. A case study is provided to demonstrate the functionality to generate 30 m daily to weekly soil moisture maps across a 70-ha crop field, followed by a spatial–temporal analysis.

Sepsis-associated encephalopathy (SAE) is defined as a syndrome of cerebral dysfunction secondary to sepsis but in the absence of direct central nervous system infection, structural abnormality, or other types of encephalopathy. The majority of clinical studies indicated that the severity and duration of SAE were highly related to the days of ICU stays, medical costs, and mortality of sepsis. Meanwhile, the persistence of cognitive impairments and psychological diseases in a majority of survived septic patients brings a heavy burden on those individuals and society. However, the pathogenesis of SAE has not been fully elucidated. A valid and unified diagnosis protocol, as well as effective remedy are still absent. The purpose of this narrative review is to discuss and update the current understanding of the clinical manifestations and risk factors, the recent findings and potential perspectives for the mechanism research, diagnostic methods, and treatments for SAE.

Sepsis-associated encephalopathy (SAE) is a serious complication of sepsis that is characterized by long-term cognitive impairment, which imposes a heavy burden on families and society. However, its pathological mechanism has not been elucidated. Ferroptosis is a novel form of programmed cell death that is involved in multiple neurodegenerative diseases. In the current study, we found that ferroptosis also participated in the pathological process of cognitive dysfunction in SAE, while Liproxstatin-1 (Lip-1) effectively inhibited ferroptosis and alleviated cognitive impairment. Additionally, since an increasing number of studies have suggested the crosstalk between autophagy and ferroptosis, we further proved the essential role of autophagy in this process and demonstrated the key molecular mechanism of the autophagy–ferroptosis interaction. Currently, we showed that autophagy in the hippocampus was downregulated within 3 days of lipopolysaccharide injection into the lateral ventricle. Moreover, enhancing autophagy ameliorated cognitive dysfunction. Importantly, we found that autophagy suppressed ferroptosis by downregulating transferrin receptor 1 (TFR1) in the hippocampus, thereby alleviating cognitive impairment in mice with SAE. In conclusion, our findings indicated that hippocampal neuronal ferroptosis is associated with cognitive impairment. In addition, enhancing autophagy can inhibit ferroptosis via degradation of TFR1 to ameliorate cognitive impairment in SAE, which shed new light on the prevention and therapy for SAE.

The gut microbiota, as an important factor affecting host health, plays a significant role in the occurrence and development of diabetes mellitus (DM), and the mechanism may be related to excessive endotoxins, altered short-chain fatty acids (SCFAs), and disordered bile acid metabolism. Traditional Chinese medicine (TCM) has a long history of treating DM, but its mechanism is not very clear. Recent research has suggested that Chinese herbal medicine can improve glucose metabolism by remodeling the gut microbiota, which opens new avenues for further research on hypoglycemic mechanisms. This review presents the recent progress of Chinese herbs, herbal extracts, and herbal compound preparations in treating DM through regulating the gut microbiota and summarizes the main mechanisms involved, namely, anti-inflammatory and antioxidative effects, protecting the intestinal barrier and inhibiting lipotoxicity. In addition, some suggestions for improvement are also proposed.

Record-breaking heatwaves caused by greenhouse effects lead to multiple hyperthermia disorders, the most serious of which is exertional heat stroke (EHS) with the mortality reaching 60 %. Repeat exercise with heat exposure, termed heat acclimation (HA), protects against EHS by fine-tuning feedback control of body temperature (Tb), the mechanism of which is opaque. This study aimed to explore the molecular and neural circuit mechanisms of the HA training against EHS. Male C57BL/6 mice (6-8 weeks) and male TRPV1-Cre mice (6-8 weeks) were used in our experiments. The EHS model with or without HA training were established for this study. RNA sequencing, qPCR, immunoblot, immunofluorescent assays, calcium imaging, optogenetic/ chemical genetic intervention, virus tracing, patch clamp, and other methods were employed to investigate the molecular mechanism and neural circuit by which HA training improves the function of the medial preoptic area (mPOA) neurons. Furthermore, a novel exosome-based strategy targeting the central nervous system to deliver irisin, a protective peptide generated by HA, was established to protect against EHS. HA-related neurons in the mPOA expressing transient receptor potential vanilloid-1 (TRPV1) were identified as a population whose activation reduces Tb; inversely, dysfunction of these neurons contributes to hyperthermia and EHS. mPOA neurons facilitate vasodilation and reduce adipose tissue thermogenesis, which is associated with their inhibitory projection to the raphe pallidus nucleus (RPa) and dorsal medial hypothalamus (DMH) neurons, respectively. Furthermore, HA improves the function of preoptic heat-sensitive neurons by enhancing TRPV1 expression, and ablation reverses the HA-induced heat tolerance. A central nervous system-targeted exosome strategy to deliver irisin, a protective peptide generated by HA, can promote preoptic TRPV1 expression and exert similar protective effects against EHS. Preoptic TRPV1 neurons could be enhanced by HA, actively contributing to heat defense through the mPOA\"DMH/RPa circuit during EHS, which results in the suppression of adipose tissue thermogenesis and facilitation of vasodilatation. A delivery strategy of exosomes engineered with RVG-Lamp2b-Irisin significantly improves the function of mPOA neurons, providing a promising preventive strategy for EHS in the future.

Organic matter pores are considered to be the most important type of pore for preserving hydrocarbon gases in shale gas reservoirs. The organic matter in each over-mature marine shale sample was separated into two organic fractions with densities of greater than and less than 1.25 g/cm 3, and then their molecular compositions and pore characteristics were quantitatively evaluated using solid state 13C-nuclear magnetic resonance (NMR) and gas (N 2 and CO 2) adsorption analyses, respectively. The results revealed that aromatic carbon is the dominant molecular composition of the over-mature organic matter in the Lower Cambrian Niutitang shale. During the over-mature stage, the organic fractions with densities of greater than and less than 1.25 g/cm 3 have no significant differences in molecular composition. The organic fractions with densities of greater than and less than 1.25 g/cm 3 do have significant differences in their organic pore characteristics. In contrast to the high density organic fraction, the low density fraction contained abundant micropores and lacked mesopores and macropores. The organic pore structures of the different occurrence states of organic matter were significantly different. The C/O of organic matter in different occurrence states are obviously different, which proves that the organic pore structure is closely related to both the occurrence state and density of the organic matter. However, these relationships are still unclear and require further study.

InP-based quantum dot light-emitting diodes (QLEDs), as less toxic than Cd-free and Pb-free optoelectronic devices, have become the most promising benign alternatives for the next generation lighting and display. However, the development of green-emitting InP-based QLEDs still remains a great challenge to the environmental preparation of InP quantum dots (QDs) and superior device performance. Herein, we reported the highly efficient green-emitting InP-based QLEDs regulated by the inner alloyed shell components. Based on the environmental phosphorus tris(dimethylamino)phosphine ((DMA)3P), we obtained highly efficient InP-based QDs with the narrowest full width at half maximum (~35 nm) and highest quantum yield (~97%) by inserting the gradient inner shell layer ZnSexS1−x without further post-treatment. More importantly, we concretely discussed the effect and physical mechanism of ZnSexS1–x layer on the performance of QDs and QLEDs through the characterization of structure, luminescence, femtosecond transient absorption, and ultraviolet photoelectron spectroscopy. We demonstrated that the insert inner alloyed shell ZnSexS1−x provided bifunctionality, which diminished the interface defects upon balancing the lattice mismatch and tailored the energy levels of InP-based QDs which could promote the balanced carrier injection. The resulting QLEDs applying the InP/ZnSe0.7S0.3/ZnS QDs as an emitter layer exhibited a maximum external quantum efficiency of 15.2% with the electroluminescence peak of 532 nm, which was almost the highest record of InP-based pure green-emitting QLEDs. These results demonstrated the applicability and processability of inner shell component engineering in the preparation of high-quality InP-based QLEDs.In this work, the pure green-emitting InP/ZnSexS1−x/ZnS quantum dots and their light-emitting diodes with high efficiency were successfully obtained by regulating the components of inner alloyed shell ZnSexS1−x layer.

Ocean color remote sensing technology has proven to be an indispensable tool for monitoring ocean conditions, as it has consistently provided critical data on global ocean optical properties, color, and biogeochemical parameters over several decades. With the rapid advancement of artificial intelligence, the integration of machine learning (ML) models into ocean color remote sensing has become a significant focus within the scientific community. This article provides a comprehensive review of the current status and challenges associated with ML models in ocean color remote sensing, assessing their applications in atmospheric correction, color inversion, carbon cycle analysis, and data reconstruction. This review highlights the advancements made in applying ML techniques, such as neural networks and deep learning, to improve data accuracy, enhance resolution, and enable more precise predictions of oceanic phenomena. Despite challenges such as model generalization and computational complexity, ML has significant potential for enhancing our understanding of marine ecosystems, facilitating real-time monitoring, and supporting global climate models.