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Abstract Land use/cover change is the second major contributor to carbon emissions, following energy emissions. Studying provincial land-use carbon emissions is crucial for achieving the “double carbon” goal. This study selects 16 prefecture-level cities in Shandong Province as the research object. It analyzes the spatial and temporal distribution pattern of carbon emissions in Shandong Province based on land-use data and energy consumption. In terms of net carbon emissions, this study utilizes the standard deviation ellipse and kernel density estimation to analyze net carbon emissions change from the municipal and regional perspectives. In terms of carbon ecological carrying capacity, not only the carbon ecological carrying capacity of forest and grassland was considered, but also the carbon ecological carrying capacity of crops in Shandong Province, which is a large grain province. Using the geographic detector to explore the drivers. Research findings indicate that carbon sources and sinks show a clear spatial and temporal distribution pattern, with the center of gravity of net carbon emissions extending to the northeast. Areas with high carbon ecological carrying capacity have high forest coverage, grassland coverage, and crop yields. Regarding driving factors, the urbanization rate, economic aggregate, and technological progress demonstrate significant explanatory power through single and interaction tests, suggesting that these factors are critical drivers of land-use carbon emissions within Shandong Province. Based on the spatiotemporal pattern analysis of land-use carbon emissions in Shandong Province, each city's growth rate and spatial distribution characteristics can be clarified, providing a scientific basis for the local government to formulate regional and differentiated emission-reduction policies. In addition, by exploring the driving factors of land-use carbon emissions in Shandong Province, the influence level of factors on carbon emissions can be revealed to provide references for formulating regional sustainable development strategies.

Abstract Accurately detecting voltage faults is essential for ensuring the safe and stable operation of energy storage power station systems. To swiftly identify operational faults in energy storage batteries, this study introduces a voltage anomaly prediction method based on a Bayesian optimized (BO)-Informer neural network. Firstly, the temporal characteristics and actual data collected by the battery management system (BMS) are considered to establish a long-term operational dataset for the energy storage station. The Pearson correlation coefficient (PCC) is used to quantify the correlations between these data. Secondly, an Informer neural network with BO hyperparameters is used to build the voltage prediction model. The performance of the proposed model is assessed by comparing it with several state-of-the-art models. With a 1 min sampling interval and one-step prediction, trained on 70% of the available data, the proposed model reduces the root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE) of the predictions to 9.18 mV, 0.0831 mV, and 6.708 mV, respectively. Furthermore, the influence of different sampling intervals and training set ratios on prediction results is analyzed using actual grid operation data, leading to a dataset that balances efficiency and accuracy. The proposed BO-based method achieves more precise voltage abnormity prediction than the existing methods.

Abstract Background Culex tritaeniorhynchus is widely distributed in China, from Hainan Island in the south to Heilongjiang in the north, covering tropical, subtropical, and temperate climate zones. Culex tritaeniorhynchus carries 19 types of arboviruses. It is the main vector of the Japanese encephalitis virus (JEV), posing a serious threat to human health. Understanding the effects of environmental factors on Culex tritaeniorhynchus can provide important insights into its population structure or isolation patterns, which is currently unclear. Results In total, 138 COI haplotypes were detected in the 552 amplified sequences, and the haplotype diversity (Hd) value increased from temperate (0.534) to tropical (0.979) regions. The haplotype phylogeny analysis revealed that the haplotypes were divided into two high-support evolutionary branches. Temperate populations were predominantly distributed in evolutionary branch II, showing some genetic isolation from tropical/subtropical populations and less gene flow between groups. The neutral test results of HNQH (Qionghai) and HNHK(Haikou) populations were negative (P

ObjectivesWe aim to investigate the associations between lifestyle, ambient air pollution with crucial outcomes in the progression of adult asthma, including asthma new-onset and asthma hospitalisation.Methods176,800 participants were included to assess the prospective association between baseline risk exposures and the subsequent asthma onset, 17,387 participants were used to evaluate asthma hospitalisation. Cox regression models were employed to examine the associations.ResultsIn terms of lifestyle factors, the HRs (95% CIs) of the least healthy lifestyle categories for asthma incidence and hospitalization were 1.099 (1.017–1.187) and 1.064 (1.008–1.123), respectively. For pollutants, PM2.5, especially the traffic-related PM2.5 component, was consistently recognized as a significant risk factor for asthma onset (HR = 1.064, 95% CI: 1.034–1.094) and hospitalisation (HR = 1.031, 95% CI: 1.010–1.052) under various model adjustments. Low socioeconomic status also played a major role in the progression of adult asthma.ConclusionOur study provides crucial insights into factors influencing the progression of adult asthma. Monitoring and reducing exposure to air pollution, particularly PM2.5, promoting healthier lifestyle, and addressing socioeconomic inequity are important in preventing and managing asthma.

Abstract Background The pathogenesis of memory impairment, a common complication of chronic neuropathic pain (CNP), has not been fully elucidated. Schwann cell (SC)-derived extracellular vesicles (EVs) contribute to remote organ injury. Here, we showed that SC-EVs may mediate pathological communication between SCs and hippocampal neurons in the context of CNP. Methods We used an adeno-associated virus harboring the SC-specific promoter Mpz and expressing the CD63-GFP gene to track SC-EVs transport. microRNA (miRNA) expression profiles of EVs and gain-of-function and loss-of-function regulatory experiments revealed that miR-142-5p was the main cargo of SC-EVs. Next, luciferase reporter gene and phenotyping experiments confirmed the direct targets of miR-142-5p. Results The contents and granule sizes of plasma EVs were significantly greater in rats with chronic sciatic nerve constriction injury (CCI)than in sham rats. Administration of the EV biogenesis inhibitor GW4869 ameliorated memory impairment in CCI rats and reversed CCI-associated dendritic spine damage. Notably, during CCI stress, SC-EVs could be transferred into the brain through the circulation and accumulate in the hippocampal CA1-CA3 regions. miR-142-5p was the main cargo wrapped in SC-EVs and mediated the development of CCI-associated memory impairment. Furthermore, α-actinin-4 (ACTN4), ELAV-like protein 4 (ELAVL4) and ubiquitin-specific peptidase 9 X-linked (USP9X) were demonstrated to be important downstream target genes for miR-142-5p-mediated regulation of dendritic spine damage in hippocampal neurons from CCI rats. Conclusion Together, these findings suggest that SCs-EVs and/or their cargo miR-142-5p may be potential therapeutic targets for memory impairment associated with CNP.

BackgroundUveitis, characterized by inflammation of the iris, ciliary body, and choroid, presents a significant global clinical challenge, contributing substantially to visual impairment. Risk factors include autoimmune diseases and immune cell dysfunctions, yet many remain unidentified. Immune cells, notably T cells, B cells, and monocytes, play pivotal roles in uveitis pathogenesis. While biologic agents show promise, comprehensive studies on immune cell types in ocular diseases are lacking. Genome-wide association studies (GWAS) and Mendelian randomization (MR) present promising avenues to elucidate genetic susceptibilities and causal relationships between immune cell traits and uveitis risk.MethodsTwo-sample MR analysis was used to evaluate the causal relationship between 731 immune cells and uveitis, and genome-wide significance analysis was performed for genetic variation in 731 immune cells traits (P < 5 × 10-8). Immune characteristics include median fluorescence intensity (MFI), relative cell counts (RC), absolute cell counts (AC), and morphological parameters (MP), which were determined by published GWAS, and public data from the IEU Open GWAS database. The main analysis method of MR is inverse variance weighting (IVW). Heterogeneity and horizontal pleiotropy were also assessed.Results5 immunophenotypes, including CD62L-DC %DC, IgD+ CD38dim %B cell, CD3 on CM CD4+T cell, CD3 on CD45RA-CD4 +T cell, and CD3 on CD39+ CD4+ Treg may increase the risk of uveitis. 5 immunophenotypes, including CD11b on CD33dim HLA DR-Myeloid cell, HLA DR on CD33dim HLA DR+ CD11b-myeloid cell, CD14-CD16 + %monocyte, HLA DR on CD14-CD16 + monocyte and PDL-1 on CD14-CD16 + monocyte was negatively associated with the risk of uveitis. Among them, HLA DR on CD14-CD16 + monocyte (OR=0.921, 95%CI =0.875-0.970, P=0.001) and HLA DR on CD33dim HLA DR+ CD11b- (OR=0.879, 95%CI = 0.833-0.927, P=0.00) were negatively associated with the risk of uveitis in bi-direction.ConclusionThese results indicate that 10 immune cells traits are significantly associated with the risk of developing uveitis and 2 of them were strongly associated with uveitis bi-directionally, after excluding the effects of confounding factors such as some immune diseases, which provided new ideas and therapeutic targets for the study of immune mechanism of uveitis.

Type 3 resistant starch from Canna edulis (Ce-RS3) is an insoluble dietary fiber which could improve blood lipids in animals, but clinically robust evidence is still lacking. We performed a double-blind randomized controlled trial to assess the effects of Ce-RS3 on lipids in mild hyperlipidemia. One hundred and fifteen patients were included followed the recruitment criteria, and were randomly allocated to receive Ce-RS3 or placebo (native starch from Canna edulis) for 12 weeks (20 g/day). In addition to serum lipids, complete blood counts, serum inflammatory factors, antioxidant indexes, and dietary survey, 16 S rRNA sequencing technique was utilized to analyze the gut microbiota alterations. Targeted quantitative metabolomics (TQM) was used to detect metabolite changes. Compared with the placebo, Ce- RS3 significantly decreased levels of total cholesterol, lowdensity lipoprotein cholesterol, and non-high-density lipoprotein cholesterol, and increased the glutathione peroxidase. Based on the 16 S rRNA sequencing, TQM, the correlation analysis, as well as the Kyoto Encyclopedia of Genes (KEGG) and Genomes and Human Metabolome Database (HMDB) analysis, we found that Ce-RS3 could increase the abundances of genera Faecalibacterium and Agathobacter, while reduce the abundances of genera norank_f_Ruminococcaceae and Christensenellaceae_R-7_ group to regulate phenylalanine metabolism, which could reduce the fatty acid biosynthesis and fatty acid elongation in the mitochondria to lower blood lipids. Conclusively, we firstly confirmed the feasibility of Ce-RS3 for clinical application, which presents a novel, effective therapy for the mild hyperlipidemia. (Chictr. org. cn. Clinical study on anti-mild hyperlipidemia of Canna edulis RS3 resistant starch, ID Number: ChiCTR2200062871).

BackgroundThe treatment of multidrug-resistant tuberculosis (MDR-TB) and pre-extensively drug-resistant tuberculosis (pre-XDR-TB) remains challenging due to the limited availability of effective drugs. Linezolid has emerged as a promising therapeutic option for these cases. However, its long-term use can lead to complications such as peripheral and optic neuropathies. Acupuncture, a cornerstone of traditional Chinese medicine, has been shown to be effective in the treatment of peripheral neuropathy (PN). This study examines the potential benefits of acupuncture in the treatment of linezolid-induced peripheral neuropathy (LIPN).MethodsFour patients, aged 27 to 60 years, diagnosed with LIPN, underwent daily acupuncture treatments. The main endpoint was to assess the efficacy of acupuncture in reducing neuropathic pain associated with LIPN in patients. This was primarily measured using changes in the Short Form McGill Pain Questionnaire (SF-MPQ) scores before and after acupuncture treatment.ResultsThree of the patients experienced significant symptom remission, while one experienced marginal improvement. Treatments ranged from 7 to 18 sessions. Specifically, the first patient reported substantial relief with a score reduction from 33 to 13; the second patient observed minimal change; the third patient’s score decreased dramatically from 10 to 2 after eight sessions; the last patient had a score reduction from 21 to 12 after five sessions, but did not continue treatment for a second assessment.ConclusionAcupuncture is a promising therapeutic approach for LIPN. However, larger and more thorough studies are needed to determine its full potential.

IntroductionResistant starch (RS) has garnered attention for its health benefits, including modulating the gut microbiota and promoting the production of short-chain fatty acids (SCFAs).MethodsThis study investigates structural changes of type 3 resistant starch from Canna edulis (CE) during in vitro simulated digestion and explores its health-relevant properties using healthy individuals’ fecal microbiota.ResultsCE, prepared with a RS content of 59.38%, underwent a comprehensive analysis employing X-ray diffraction (XRD), fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). During simulated digestion, XRD analysis demonstrated a significant rise in CE’s relative crystallinity from 38.92 to 49.34%. SEM illustrated the transition of CE from a smooth to a rough surface, a notable morphological shift. Post-digestion, CE was introduced into microbial fermentation. Notably, propionic acid and valeric acid levels significantly increased compared to the control group. Furthere more, beneficial Bifidobacterium proliferated while pathogenic Escherichia-Shigella was suppressed. When comparing CE to the well-known functional food fructo-oligosaccharide (FOS), CE showed a specific ability to support the growth of Bifidobacterium and stimulate the production of short-chain fatty acids (SCFAs) without causing lactic acid accumulation.DiscussionCE demonstrates potential as a functional health food, with implications for gut health enhancement and SCFAs production.

Abstract Genomic DNA exhibits high heterogeneity in terms of its dynamic within the nucleus, its structure and functional roles. CRISPR-based imaging approaches can image genomic loci in living cells. However, conventional CRISPR-based tools involve expressing constitutively fluorescent proteins, resulting in high background and nonspecific nucleolar signal. Here, we construct fluorogenic CRISPR (fCRISPR) to overcome these issues. fCRISPR is designed with dCas9, an engineered sgRNA, and a fluorogenic protein. Fluorogenic proteins are degraded unless they are bound to specific RNA hairpins. These hairpins are inserted into sgRNA, resulting in dCas9: sgRNA: fluorogenic protein ternary complexes that enable fluorogenic DNA imaging. With fCRISPR, we image various genomic DNA in different human cells with high signal-to-noise ratio and sensitivity. Furthermore, fCRISPR tracks chromosomes dynamics and length. fCRISPR also allows DNA double-strand breaks (DSBs) and repair to be tracked in real time. Taken together, fCRISPR offers a high-contrast and sensitive platform for imaging genomic loci.

Abstract Purpose Sequenced Protein–Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventions. Conventional methods for extracting features through experimental processes have proven to be both costly and exceedingly complex. In light of these challenges, the scientific community has turned to computational approaches, particularly those grounded in deep learning methodologies. Despite the progress achieved by current deep learning technologies, their effectiveness diminishes when applied to larger, unfamiliar datasets. Results In this study, the paper introduces a novel deep learning framework, termed DL-PPI, for predicting PPIs based on sequence data. The proposed framework comprises two key components aimed at improving the accuracy of feature extraction from individual protein sequences and capturing relationships between proteins in unfamiliar datasets. 1. Protein Node Feature Extraction Module: To enhance the accuracy of feature extraction from individual protein sequences and facilitate the understanding of relationships between proteins in unknown datasets, the paper devised a novel protein node feature extraction module utilizing the Inception method. This module efficiently captures relevant patterns and representations within protein sequences, enabling more informative feature extraction. 2. Feature-Relational Reasoning Network (FRN): In the Global Feature Extraction module of our model, the paper developed a novel FRN that leveraged Graph Neural Networks to determine interactions between pairs of input proteins. The FRN effectively captures the underlying relational information between proteins, contributing to improved PPI predictions. DL-PPI framework demonstrates state-of-the-art performance in the realm of sequence-based PPI prediction.

Abstract Background The neurological symptoms caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of increasing concern. Convulsions are among the main neurological manifestations reported in children with coronavirus disease-2019 (COVID-19), and cause serious harm to physical and mental health. This study aimed to investigate the risk factors for convulsion in children with COVID-19. Methods This prospective study was conducted at the Children’s Hospital of Soochow University. In total, 102 COVID-19 patients with convulsion, 172 COVID-19 patients without convulsion, and 50 healthy controls were enrolled in the study. The children’s clinical and laboratory data were analyzed to assess the risk factors for convulsion in COVID-19 patients. Results Convulsions occurred in 37.2% of children, mostly those aged 1–3 years, who were hospitalized with the Omicron variant. The neutrophil count, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume-to-platelet ratio (MPR) were significantly higher in the convulsion group than those in the non-convulsion and control groups (P

Urban agglomerations (UAs), which play a significant role in socioeconomic development and urbanization, are confronted with mounting ecological stress and a profound global imbalance in ecosystem services (ES). Understanding the conflict and coordination of knowledge about ES supply and demand (ESSD) can facilitate more efficacious guidance on the ecological sustainable development of UAs. Nevertheless, the characteristics of the conflict and coordination relationship between ESSD in Chinese UAs remain unclear, and further investigation into the interactive coercive relationship between ESSD is warranted. Consequently, we employed spatial regression and coupled coordination models to elucidate the conflict and coordination relationship between ESSD, utilizing multi-source data on Chinese UAs from 2000 to 2020. We found that ES supply in the UAs decreased, while ES demand increased. Furthermore, the coupling coordination degree between ESSD demonstrated an increase trend. The overall coupling coordination degrees between ESSD in UAs were 0.260, 0.285, and 0.311 in 2000, 2010, and 2020, respectively. The central UAs were identified as stress areas, whereas the peripheral areas were classified as non-stress areas. This study offered valuable insights into the interactive relationship between ESSD in UAs and provided a basis for formulating differentiated policies for the sustainable development of ecosystems and human activities.

Clarifying the issues related to the supply, demand, and flow of ecosystem services is crucial for regional landscape management. This study employs the equivalence factor method and demand index quantification to analyze the supply and demand of ecosystem services in the Zheng-Bian-Luo region in 2000 and 2020. We used hotspot analysis tools and the minimum cumulative resistance model to establish the ecological corridors, identifying the spatial flow paths of ecosystem services in our site. By calculating the flow volume of the key corridor value through the breakpoint formula and field strength theory and combining this with the ratio of the regulating service value, we computed the ecological compensation amount, thereby realizing the value of the ecosystem service. The results indicate that the area of balance between ecosystem service supply and demand gradually decreased and the deficit area in the Zheng-Bian-Luo region increased 43.62% from 2000 to 2020 along with rapid urbanization. The total value flow of ecosystem services by the important ecological corridors in 2000 and 2020 was USD 242.40 million and USD 365.92 million, respectively. In 2020, it was predicted that Luanchuan County would receive ecological compensation totals of USD 237.76 million from each ecological demand area, and mainly from Jinshui District. Our findings support enhancing the quality of the ecological environment and optimizing the landscape management of the Yellow River’s Henan section.

ObjectiveTo investigate the effects of different rehabilitation modalities on cardiopulmonary function in patients with acute coronary syndrome after revascularization.MethodsTwo randomized controlled trials were conducted. All patients were stable for more than 48 h and less than 1 week after revascularization for acute coronary syndrome and were randomly assigned to Group A (home-based rehabilitation group) or Group B (center guided home-based rehabilitation group). The cardiopulmonary exercise test was mainly performed before and 3 months after cardiac rehabilitation (at the end of intervention). The primary endpoints of the study were peak oxygen uptake (VO2peak), and the secondary endpoints were maximum metabolic equivalents (METs), anaerobic threshold exercise load (Load AT), maximal workload (Load max), and anaerobic threshold oxygen uptake (VO2 AT).ResultsA total of 106 patients were included in the study, with 47 patients in Group A (with 6 losses) and 50 patients in Group B (with 3 losses). There were no significant difference between the two groups in terms of age, gender, body mass index (BMI), left ventricular ejection fraction(LVEF), low-density lipoprotein cholesterol(LDL-C),cardiovascular risk factors. In Group A, no significant differences in CPET indices were observed before and after the intervention. In Group B, values of maximum metabolic equivalents (METs), peak heart rate (PHR), anaerobic threshold exercise load (Load AT), maximal workload (Load max), maximum ventilation per minute (VE max), peak oxygen uptake (VO2peak), anaerobic threshold oxygen uptake (VO2 AT) and maximum oxygen pulse (VO2/HRmax) were higher than those before the intervention (P

Abstract Background Noncoding RNAs such as circular RNAs (circRNAs) are abundant in the human body and influence the occurrence and development of various diseases. Non-small cell lung cancer (NSCLC) is one of the most common malignant cancers. Information on the functions and mechanism of circRNAs in lung cancer is limited; thus, the topic needs more exploration. The purpose of this study was to identify aberrantly expressed circRNAs in lung cancer, unravel their roles in NSCLC progression, and provide new targets for lung cancer diagnosis and therapy. Methods High-throughput sequencing was used to analyze differential circRNA expression in patients with lung cancer. qRT‒PCR was used to determine the level of circHERC1 in lung cancer tissues and plasma samples. Gain- and loss-of-function experiments were implemented to observe the impacts of circHERC1 on the growth, invasion, and metastasis of lung cancer cells in vitro and in vivo. Mechanistically, dual luciferase reporter assays, fluorescence in situ hybridization (FISH), RNA immunoprecipitation (RIP) and RNA pull-down experiments were performed to confirm the underlying mechanisms of circHERC1. Nucleocytoplasmic localization of FOXO1 was determined by nucleocytoplasmic isolation and immunofluorescence. The interaction of circHERC1 with FOXO1 was verified by RNA pull-down, RNA immunoprecipitation (RIP) and western blot assays. The proliferation and migration of circHERC1 in vivo were verified by subcutaneous and tail vein injection in nude mice. Results CircHERC1 was significantly upregulated in lung cancer tissues and cells, ectopic expression of circHERC1 strikingly facilitated the proliferation, invasion and metastasis, and inhibited the apoptosis of lung cancer cells in vitro and in vivo. However, knockdown of circHERC1 exerted the opposite effects. CircHERC1 was mainly distributed in the cytoplasm. Further mechanistic research indicated that circHERC1 acted as a competing endogenous RNA of miR-142-3p to relieve the repressive effect of miR-142-3p on its target HMGB1, activating the MAPK/ERK and NF-κB pathways and promoting cell migration and invasion. More importantly, we found that circHERC1 could bind FOXO1 and sequester it in the cytoplasm, adjusting the feedback AKT pathway. The accumulation of FOXO1 in the cytosol and nuclear exclusion promoted cell proliferation and inhibited apoptosis. CircHERC1 is a new circRNA that promotes tumor function in NSCLC and may serve as a potential prognostic biomarker and therapeutic target for NSCLC. Conclusions CircHERC1 is a new circRNA that promotes tumor function in NSCLC and may serve as a potential diagnosis biomarker and therapeutic target for NSCLC. Our findings indicate that circHERC1 facilitates the invasion and metastasis of NSCLC cells by regulating the miR-142-3p/HMGB1 axis and activating the MAPK/ERK and NF-κB pathways. In addition, circHERC1 can promote cell proliferation and inhibit apoptosis by sequestering FOXO1 in the cytoplasm to regulate AKT activity and BIM transcription.

Antimony (Sb) in natural water has long-term effects on both the ecological environment and human health. Iron mineral phase transformation (IMPT) is a prominent process for removing Sb(V) from natural water. However, the importance of IMPT in eliminating Sb remains uncertain. This study examined the various Sb–Fe binding mechanisms found in different IMPT pathways in natural water, shedding light on the underlying mechanisms. The study revealed that the presence of goethite (Goe), hematite (Hem), and magnetite (Mag) significantly affected the concentration of Sb(V) in natural water. Elevated pH levels facilitated higher Fe content in iron solids but impeded the process of removing Sb(V). To further our understanding, polluted natural water samples were collected from various locations surrounding Sb smelter sites. Results confirmed that converting ferrihydrite (Fhy) to Goe significantly reduced Sb levels (

Abstract Understanding gene expression processes necessitates the accurate classification and identification of transcription factors, which is supported by high-throughput sequencing technologies. However, these techniques suffer from inherent limitations such as time consumption and high costs. To address these challenges, the field of bioinformatics has increasingly turned to deep learning technologies for analyzing gene sequences. Nevertheless, the pursuit of improved experimental results has led to the inclusion of numerous complex analysis function modules, resulting in models with a growing number of parameters. To overcome these limitations, it is proposed a novel approach for analyzing DNA transcription factor sequences, which is named as DeepCAC. This method leverages deep convolutional neural networks with a multi-head self-attention mechanism. By employing convolutional neural networks, it can effectively capture local hidden features in the sequences. Simultaneously, the multi-head self-attention mechanism enhances the identification of hidden features with long-distant dependencies. This approach reduces the overall number of parameters in the model while harnessing the computational power of sequence data from multi-head self-attention. Through training with labeled data, experiments demonstrate that this approach significantly improves performance while requiring fewer parameters compared to existing methods. Additionally, the effectiveness of our approach is validated in accurately predicting DNA transcription factor sequences.

Urban agglomerations (UAs) are the main battlefield of urbanization and the most concentrated areas of carbon emissions (CEs). Nevertheless, limited studies have examined the impact of urbanization level (UL) on CEs in UAs in China. This study aimed to identify the spatial relationship between UL and CEs in Chinese UAs and to conduct a comprehensive analysis of the differences in CEs caused by urbanization. The findings would provide scientific support for the China’s dual-carbon goals and the achievement of green and low-carbon urban development. Spatial variations in UL and CEs in 19 Chinese UAs were assessed in 2000, 2010, and 2020 using distribution dynamics and spatial regression models. The results indicated that the UL of UAs in China evidently increased over time, and UAs contributed approximately 80% of the national CEs. Significant spatial dependence was identified between urbanization factors and CEs. The regression results indicated that an increase in UL promoted the growth of CEs, and the form of the urban land had a significant and highly variable impact on CEs. Our findings provide a valuable case study for exploring relationships between UL and CEs in other UAs worldwide.

3,4-disubstituted maleimides find wide applications in various pharmacologically active compounds. This study presents a highly effective approach for synthesizing derivatives of 3,4-disubstituted maleimides through the direct isomerization of α-succinimide-substituted allenoates, followed by a cascade γ′-addition and aryl imines using PR3 as a catalyst. The resulting series of 3,4-disubstituted maleimides exhibited excellent stereoselectivities, achieving yields of up to 86%. To our knowledge, the phosphine-mediated γ′-addition reaction of allenoates is seldom reported.

Objective: The aim of this study was to prospectively evaluate the quality of postoperative neck ultrasound (POU) for thyroid cancer patients after implementing European Thyroid Association (ETA) guideline-based POU assessment. Methods: Our analysis involved 672 differentiated thyroid cancer patients. POU report quality was compared between the implementation radiology group (IRG), which implemented ETA guideline-based assessment in 2018, and all non-implementation radiology groups (NIRG). Differences in POU quality were evaluated before and after the implementation of guideline-based assessment. Additionally, we evaluated the ability of serum thyroglobulin (Tg) level

Abstract Chronic pain is often associated with cognitive decline, which could influence the quality of the patient’s life. Recent studies have suggested that Toll-like receptor 3 (TLR3) is crucial for memory and learning. Nonetheless, the contribution of TLR3 to the pathogenesis of cognitive decline after chronic pain remains unclear. The level of TLR3 in hippocampal neurons increased in the chronic constriction injury (CCI) group than in the sham group in this study. Importantly, compared to the wild-type (WT) mice, TLR3 knockout (KO) mice and TLR3-specific neuronal knockdown mice both displayed improved cognitive function, reduced levels of inflammatory cytokines and neuronal apoptosis and attenuated injury to hippocampal neuroplasticity. Notably, extracellular RNAs (exRNAs), specifically double-stranded RNAs (dsRNAs), were increased in the sciatic nerve, serum, and hippocampus after CCI. The co-localization of dsRNA with TLR3 was also increased in hippocampal neurons. And the administration of poly (I:C), a dsRNA analog, elevated the levels of dsRNAs and TLR3 in the hippocampus, exacerbating hippocampus-dependent memory. In additon, the dsRNA/TLR3 inhibitor improved cognitive function after CCI. Together, our findings suggested that exRNAs, particularly dsRNAs, that were present in the condition of chronic neuropathic pain, activated TLR3, initiated downstream inflammatory and apoptotic signaling, caused damage to synaptic plasticity, and contributed to the etiology of cognitive impairment after chronic neuropathic pain.

Abstract Background Postoperative cognitive dysfunction (POCD) is a common neurological complication following anesthesia and surgery. Increasing evidence has demonstrated that neuroinflammation caused by systemic inflammatory responses during the perioperative period is a key factor in the occurrence of POCD. In addition, SMAD family member 7 (Smad7) has been confirmed to play vital roles in the pathogenesis and treatment of inflammatory diseases, such as inflammatory bowel disease. However, whether Smad7 participates in the regulatory process of neuroinflammation and apoptosis in the development of POCD is still unknown. Methods In this study, a POCD mouse model was constructed by unilateral nephrectomy under anesthesia, and cognitive function was assessed using the fear conditioning test and open field test. The expression of Smad7 at the mRNA and protein levels in the hippocampus 3 days after surgery was examined by qRT-PCR, western blot and immunofluorescence assays. Furthermore, to identify whether the elevation of Smad7 in the hippocampus after unilateral nephrectomy contributes to cognitive impairment, the expression of Smad7 in the hippocampal CA1 region was downregulated by crossing Smad7fl/fl conditional mutant mice and CaMKIIα-Cre line T29-1 transgenic mice or stereotaxic injection of shRNA–Smad7. Inflammation and apoptosis in the hippocampus were assessed by measuring the mRNA levels of typical inflammatory cytokines, including TNF-α, IL-1β, IL-6, CCL2, CXCL1, and CXCL2, and the protein levels of apoptotic proteins, including Bax and Bcl2. In addition, apoptosis in the hippocampus postoperation was investigated by a terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining assay. Finally, western blotting was used to explore how Smad7 mediates inflammation and apoptosis postoperation. Results The results unequivocally revealed that elevated Smad7 in the hippocampal CA1 region significantly inhibited TGF-β signal transduction by blocking Smad2/3 phosphorylation, which enhanced neuroinflammation and apoptosis in the hippocampus and further led to learning and memory impairment after surgery. Conclusions Our results revealed that Smad7 contributes to cognitive impairment after surgery by enhancing neuroinflammation and apoptosis in the hippocampus and might serve as a promising therapeutic target for the treatment of memory impairment after anesthesia surgery.

This study aimed to evaluate the efficacy and safety of intravitreal dexamethasone implants in the treatment of ocular toxocariasis (OT). A retrospective analysis was performed on 6 cases in which laboratory tests diagnosed OT. All patients were administered with intravitreal dexamethasone implants with or without vitrectomy. The average follow-up time was 19.7 months. All operated eyes achieved anatomic success, and all patients’ visual acuity was improved. Five of these six had a visual acuity of 20/100, and three had final acuity of 20/40 or even better. Intravitreal dexamethasone implants can be used to treat different types of OT, which not only effectively control inflammation and improve the patient’s vision but also reduce the use of systemic glucocorticoids.

ABSTRACTThe gut-joint axis, one of the mechanisms that mediates the onset and progression of joint and related diseases through gut microbiota, and shows the potential as therapeutic target. A variety of drugs exert therapeutic effects on rheumatoid arthritis (RA) through the gut-joint axis. However, the anti-inflammatory and immunomodulatory effect of novel photobiomodulatory therapy (PBMT) on RA need further validation and the involvement of gut-joint axis in this process remains unknown. The present study demonstrated the beneficial effects of PBMT on RA, where we found the restoration of gut microbiota homeostasis, and the related key pathways and metabolites after PBMT. We also discovered that the therapeutic effects of PBMT on RA mainly through the gut-joint axis, in which the amino acid metabolites (Alanine and N-acetyl aspartate) play the key role and rely on the activity of metabolic enzymes in the target organs. Together, the results prove that the metabolites of amino acid from gut microbiota mediate the regulation effect on the gut-joint axis and the therapeutic effect on rheumatoid arthritis of PBMT.

Abstract Beetroot is a homodimeric in vitro selected RNA that binds and activates DFAME, a conditional fluorophore derived from GFP. It is 70% sequence-identical to the previously characterized homodimeric aptamer Corn, which binds one molecule of its cognate fluorophore DFHO at its interprotomer interface. We have now determined the Beetroot-DFAME co-crystal structure at 1.95 Å resolution, discovering that this RNA homodimer binds two molecules of the fluorophore, at sites separated by ~30 Å. In addition to this overall architectural difference, the local structures of the non-canonical, complex quadruplex cores of Beetroot and Corn are distinctly different, underscoring how subtle RNA sequence differences can give rise to unexpected structural divergence. Through structure-guided engineering, we generated a variant that has a 12-fold fluorescence activation selectivity switch toward DFHO. Beetroot and this variant form heterodimers and constitute the starting point for engineered tags whose through-space inter-fluorophore interaction could be used to monitor RNA dimerization.

Abstract The Yangtze River Basin (YRB) is the birthplace of Chinese civilization and is rich in traditional village resources. Studying their spatial distribution characteristics and influencing factors can guide the protection, inheritance, and development of traditional villages in YRB. This study takes 5 batches of 3346 traditional villages in YRB since 2012 as the research object. Using the nearest neighbor index, kernel density analysis, standard deviation ellipse, and Geodetector model, we analyzed the spatial distribution characteristics of traditional villages in YRB and detected their influencing factors. The results show that the distribution of traditional villages in YRB exhibited a spatial pattern of cohesive clusters, forming a high-density area and development center in the junction zone between Guizhou and Hunan provinces and southeast of Anhui Province, and secondary-density areas in Northeast Yunnan Province and east Jiangxi Province. The results of the Geodetector show that the formation of the spatial distribution pattern of traditional villages in YRB is affected by the combined effects of natural and socio-economic factors, among which elevation and NDVI were the main factors, and the interaction of multiple factors showed an enhanced trend. The findings of this study can provide scientific decision-making support for the development and protection of traditional villages in YRB.

In this paper, an interesting γ′-carbon 1,6-conjugate addition for phosphine-catalyzed α-succinimide substituted allenoates has been disclosed. A wide array of substrates was found to participate in the reaction, resulting in the production of diverse 4-diarylmethylated 3,4-disubstituted maleimides with satisfactory to outstanding yields. Furthermore, a plausible mechanism for the reaction was proposed by the investigators.

In recent years, asphalt pavement has been subjected to varied environmental conditions during its service life, conditions that predispose it to deformation and cracking. To enhance the performance of asphalt pavement, rock asphalt has been selected as a modifier due to its good compatibility with virgin asphalt binder and its ability to improve the fatigue cracking resistance of asphalt mixtures. Although scholars have conducted some studies on rock asphalt mixtures, research on the fatigue and self-healing performance of these mixtures under conditions such as ultraviolet (UV) aging and freeze–thaw remains limited. This paper presents findings from a study that employs a combined fatigue-healing test to assess the impact of such complex environmental factors on the fatigue and self-healing properties of fine aggregate matrix (FAM) mixtures containing three types of rock asphalts, i.e., Buton, Qingchuan (QC), and Uintaite Modifier (UM). The analysis of fatigue-healing test results, grounded in viscoelastic continuum damage (VECD) theory, indicates that rock asphalt can extend the fatigue life of FAM mixtures, albeit with a concomitant decrease in their self-healing capabilities. The study further reveals that UV aging, freeze–thaw, and UV aging–freeze–thaw conditions all led to a diminution in the fatigue and self-healing properties of FAM mixtures. However, FAM mixtures containing rock asphalt demonstrated greater resilience against these reductions. Atomic force microscope (AFM) results indicate that UV aging reduced the number of bee-structures and enlarged their area, whereas the incorporation of rock asphalt enhanced the uniformity of these structures’ distribution, thereby improving the fatigue cracking resistance of FAM mixtures. Fourier transform infrared spectroscopy (FTIR) analysis reveals that while UV aging increased the carbonyl and sulfoxide indices within the asphalt binder, rock asphalt is effective in mitigating this effect to a certain degree, thereby enhancing the aging resistance of FAM mixtures.

The uncertainty in the new power system has increased, leading to limitations in traditional stability analysis methods. Therefore, considering the perspective of the three-dimensional static security region (SSR), we propose a novel approach for system static stability analysis. To address the slow training speed of traditional deep learning algorithms using batch gradient descent (BGD), we introduce an improved stochastic–batch gradient descent (S-BGD) search method that combines the advantages of stochastic gradient descent (SGD) in fast training. This method ensures both speed and precision in parameter training. Moreover, to tackle the problem of getting trapped in local optima and saddle points during parameter training, we draw inspiration from kinematic theory and propose a gradient pile (GP) training method. By utilizing accumulated gradients as parameter corrections, this method effectively avoids getting stuck in local optima and saddle points, thereby enhancing precision. Finally, we apply the proposed methods to construct the static security region for the IEEE-118 new power system using its data as samples, demonstrating the effectiveness of our approach.

Background: A diet high in purines can impair the function of the gut microbiota and disrupt purine metabolism, which is closely associated with the onset of hyperuricemia. Dietary regulation and intestinal health maintenance are key approaches for controlling uric acid (UA) levels. Investigating the impacts of fermented foods offers potential dietary interventions for managing hyperuricemia. Methods: In this study, we isolated a strain with potent UA-degrading capabilities from “Jiangshui”, a fermented food product from Gansu, China. We performed strain identification and assessed its probiotic potential. Hyperuricemic quails, induced by a high-purine diet, were used to assess the UA degradation capability of strain JS-3 by measuring UA levels in serum and feces. Additionally, the UA degradation pathways were elucidated through analyses of the gut microbiome and fecal metabolomics. Results: JS-3, identified as Lacticaseibacillus paracasei, was capable of eliminating 16.11% of uric acid (UA) within 72 h, rapidly proliferating and producing acid within 12 h, and surviving in the gastrointestinal tract. Using hyperuricemic quail models, we assessed JS-3’s UA degradation capacity. Two weeks after the administration of JS-3 (2 × 108 cfu/d per quail), serum uric acid (SUA) levels significantly decreased to normal levels, and renal damage in quails was markedly improved. Concurrently, feces from the JS-3 group demonstrated a significant degradation of UA, achieving up to 49% within 24 h. 16S rRNA sequencing revealed JS-3’s role in gut microbiota restoration by augmenting the probiotic community (Bifidobacterium, Bacteroides unclassified_f-Lachnospiraceae, and norank_fynorank_o-Clostridia_UCG-014) and diminishing the pathogenic bacteria (Macrococus and Lactococcus). Corresponding with the rise in short-chain fatty acid (SCFA)-producing bacteria, JS-3 significantly increased SCFA levels (p < 0.05, 0.01). Additionally, JS-3 ameliorated metabolic disturbances in hyperuricemic quails, influencing 26 abnormal metabolites predominantly linked to purine, tryptophan, and bile acid metabolism, thereby enhancing UA degradation and renal protection. Conclusions: For the first time, we isolated and identified an active probiotic strain, JS-3, from the “Jiangshui” in Gansu, used for the treatment of hyperuricemia. It modulates host–microbiome interactions, impacts the metabolome, enhances intestinal UA degradation, reduces levels of SUA and fecal UA, alleviates renal damage, and effectively treats hyperuricemia without causing gastrointestinal damage. In summary, JS-3 can serve as a probiotic with potential therapeutic value for the treatment of hyperuricemia.

Target detection technology based on unmanned aerial vehicle (UAV)-derived aerial imagery has been widely applied in the field of forest fire patrol and rescue. However, due to the specificity of UAV platforms, there are still significant issues to be resolved such as severe omission, low detection accuracy, and poor early warning effectiveness. In light of these issues, this paper proposes an improved YOLOX network for the rapid detection of forest fires in images captured by UAVs. Firstly, to enhance the network’s feature-extraction capability in complex fire environments, a multi-level-feature-extraction structure, CSP-ML, is designed to improve the algorithm’s detection accuracy for small-target fire areas. Additionally, a CBAM attention mechanism is embedded in the neck network to reduce interference caused by background noise and irrelevant information. Secondly, an adaptive-feature-extraction module is introduced in the YOLOX network’s feature fusion part to prevent the loss of important feature information during the fusion process, thus enhancing the network’s feature-learning capability. Lastly, the CIoU loss function is used to replace the original loss function, to address issues such as excessive optimization of negative samples and poor gradient-descent direction, thereby strengthening the network’s effective recognition of positive samples. Experimental results show that the improved YOLOX network has better detection performance, with mAP@50 and mAP@50_95 increasing by 6.4% and 2.17%, respectively, compared to the traditional YOLOX network. In multi-target flame and small-target flame scenarios, the improved YOLO model achieved a mAP of 96.3%, outperforming deep learning algorithms such as FasterRCNN, SSD, and YOLOv5 by 33.5%, 7.7%, and 7%, respectively. It has a lower omission rate and higher detection accuracy, and it is capable of handling small-target detection tasks in complex fire environments. This can provide support for UAV patrol and rescue applications from a high-altitude perspective.

The impact of COVID-19 has boosted growth in the takeaway and medical industries but has also generated a large amount of plastic waste. Peanut shells (PS) are produced in large quantities and are challenging to recycle in China. Co-pyrolysis of peanut shells (PS) and polypropylene (PP) is an effective method for processing plastic waste and energy mitigation. Thermogravimetric analysis was conducted on PS, PP, and their blends (PS-PP) at different heating rates (10, 20, 30 °C·min−1). The results illustrated that the co-pyrolysis process of PS-PP was divided into two distinct decomposition stages. The first stage (170–400 °C) was predominantly linked to PS decomposition. The second stage (400–520 °C) resulted from the combinations of PS and PP’s thermal degradations, with the most contribution from PP degradation. With the increase in heating rate, thermogravimetric hysteresis appeared. Kinetic analysis indicated that the co-pyrolysis process reduced the individual pyrolysis activation energy, especially in the second stage, with a correlation coefficient (R2) generally maintained above 0.95. The multi-level reaction mechanism function model can effectively reveal the co-pyrolysis process mechanism. PS proved to be high-quality biomass for co-pyrolysis with PP, and all mixtures exhibited synergistic effects at a mixing ratio of 1:1 (PS1-PP1). This study accomplished effective waste utilization and optimized energy consumption. It holds significance in determining the interaction mechanism of mixed samples in the co-pyrolysis process.

Abstract Background The early diagnosis and treatment of bacterial meningitis (BM) in young infants was very critical. But, it was difficult to make a definite diagnosis in the early stage due to nonspecific clinical symptoms. Our objectives were to find the risk factors associated with BM and develop a prediction model of BM especially for young infants. Methods We retrospectively reviewed the clinical data of young infants with meningitis between January 2011 and December 2020 in Children’s Hospital of Soochow University. The independent risk factors of young infants with BM were screened using univariate and multivariate logistic regression analyses. The independent risk factors were used to construct a new scoring model and compared with Bacterial Meningitis Score (BMS) and Meningitis Score for Emergencies (MSE) models. Results Among the 102 young infants included, there were 44 cases of BM and 58 of aseptic meningitis. Group B Streptococcus (22, 50.0%) and Escherichia coli (14, 31.8%) were the main pathogens of BM in the young infants. Multivariate logistic regression analysis identified procalcitonin (PCT), cerebrospinal fluid (CSF) glucose, CSF protein as independent risk factors for young infants with BM. We assigned one point for CSF glucose ≤ 1.86 mmol/L, two points were assigned for PCT ≥ 3.80 ng/ml and CSF protein ≥ 1269 mg/L. Using the not low risk criterion (score ≥ 1) with our new prediction model, we identified the young infantile BM with 100% (95% CI 91.9%-100%) sensitivity and 60.3% (95% CI 46.4%-72.9%) specificity. Compared with BMS and MSE model, our prediction model had larger area under receiver operating characteristic curve and higher specificity, the differences were statistically significant. Conclusion Our new scoring model for young infants can facilitate early identification of BM and has a better performance than BMS and MSE models.

This paper investigates a doubly-fed wind turbine generation system (DFIG) where the rotor-side control parameters have a significant impact on the effectiveness of the DFIG due to the adoption of its inner-loop current and outer-loop power control strategies. Under rated operation, the original DFIG parameter adjustment relies mainly on manual adjustment. In this paper, mathematical models are established through literature research and data search, and neural networks are found to have unique advantages in dynamic automatic parameter tuning. First, a mathematical model of DFIG based on PI controller is established in this paper, and then the improved recurrent neural network is applied to the parameter tuning control of rotor-side PI controller, and an experimental model of DFIG simulation based on the improved recurrent neural network is established in MATLAB/Simulink. By comparing the DFIG models before and after the improvement, the simulation experiments verify that the DFIG system based on the improved recurrent neural network (CLR-DRNN) has significant control advantages under the wind speed fluctuation. The simulation experimental results show that the DFIG system based on the improved recurrent neural network achieves significant improvement in wind energy utilization coefficient, active power, reactive power, response time of rotor speed, overshoot and static error compared with the conventional PI-regulated DFIG system.

Objective: The aim of the study was to identify patients with NTRK fusion-positive or RET fusion/mutation-positive thyroid cancers, who could benefit from neurotrophic tyrosine kinase receptor (NTRK) or receptor tyrosine kinase (RET) inhibitors. Methods: Patients were identified in the Calgary prospective thyroid ca ncer database (N = 482). Patients were ‘pre-screened’ with clinically available MassARRAY® BRAF test, Colon Panel, Melanoma Panel, or ThyroSPEC™. Mutation-negative tumors were ‘screened’ for NTRK fusions and RET fusions/mutations with the Oncomine™ Comprehensive Assay v3 (OCAv3). Results: A total of 86 patients were included in 1 of 2 separate analyses. Analysis A included 42 patients with radioactive iodine (RAI)-resistant distant metastases. After pre-screening, 20 BRAF and RAS mutation-negative patients underwent OCAv3 screening, resulting in the detection of 4 patients with NTRK fusions and 4 patients with RET fusions (8/20, 40% of analyzed patients). Analysis B included 44 patients, 42 with American Thyroid Association (ATA) high and intermediate risk of recurrence and 2 with medullary thyroid carcinoma. During pre-screening, 1 patient with an NTRK fusion, 1 patient with a RET fusion, and 30 patients with BRAF mutations were identified. The remaining 9 patients received OCAv3 screening, resulting in detection of 1 patient with an NTRK fusion and 1 with a RET fusion (4/11, 36% of analyzed patients). Conclusions: Our findings indicate a higher rate of NTRK fusions and RET fusions in patients with thyroid cancer with RAI-resistant distant metastases and ATA high or intermediate risk of recurrence. This highlights the importance of early screening to enable intervention with a NTRK or RET inhibitor.

Abstract Place-based short-term crime prediction models leverage the spatio-temporal patterns of historical crimes to predict aggregate volumes of crime incidents at specific locations over time. Under the umbrella of the crime opportunity theory, that suggests that human mobility can play a role in crime generation, increasing attention has been paid to the predictive power of human mobility in place-based short-term crime models. Researchers have used call detail records (CDR), data from location-based services such as Foursquare or from social media to characterize human mobility; and have shown that mobility metrics, together with historical crime data, can improve short-term crime prediction accuracy. In this paper, we propose to use a publicly available fine-grained human mobility dataset from a location intelligence company to explore the effects of human mobility features on short-term crime prediction. For that purpose, we conduct a comprehensive evaluation across multiple cities with diverse demographic characteristics, different types of crimes and various deep learning models; and we show that adding human mobility flow features to historical crimes can improve the F1 scores for a variety of neural crime prediction models across cities and types of crimes, with improvements ranging from 2% to 7%. Our analysis also shows that some neural architectures can slightly improve the crime prediction performance when compared to non-neural regression models by at most 2%.

ObjectiveTo examine the effects of lifestyle interventions, including dietary guidance, health education and weight management, on pregnancy outcomes in women at high risk of gestational diabetes mellitus (GDM).MethodsOur study included 251 women at high risk of GDM and 128 randomized to lifestyle interventions (dietary guidance, health education, and weight management); One hundred and twenty-three people were randomly assigned to a control group (regular pregnancy check-ups). Counts between groups were compared using either chi-square test or Fisher’s exact test.ResultsCompared with the control group, the risk of GDM was reduced by 46.9% (16.4% vs 30.9%, P = 0.007) and the risk of pregnancy induced hypertension (PIH) was reduced by 74.2% (2.3% vs 8.9%, P = 0.034) in the intervention group. There were no significant differences in macrosomia, cesarean section, or preterm birth (P >0.05).ConclusionThe lifestyle intervention in this study helped pregnant women to better understand knowledge related to pregnancy, reduce stress and anxiety, and increase intake of adequate prenatal nutrition. This intervention prevented metabolic abnormalities that may occur due to inadequate nutrient intake during pregnancy. In addition, it helped women to control weight gain, maintain appropriate weight gain during pregnancy, and reduce the risk of excessive or insufficient weight gain, ultimately lowering the incidence of GDM and PIH. This highlights the importance of early screening and intervention for high-risk pregnant women.Clinical Trial Registrationhttps://www.chictr.org.cn, identifier ChiCTR2300073766.

In this study, colorimetric indicator nanofiber films based on ethyl cellulose (EC)/gelatin (G) incorporating purple sweet potato anthocyanins (PSPAs) were designed via electrospinning technology for monitoring and maintaining the freshness of pork. The film presented good structural integrity and stability in a humid environment with water vapor permeability (WVP) of 6.07 ± 0.14 × 10−11 g·m−1s−1Pa−1 and water contact angle (WCA) of 81.62 ± 1.43°. When PSPAs were added into the nanofiber films, the antioxidant capacity was significantly improved (p < 0.05) with a DPPH radical scavenging rate of 68.61 ± 1.80%. The nanofiber films showed distinguishable color changes as pH changes and was highly sensitive to volatile ammonia than that of casting films. In the application test, the film color changed from light pink (fresh stage) to light brown (secondary freshness stage) and then to brownish green (spoilage stage), indicating that the nanofiber films can be used to detect the real-time freshness of pork during storage. Meanwhile, it could prolong the shelf life of pork by inhibiting the oxidation degree. Hence, these results suggested that the EC/G/PSPA film has promising future for monitoring freshness and extending shelf life of pork.

Xiao Cheng Qi (XCQ) decoction, an ancient Chinese herbal mixture, has been used in treating slow-transit constipation (STC) for years. The underlying action mechanism in relieving the clinical symptoms is unclear. Several lines of evidence point to a strong link between constipation and gut microbiota. Short-chain fatty acids (SCFAs) and microbial metabolites have been shown to affect 5-HT synthesis by activating the GPR43 receptor localized on intestinal enterochromaffin cells, since 5-HT receptors are known to influence colonic peristalsis. The objective of this study was to evaluate the efficacy of XCQ in alleviating clinical symptoms in a mouse model of STC induced by loperamide. The application of loperamide leads to a decrease in intestinal transport and fecal water, which is used to establish the animal model of STC. In addition, the relationship between constipation and gut microbiota was determined. The herbal materials, composed of Rhei Radix et Rhizoma (Rhizomes of Rheum palmatum L., Polygonaceae) 55.2 g, Magnoliae Officinalis Cortex (Barks of Magnolia officinalis Rehd. et Wils, Magnoliaceae) 27.6 g, and Aurantii Fructus Immaturus (Fruitlet of Citrus aurantium L., Rutaceae) 36.0 g, were extracted with water to prepare the XCQ decoction. The constipated mice were induced with loperamide (10 mg/kg/day), and then treated with an oral dose of XCQ herbal extract (2.0, 4.0, and 8.0 g/kg/day) two times a day. Mosapride was administered as a positive drug. In loperamide-induced STC mice, the therapeutic parameters of XCQ-treated mice were determined, i.e., (i) symptoms of constipation, composition of gut microbiota, and amount of short-chain fatty acids in feces; (ii) plasma level of 5-HT; and (iii) expressions of the GPR43 and 5-HT4 receptor in colon. XCQ ameliorated the constipation symptoms of loperamide-induced STC mice. In gut microbiota, the treatment of XCQ in STC mice increased the relative abundances of Lactobacillus, Prevotellaceae_UCG_001, Prevotellaceae_NK3B31_group, Muribaculaceae, and Roseburia in feces and decreased the relative abundances of Desulfovibrio, Tuzzerella, and Lachnospiraceae_ NK4A136_group. The levels of SCFAs in stools from the STC group were significantly lower than those the control group, and were greatly elevated via treatment with XCQ. Compared with the STC group, XCQ increased the plasma level of 5-HT and the colonic expressions of the GPR43 and 5-HT4 receptor, significantly. The underlying mechanism of XCQ in anti-constipation could be related to the modulation of gut microbiota, the increase in SCFAs, the increase in plasma 5-HT, and the colonic expressions of the GPR43 and 5-HT4 receptor. Our results indicate that XCQ is a potent natural product that could be a therapeutic strategy for constipation.

Radix asparagi is the dried root tuber of the Liliaceae plant Asparagus cochinchinensis (Lour.) Merr., which is a major Chinese medicinal herb with high medicinal and edible value in China. The planting area of A. cochinchinensis is extensive, and there is blind introduction in various regions, leading to confusion the origin of Radix asparagi and impure germplasm. This study conducted morphological and karyotype analyses on cultivated Asparagus resources from seven main production areas in China and developed SSR molecular markers suitable for the identification of Asparagus germplasm resources based on the transcriptome sequencing results. The morphological results indicate that in addition to A. cochinchinensis (Lour.) Merr., recorded in the Pharmacopoeia of the People’s Republic of China, there are also A. taliensis Wang et Tang and A. lycopodineus (Baker) Wang et Tang cultivated in China. All the tested Asparagus resources were diploid and had 20 chromosomes. A total of 8841 single genes containing SSR loci were identified using transcriptome sequencing of Neijiang Asparagus, including 761 SSR loci with trinucleotide repeat units. One hundred pairs of SSR primers were randomly designed from the trinucleotide repeat loci for PCR and polymorphism verification, and ten pairs were selected for identification of Asparagus germplasm resources. The genetic diversity results of ten pairs of primers in seven Asparagus-producing regions were consistent with the morphological identification. This study provides technical support for the comprehensive evaluation and utilization of Asparagus germplasm resources.

Potato is an important crop, used not only for food production but also for various industrial applications. With the introduction of the potato as a staple food strategy, the potato industry in China has grown rapidly. However, issues related to bacterial wilt, exacerbated by factors such as seed potato transportation and continuous cropping, have become increasingly severe in the primary potato cultivation regions of China, leading to significant economic losses. The extensive genetic diversity of Ralstonia solanacearum (R. solanacearum), which is the pathogen of bacterial wilt, has led to a lack of highly resistant potato genetic resources. There is a need to identify and cultivate potato varieties with enhanced resistance to reduce the adverse impact of this disease on the industry. We screened 55 accessions of nine different wild potato species against the bacterial wilt pathogen R. solanacearum PO2-1, which was isolated from native potato plants and belongs to phylotype II. Three accessions of two species (ACL24-2, PNT880-3, and PNT204-23) were identified with high resistance phenotypes to the tested strains. We found these accessions also showed high resistance to different phylotype strains. Among them, only PNT880-3 was capable of flowering and possessed viable pollen, and it was diploid. Consistent with the high resistance, decreased growth of R. solanacearum was detected in PNT880-3. All these findings in our study reveal that the wild potato PNT880-3 was a valuable resistance source to bacterial wilt with breeding potential.

In order to harness a greater share of wind energy resources, offshore wind energy projects are venturing into deep-sea locations. In this progression, the issue of grid integration control becomes increasingly challenging. Traditional Model Predictive Control (MPC) has been introduced in offshore wind energy grid integration control due to its merits, such as not requiring modulators, dispensing with decoupling, incorporating constraint handling, and facilitating online optimization. However, it heavily relies on a model and consequently experiences a substantial loss of control effectiveness in the face of system parameter variations. In light of this, this study presents an active-disturbance-rejection-based three-vector sequence model predictive control approach. This method effectively mitigates the influence caused by changes in system parameters, endowing the system with self-disturbance rejection capabilities and enhancing its fault recovery abilities. The method employs self-disturbance control to track voltage reference values and employs the concept of sequence control to eliminate weighting factors in the cost function. Furthermore, it employs three-vector control to achieve error-free operation. The simulation results confirmed that the proposed method effectively minimizes voltage and power transients. It demonstrated superior control effectiveness and shorter response times, enabling the system to rapidly restore to a stable operational state following disturbances.

Abstract Grid-connection of new energy is highly important in promoting the use of clean and renewable energy. However, it will bring huge risks to the power grid operation security, such as frequency stability, voltage stability, small signal stability, and transient stability, etc.,. In the study, SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis has been employed to construct 24 kinds of internal and external evaluation factors and 8 kinds of improvement strategies, for assessing operation security prospective with new energy power system of HM in China. The weights of SWOT factors are determined with the fuzzy-AHP method. Moreover, the fuzzy-MARCOS approach is used to select the most suitable strategies for power system operation security effective implementation. The reported research reveals that new energy in HM area not only has an ample potential for full development and generating electricity, but also brings operation security problems due to large-scale grid connection. Therefore, 8 kinds of improvement strategies are suggested to encourage the government to exploit and develop new resources, improve the investment pay, power generation and transmission technologies to mitigate the current energy crisis, and increase the energy security for sustainable development of the country. The methodology proposed herein is applicable with a case study concerning the operation security prospective of HM power grid, and all phases of the comparative analysis and sensitivity analysis illustrate the validity of MARCOS method. Furthermore, the ranked order of strategies is obtained as A 2 > A 6 > A 5 > A 1 > A 8 > A 7 > A 4 > A 3. The three most important strategies are A 2, A 6 and A 5, i.e., “improving the technical establishment to encourage efficient and cheap electricity production”, “strive to build local permanent load, and reduce the risk of long-distance and high-capacity transmission”, “taking advantage of government incentives and investment to modify the irrational energy policies and energy planning”, respectively.

Abstract Background Ticks are hematophagous parasites that transmit an extensive range of pathogens to their vertebrate hosts. Ticks can destroy invading microorganisms or alleviate infection via their rudimentary but orchestrated innate immune system. Antimicrobial peptides (AMPs) are important components of tick innate immunity. Among these humoral effector molecules, defensins are well-studied and widely identified in various species of Ixodidae (hard ticks) and Argasidae (soft ticks). This review was aimed at presenting the characterization of tick defensins from structure-based taxonomic status to antimicrobial function. Main text All published papers written in English from 2001 to May 2022 were searched through PubMed and Web of Science databases with the combination of relevant terms on tick defensins. Reports on identification and characterization of tick defensins were included. Of the 329 entries retrieved, 57 articles were finally eligible for our scoping review. Tick defensins mainly belong to the antibacterial ancient invertebrate-type defensins of the cis-defensins superfamily. They are generally small, cationic, and amphipathic, with six cysteine residues forming three intra-molecular disulfide bonds. Tick defensins primarily target membranes of a variety of pathogens, including Gram-positive and Gram-negative bacteria, fungi, viruses, and protozoa. Since tick defensins have a high degree of variability, we summarize their common biological properties and enumerate representative peptides. Along with the various and potent antimicrobial activities, the role of tick defensins in determining vector competence is discussed. Conclusions Due to their broad-spectrum antimicrobial activities, tick defensins are considered novel candidates or targets for controlling infectious diseases. Graphical Abstract

To improve the heat transfer coefficient of a condenser, this paper proposes using a fin-tube condenser to replace a smooth-tube condenser in a domestic heat pump water heater. The finite element method is used to analyze the heat transfer coefficient of fin-tube condensers with different design parameters. By comparing the results of experiments with those obtained using CFD methods, it has been determined that the CFD method used in this study is feasible. Simulation results showed that the heat transfer coefficient enhanced clearly. The total thermal resistance of the fin-tube condenser decreased by 7% through increasing fin thickness. The total thermal resistance of the fin-tube condenser increased by 1–1.3% when fin spacing was increased. The heat transfer coefficient decreased severely and the maximum total thermal resistance of the fin-tube condenser increased by 8.7% with increasing fin height. In 600 s, when the fin spacing, fin height, fin thickness and inner diameter were 14 mm, 12.5 mm, 1.2 mm and 22.5 mm, respectively, compared to the smooth-tube condenser, the fin-tube condenser could increase the final water temperature by 18.37%, and the heat transfer coefficient would increase by about 95%. This research could provide a low-cost way to improve the heat transfer coefficient of condensers in domestic heat pump water heaters.

The effect and mechanism of phenol removal by immobilized microorganisms in Fe3O4 nanomaterial-modified pharmaceutical residue biochar was investigated to develop efficient biochar immobilizing microbial technology. Plant residue biochar (Y3, Y5, and Y7) was prepared from Andrographis paniculata plant residues as the raw material at 300 °C, 500 °C, and 700 °C, respectively. Y7 was modified with Fe3O4 nanomaterial (Fe-Y7). These four kinds of biochars were used as carriers to adsorb immobilized Alcaligenes faecalis strain JH1, JY3, JY5, JY7, and Fe-Y7 to investigate the mechanism of phenol removal, and eight cycles were performed to analyze their immobilization performance. Compared with suspended bacteria, biochar-immobilized bacteria could improve their tolerance in different environments. At temperatures of 25 °C to 40 °C, pH = 5~9, initial phenol concentration of 300–500 mg/L, and salinity of 3%, the bacteria could still grow and maintain strong activity within 48 h. The water-extractable organic carbon of biochar was also tested for the degradation of phenol by bacteria, which was found to have different stimulating effects on bacteria. In the batch experiments, as the number of cycles increased, the bacteria grew and adhered rapidly to the biochar, eventually forming a thick and sticky biofilm. After the sixth cycle, all the biochar-immobilized bacteria could remove 300 mg/L phenol solution within 12 h. The removal rate of phenol by JFe-Y7 was relatively fast in the eighth cycle. The results indicated that biochar-immobilized bacteria have good durability, stability, and reproducibility and that Fe3O4 nanoparticle modification could improve the removal of phenol by increasing the phenol adsorption amount, the adsorption capacity of bacteria, and the enzymatic activity of bacteria.

Drought stress is an important factor that reduces plant biomass production and quality. As one of the most important economic forage grasses, orchardgrass (Dactylis glomerata) has high drought tolerance. Auxin/indole-3-acetic acid (Aux/IAA) is one of the early responsive gene families of auxin and plays a key role in the response to drought stress. However, the characteristics of the Aux/IAA gene family in orchardgrass and their potential function in responding to drought stress remain unclear. Here, 30 Aux/IAA members were identified in orchardgrass. Segmental duplication may be an important driving force in the evolution of the Aux/IAA gene family in orchardgrass. Some Aux/IAA genes were induced by IAA, drought, salt, and temperature stresses, implying that these genes may play important roles in responding to abiotic stresses. Heterologous expression in yeast revealed that DgIAA21 can reduce drought tolerance. Similarly, the overexpression of DgIAA21 also reduced drought tolerance in transgenic Arabidopsis, which was supported by lower total chlorophyll content and relative water content as well as higher relative electrolyte leakage and malondialdehyde content (MDA) than Col-0 plants under drought conditions. The results of this study provided valuable insight into the function of DgIAAs in response to drought stress, which can be further used to improve forage grass breeding programs.

In this paper, a hybrid-bridge-based dual-active-bridge (DAB) converter with a three-level (TL) half-bridge and a two-level full-bridge is proposed, which can be utilized to interface the medium voltage and low voltage DC. In the proposed converter, there are only eight power switches in total. Compared with the traditional hybrid-bridge-based DAB converter with a neutral-point-clamped (NPC) type TL half-bridge, a fewer power device count and higher efficiency can be realized in the proposed converter due to removing clamping diodes. Thus, a more compact circuit structure and a lower cost can be obtained. Moreover, zero-voltage-switching (ZVS) of all switches in primary-side and secondary-side can be achieved in the proposed converter. The operating principle, performances, and characteristics of the proposed converter are analyzed in detail. Also, a specification design case with a detailed key parameter design is given. Finally, a 1-kW experimental prototype is established to validate the proposed converter, and obtained experimental results are highly consistent with the theoretical analysis.