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Acute ischemic stroke (AIS) is a major global health concern due to its high mortality and disability rates. Hemorrhagic transformation, a common complication of AIS, leads to poor prognosis yet lacks effective treatments. Preclinical studies indicate that hyperbaric oxygen (HBO) treatment within 12 h of AIS onset alleviates ischemia/reperfusion injuries, including hemorrhagic transformation. However, clinical trials have yielded conflicting results, suggesting some underlying mechanisms remain unclear. In this study, we confirmed that HBO treatments beginning within 1 h post reperfusion significantly alleviated the haemorrhage and neurological deficits in hyperglycemic transient middle cerebral arterial occlusion (tMCAO) mice, partly due to the inhibition of the NLRP3 inflammasome-mediated pro-inflammatory response in microglia. Notably, reactive oxygen species (ROS) mediate the anti-inflammatory and protective effect of early HBO treatment, as edaravone and N-Acetyl-L-Cysteine (NAC), two commonly used antioxidants, reversed the suppressive effect of HBO treatment on NLRP3 inflammasome-mediated inflammation in microglia. Furthermore, NAC countered the protective effect of early HBO treatment in tMCAO mice with hyperglycemia. These findings support that early HBO treatment is a promising intervention for AIS, however, caution is warranted when combining antioxidants with HBO treatment. Further assessments are needed to clarify the role of antioxidants in HBO therapy for AIS.

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Metal-organic frameworks, a type of porous architecture, have caught wide attention for their pore-rich and special metal-active centres. However, the non-conductive MOFs show limitations in lithium-sulfur batteries (LSBs). Herein, we first synthesized a lamellar nickel-based MOF and subsequently conducted pre-carbonization to attain a conductive Ni-carbon (Ni@C) catalyst. On account of the retained three-dimensional architecture and elevated conductivity, using Ni@C as the interlayer can realize polysulfide-regulated and kinetically promoted LSBs. This work offers a viable strategy to extend the implementation of MOFs in state-of-the-art LSB systems.

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Angiogenesis plays a pivotal role in the progression and metastasis of solid cancers, including prostate cancer (PCa). While small extracellular vesicles derived from PCa cell lines induce a proangiogenic phenotype in vascular endothelial cells, the contribution of plasma exosomes from patients with PCa to this process remains unclear. Here, we successfully extracted and characterized plasma exosomes. Notably, a ring of PKH67-labeled exosomes was observed around the HUVEC nucleus using fluorescence microscopy, indicating the uptake of exosomes by HUVEC. At the cellular level, PCa plasma exosomes enhanced angiogenesis, proliferation, invasion, and migration of HUVEC cells. Moreover, PCa plasma exosomes promoted angiogenesis and aortic sprouting. MicroRNAs are the most common genetic material in exosomes, and to identify miRNAs associated with the angiogenic response, we performed small RNA sequencing followed by RT-qPCR and bioinformatics analysis. These analyses revealed distinct miRNA profiles in plasma exosomes from patients with PCa compared to healthy individuals. Notably, hsa-miR-184 emerged as a potential regulator implicated in the proangiogenic effects of PCa plasma exosomes.

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Achieving Ohmic contacts with low resistance is quite desirable for two-dimensional (2D) Schottky barrier field effect transistors (SBFETs). We verify the electrode effect on monolayer (ML) SnS2 SBFETs using ab initio calculations. With the aforeselected ML electrodes from matching lattices and work functions, we obtain n-type Ohmic contacts or quasi-Ohmic contacts to ML SnS2 with ML 1T-NbTe2, Sc2NF2, Mo2NF2, Nb2CF2, and graphene electrodes. The n-type ML SnS2 SBFET with the Ohmic-contact 1T-NbTe2 electrode exhibits remarkably better device performance than that with a Schottky-contact 2H-NbTe2 electrode, and their on-state currents of 629/1048 µA µm-1, delay times of 0.236/0.169 ps, and power dissipations of 0.074/0.089 fJ µm-1 exceed the International Roadmap for Devices and Systems targets for low-power/high-performance application. This study reports on Ohmic-contact electrodes for n-type ML SnS2 SBFETs and can give hints for future theoretical and experimental studies on 2D SBFETs.

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The walnut cracking process is the most critical and delicate step for achieving high-quality kernels. The traditional method for cracking (manually) is labor-intensive, time-consuming, and tedious. The existing cracking approaches are low production efficiency and serious walnut kernel breakage. Increasing cracking efficiency with minimum kernel breakage has been a challenging issue in the preliminary processing of walnuts. Therefore, this study develops an innovative walnut cracker with self-grading and multi-station extrusion, combined with theoretical investigation and experiment verification. First, a statistical analysis of walnut physical properties was conducted, including dimensions, shell thickness as well as shape characteristics. The mechanical properties of walnut cracking were examined by a series of experiments. Based on mechanical theory, a grading mechanism was designed for preliminary processing before walnut cracking. Then a shaftless screw conveying mechanism and an extrusion cracking mechanism were developed. To evaluate the cracker's performance, a comprehensive examination was carried out. The experiments yielded impressive results, with a grading rate of 87.3%, a shell-breaking rate of 91.50%, and a kernel-exposed rate of 84.72%. These outcomes signify a substantial improvement in production efficiency while minimizing kernel breakage. The developed walnut cracker plays a crucial role in walnut processing and kernel extraction, thereby elevating economic value. PRACTICAL APPLICATION: A self-grading multi-station extrusion walnut cracker is developed, which includes a grading mechanism with a shaftless screw conveyor and a grid-type trommel screen for conveying and classifying walnuts. This cracker can adapt to different walnut varieties by changing the gap-adjusting guide to control the breaking gap. Compared to similar extrusion-type walnut crackers, the developed cracker not only incorporates preliminary classification but also exhibits superior performance. HIGHLIGHTS: A novel multi-station extrusion mechanism for walnuts cracking is developed. The cracker can accommodate various walnut sizes for self-grading and screening. The design with semi-arc plates converts extrusion force into alternating stress. The shell-breaking rate and kernel-exposed rate achieves 91.50% and 84.72%.

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BACKGROUND AND OBJECTIVE: Coronary artery segmentation is a pivotal field that has received increasing attention in recent years. However, this task remains challenging because of the inhomogeneous distributions of the contrast agent and dim light, resulting in noise, vascular breakages and small vessel losses in the obtained segmentation results. METHODS: To acquire better automatic blood vessel segmentation results for coronary angiography images, a UNet-based segmentation network (SARC-UNet) is constructed for coronary artery segmentation; this approach is based on residual convolution and spatial attention. First, we use the low-light image enhancement (LIME) approach to increase the contrast and clarity levels of coronary angiography images. Then, we design two residual convolution fusion modules (RCFM1 and RCFM2) that can successfully fuse the local and global information of coronary images while also capturing the characteristics of finer-grained blood vessels, hence preventing the loss of tiny blood vessels in the segmentation findings. Finally, using a cascaded waterfall structure, we create a new location-enhanced spatial attention (LESA) mechanism that can efficiently improve the long-distance dependencies between coronary vascular pixel features, eradicating vascular ruptures and noise in the segmentation results. RESULTS: This article subjectively and objectively evaluates the experimental results. This method has performed well on five general indicators. Furthermore, it outperforms the connectivity indicators proposed in this article. This method can effectively segment blood vessels and obtain higher accuracy results. CONCLUSIONS: Numerous experiments have shown that the suggested method outperforms the state-of-the-art approaches, particularly in terms of vessel connectivity and small blood vessel segmentation.

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VO2 affords ultrafast polysulfide adsorption on account of its oxidation potential, which matches the sulfur working window (1.7-2.8 V). Nevertheless, its nonconductive surface limits direct sulfur conversion. Herein, we gently load carbon quantum dots on VO2 to increase direct Li2S nucleation by enhanced electron conductivity. As a result, the soft-packaged lithium-sulfur pouch cell yields a capacity retention of 88.8% at 0.5C after 100 cycles and a decay rate of 0.17% per cycle over 200 cycles at 2C. The cell energy density of the multilayer cell is up to 386.1 W h kg-1.

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INTRODUCTION: This multi-center study aims to explore the roles of plasma exosomal microRNAs (miRNAs), ultrasound (US) radiomics, and total prostate-specific antigen (tPSA) levels in early prostate cancer detection. METHODS: We analyzed the publicly available dataset GSE112264 to identify the differentially expressed miRNAs associated with prostate cancer. Then, PyRadiomics was used to extract image features, and least absolute shrinkage and selection operator (LASSO) was used to screen the data. Subsequently, according to strict inclusion and exclusion criteria, the internal dataset (n = 199) was used to construct a diagnostic model, and the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and DeLong test were used to evaluate its diagnostic performance. Finally, we used an external dataset (n = 158) for further validation. RESULTS: The number of features extracted by PyRadiomics was 851, and the number of features screened by LASSO was 23. We combined the hsa-miR-320c, hsa-miR-944, radiomics, and tPSA features to construct a joint model. The area under the ROC curve of the combined model was 0.935. In the internal validation, the area under the curve (AUC) of the training set was 0.943, and the AUC of the test set was 0.946. The AUC of the external data set was 0.910. The calibration curve and decision curve were consistent with the performance of the combined model. There was a significant difference in the prediction ability between the combined prediction model and the single index prediction model, indicating the high credibility and accuracy of the combined model in predicting PCa. CONCLUSIONS: The combined prediction model, consisting of plasma exosomal miRNAs (hsa-miR-320c and hsa-miR-944), US radiomics, and clinical tPSA, can be utilized for the early diagnosis of prostate cancer.

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Purpose: Although brain metastasis (BM) from gastric cancer (GC) is relatively uncommon, its incidence has been increasing owing to advancements in treatment modalities. Unfortunately, patients diagnosed with BM from gastric cancer have poor life expectancy. Our study aims to establish a predictive model for brain metastasis in advanced gastric cancer patients, thus enabling the timely diagnosis of brain metastasis. Patients and Methods: The clinicopathological features of a cohort which included 40 GC patients with brain metastasis, 32 of whom from the First Affiliated Hospital of Nanchang University, 2 from Gaoxin Branch of the First Affiliated Hospital of Nanchang University, remaining 6 from Anyang District Hospital, and 80 non-metastatic advanced GC patients from the First Affiliated Hospital of Nanchang University between 2018 and 2022. Data were retrospectively analyzed. Results: Age, tumor size, differentiation, lymph node grade, tumor location, Lauren classification, liver metastasis, carbohydrate antigen 199 (CA199), lactate dehydrogenase (LDH), and human epidermal growth factor receptor 2 (Her-2) were associated with BM. A nomogram integrated with nine risk factors (tumor size, differentiation, lymph node grade, tumor location, Lauren classification, liver metastasis, CA-199, LDH, and Her-2) showed good performance (Area Under Curve 0.95, 95% CI: 0.91-0.98). Conclusion: We developed and validated a nomogram that achieved individualized prediction of the possibility of BM from GC. This model enables personalized imaging review schedules for timely brain metastasis detection in advanced gastric cancer patients.

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PURPOSE: To investigate the associations between the most popular social media platform WeChat usage and cognitive performance among the middle-aged and older Chinese population using data from a nationally representative survey. METHODS: In total, 17,472 participants (≥ 45 years old) from the China Health and Retirement Longitudinal Study (CHARLS, Wave 4, 2018) were analyzed. Cognitive performance including episodic memory and executive function was assessed using Mini-Mental Status Examination (MMSE). Other confounding variables included socio-economic characteristics, medical status, and lifestyle-related information. Multiple linear regression models were used to test the association between cognitive performance and WeChat usage by introducing covariates hierarchically. Subgroup analyses of age and gender were conducted to estimate the robustness of the primary findings. RESULTS: After adjusting for multiple confounders across all linear models, WeChat usage is significantly associated with executive function, episodic memory, and global cognitive performance (all p values<0.05). Such results remained robust in subgroup analyses, stratified by age and gender, and also verified according to longitudinal analyses. Compared to 'Chat-only' users who only used WeChat for online interpersonal communication, further usage of WeChat functions such as using 'Moments' appeared to be significantly associated with better cognitive performance, especially for episodic memory. CONCLUSION: Social media usage is significantly and positively associated with better cognitive performance among the middle-aged and older Chinese population. Along with point-to-point messaging, using 'Moments' and extended social media platform functions may correlate to better cognitive performance.

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Grooming, as an evolutionarily conserved repetitive behavior, is common in various animals, including humans, and serves essential functions including, but not limited to, hygiene maintenance, thermoregulation, de-arousal, stress reduction, and social behaviors. In rodents, grooming involves a patterned and sequenced structure, known as the syntactic chain with four phases that comprise repeated stereotyped movements happening in a cephalocaudal progression style, beginning from the nose to the face, to the head, and finally ending with body licking. The context-dependent occurrence of grooming behavior indicates its adaptive significance. This review briefly summarizes the neural substrates responsible for rodent grooming behavior and explores its relevance in rodent models of neuropsychiatric disorders and neurodegenerative diseases with aberrant grooming phenotypes. We further emphasize the utility of rodent grooming as a reliable measure of repetitive behavior in neuropsychiatric models, holding promise for translational psychiatry. Herein, we mainly focus on rodent self-grooming. Allogrooming (grooming being applied on one animal by its conspecifics via licking or carefully nibbling) and heterogrooming (a form of grooming behavior directing towards another animal, which occurs in other contexts, such as maternal, sexual, aggressive, or social behaviors) are not covered due to space constraints.

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Soybean quality and production are determined by seed viability. A seed's capacity to sustain germination via dry storage is known as its seed life. Thus, one of the main objectives for breeders is to preserve genetic variety and gather germplasm resources. However, seed quality and germplasm preservation have become significant obstacles. In this study, four artificially simulated aging treatment groups were set for 0, 24, 72, and 120 hours. Following an aging stress treatment, the transcriptome and metabolome data were compared in two soybean lines with notable differences in seed vigor-R31 (aging sensitive) and R80 (aging tolerant). The results showed that 83 (38 upregulated and 45 downregulated), 30 (19 upregulated and 11 downregulated), 90 (52 upregulated and 38 downregulated), and 54 (25 upregulated and 29 downregulated) DEGs were differentially expressed, respectively. A total of 62 (29 upregulated and 33 downregulated), 94 (49 upregulated and 45 downregulated), 91 (53 upregulated and 38 downregulated), and 135 (111 upregulated and 24 downregulated) differential metabolites accumulated. Combining the results of transcriptome and metabolome investigations demonstrated that the difference between R31 and R80 responses to aging stress was caused by genes related to phenylpropanoid metabolism pathway, which is linked to the seed metabolite caffeic acid. According to this study's preliminary findings, the aging-resistant line accumulated more caffeic acid than the aging-sensitive line, which improved its capacity to block lipoxygenase (LOX) activity. An enzyme activity inhibition test was used to demonstrate the effect of caffeic acid. After soaking seeds in 1 mM caffeic acid (a LOX inhibitor) for 6 hours and artificially aging them for 24 hours, the germination rates of the R31 and R80 seeds were enhanced. In conclusion, caffeic acid has been shown to partially mitigate the negative effects of soybean seed aging stress and to improve seed vitality. This finding should serve as a theoretical foundation for future research on the aging mechanism of soybean seeds.

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The agriculture Internet of Things (IoT) has been widely applied in assisting pear farmers with pest and disease prediction, as well as precise crop management, by providing real-time monitoring and alerting capabilities. To enhance the effectiveness of agriculture IoT monitoring applications, clustering protocols are utilized in the data transmission of agricultural wireless sensor networks (AWSNs). However, the selection of cluster heads is a NP-hard problem, which cannot be solved effectively by conventional algorithms. Based on this, This paper proposes a novel AWSNs clustering model that comprehensively considers multiple factors, including node energy, node degree, average distance and delay. Furthermore, a novel high-performance cluster protocol based on Gaussian mutation and sine cosine firefly algorithm (GSHFA-HCP) is proposed to meet the practical requirements of different scenarios. The innovative Gaussian mutation strategy and sine-cosine hybrid strategy are introduced to optimize the clustering scheme effectively. Additionally, an efficient inter-cluster data transmission mechanism is designed based on distance between nodes, residual energy, and load. The experimental results show that compared with other four popular schemes, the proposed GSHFA-HCP protocol has significant performance improvement in reducing network energy consumption, extending network life and reducing transmission delay. In comparison with other protocols, GSHFA-HCP achieves optimization rates of 63.69%, 17.2%, 19.56%, and 35.78% for network lifespan, throughput, transmission delay, and packet loss rate, respectively.

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As the weak link in electro-optical imaging systems, photodetectors have always faced the threat of laser damage. In this paper, we experimentally investigated the damage mechanism of the photodetector induced by the out-of-band laser. The damage thresholds of the mid-infrared pulsed laser for Charge Coupled Device (CCD) and HgCdTe detectors were determined through damage experiments. The analysis of the damage phenomena and data for both CCD and HgCdTe detectors clearly demonstrated that out-of-band mid-infrared pulsed lasers could entirely incapacitate CCD and HgCdTe detectors. Our analysis of the damage process and data revealed that the primary mechanism of damage to CCD and HgCdTe detectors by mid-infrared pulsed lasers was primarily thermal. This study serves as a reference for further research on the mid-infrared pulsed laser damage mechanisms of CCD and HgCdTe detectors, as well as for laser protection and performance optimization in imaging systems.

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Global climate change has led to shifts in the distribution ranges of many terrestrial species, promoting their migration from lower altitudes or latitudes to higher ones. Meanwhile, successful invaders have developed genetic adaptations enabling the colonization of new environments. Over the past 40 years, Rattus tanezumi (RT) has expanded into northern China (Northwest and North China) from its southern origins. We studied the cold adaptation of RT and its potential for northward expansion by comparing it with sympatric Rattus norvegicus (RN), which is well adapted to cold regions. Through population genomic analysis, we revealed that the invading RT rats have split into three distinct populations: the North, Northwest, and Tibetan populations. The first two populations exhibited high genetic diversity, while the latter population showed remarkably low genetic diversity. These rats have developed various genetic adaptations to cold, arid, hypoxic, and high-UV conditions. Cold acclimation tests revealed divergent thermoregulation between RT and RN. Specifically, RT exhibited higher brown adipose tissue activity and metabolic rates than did RN. Transcriptome analysis highlighted changes in genes regulating triglyceride catabolic processes in RT, including Apoa1 and Apoa4, which were upregulated, under selection and associated with local adaptation. In contrast, RN showed changes in carbohydrate metabolism genes. Despite the cold adaptation of RT, we observed genotypic and phenotypic constraints that may limit its ability to cope with severe low temperatures farther north. Consequently, it is less likely that RT rats will invade and overlap with RN rats in farther northern regions.

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Microplastics (MPs), found in many places around the world, are thought to be more detrimental than other forms of plastics. At present, physical, chemical, and biological methods are being used to break down MPs. Compared with physical and chemical methods, biodegradation methods have been extensively studied by scholars because of their advantages of greenness and sustainability. There have been numerous reports in recent years summarizing the microorganisms capable of degrading MPs. However, there is a noticeable absence of a systematic summary on the technology for breeding strains that can degrade MPs. This paper summarizes the strain-breeding technology of MP-degrading strains for the first time in a systematic way, which provides a new idea for the breeding of efficient MP-degrading strains. Meanwhile, potential techniques for breeding bacteria that can degrade MPs are proposed, providing a new direction for selecting and breeding MP-degrading bacteria in the future. In addition, this paper reviews the sources and pollution status of soil MPs, discusses the current challenges related to the biodegradation of MPs, and emphasizes the safety of MP biodegradation.

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In recent years, heavy metal pollution has become increasingly prominent, severely damaging ecosystems and biodiversity, and posing a serious threat to human health. However, the results of current methods for heavy metal restoration are not satisfactory, so it is urgent to find a new and effective method. Peptides are the units that make up proteins, with small molecular weights and strong biological activities. They can effectively repair proteins by forming complexes, reducing heavy metal ions, activating the plant's antioxidant defense system, and promoting the growth and metabolism of microorganisms. Peptides show great potential for the remediation of heavy metal contamination due to their special structure and properties. This paper reviews the research progress in recent years on the use of peptides to remediate heavy metal pollution, describes the mechanisms and applications of remediation, and provides references for the remediation of heavy metal pollution.

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Since industrialization, global temperatures have continued to rise. Human activities have resulted in heavy metals being freed from their original, fixed locations. Because of global warming, glaciers are melting, carbon dioxide concentrations are increasing, weather patterns are shifting, and various environmental forces are at play, resulting in the movement of heavy metals and alteration of their forms. In this general context, the impact of heavy metals on ecosystems and organisms has changed accordingly. For most ecosystems, the levels of heavy metals are on the rise, and this rise can have a negative impact on the ecosystem as a whole. Numerous studies have been conducted to analyze the combined impacts of climate change and heavy metals. However, the summary of the current studies is not perfect. Therefore, this review discusses how heavy metals affect ecosystems during the process of climate change from multiple perspectives, providing some references for addressing the impact of climate warming on environmental heavy metals.

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Diazinon, an organophosphorus insecticide, is predominantly removed through photodegradation and biodegradation in the environment. However, photodegradation can generate diazoxon, a highly toxic oxidation byproduct, while biodegradation is hard to complete mineralize diazinon, showing limitations in both methods. In this study, we provided an efficient strategy for the complete and harmless removal of diazinon by synergistically employing biodegradation and photodegradation. The diazinon-degrading strain X1 was capable of completely degrading 200 µM of diazinon into 2-isopropyl-6-methyl-4-pyrimidinol (IMP) within 6 h without producing the highly toxic diazoxon. IMP was the only intermediate metabolite in biodegradation process, which cannot be further degraded by strain X1. Through RT-qPCR and prokaryotic expression analyses, the hydrolase OpdB was pinpointed as the key enzyme for diazinon degradation in strain X1. Photodegradation was further used to degrade IMP and a pyridazine ring-opening product of IMP was identified via high resolution mass spectrometry. The acute toxicity of this product to aquatic organisms were 123 times and 6630 times lower than that of diazinon and IMP, respectively. The stepwise application of biodegradation and photodegradation was proved to be a successful approach for the remediation of diazinon and its metabolite IMP. This integrated method ensures the harmless and complete elimination of diazinon and IMP within only 6 h. The research provides a theoretical basis for the efficient and harmless remediation of organophosphorus insecticide residuals in the environment.

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Mining activities in the kaolin mining area have led to the disruption of the ecological health of the mining area and nearby soils, but the effects on the fungal communities in the rhizosphere soils of the plants are not clear. Three common plants (Conyza bonariensis, Artemisia annua, and Dodonaea viscosa) in kaolin mining areas were selected and analyzed their rhizosphere soil fungal communities using ITS sequencing. The alpha diversity indices (Chao1, Shannon, Simpson, observed-species, pielou-e) of the fungal communities decreased to different extents in different plants compared to the non-kauri mining area. The ß-diversity (PCoA, NMDS) analysis showed that the rhizosphere soil fungal communities of the three plants in the kaolin mine area were significantly differentiated from those of the control plants grown in the non-kaolin mine area, and the extent of this differentiation varied among the plants. The analysis of fungal community composition showed that the dominant fungi in the rhizosphere fungi of C. bonariensis and A. annua changed, with an increase in the proportion of Mycosphaerella (genus) by about 20% in C. bonariensis and A. annua. An increase in the proportion of Didymella (genus) by 40% in D. viscosa was observed. At the same time, three plant rhizosphere soils were affected by kaolin mining activities with the appearance of new fungal genera Ochrocladosporium and Plenodomus. Predictive functional potential analysis of the samples revealed that a significant decrease in the potential of functions such as biosynthesis and glycolysis occurred in the rhizosphere fungal communities of kaolin-mined plants compared to non-kaolin-mined areas. The results show that heavy metals and plant species are the key factors influencing these changes, which suggests that selecting plants that can bring more abundant fungi can adapt to heavy metal contamination to restore soil ecology in the kaolin mining area.