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Abstract Background Gender is a significant risk factor for late-onset Alzheimer’s disease (AD), often attributed to the decline of estrogen. The plant estrogen secoisolariciresinol diglucoside (SDG) has demonstrated anti-inflammatory and neuroprotective effects. However, the protective effects and mechanisms of SDG in female AD remain unclear. Methods Ten-month-old female APPswe/PSEN1dE9 (APP/PS1) transgenic mice were treated with SDG to assess its potential ameliorative effects on cognitive impairments in a female AD model through a series of behavioral and biochemical experiments. Serum levels of gut microbial metabolites enterodiol (END) and enterolactone (ENL) were quantified using HPLC-MS. Correlation analysis and broad-spectrum antibiotic cocktail (ABx) treatment were employed to demonstrate the involvement of END and ENL in SDG’s cognitive improvement effects in female APP/PS1 mice. Additionally, an acute neuroinflammation model was constructed in three-month-old C57BL/6J mice treated with lipopolysaccharide (LPS) and subjected to i.c.v. injection of G15, an inhibitor of G protein-coupled estrogen receptor (GPER), to investigate the mediating role of the estrogen receptor GPER in the cognitive benefits conferred by SDG. Results SDG administration resulted in significant improvements in spatial, recognition, and working memory in female APP/PS1 mice. Neuroprotective effects were observed, including enhanced expression of CREB/BDNF and PSD-95, reduced β-amyloid (Aβ) deposition, and decreased levels of TNF-α, IL-6, and IL-10. SDG also altered gut microbiota composition, increasing serum levels of END and ENL. Correlation analysis indicated significant associations between END, ENL, cognitive performance, hippocampal Aβ-related protein mRNA expression, and cortical neuroinflammatory cytokine levels. The removal of gut microbiota inhibited END and ENL production and eliminated the neuroprotective effects of SDG. Furthermore, GPER was found to mediate the inhibitory effects of SDG on neuroinflammatory responses. Conclusion These findings suggest that SDG promotes the production of gut microbial metabolites END and ENL, which inhibit cerebral β-amyloid deposition, activate GPER to enhance CREB/BDNF signaling pathways, and suppress neuroinflammatory responses. Consequently, SDG exerts neuroprotective effects and ameliorates cognitive impairments associated with AD in female mice.

Tunnelling has increasingly become an essential tool in the exploration of underground space. A typical construction problem is the face instability during tunnelling, posing a great threat to associated infrastructures. Tunnel face instability often occurs with the soil arching collapse. This study investigates the combined effect of cutterhead opening ratio and soil non-uniformity on soil arching effect and face stability, via conducting random finite-element analysis coupled with Monte–Carlo simulations. The results underscore that the face stability is strongly associated with the evolution of stress arch. The obtained stability factors in the uniform soils can serve as a reference for the design of support pressure in practical tunnelling engineering. In addition, non-uniform soils exhibit a lower stability factor than uniform soils, which implies that the latter likely yields an underestimated probability of face failure. The tunnel face is found to have a probability of failure more than 50% if the spatial non-uniformity of soil is ignored. In the end, a practical framework is established to determine factor of safety (FOS) corresponding to different levels of probability of face failure considering various opening ratios in non-uniform soils. The required FOS is 1.70 to limit the probability of face instability no more than 0.1%. Our findings can facilitate the prediction of probability of instability in the conventionally deterministic design of face pressure.

Abstract Background Dysfunction of cholesterol metabolism may be associated with low skeletal muscle mass. This study aimed to explore the relationship between skeletal muscle mass and cholesterol metabolic disorders in adults. Methods The data of a total of 5949 people with complete medical history data, biochemical data and body composition analysis were recruited. According to the serum cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL) and nonHDL, the population was divided into a disorder group and a normal group. Independent sample t tests, chi-square tests, Pearson's correlation analyses and binary logistic regression analyses were used to study the effect of body composition on abnormal cholesterol metabolism. According to BMI and sex, the population was divided into different subgroups, and binary logistic regression analysis was used to study the effect of the skeletal mass ratio on cholesteral metabolic disorders in different subgroups. Results There were significant differences in sex, alcohol consumption, body weight, BMI, skeletal muscle mass index (SMI) [total skeletal muscle mass (kg)/height 2 (m2)] and skeletal muscle mass ratio (SMR) [total skeletal muscle mass (kg)/weight (kg) *100] between the disorder group (hypercholesterolemia, hyper-LDL, lower-HDL and hyper-nonHDL) and the normal group. Pearson correlation analysis revealed that the SMR was negatively correlated, while the SMI was positively correlated with cholesterol metabolic disorders in both sexes. The overweight group was older and had a greater SMI, abnormal cholesteral metabolism ratio and lower SMR than the normal-weight group. In the normal-weight group, the SMR was an independent protective factor against different kinds of cholesteral metabolic disorders in both sexes, while the SMI was a risk factor. In the overweight subgroup, the protective effect on HDL and nonHDL metabolism remained in the male subgroup but disappeared in the female subgroup. However, the SMI was an independent risk factor for different kinds of cholesteral metabolic disorders in both sexes. Conclusions SMR was an independent protective factor against cholesterol metabolic disorders in both males and females, especially in the normal weight group. SMI was an independent risk factor, especially in the overweight group.

Abstract Pazopanib (PAZ), an oral multi-tyrosine kinase inhibitor, demonstrates promising cytostatic activities against various human cancers. However, its clinical utility is limited by substantial side effects and therapeutic resistance. We developed a nanoplatform capable of delivering PAZ for enhanced anti-breast cancer therapy. Nanometer-sized PAZ@Fe-MOF, compared to free PAZ, demonstrated increased anti-tumor therapeutic activities in both syngeneic murine 4T1 and xenograft human MDA-MB-231 breast cancer models. High-throughput single-cell RNA sequencing (scRNAseq) revealed that PAZ@Fe-MOF significantly reduced pro-tumorigenic M2-like macrophage populations at tumor sites and suppressed M2-type signaling pathways, such as ATF6-TGFBR1-SMAD3, as well as chemokines including CCL17, CCL22, and CCL24. PAZ@Fe-MOF reprogramed the inhibitory immune microenvironment and curbed tumorigenicity by blocking the polarization of M2 phenotype macrophages. This platform offers a promising and new strategy for improving the cytotoxicity of PAZ against breast cancers. It provides a method to evaluate the immunological response of tumor cells to PAZ-mediated treatment.

Abstract Exploring the promiscuity of native enzymes presents a promising strategy for expanding their synthetic applications, particularly for catalyzing challenging reactions in non-native contexts. In this study, we explore the promiscuous potential of old yellow enzymes (OYEs) to facilitate the Morita-Baylis-Hillman reaction (MBH reaction), leveraging substrate similarities between MBH reaction and reduction reaction. Using mass spectrometry and spectroscopic techniques, we confirm promiscuity of GkOYE in both MBH and reduction reactions. By blocking H- and H+ transfer pathways, we engineer GkOYE.8, which loses its reduction ability but enhances its MBH activity. The structural basis of MBH reaction catalyzed by GkOYE.8 is obtained through mutation studies and kinetic simulations. Furthermore, enantiocomplementary mutants GkOYE.11 and GkOYE.13 are obtained by directed evolution, exhibiting the ability to accept various aromatic aldehydes and alkenes as substrates. This study demonstrates the potential of leveraging substrate similarities to unlock enzyme functionalities, enabling the catalysis of new-to-nature reactions.

Abstract Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

Abstract The mechanical properties of rocks in cold regions undergo significant changes as a result of decades of freeze‒thaw cycles with seasonal variations, which can lead to a series of geological disasters, such as collapse. This study investigates the evolution of the mechanical characteristics and internal progressive damage characteristics of mixed granite under freeze‒thaw cycling and axial loading. By measuring the mass, wave velocity, and uniaxial compressive strength of rock samples and combining these metrics with acoustic emission (AE) characteristics, the physical and mechanical properties and microfracture development of mixed granite after different numbers of freeze‒thaw cycles were investigated. The results indicate that as the number of freeze‒thaw cycles increases, the longitudinal wave velocity, uniaxial compressive strength, and elastic modulus of the mixed granite decrease nonlinearly, while the peak strain gradually increases. Combined with the stress‒strain curve, the AE characteristics can be divided into four stages. As the number of freeze‒thaw cycles increases, the AE cumulative count decreases, and the AE counts of the four stages are different. The low-frequency-high-amplitude signals first increases and then tends to stabilize, and they only appeared in the third and fourth stages. At the same time, the proportion of the low-frequency ratio gradually increases, and the proportion of the high-frequency ratio decreases. In addition, based on the rise time/amplitude (RA) and average frequency (AF) characteristics and failure modes, it was found that the internal crack types of mixed granite transition from shear cracks to tensile cracks, among which tensile cracks play a crucial role in rock failure.

Based on the latest results of near-source exploration in the Middle and Lower Jurassic of the Tuha Basin, a new understanding of the source rocks, reservoir conditions, and source-reservoir-cap rock combinations of the Jurassic Shuixigou Group in the Taibei Sag is established using the concept of the whole petroleum system, and the coal-measure whole petroleum system is analyzed thoroughly. The results are obtained in three aspects. First, the coal-measure source rocks of the Badaowan Formation and Xishanyao Formation and the argillaceous source rocks of the Sangonghe Formation in the Shuixigou Group exhibit the characteristics of long-term hydrocarbon generation, multiple hydrocarbon generation peaks, and simultaneous oil and gas generation, providing sufficient oil and gas sources for the whole petroleum system in the Jurassic coal-bearing basin. Second, multi-phase shallow braided river delta–shallow lacustrine deposits contribute multiple types of reservoirs, e.g. sandstone, tight sandstone, shale and coal rock, in slope and depression areas, providing effective storage space for the petroleum reservoir formation in coal-measure strata. Third, three phases of hydrocarbon charging and structural evolution, as well as effective configuration of multiple types of reservoirs, result in the sequential accumulation of conventional-unconventional hydrocarbons. From high structural positions to depression, there are conventional structural and structural-lithological reservoirs far from the source, low-saturation structural-lithological reservoirs near the source, and tight sandstone gas, coal rock gas and shale oil accumulations within the source. Typically, the tight sandstone gas and coal rock gas are the key options for further exploration, and the shale oil and gas in the depression area is worth of more attention. The new understanding of the whole petroleum system in the coal measures could further enrich and improve the geological theory of the whole petroleum system, and provide new ideas for the overall exploration of oil and gas resources in the Tuha Basin.

Abstract Renal cell carcinoma, a leading cause of death in urological malignancies, arises from the nephron. Its characteristics include diversity in disease biology, varied clinical behaviors, different prognoses, and diverse responses to systemic therapies. The term ‘organoids’ is used to describe structures resembling tissues created through the three-dimensional cultivation of stem cells in vitro. These organoids, when derived from tumor tissues, can retain the diversity of the primary tumor, mirror its spatial tissue structure, and replicate similar organ-like functions. In contrast to conventional two-dimensional cell cultures and the transplantation of tumor tissues into other organisms, organoids derived from tumors maintain the complexity and microenvironment of the original tumor tissue. This fidelity makes them a more reliable model for the development of cancer drugs, potentially accelerating the translation of these drugs to clinical use and facilitating personalized treatment options for patients. This review aims to summarize the recent advancements in the use of organoids for studying renal cell carcinoma, focusing on their cultivation, potential applications, and inherent limitations.

Abstract Background Mammalian intestine harbors a mass of phages that play important roles in maintaining gut microbial ecosystem and host health. Pig has become a common model for biomedical research and provides a large amount of meat for human consumption. However, the knowledge of gut phages in pigs is still limited. Results Here, we investigated the gut phageome in 112 pigs from seven pig breeds using PhaBOX strategy based on the metagenomic data. A total of 174,897 non-redundant gut phage genomes were assembled from 112 metagenomes. A total of 33,487 gut phage genomes were classified and these phages mainly belonged to phage families such as Ackermannviridae, Straboviridae, Peduoviridae, Zierdtviridae, Drexlerviridae, and Herelleviridae. The gut phages in seven pig breeds exhibited distinct communities and the gut phage communities changed with the age of pig. These gut phages were predicted to infect a broad range of 212 genera of prokaryotes, such as Candidatus Hamiltonella, Mycoplasma, Colwellia, and Lactobacillus. The data indicated that broad KEGG and CAZy functions were also enriched in gut phages of pigs. The gut phages also carried the antimicrobial resistance genes (ARGs) and the most abundant antimicrobial resistance genotype was diaminopyrimidine resistance. Conclusions Our research delineates a landscape for gut phages in seven pig breeds and reveals that gut phages serve as a key reservoir of ARGs in pigs. Video Abstract

Abstract Very high-resolution remote sensing images hold promising applications in ground observation tasks, paving the way for highly competitive solutions using image processing techniques for land cover classification. To address the challenges faced by convolutional neural network (CNNs) in exploring contextual information in remote sensing image land cover classification and the limitations of vision transformer (ViT) series in effectively capturing local details and spatial information, we propose a local feature acquisition and global context understanding network (LFAGCU). Specifically, we design a multidimensional and multichannel convolutional module to construct a local feature extractor aimed at capturing local information and spatial relationships within images. Simultaneously, we introduce a global feature learning module that utilizes multiple sets of multi-head attention mechanisms for modeling global semantic information, abstracting the overall feature representation of remote sensing images. Validation, comparative analyses, and ablation experiments conducted on three different scales of publicly available datasets demonstrate the effectiveness and generalization capability of the LFAGCU method. Results show its effectiveness in locating category attribute information related to remote sensing areas and its exceptional generalization capability. Code is available at https://github.com/lzp-lkd/LFAGCU .

Oncolytic viruses (OVs), a group of replication-competent viruses that can selectively infect and kill cancer cells while leaving healthy cells intact, are emerging as promising living anticancer agents. Unlike traditional drugs composed of non-replicating compounds or biomolecules, the replicative nature of viruses confer unique pharmacokinetic properties that require further studies. Despite some pharmacokinetics studies of OVs, mechanistic insights into the connection between OV pharmacokinetics and antitumor efficacy remain vague. Here, we characterized the pharmacokinetic profile of oncolytic virus M1 (OVM) in immunocompetent mouse tumor models and identified the JAK‒STAT pathway as a key modulator of OVM pharmacokinetics. By suppressing the JAK‒STAT pathway, early OVM pharmacokinetics are ameliorated, leading to enhanced tumor-specific viral accumulation, increased AUC and Cmax, and improved antitumor efficacy. Rather than compromising antitumor immunity after JAK‒STAT inhibition, the improved pharmacokinetics of OVM promotes T cell recruitment and activation in the tumor microenvironment, providing an optimal opportunity for the therapeutic outcome of immune checkpoint blockade, such as anti-PD-L1. Taken together, this study advances our understanding of the pharmacokinetic-pharmacodynamic relationship in OV therapy.

Abstract Chemotherapeutic agents can inhibit the proliferation of malignant cells due to their cytotoxicity, which is limited by collateral damage. Dihydroartemisinin (DHA), has a selective anti-cancer effect, whose target and mechanism remain uncovered. The present work aims to examine the selective inhibitory effect of DHA as well as the mechanisms involved. The findings revealed that the Lewis cell line (LLC) and A549 cell line (A549) had an extremely rapid proliferation rate compared with the 16HBE cell line (16HBE). LLC and A549 showed an increased expression of NRAS compared with 16HBE. Interestingly, DHA was found to inhibit the proliferation and facilitate the apoptosis of LLC and A549 with significant anti-cancer efficacy and down-regulation of NRAS. Results from molecular docking and cellular thermal shift assay revealed that DHA could bind to epidermal growth factor receptor (EGFR) molecules, attenuating the EGF binding and thus driving the suppressive effect. LLC and A549 also exhibited obvious DNA damage in response to DHA. Further results demonstrated that over-expression of NRAS abated DHA-induced blockage of NRAS. Moreover, not only the DNA damage was impaired, but the proliferation of lung cancer cells was also revitalized while NRAS was over-expression. Taken together, DHA could induce selective anti-lung cancer efficacy through binding to EGFR and thereby abolishing the NRAS signaling pathway, thus leading to DNA damage, which provides a novel theoretical basis for phytomedicine molecular therapy of malignant tumors.

Abstract Intervertebral disc degeneration (IDD) is a highly prevalent musculoskeletal disorder affecting millions of adults worldwide, but a poor understanding of its pathogenesis has limited the effectiveness of therapy. In the current study, we integrated untargeted LC/MS metabolomics and magnetic resonance spectroscopy data to investigate metabolic profile alterations during IDD. Combined with validation via a large-cohort analysis, we found excessive lipid droplet accumulation in the nucleus pulposus cells of advanced-stage IDD samples. We also found abnormal palmitic acid (PA) accumulation in IDD nucleus pulposus cells, and PA exposure resulted in lipid droplet accumulation and cell senescence in an endoplasmic reticulum stress-dependent manner. Complementary transcriptome and proteome profiles enabled us to identify solute carrier transporter (SLC) 43A3 involvement in the regulation of the intracellular PA level. SLC43A3 was expressed at low levels and negatively correlated with intracellular lipid content in IDD nucleus pulposus cells. Overexpression of SLC43A3 significantly alleviated PA-induced endoplasmic reticulum stress, lipid droplet accumulation and cell senescence by inhibiting PA uptake. This work provides novel integration analysis-based insight into the metabolic profile alterations in IDD and further reveals new therapeutic targets for IDD treatment.

Abstract Introduction Post liver transplantation (LT) patients endure high morbidity rate of multi-organ ischemic symptoms following reperfusion. We hypothesize that enhanced external counterpulsation (EECP) as a typical non-invasive assisted circulation procedure, which can efficiently inhibit the relative ischemic symptoms via the systemic improvement of hemodynamics. Case presentation A 51-year-old male patient, 76 kg, 172 cm, received orthotopic LT surgery for viral hepatitis B induced acute-on-chronic liver failure hepatic failure. His medical records revealed ischemic symptoms in multi-organ at the time of hospital discharge, including headache, refractory insomnia, abdominal paralysis, and lower limb pain. The EECP treatment was introduced for assisted rehabilitation and to improve the postoperative quality of life. Doppler Ultrasound examination showed significant augmentation of blood flow volume in the carotid arteries, the hepatic artery, the portal vein and the femoral artery during EECP intervention. A standard 35-hour EECP treatment led to significant improvement in quality of life, e.g. sleep quality and walking ability. Conclusion We report a case of multi-organ ischemic symptoms in a post LT patient. EECP treatment can significantly improve the quality of life via the systematic promotion of hemodynamics.

Repetitive implant-related infections (IRIs) are devastating complications in orthopedic surgery, threatening implant survival and even the life of the host. Biofilms conceal bacterial-associated antigens (BAAs) and result in a ''cold tumor''-like immune silent microenvironment, allowing the persistence of IRIs. To address this challenge, an iron-based covalent organic framed nanoadjuvant doped with curcumin and platinum (CFCP) was designed in the present study to achieve efficient treatment of IRIs by inducing a systemic immune response. Specifically, enhanced sonodynamic therapy (SDT) from CFCP combined with iron ion metabolic interference increased the release of bacterial-associated double-stranded DNA (dsDNA). Immunogenic dsDNA promoted dendritic cell (DC) maturation through activation of the stimulator of interferon gene (STING) and amplified the immune stimulation of neutrophils via interferon-β (IFN-β). At the same time, enhanced BAA presentation aroused humoral immunity in B and T cells, creating long-term resistance to repetitive infections. Encouragingly, CFCP served as neoadjuvant immunotherapy for sustained antibacterial protection on implants and was expected to guide clinical IRI treatment and relapse prevention.

Abstract Background Severe burns may alter the stability of the intestinal flora and affect the patient’s recovery process. Understanding the characteristics of the gut microbiota in the acute phase of burns and their association with phenotype can help to accurately assess the progression of the disease and identify potential microbiota markers. Methods We established mouse models of partial thickness deep III degree burns and collected faecal samples for 16 S rRNA amplification and high throughput sequencing at two time points in the acute phase for independent bioinformatic analysis. Results We analysed the sequencing results using alpha diversity, beta diversity and machine learning methods. At both time points, 4 and 6 h after burning, the Firmicutes phylum content decreased and the content of the Bacteroidetes phylum content increased, showing a significant decrease in the Firmicutes/Bacteroidetes ratio compared to the control group. Nine bacterial genera changed significantly during the acute phase and occupied the top six positions in the Random Forest significance ranking. Clustering results also clearly showed that there was a clear boundary between the communities of burned and control mice. Functional analyses showed that during the acute phase of burn, gut bacteria increased lipoic acid metabolism, seleno-compound metabolism, TCA cycling, and carbon fixation, while decreasing galactose metabolism and triglyceride metabolism. Based on the abundance characteristics of the six significantly different bacterial genera, both the XGboost and Random Forest models were able to discriminate between the burn and control groups with 100% accuracy, while both the Random Forest and Support Vector Machine models were able to classify samples from the 4-hour and 6-hour burn groups with 86.7% accuracy. Conclusions Our study shows an increase in gut microbiota diversity in the acute phase of deep burn injury, rather than a decrease as is commonly believed. Severe burns result in a severe imbalance of the gut flora, with a decrease in probiotics and an increase in microorganisms that trigger inflammation and cognitive deficits, and multiple pathways of metabolism and substance synthesis are affected. Simple machine learning model testing suggests several bacterial genera as potential biomarkers of severe burn phenotypes.

Abstract Fast computational ghost imaging with high quality and ultra-high-definition resolution reconstructed images has important application potential in target tracking, biological imaging and other fields. However, as far as we know, the resolution (pixels) of the reconstructed image is related to the number of measurements. And the limited resolution of reconstructed images at low measurement times hinders the application of computational ghost imaging. Therefore, in this work, a new computational ghost imaging method based on saliency variable sampling detection is proposed to achieve high-quality imaging at low measurement times. This method physically variable samples the salient features and realizes compressed detection of computational ghost imaging based on the salient periodic features of the bucket detection signal. Numerical simulation and experimental results show that the reconstructed image quality of our method is similar to the compressed sensing method at low measurement times. Even at 500 (sampling rate $$0.76\%$$ 0.76 % ) measurement times, the reconstructed image of the method still has the target features. Moreover, the $$2160\times 4096$$ 2160 × 4096 (4K) pixels ultra-high-definition resolution reconstructed images can be obtained at only a sampling rate of $$0.11\%$$ 0.11 % . This method has great potential value in real-time detection and tracking, biological imaging and other fields.

Pectin is a vital component of plant cell walls and its methylation process is regulated by pectin methylesterase inhibitors (PMEIs). PMEIs regulate the structural and functional modifications of cell walls in plants and play an important role in plant processes such as seed germination, fruit ripening, and stress response. Although the PMEI gene family has been well characterized in model plants, the understanding of its molecular evolution and biological functions in watermelon remains limited. In this study, 60 ClPMEI genes were identified and characterized, revealing their dispersion on multiple chromosomes. Based on a systematic developmental analysis, these genes were classified into three subfamilies, which was further supported by the exon, intron, and conserved motif distribution. Analysis of cis-elements and expression patterns indicated that ClPMEIs might be involved in regulating the tolerance of watermelon to various abiotic stresses. Moreover, distinct ClPMEI genes exhibit specific functions under different abiotic stresses. For example, ClPMEI51 and ClPMEI54 showed a significant upregulation in expression levels during the late stage of drought treatments, whereas ClPMEI3 and ClPMEI12 displayed a significant downregulation under low-temperature induction. Subcellular localization prediction and analysis revealed that the ClPMEI family member proteins were localized to the cell membrane. This study provided an important foundation for the further exploration of the functions of ClPMEI genes in watermelon.

N6-methyladenosine (m6A) methylation is one of the most predominant internal RNA modifications in eukaryotes and has become a hot spot in the field of epigenetics in recent years. Cardiovascular diseases (CVDs) are a leading cause of death globally. Emerging evidence demonstrates that RNA modifications, such as the m6A modification, are associated with the development and progression of many diseases, including CVDs. An increasing body of studies has indicated that programmed cell death (PCD) plays a vital role in CVDs. However, the molecular mechanisms underlying m6A modification and PCD in CVDs remain poorly understood. Herein, elaborating on the highly complex connections between the m6A mechanisms and different PCD signaling pathways and clarifying the exact molecular mechanism of m6A modification mediating PCD have significant meaning in developing new strategies for the prevention and therapy of CVDs. There is great potential for clinical application.

PurposeGynecologic oncology laparotomy leads to severe postoperative pain. We aimed to evaluate the effects of preemptive multimodal analgesic regimen on postoperative opioid consumption for patients undergoing gynecologic oncology laparotomy.MethodsIn this prospective, randomized clinical trial, 80 female patients scheduled for gynecologic oncology laparotomy were randomized to receive preemptive multimodal analgesia consisted of transversus abdominis plane (TAP) block, cyclooxygenase−2 inhibitors, acetaminophen and intravenous morphine patient-controlled analgesia (PCA) (Study group) or conventional analgesia with cyclooxygenase−2 inhibitors and morphine PCA (Control group). The primary outcome was morphine consumption in the first 24 h after surgery. Secondary outcomes were pain scores, nausea, vomiting, time to ambulation and flatus, length of hospital stay, satisfaction score, the 40-item Quality of Recovery score (QoR-40) and the Short-Form Health Survey (SF-36) scale.ResultsMorphine consumption in the first 24 h was 6 (3–9.8) mg in the Study group and 7 (3.5–12.5) mg in the Control group (p = 0.222). The Study group showed lower morphine consumption up to 6 h, lower pain scores up to 48 h, and earlier time to ambulation and flatus. The global QoR-40 score at 48 h [182 (173–195) vs. 173.5 (154–185.5), p = 0.024], subdimension scores of physical dependence at 24 h, physical comfort and pain at 48 h were significantly improved in the Study group.ConclusionPreemptive multimodal analgesia was not superior to conventional analgesia in reducing 24 h morphine consumption; however, it showed a significantly improved pain control and early quality of recovery thus can be recommended for gynecologic oncology patients undergoing laparotomy.

BackgroundStable mild cognitive impairment (sMCI) and progressive mild cognitive impairment (pMCI) represent two distinct subtypes of mild cognitive impairment (MCI). Early and effective diagnosis and accurate differentiation between sMCI and pMCI are crucial for administering targeted early intervention and preventing cognitive decline. This study investigated the intrinsic dysconnectivity patterns in sMCI and pMCI based on degree centrality (DC) and effective connectivity (EC) analyses, with the goal of uncovering shared and distinct neuroimaging mechanisms between subtypes.MethodsResting-state functional magnetic resonance imaging combined with DC analysis was used to explore the functional connectivity density in 42 patients with sMCI, 31 patients with pMCI, and 82 healthy control (HC) participants. Granger causality analysis was used to assess changes in EC based on the significant clusters found in DC. Furthermore, correlation analysis was conducted to examine the associations between altered DC/EC values and cognitive function. Receiver operating characteristic curve analysis was performed to determine the accuracy of abnormal DC and EC values in distinguishing sMCI from pMCI.ResultsCompared with the HC group, both pMCI and sMCI groups exhibited increased DC in the left inferior temporal gyrus (ITG), left posterior cerebellum lobe (CPL), and right cerebellum anterior lobe (CAL), along with decreased DC in the left medial frontal gyrus. Moreover, the sMCI group displayed reduced EC from the right CAL to bilateral CPL, left superior temporal gyrus, and bilateral caudate compared with HC. pMCI demonstrated elevated EC from the right CAL to left ITG, which was linked to episodic memory and executive function. Notably, the EC from the right CAL to the right ITG effectively distinguished sMCI from pMCI, with sensitivity, specificity, and accuracy of 0.5806, 0.9512, and 0.828, respectively.ConclusionThis study uncovered shared and distinct alterations in DC and EC between sMCI and pMCI, highlighting their involvement in cognitive function. Of particular significance are the unidirectional EC disruptions from the cerebellum to the temporal lobe, which serve as a discriminating factor between sMCI and pMCI and provide a new perspective for understanding the temporal-cerebellum. These findings offer novel insights into the neural circuit mechanisms involving the temporal-cerebellum connection in MCI.

IntroductionInsomnia is a common comorbidity symptom in major depressive disorder (MDD) patients. Abnormal brain activities have been observed in both MDD and insomnia patients, however, the central pathological mechanisms underlying the co-occurrence of insomnia in MDD patients are still unclear. This study aimed to explore the differences of spontaneous brain activity between MDD patients with and without insomnia, as well as patients with different level of insomnia.MethodsA total of 88 first-episode drug-naïve MDD patients including 44 with insomnia (22 with high insomnia and 22 with low insomnia) and 44 without insomnia, as well as 44 healthy controls (HC), were enrolled in this study. The level of depression and insomnia were evaluated by HAMD-17, adjusted HAMD-17 and its sleep disturbance subscale in all subjects. Resting-state functional and structural magnetic resonance imaging data were acquired from all participants and then were preprocessed by the software of DPASF. Regional homogeneity (ReHo) values of brain regions were calculated by the software of REST and were compared. Finally, receiver operating characteristic (ROC) curves were conducted to determine the values of abnormal brain regions for identifying MDD patients with insomnia and evaluating the severity of insomnia.ResultsAnalysis of variance showed that there were significant differences in ReHo values in the left middle frontal gyrus, left pallidum, right superior frontal gyrus, right medial superior frontal gyrus and right rectus gyrus among three groups. Compared with HC, MDD patients with insomnia showed increased ReHo values in the medial superior frontal gyrus, middle frontal gyrus, triangular inferior frontal gyrus, calcarine fissure and right medial superior frontal gyrus, medial orbital superior frontal gyrus, as well as decreased ReHo values in the left middle occipital gyrus, pallidum and right superior temporal gyrus, inferior temporal gyrus, middle cingulate gyrus, hippocampus, putamen. MDD patients without insomnia demonstrated increased ReHo values in the left middle frontal gyrus, orbital middle frontal gyrus, anterior cingulate gyrus and right triangular inferior frontal gyrus, as well as decreased ReHo values in the left rectus gyrus, postcentral gyrus and right rectus gyrus, fusiform gyrus, pallidum. In addition, MDD patients with insomnia had decreased ReHo values in the left insula when compared to those without insomnia. Moreover, MDD patients with high insomnia exhibited increased ReHo values in the right middle temporal gyrus, and decreased ReHo values in the left orbital superior frontal gyrus, lingual gyrus, right inferior parietal gyrus and postcentral gyrus compared to those with low insomnia. ROC analysis demonstrated that impaired brain region might be helpful for identifying MDD patients with insomnia and evaluating the severity of insomnia.ConclusionThese findings suggested that MDD patients with insomnia had wider abnormalities of brain activities in the prefrontal-limbic circuits including increased activities in the prefrontal cortex, which might be the compensatory mechanism underlying insomnia in MDD. In addition, decreased activity of left insula might be associated with the occurrence of insomnia in MDD patients and decreased activities of the frontal–parietal network might cause more serious insomnia related to MDD.

BackgroundThe systemic immune-inflammation index (SII) is a novel inflammatory marker used to assess the immune-inflammatory status of the human body. The systemic immune inflammation has an interplay and mutual relationship with neurological disorders. Serum neurofilament light chain (sNfL) is widely regarded as a potential biomarker for various neurological diseases. The study aimed to examine the association between SII and sNfL.MethodsThis cross-sectional investigation was conducted in a population with complete data on SII and sNfL from the 2013–2014 National Health and Nutrition Examination Survey (NHANES). The SII was calculated by dividing the product of platelet count and neutrophil count by the lymphocyte count. Multivariate linear regression models and smooth curves were used to explore the linear connection between SII and sNfL. Sensitivity analyses, interaction tests, and diabetes subgroup smoothing curve fitting were also performed.ResultsA total of 2,025 participants were included in our present research. SII showed a significant positive association with the natural logarithm-transformed sNfL (ln-sNfL) in crude model [0.17 (0.07, 0.28)], partially adjusted model [0.13 (0.03, 0.22)], and fully adjusted model [0.12 (0.02, 0.22)]. In all participants, the positive association between SII and ln-sNfL served as a linear relationship, as indicated by a smooth curve. Interaction tests showed that age, gender, BMI, hypertension, and diabetes did not have a significant impact on this positive association (p for interaction >0.05). The subgroup analysis of diabetes was conducted using smooth curve fitting. It was found that compared to the group without diabetes and the group in a pre-diabetic state, the effect was more pronounced in the group with diabetes.ConclusionOur findings suggest that there is a positive association between SII and sNfL. Furthermore, in comparison to individuals without diabetes and those in a pre-diabetic state, the positive association between SII and sNfL was more pronounced in individuals with diabetes. Further large-scale prospective studies are needed to confirm the association between SII and sNfL.

IntroductionEmergent crises can have a catastrophic impact on regional economic systems. The concurrent outbreaks of African Swine Fever (ASF) and the COVID-19 pandemic have severely affected Macau’s pork industry, making it an interesting case study for analyzing the effects of simultaneous emergent crises on food prices.MethodsThe study utilized a comprehensive dataset spanning from March 30, 2018, to April 15, 2022. The analysis employed the Ensemble Empirical Mode Decomposition (EEMD) method to decompose the pork price data into high-frequency, low-frequency, and trend components, while the Bai-Perron test pinpointed key events and regulatory interventions affecting pork prices.ResultsThe findings revealed that short-term market fluctuations had a limited impact on pork price dynamics, with primary drivers being long-term and low-frequency emergencies. The Bai-Perron test identified four significant emergencies or regulatory policies as critical turning points, segmenting the price series into five distinct phases. The results highlight the importance of considering long-cycle emergencies when assessing their impact on food prices and underline the need for more resilient agricultural supply chains.DiscussionThe study provides insights into how compounded emergent crisis threats impact market behavior and offers policy recommendations for enhancing market stability. Recommendations include strengthening cross-regional epidemic control, investing in vaccine research, optimizing cold chain logistics, updating legal frameworks, and improving emergency preparedness. The implications of these findings are relevant for similar regions facing concurrent health and economic crises, contributing to a better understanding of crisis management and market stability maintenance.

Background: Aging is characterized by a decline in the adaptability and resistance of the body. In this study, Bushen Kangshuai Granules (BKG), as a kind of Chinese herbal formula, was developed and shown to alleviate aging-related symptoms.Methods: Self-controlled study combined with RNA-seq and metabonomics were used to expound the efficacy and safety of BKG and revealed the regulation mechanism of BKG treating aging. In vitro experiments were used to confirm the analytical results. The aging cell model of AC16 cells were treated with D-galactose. The RT-qPCR was used to detect the impact of BKG on telomere length. The DCFH-DA staining was used for detecting intracellular ROS. The targeted signaling pathway was selected and verified using Western blot.Results: After 8 weeks of treatment, BKG significantly reduced SOD level (p = 0.046), TCM aging symptoms (p < 0.001) and TNF-α level (p = 0.044) in the elderly participants. High-throughput sequencing showed that BKG reversed the expression of 70 and 79 age-related genes and metabolites, respectively. Further enrichment analysis indicated that BKG downregulated the PI3K-AKT signaling pathway, extracellular matrix (ECM)-receptor interaction, and Rap1 signaling pathway, while up-regulating sphingolipid metabolism. The results of in vitro experiments show that, after D-gal treatment, the viability and telomere length of AC16 cells significantly decreased (p < 0.05), while the expression of ROS increased (p < 0.05), BKG significantly increased the telomere length of AC16 cells and reduced the level of ROS expression (p < 0.05). In addition, BKG decreased the expression of THBS1, PDGFRA, and EPS8L1(p < 0.05), consistent with the RNA-seq results. Our results also showed that BKG affects PI3K-AKT signaling pathway.Conclusion: BKG can significantly improve aging-related symptoms and increase SOD levels, which may be associated with the reversal of the expression of various aging-related genes. The PI3K-AKT signaling pathway and sphingolipid metabolism may be potential mechanisms underlying BKG anti-aging effects.

BackgroundPost-stroke depression (PSD) is a prevalent psychiatric disorder affecting about one-third of stroke survivors, significantly hindering recovery and quality of life. PSD also imposes a substantial burden on caregivers and healthcare systems. Aromatherapy has shown promise in alleviating depression, anxiety, and sleep disorders. This pilot randomized controlled trial aims to assess the feasibility and preliminary efficacy of mixed herb aromatherapy in treating PSD. Feasibility outcomes encompass recruitment, intervention adherence, assessment completion and safety assessment. Secondary outcomes include evaluations of depression, anxiety, cognitive function, sleep quality, quality of life, and brain function using EEG and fNIRS.MethodsThis single-blind pilot randomized controlled trial will be conducted at the Second Rehabilitation Hospital of Shanghai, enrolling ninety-nine post-stroke patients with PSD. Participants will be randomized into three groups: a Non-Active Control Group receiving standardized rehabilitation therapy, a CBT Group receiving conventional rehabilitation with bi-weekly CBT sessions, and an Aromatherapy Group receiving conventional rehabilitation with daily aromatic inhalation sessions. Interventions will last for four weeks, with efficacy assessed at baseline, post-intervention, and one month post-intervention. Rating scales will be used to measure changes in depression, sleep quality, cognitive function, and quality of life. EEG and fNIRS will specifically be used to measure changes in cerebral cortex activity and their correlations with depression. Feasibility will be evaluated through recruitment, intervention adherence, assessment completion and safety assessment.DiscussionThis pilot study highlights the potential of mixed herb aromatherapy inhalation for treating PSD, addressing limitations of CBT by promoting self-management. While demonstrating feasibility through recruitment, adherence, assessment completion and safety assessment, the study also acknowledges limitations such as unequal intervention times, the lack of physical function data. And the use of culturally relevant plant powders may enhance compliance but limits generalizability. Despite these constraints, the study provides valuable preliminary data and insights into the mechanisms of aromatherapy, encouraging further research and development of effective PSD treatments.

Abstract Root tips can sense moisture gradients and grow into environments with higher water potential. This process is called root hydrotropism. Here, we report three closely related receptor-like kinases (RLKs) that play critical roles in root hydrotropism: ALTERED ROOT HYDROTROPIC RESPONSE 1 (ARH1), FEI1, and FEI2. Overexpression of these RLKs strongly reduce root hydrotropism, but corresponding loss-of-function mutants exhibit an increased hydrotropic response in their roots. All these RLKs show polar localization at the plasma membrane regions in root tips. The biosynthesis of the cell wall, cutin, and wax (CCW) is significantly impaired in root tips of arh1-2 fei1-C fei2-C. A series of known CCW mutants also exhibit increased root hydrotropism and reduced osmotic tolerance, similar to the characteristics of the triple mutant. Our results demonstrat that the integrity of the cell wall, cutin, and root cap wax mediate a trade-off between root hydrotropism and osmotic tolerance.

Abstract Cell migration is crucial for numerous physiological and pathological processes. A cell adapts its morphology, including the overall and nuclear morphology, in response to various cues in complex microenvironments, such as topotaxis and chemotaxis during migration. Thus, the dynamics of cellular morphology can encode migration strategies, from which diverse migration mechanisms can be inferred. However, deciphering the mechanisms behind cell migration encoded in morphology dynamics remains a challenging problem. Here, we present a powerful universal metric, the Cell Morphological Entropy (CME), developed by combining parametric morphological analysis with Shannon entropy. The utility of CME, which accurately quantifies the complex cellular morphology at multiple length scales through the deviation from a perfectly circular shape, is illustrated using a variety of normal and tumor cell lines in different in vitro microenvironments. Our results show how geometric constraints affect the MDA-MB-231 cell nucleus, the emerging interactions of MCF-10A cells migrating on collagen gel, and the critical transition from proliferation to invasion in tumor spheroids. The analysis demonstrates that the CME-based approach provides an effective and physically interpretable tool to measure morphology in real-time across multiple length scales. It provides deeper insight into cell migration and contributes to the understanding of different behavioral modes and collective cell motility in more complex microenvironments.

BackgroundThe number of persons with thyroid nodules has increased rapidly in recent years, and thyroid cancer caused by malignant nodules has become a key problem endangering the health of young and middle-aged groups in China. ObjectiveTo explore work and lifestyle influencing factors for developing thyroid cancer among young and middle-aged patients with thyroid nodules. MethodsThe subjects with thyroid nodules were reported by routine physical examines ordered at the Huadong Sanatorium. We conducted a 1∶4 matched case-control study in which 232 patients diagnosed with thyroid cancer from 2012 to 2022 were matched to 928 controls by gender and age (±5 years). A validated questionnaire was used to collect data on work and lifestyle behaviors. Univariate and multivariate logistic regression models were applied to explore potential relationships between selected factors (including environment, working hours, stress, diet, exercise, and mental health) and thyroid cancer. Spearman rank correlation was used to analyze the correlations between variables. ResultsThe results of univariate logistic regression showed a history of thyroid cancer reported among first-degree relatives (OR=6.059, 95%CI: 1.007, 36.473), obesity (OR=1.973, 95%CI: 1.296, 3.004), noise and vibration exposure (OR=1.988, 95%CI: 1.143, 3.456), frequent stress (OR=2.093, 95%CI: 1.231, 3.559), frequent depression (OR=2.034, 95%CI: 1.048, 3.947), frequent anger (OR=1.791, 95%CI: 1.066, 3.012), frequent fried food diet (OR=1.535, 95%CI: 1.026, 2.297), and frequent fast food diet (OR=1.836, 95%CI: 1.048, 3.215) were risk factors for reporting thyroid cancer developing from thyroid nodules, while regular meals (OR=0.245, 95%CI: 0.061, 0.989) and frequent exercise (OR=0.571, 95%CI: 0.342, 0.952) were protective factors for reporting no thyroid cancer. The results of Spearman correlation analysis showed that body mass index was positively correlated with frequent fried food, fast food, and sugary beverage diets (r=0.123, 0.083, 0.077, P 30 min per episode) (OR=0.516, 95%CI: 0.300, 0.890) was associated with a lowered risk of reporting thyroid cancer. ConclusionsMultiple risk factors associated with reporting thyroid cancer among young and middle-aged groups with thyroid nodules are identified, such as obesity, noise and vibration exposure, frequent stress, and lack of exercise.

Abstract Precise synthesis of carbon-based nanostructures with well-defined structural and chemical properties is of significance towards organic nanomaterials, but remains challenging. Herein, we report on a synthesis of nitrogen-doped porous carbon nanoribbons through a stepwise on-surface polymerization. Scanning tunneling microscopy revealed that the selectivity in molecular conformation, intermolecular debrominative aryl-aryl coupling and inter-chain dehydrogenative cross-coupling determined the well-defined topology and chemistry of the final products. Density functional theory calculations predict that the ribbons are semiconductors, and the band gap can be tuned by the width of the ribbons.

Abstract There has been no consensus yet regarding the precise initial timing and duration of the late Mesozoic extensional tectonics in the South‐eastern China Block. This work focusses on the growth strata of the Early Cretaceous red beds in the South‐eastern China Block to determine the late Mesozoic tectonics and the precise timing of the initiation and duration of extensional tectonics in this area. Field observation of several terrigenous basins shows that the dip angles of the Cretaceous red beds have varied from moderate to gentle from basin edges to interiors (or centres). The visible and estimated thickness within a single bed increases slightly downwards from the upper to the lower part. These characteristics indicate that the sedimentary area of these beds has undergone an extensional process with expansion and deepening of the sedimentary basins. Rotation of the border surfaces (limbs) and downward warping of the hanging walls or retreat of the footwalls of listric normal faults causes three types of extensional growth (or syntectonic) strata in the deposits of different basins. Dating of the volcanic rocks related to the growth beds reveals that the sedimentary basins were enlarged and deepened when the Early Cretaceous strata were deposited in the South‐eastern China Block from ca 140 to 137 Ma. Regionally, under the influence of Palaeo‐Pacific plate rollback since ca 140 Ma, the South‐eastern China Block stress field has led to lithospheric uplift and pull‐apart structures near the surface, causing the half‐graben basins to receive sedimentation. Although the extensional event was interrupted by a short compressional event during 120 to 105 Ma, with the oceanward retreat of the trench, the area of extension gradually enlarged and rejuvenated south‐eastwards until the end of the Cretaceous. This Cretaceous extension event of the South‐eastern China Block must belong to a worldwide geological event with global significance.

Relation extraction is the foundation for constructing a Event Evolution Graph. However, existing methods for extracting relation are more focus on data sufficient. This paper proposes a method for extracting relation in low-resource domain. Firstly, a incentive instruction is designed for task. We incorporate incentive instruction into the original text, which contain factual descriptions of the relation between defective events and the relation that need to be predicted. Additionally, defective events are included in the incentive instruction, allowing the model to shift its focus from the contextual representation of individual event words to the overall representation of text units. By employing this approach, we transform the relation extraction task into a pre-training task. Specifically, the Bidirectional Encoder Representation from Transformers places relation prediction words in designated positions within the incentive instructions and generates labels for each prediction word. Finally, we obtain the optimal relation. Compared with other models, the proposed method improves the F1 scores of the three logical relations by 14.41% to 23.19%, 15.45% to 28.42%, and 15.33% to 27.02%, respectively.

Introduce government competition policies and technological innovation efforts into the profit game model of the photovoltaic industry supply chain, establish two different supply chain profit models, and study the impact of government competition policies and manufacturers' technological innovation efforts on the profits of each manufacturer and the overall profit of the supply chain. Construct profit models in both competitive and cooperative situations, and empirically analyze the impact of government competition policies and manufacturers' technological innovation efforts on the optimal supply chain profits in both competitive and cooperative situations. Research has shown that: (1) government competition policies are conducive to promoting an increase in manufacturers' profits; (2) The increase in technological innovation efforts can quickly increase manufacturers' profits; (3) Compared to the cooperation situation, the profit of each manufacturer and the total profit of the entire supply chain are higher in the competitive situation.

From the perspective of carbon quota policy, we consider integrating carbon quota sharing contracts into the collaborative decision-making model of the photovoltaic industry chain and compare and explore the collaborative decision-making of the photovoltaic industry chain under decentralized decision-making and considering carbon quota sharing contracts. Research has found that carbon quota sharing contracts can effectively promote green innovation among the main body of the photovoltaic industry chain; In the case of carbon quota sharing contracts, the pricing between photovoltaic system suppliers and photovoltaic power plant enterprises is lower; Under the carbon quota sharing contract, the profits, and overall profits of each entity in the photovoltaic industry chain are better than the optimal profits under decentralized conditions.

The scattering properties of targets in polarimetric synthetic aperture radar (PolSAR) images are directly influenced by the targets' orientations, as the scattering properties from the same target with different orientations can be very different. This interpretation diversity caused by the target orientations is one of the primary technical bottlenecks in PolSAR image interpretation. In this article, a 3-D convolutional vision transformer (3-D-Conv-ViT) is proposed to describe the relationship between polarimetric coherent matrices with different polarization orientation angles (POAs) for PolSAR image classification and change detection. First, 3-D convolutional neural networks are used to capture the high-level feature representations of the polarimetric coherent matrix sequence. Second, a new Rotation-3-D-ViT block is proposed to learn the local and global representations of the high-level feature maps. The self-attention mechanism in the ViT can express the regularity of polarimetric coherent matrices with different POAs and improve the PolSAR image interpretation performance. Third, combined with different classifiers, the proposed 3-D-Conv-ViT can be applied to both PolSAR image classification and change detection. Experiments on real PolSAR image datasets demonstrate that the proposed method can overcome the problem of the interpretation ambiguity caused by the target orientation. The classification accuracies of the proposed method can reach 94.01%–99.48%, and the change detection accuracies can reach 93.84%–96.86%.

The 531 New Deal has gradually transitioned the photovoltaic market policy from industrial policy to competition policy. This paper considers the two policy orientations of the photovoltaic supply chain: industrial policy and competition policy. Based on differential game theory, the profit models of photovoltaic supply chain entities under the two policy orientations are constructed, and the optimal solutions of each model are solved. The research finds that policy guidance factors affect the strategic choices of photovoltaic supply chain entities; Compared to industrial policies, competition policy orientation can increase the profits of various entities in the photovoltaic supply chain to varying degrees.

The ubiquitous power Internet of Things (UPIoT) uses modern information technology and advanced communication technologies to realize interconnection and human-computer interaction in all aspects of the power system. UPIoT has the characteristics of comprehensive state perception and efficient information processing, and has broad application prospects for transformation of the energy industry. The fundamental facility of the UPIoT is the sensor-based information network. By using advanced sensors, Wireless Sensor Networks (WSNs), and advanced data processing technologies, Internet of Things can be realized in the power system. In this paper, a framework of WSNs based on advanced sensors towards UPIoT is proposed. In addition, the most advanced sensors for UPIoT purposes are reviewed, along with an explanation of how the sensor data obtained in UPIoT is utilized in various scenarios.

Polypropylene (PP) is considered to be a rather promising material for HVDC cable insulation. Grafting modi-fication has proved to be an effective method on the electrical property improvements of PP. This paper reports on the highly-enhanced electrical properties of styrene-grafted polypropylene (PP-g-St) and their related mechanism. The influence of grafting styrene on crystallization structures, thermal properties and electrical properties of PP-g-St are characterized and analyzed. These results show that PP-g-St exhibits remarkably enhanced DC volume resistivity, suppressed space charge accumulation and improved DC breakdown strengths as compared to PP. Crystallization observation shows PP-g-St has small, imperfect spherulites with indistinct boundaries, which is strongly correlated to enhanced electrical properties. This study provides an effective grafting strategy to design high-performance HVDC cable insulation materials for bulk power transmission systems.

In this paper, a microwave absorption/transmission switchable frequency selective surface (A/T-SFSS) with enhanced multispectral functionality in the visible and infrared spectra is developed. By simply controlling the flowing liquid medium (pure water in this work), efficient manipulation of two opposite states, absorption and transmission, can be achieved in the microwave frequency band with a wide switchable bandwidth. When functioning as a wideband absorber, the proposed A/T-SFSS exhibits an absorption rate over 90% from 6.50 GHz to 10.48 GHz. Conversely, it can be employed as a transmitter with high selectivity, featuring a second-order passband with two transmission zeros at both sides and an impressive −1 dB transmission bandwidth ranging from 7.04 GHz to 8.47 GHz. The design also demonstrates stable responses under different polarizations and incident angles. Additionally, the proposed A/T-SFSS offers flexibility in tailoring the visible and infrared spectra by actively changing the color and temperature of aqueous solutions. The influences of electromagnetic (EM) parameters and liquid temperature variations on the microwave performance are also thoroughly investigated. Finally, experimental verification through free-space tests of scattering parameters, image analyses of grayscale histogram, and infrared radiation detected by thermal imager provides compelling evidence for the potential of the developed A/T-SFSS. The results demonstrate its remarkable capability to achieve switchable microwave functionality as well as active control of visible light and infrared spectra, which significantly contributes to the field by advancing the development of multifunctional and multispectral structures.

With the annual promotion of the international “dual carbon” goals, countries attach great importance to the development and innovation of clean energy. The United States, Japan, and China have all created many policies for the research and market development of photovoltaic energy. This article incorporates market dynamic regulation capability into a two-dimensional system of government subsidy policies and photovoltaic revenue, constructs a three-dimensional dynamic nonlinear model based on market dynamic regulation capability, government subsidies, and enterprise revenue, and numerically simulates and analyzes the impact of parameter and initial value changes in the equation on enterprise revenue. The market dynamic regulation capability is obtained from Chaotic attractors and dynamic evolution graphs of the nonlinear evolution between government subsidies and corporate profits in different scenarios. Research has shown that: (1) Rapidly improving the dynamic regulation ability of the market cannot continuously increase the revenue of the photovoltaic industry; (2) The changes in market dynamics affect the dependence of enterprises on government subsidies; (3) The demand for government subsidies by enterprises gradually decreases with the increase of their own profits.

Abstract Through the uniaxial compression test of double parallel fissured layered rock mass, the mechanical properties of layered rock mass with different fissure dip angle, and the characteristics of acoustic emission (AE) parameters in the process of fracture are studied. The influence of fissure dip angle on the progressive damage, and macroscopic fracture of layered rock mass is explored. The fracture mode, local stress variation characteristics, and stress field evolution law of fissured layered rock mass are analyzed from a mesoscopic point of view. The results show that with the increase of the fissure dip angle α, the peak strength and the elastic modulus of the layered rock mass decrease first and then increase. The low frequency-high amplitude (LF-HA) signals of AE all appear in the crack propagation stage. With the increase of fissure dip angle α, the LF-HA signal ratio increases first, then decreases and then increases, and shows significant stage characteristics. The cracks are mainly generated around the relatively low strength A rock and prefabricated fissures, and all pass through the interface between A rock and B rock. Eight types mesoscopic displacement field models are found, and the final failure mode of the model is tensile-shear mixed failure. The upper and lower regions of the fissure are tensile stress areas, while the left and right regions are compressive shear stress areas, which are distributed in a “butterfly” type. The stress difference at the fissure tip is negatively correlated with the mechanical parameters of the layered rock mass.

Abstract Background Transcranial alternating current stimulation (tACS) has proven to be an effective treatment for improving cognition, a crucial factor in motor learning. However, current studies are predominantly focused on the motor cortex, and the potential brain mechanisms responsible for the therapeutic effects are still unclear. Given the interconnected nature of motor learning within the brain network, we have proposed a novel approach known as multi-target tACS. This study aims to ascertain whether multi-target tACS is more effective than single-target stimulation in stroke patients and to further explore the potential underlying brain mechanisms by using techniques such as transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI). Methods This study employs a double-blind, sham-controlled, randomized controlled trial design with a 2-week intervention period. Both participants and outcome assessors will remain unaware of treatment allocation throughout the study. Thirty-nine stroke patients will be recruited and randomized into three distinct groups, including the sham tACS group (SS group), the single-target tACS group (ST group), and the multi-target tACS group (MT group), at a 1:1:1 ratio. The primary outcomes are series reaction time tests (SRTTs) combined with electroencephalograms (EEGs). The secondary outcomes include motor evoked potential (MEP), central motor conduction time (CMCT), short interval intracortical inhibition (SICI), intracortical facilitation (ICF), magnetic resonance imaging (MRI), Box and Block Test (BBT), and blood sample RNA sequencing. The tACS interventions for all three groups will be administered over a 2-week period, with outcome assessments conducted at baseline (T0) and 1 day (T1), 7 days (T2), and 14 days (T3) of the intervention phase. Discussion The study’s findings will determine the potential of 40-Hz tACS to improve motor learning in stroke patients. Additionally, it will compare the effectiveness of multi-target and single-target approaches, shedding light on their respective improvement effects. Through the utilization of techniques such as TMS and MRI, the study aims to uncover the underlying brain mechanisms responsible for the therapeutic impact. Furthermore, the intervention has the potential to facilitate motor learning efficiency, thereby contributing to the advancement of future stroke rehabilitation treatment. Trial registration Chinese Clinical Trial Registry ChiCTR2300073465. Registered on 11 July 2023.

Monitoring the actual surface deformation caused by subsurface fluid activities is crucial for comprehending the subsurface fluid mutation process. Incorporation of InSAR observations in a prior volume strain model can facilitate the estimation of subsurface fluid volumetric changes and three-dimensional (3-D) surface deformation. However, the model parameters, i.e., the thickness and depth of the subsurface fluid reservoir, are assumed to be known a priori. Therefore, it is impossible to acquire the precise model parameters in practice. Therefore, we proposed a novel approach for adaptive estimation of the model parameters by utilizing the black hole strategy method integrated with the particle swarm optimization algorithm. First, the performance of this method was tested through simulation experiments. The results suggest that the proposed method can precisely determine the model parameters and 3-D deformations of the subsurface fluids. Finally, the proposed model was tested using actual data from the Shale gas area in Texas and the Kilauea Caldera volcano in Hawaii, USA. For long-term, slow small deformations or sudden large deformations caused by the subsurface fluids, the proposed algorithm can obtain corresponding 3-D deformations, especially in the presence of incoherent regions, which can still obtain a complete 3-D deformation field.

Detection based on LiDAR and camera fusion is increasingly popular for researchers in the autonomous driving domain. Compared to the camera-only and LiDAR-only methods, the fusion-based methods indeed improve the detection accuracy on public-available datasets. However, due to the complexity of the projection or fusion mechanism, few of these methods can run in real time even on an advanced desktop GPU. Thus, in this paper, we propose a new fusion detection model G-Fusion with a light and fast image view-transform module. According to our receptive field analysis of image feature maps, we directly project image features to only one voxel layer located on the ground, then fuse the LiDAR and image features by concatenation and convolution. With this delicately designed module, G-Fusion greatly boosts the state-of-the-art speed performance on the nuScenes dataset, achieving a good balance with the competitive detection scores. Meanwhile, since the precision of sensor extrinsic parameters is important for most fusion-based methods, we also deeply dig into our model’s calibration error tolerance ability and discover the failure noise condition.

The Three Gorges hydropower station in China creates a large reservoir by diverting water from the Yangtze River, increasing the risk of geological disasters, especially massive landslides along the reservoir shoreline. To mitigate these risks, improving geological monitoring and early warning systems is crucial. Interferometric Synthetic Aperture Radar (InSAR) is widely used to monitor reservoir bank landslides. However, its potential in early warning systems is limited due to temporal resolution constraints, preventing timely warnings. To address this, we propose integrating daily hydrological data (precipitation and water level observations) with historical InSAR deformation sequences using our deep learning-based multivariate united state estimation network, “MUSEnet.” This approach generates customized daily landslide deformation products for high-risk areas, greatly enhancing early warning capabilities by providing timely and accurate information on landslide occurrence and magnitude. We validated our method using 161 Sentinel-1 A images of the Xinpu landslide in the Three Gorges Reservoir area. Through statistical analysis, we identified different degrees of influence from rainfall and reservoir water level on the deformation of the Xinpu landslide at various locations. Additionally, we observed distinct lag times between deformation and corresponding rainfall and reservoir water level events. By utilizing deep learning, our method estimates nonlinear states by considering hysteresis and intelligently accounts for the impact of rainfall and reservoir water level, resulting in more accurate estimations compared to traditional models.

To date, the knowledge of benthic macroinvertebrates in the upper reaches of the Jinsha River remains quite limited compared to other rivers in China due to the difficulty of sampling and special geographical environment. In this study, benthic macroinvertebrates in the upper reaches of the Jinsha River were investigated to address the knowledge gap. The results showed that dipterans dominated the communities, followed by amphipods and EPT taxa. The density, biomass and biodiversity were at a low level. As a high sediment-loaded river, unlike the Yellow River and the Wei River, oligochaetes are not commonly found in the upper reaches of the Jinsha River, and no mollusks were collected. The results of db-RDA showed that some natural factors influenced the spatial distribution of benthic macroinvertebrates in both dry and wet seasons, but during the flood season (summer and autumn), nitrogen and phosphorus became important factors due to severe soil erosion and high sediment loads in the water. The sections between above Batang and below Batang have obviously different substrates, resulting in the significantly different species composition and functional feeding groups. Moreover, higher habitat diversity can lead to higher benthic macroinvertebrate diversity after comparing the substrate types of the two sections. We consider that the unstable habitat conditions in the upper reaches of the Jinsha River are not conducive to completing the entire life cycle of benthic macroinvertebrates within a localized small habitat, and the communities are likely influenced more by seasonal contributions from populations in tributaries. Considering the impact of the existing cascade hydropower stations in the middle and lower reaches, and the realistic and potential impacts expected from the planned cascade hydropower stations in the upper reaches, it is imperative to prioritize the conservation of the tributaries along both banks of the upper Jinsha River. This enhanced conservation effort aims to preserve the diversity and integrity of benthic macroinvertebrates, which is of great significance in providing reliable food sources for the rare cold-water fish species and ensuring the safety of the aquatic ecosystem in the region.